Download DRAFT: IOOS® Summit Report - Interagency Ocean Observation

DRAFT: IOOS®
Summit Report
Version 1-3
September 18, 2012
CHAPTER ONE: HIGHLIGHTING THE PAST DECADE
I. Introduction .................................................................................................................................... 3
II. History and Structure of the U.S. IOOS.................................................................................. 3
A. Initial Efforts in the U.S: Ocean.US ................................................................................................... 4
B. Funding the Regional Coastal Ocean Observing Systems ....................................................... 6
C. U.S. IOOS National Program Office; the Integrated Coastal Ocean Observing Act of
2009 .................................................................................................................................................................. 7
III: Accomplishments and Introspection .................................................................................. 8
A. System Accomplishments.................................................................................................................... 8
B. Enterprise Accomplishments.......................................................................................................... 12
C. Delivering the benefits: ..................................................................................................................... 18
D. Partnerships .......................................................................................................................................... 24
E. Introspection ........................................................................................................................................ 27
CHAPTER TWO: USERS AND REQUIREMENTS
I. Introduction ................................................................................................................................. 28
II. Users and Their Requirements ............................................................................................. 31
A. Hallmarks of Successful User Engagement................................................................................ 31
B. User Engagement Steps ..................................................................................................................... 34
C. Current Knowledge of User Requirements ................................................................................ 36
III. The Current Challenges ......................................................................................................... 37
IV.
Future Opportunities and Recommendations .......................................................... 45
A. Recommendations .............................................................................................................................. 45
CHAPTER THREE: OBSERVING SYSTEM CAPABILITIES- GAP ASSESSMENT AND
DESIGN
I. Introduction ................................................................................................................................. 50
2. Overarching Issues .................................................................................................................... 50
3. Subsystems ............................................................................................................................................. 54
Web Services are the interface between systems ........................................................................ 60
How should IOOS DMAC be structured? .......................................................................................... 60
Open Data/Open Software Development/Open Standards ..................................................... 61
Quality Control and Quality Assurance ............................................................................................ 61
Aggregated Recommendations .................................................................................................. 64
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Other References ............................................................................................................................ 68
CHAPTER FOUR: INTEGRATION CHALLENGES AND OPPORTUNITIES
I. Introduction .................................................................................................................................. 70
II. The “I” in IOOS ............................................................................................................................. 71
III. Opportunities for, and Challenges to Integration ......................................................... 73
A. Overall ...................................................................................................................................................... 73
B. Observations.......................................................................................................................................... 74
C. Models ...................................................................................................................................................... 76
D. Data Management & Communications ........................................................................................ 77
IV. The Way Forward ..................................................................................................................... 81
A. Overall ...................................................................................................................................................... 81
B. Observations.......................................................................................................................................... 82
C. Models ...................................................................................................................................................... 83
D. Data Management & Communications ........................................................................................ 84
V. Success Stories ............................................................................................................................ 85
VI. Coastal IOOS and Global GOOS ............................................................................................. 90
CHAPTER FIVE: A VISION FOR AN INTEGRATED OBSERVING SYSTEM
I. The year is 2022 ... ...................................................................................................................... 99
II. Drivers For A New Decade Of Ocean Observing ........................................................... 100
A. People and Culture ............................................................................................................................ 100
B. Commerce and Economy ................................................................................................................ 101
C. Technology and Communications ............................................................................................... 101
D. Politics and Governance ................................................................................................................. 101
E. U.S. Public Policy Drivers ................................................................................................................ 102
II. The Challenge ........................................................................................................................... 102
IV. The Vision................................................................................................................................. 104
V. Conclusion ................................................................................................................................. 105
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Chapter One:
Highlighting the Past Decade
I. Introduction
The oceans are of fundamental importance to the health, national security and economy of
the United States. Decades of focused investments in ocean observing and predicting have
produced numerous examples of substantive societal and economic benefit resulting from
improved knowledge of ocean parameters and behavior. However, more complex and
difficult questions about the ocean, particularly in the coastal regions, remain to be
answered. Addressing these more complex issues requires innovative approaches to
stimulate collaborative ventures between academia, industry, and Tribal, local, state and
federal government entities. Recognizing this, beginning some two decades ago, the United
States embarked on a series of efforts to define a path towards developing an optimal
ocean observing, prediction, and product development/delivery system capable of
addressing societal needs. As part of this ambitious enterprise, ten years ago, on March 1015, 2002, a major Workshop was held at the Airlie Center in Warrenton, Virginia to develop
a strategic design plan for a United States Integrated Ocean Observing System (IOOS®) to
fulfill this role. The community refers to this workshop as the Airlie House workshop.
Today, as we examine how best to continue this important effort, it is important to review
the path we have taken to get where we are today and to understand the initial vision for
IOOS and better appreciate how far we have progressed towards our goals.
II. History and Structure of the U.S. IOOS
For millennia, the oceans have stimulated commerce, industry and culture. Beginning in
the middle part of the last century, as war and technology made global science more
imperative, systematic study of the oceans and their processes began to be addressed
broadly within the international scientific community. What these studies lacked was a
comprehensive way to collect, manage and distribute observations to support the growing
demand for ocean research.
During the latter part of the 1990’s, the Intergovernmental Oceanographic Commission
(IOC), the United Nations Environmental Program, the World Meteorological Organization
and the International Council for Science took the lead at the global level in planning for a
coordinated effort to increase our understanding of the oceans through an improved
system of observations, data management and communications.1 From these efforts, the
The IOC took the lead in hosting these efforts with its partner agencies within and outside of the
U.N. system. Most of the seminal documents are contained in its electronic archives. See, e.g.,
<http://www.iocunesco.org/index.php?option=com_wrapper&view=
wrapper&Itemid=100003>.
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Global Ocean Observing System (GOOS) was born. From its earliest days, the ocean science
community has recognized that a successful ocean observing program would have to exist
at two levels: a global, open-ocean module and coastal modules developed and
implemented on relevant regional scales.2
A. Initial Efforts in the U.S: Ocean.US
The ocean science community in the United States participated fully in the multi-national
processes to develop GOOS. As this was under way at the global level, two points were
clearly recognized in the U.S. First, implementation of the coastal module for ocean
observing would need to be done domestically -- paralleling the global efforts, and
providing U.S. data to support the global efforts. Second, the national interests of this
country – security, economic, environmental – were sufficiently strong drivers for the U.S.
to move forward to address its own particular concerns, regardless what was happening in
the international community.
The National Ocean Partnership Program (NOPP) was established by the United States
Congress Public Law 104-201in Fiscal Year 1997 for two general purposes:
 To promote the national goals of assuring national security, advancing economic
development, protecting quality of life, and strengthening science education and
communication through improved knowledge of the ocean; and
 To coordinate and strengthen oceanographic efforts in support of those goals
The legislation also established an oversight body, the National Ocean Research Leadership
Council (NORLC) 3 , and a federal advisory committee, the Ocean Research Advisory Panel
(ORAP). The law also called for “a plan to achieve a truly integrated ocean observing
system.” In 1998, the U.S. GOOS Steering Committee was formed and charged with assisting
the development of requirements for U.S. IOOS.
In 1999, under the auspices of NORLC, a joint federal/non-federal task team prepared
the report, “Toward a U.S. Plan for an Integrated, Sustained Ocean Observing System.” In
December of that year, ORAP responded to this report with a series of recommendations in
its report, “An Integrated Ocean Observing System: A Strategy for Implementing the First
Steps of a U.S. Plan.” The following May, NORLC approved establishing an interagency
planning office, Ocean.US. Ocean.US was tasked with integrating existing and planned
elements to establish a sustained ocean observing system to meet the common research
and operational agency needs in the following areas:
 Detecting and forecasting oceanic components of climate variability
As a matter of implementation of GOOS, specific regional alliances are recognized as having
competence for collaborative ocean and coastal observing in their areas. U.S. IOOS has been
recognized as the relevant GOOS regional alliance for the United States.
3 P.L. 104-201. The responsibilities of NORLC were subsumed into the National Ocean Council
under the executive order (cite) establishing a National Ocean Policy in 2010.
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Facilitating safe and efficient marine operations
Ensuring national security
Managing resources for sustainable use
Preserving and restoring healthy marine ecosystems
Mitigating natural hazards
Ensuring public health
Ocean.US’ initial focus was on developing an initial plan to achieve the vision of a
national IOOS which culminated in the Airlie House workshop. At this workshop, broad
consensus was achieved regarding the vision and direction for U.S. IOOS. Consistent with
the GOOS program, U.S. IOOS would contain both a global, open-ocean component, as well
as a coastal component focused on this country’s Exclusive Economic Zone. Contributions
to GOOS would principally be a responsibility of federal agencies, working as necessary
with academic institutions, the states and the private sector. The coastal component would
be addressed by a suite of core observations supported by federal agencies considered to
be the “backbone” of the coastal system. Other entities (Tribal, state, regional and local
governments, the private sector, academia and non-governmental organizations) would
contribute observations to the coastal component; and with additional resources, would
provide additional ocean observations to address particular regional needs. Regional
institutions would have to be developed to provide coordination in their areas.
Consensus was also achieved at the Airlie House workshop around the concept that a
robust and fully competent data management and communications (DMAC) system must
be funded and developed. For the IOOS to succeed, data management and communications
were considered and funded from the inception of this national effort, not as an
afterthought. It is significant that in the intervening years, DMAC has returned some of the
major successes and real benefits of the U.S. IOOS collaborations.
Thus, U.S. IOOS would be an end-to-end, heterogeneous, distributed system of linked
elements, with organizational structures and interfaces developed where common good is
identified. It would be a system-of-systems, consisting of the physical links, servers, and
other elements that contribute to user-defined missions, regardless of their ownership or
operational responsibility. Only this approach could routinely generate user-relevant
products necessary to meet critical national requirements over the long term. The concept
of the end-to-end nature of the IOOS consists of the following, interrelated components
connected by a two-way flow of information and data:
• The Observing Subsystem consisting of the platforms, sensors, instrumentation and
techniques necessary to measure required parameters at the temporal and spatial
scales relevant to the detection and prediction of particular user requirements,
including to detect and predict changes in coastal indicators;
• The Data Communications and Management Subsystem which consists of the
hardware and software to provide physical telemetry, exchange protocols and
standards for quality assurance and control, data dissemination and exchange,
archival, and user access; and
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•
The Analysis, Modeling and Applications subsystem consisting of data assimilation
and blending techniques, data and knowledge synthesis and analysis; and the
procedures for translating data and knowledge into user-specified products.
Following on the Airlie House workshop, Ocean.US continued to engage federal agencies
and the ocean observing community at large concerning development of U.S. IOOS at the
national scale. Products were regularly developed focusing on system development
planning, economic benefits, data management and communications, regional
organizations, modeling and analysis, and other technical and organizational details.
Along with the activity specific to U.S. IOOS and Ocean.US, broader issues of ocean policy
were playing out in the executive and legislative branches of the U.S. government. The U.S.
Commission on Ocean Policy released a far-ranging report4 in September, 2004, and among
many other recommendations highlighted and supported the development and
implementation of improved ocean and coastal observing systems. In response to the
Commission report, the President issued the U.S. Ocean Action plan that renewed the
federal government’s commitment to ocean observing, and revised the governance
structure for U.S. IOOS.
B. Funding the Regional Coastal Ocean Observing Systems
Coincident with the efforts of Ocean.US to provide national leadership in laying out a
structure and direction to U.S. IOOS, efforts were under way to develop and support efforts
in various regions of the U.S. to address specific requirements for coastal ocean observing.
To initiate particular efforts, Congress provided funding to develop limited Regional
observing system components; however these funds were used for specific projects at
individual and groups of academic institutions. This resulted in a number of success (e.g.,
the Gulf of Maine buoy network, a South East Costal Ocean Observing System providing
buoys in North Carolina, South Carolina and Florida) that served to illustrate the basic
soundness of the Regional approach. As well, under NOAA’s Coastal Services Center,
competitive grants were award to 11 entities to establish initial Regional Associations (RA)
to manage regional observing efforts. As the program matured, it was realized that for U.S.
IOOS® to survive, there needed to be formal funding within the Administration’s budget
and that the Regional Associations needed to become a coherent network of Regional
Coastal Ocean Observing Systems (RCCOOS). In October 2005, leading oceanographic
research institutions and CORE signed a letter to agree to move away from earmarks and
move towards an open, competitive approach to obtain funding that a formal budget line
and national RCOOS consistency would require. In FY2008, funding for US IOOS was
committed as part of the Administration’s budget. The funding of Regions transitioned
from a series of Congressionally-directed awards to a competitive, peer-reviewed funding
process to maximize taxpayer return on investment and transition from a variety of
“An Ocean Blueprint for the 21st Century.” The Commission was chaired by the late Admiral James
Watkins. A parallel, privately-funded and –organized effort, the Pew Oceans Commission, came to
many of the same recommendations at about the same time.
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distinct, sub-regional observing elements to eleven, more cohesive regional systems
directed toward common goals. NOAA administered the selection and funding process and
provides the leadership, management, and oversight needed to ensure IOOS Regional
activities develop in a manner consistent and compatible with national IOOS data
management standards and infrastructure. This regional participation helps lay the
groundwork for rapid expansion of data interoperability to provide, for the first time,
widespread interoperable ocean data.
Ocean.US also recognized the need for regional collaboration and leadership to sustain
coastal ocean observations. In 2003 it sponsored a summit to address requirements for the
structure and functions of regional coordination. As a result of this summit, the Regional
Associations (RA) were recognized as a part of the overall U.S. IOOS governance paradigm.
In addition, the summit acknowledged the need for a National Federation of Regional
Associations (NFRA) to help coordinate activities among the RAs and to facilitate
collaboration with the federal agencies. Thus NFRA was formed and continues to play a
strong role in supporting the diverse collaborations that are the fabric of U.S. IOOS.
C. U.S. IOOS National Program Office; the Integrated Coastal Ocean Observing Act of
2009
NOAA found itself in an interesting position with respect to all of these efforts. Funding
for IOOS was included in the Administration’s budget and in order to provide a more
focused leadership to the federal agency partners, and to work to better align different
sources of funding into a coordinated system directed at U.S. IOOS goals, NOAA established
an IOOS Program Office within the National Ocean Service in late 2006.5 At about the same
time, the governing body for Ocean.US6 was considering the next steps to take to follow-up
on the products that had been developed during the previous seven years. Recognizing the
steps being taken by NOAA and the progress that had been made to date, the governing
body recommended disestablishment of Ocean.US, placing greater emphasis on agency
responsibilities, and undertaking to oversee program coordination itself. This
recommendation was accepted by its senior bodies in the federal ocean sciences
governance structure; and on September 2008 Ocean.US was closed.
The next era of US IOOS began when the President signed the Integrated Coastal and
Ocean Observation System Act of 2009 (ICOOSA). ICOOSA mandates the establishment of a
National Integrated Coastal and Ocean Observation System, and provides for the federal
NOAA is still the only agency to have taken the step of establishing a specific, internal
organizational entity specifically to address U.S. IOOS. Given its mission to address questions of
ocean science, this is perhaps to be expected.
6 The Interagency Working Group on Ocean Observing. After enactment of the Integrated Coastal
Ocean Observing Act of 2009, this group’s functions were undertaken by the new Interagency
Committee for Ocean Observing Systems.
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government support to sustain it, designated NOAA as the lead federal agency.
Structurally, the ICOOSA established the following:
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Council: Defined as the NORLC, functionally the National Ocean Council Deputy
Level, for policy and coordination oversight
Committee: Establishes an Interagency Ocean Observation Committee (IOOC) to
manage tasks such as budgeting, standards, protocols, and coordination
Integrated Ocean Observing System Program Office: Implementation and
Administration of the system. Established within NOAA, with personnel from IOOC
member agencies.
System Advisory Committee: Advises the Administrator and the Interagency Ocean
Observing Committee.
ICOOSA recognizes the national and regional components of the system, with regional
information coordination entities (essentially, RAs once certified) to take leadership in
their areas. In 2011 the NOAA IOOS Program office was recognized by the IOOC and NFRA
as the US IOOS Program Office. The US Army Corps of Engineers (USACE) established a
liaison billet to this office. United States Geological Survey (USGS) provided a detailee for 1
year, who still today maintains a close working relationship with the IOOS Program Office.
In the past three years, the IOOC, the U.S. IOOS Program Office, the RAs, and NFRA, along
with other partners and collaborators, have also achieved other significant objectives in
developing the system. To note just a few highlights, there is now a formal policy on the
public/private use of data; A Blueprint for Full Capability (Blueprint); RAs have developed
coordinated build-out scenarios to meet the requirements of the coming decade, and the
independent cost estimate is nearing completion.
III: Accomplishments and Introspection
A. System Accomplishments
U.S. IOOS was envisioned as a National program where Federal agencies continue to
provide observations, data management, products and services to meet their own mission,
which then also contribute these to the IOOS. IOOS would set up a Regional observing
network that connects IOOS to the local level and serves as the overall integration
mechanism resulting in the nation being able to better support the seven societal benefits
identified in section II. Overall IOOS has been successful in the following areas:
• Setting up the national framework for ocean observing and providing the
mechanism for the integration of regional observations from non-Federal sources
• Moved the U.S. IOOS enterprise from planning to implementation
• Adding observing capability
• Integrating data, which has significantly increased access to ocean, coastal and Great
Lakes information
• Initiating An ocean modeling capacity based on community modeling
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•
•
Fostering Industries which lead the lead the world in ocean observing technology
NSF’s Oceans Observatories Initiative (OOI) delivering a significant boost to
Research and Development.
Assessing a complex system such as IOOS is difficult, but we felt that the system needed
to be measure against a baseline therefore the assessment is a combination of evaluation
based on the Airlie House workshop, The First U.S. IOOS Development Plan and US IOOS
Blueprint (http://www.ioos.gov/about/governance/welcome.html). This resulted in both
a quantitative and qualitative evaluation. The Airlie House report and the IOOS
development plan laid out specific milestones for each of the sub-systems of IOOS. A
detailed comparison of the state of the ocean observing enterprise between what we set
out to do, the state in 2002 and the state in 2012 is contained in Appendix XX. Looking at
the Airlie House report and the US IOOS evaluated the status of the goals in 2002 and
where we are in 2012. Table 1 summarizes our progress.
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Table 1: US IOOS Progress
Global
Component:
Past - 2002
Present - 2012
45% completed in 2004
62% completed
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Observing:
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Data Management
and
Communications
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12 PORTS® operational nationwide
175 National Water Level Observation Network (NWLON)
(none with real-time data delivery or meteorological sensors)
60 NDBC buoys
89 stations measuring directional waves
Disparate and uncoordinated
standards, protocols, and formats
No coherent data management
strategy
Call for National Standards
Ocean Biogeographic Information System (OBIS) in the
pilot stage with the first set of
OBIS nodes funded by the National Oceanographic Partnership Program (NOPP) in the mid-2000.
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21 PORTS® operational nationwide
210 NWLON (all real-time; 181
with meteorological sensors)
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103 NDBC buoys
A National Waves Plan has been
completed.

Quality Assurance of Real Time
Oceanographic Data (QARTOD)
was established in 2003 with increased development of quality control.
DMAC Steering Team was established by Ocean.US in the Spring
2002 and continues to function today
Data Management and Communications System Architect in the U.S.
IOOS Program Office
Creation of Data Integration Framework (DIF) Master Project Plan
Eleven Regional Associations Data
Assembly Centers in the Regional
Coastal Ocean Observing System
(RCOOS)
OBIS
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Modeling
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No coordinated effort on:
 improving, developing, testing
and validating operational models;
 producing accurate estimates of
current states of marine sysDRAFT IOOS Summit Report: September 18, 2012
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US IOOS Coastal and Ocean Modeling Testbed endorsed by Federal
agencies
Regional models and products are
now serving stakeholder needs
While capabilities exists in the
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Research and
Development
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Education and
Outreach
tems, or
developing assimilation techniques
Less than 15 High Frequency
radar nodes for coastal current
mapping nationwide.
Limited Glider projects for water column profiling
Call for In situ sensors for real-time
measurements and data transmission
of key biological and chemical variables
Call for coupled physical-ecosystem
National Oceanographic Partnership
Program (NOPP) and NASA awards
Call to:
 Establish an IOOS Allied Education Community
 Develop an ocean literate society based on US IOOS information
 Develop Professional certificate
programs
community, funding has not yet
been applied towards optimizing the
observing subsystem
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130 High Frequency Radars and a
national data management; assimilated operationally by Coast Guard
and NOAA
Navy using gliders operationally; 52
gliders in Regions; employed by
OOI; National Glider Asset map and
national Glider plan being developed.
Partially operational Harmful Algal
Blooms forecasting system
NEED to check with NOPP Office
NSF COSEE program in place
A number of regions have developed
lesson plans using IOOS data for
classrooms
(http://www.ioos.gov/education/wel
come.html)
MARACOOS has developed HF
Radar and Glider technician certificate programs
A priority of IOOS is the sustainment and improvement of satellite observations. Figure
1 shows that through strong international collaboration we have raised the awareness of
the gaps on the adequacy of the satellite observations but the overall health of our oceanrelated remote sensing capability is marginal. Efforts in this area have focused on
extending and improving observing capabilities that were already in place during the
1990’s and to maintain those that were launched subsequently.
Figure 1: Satellite Observation Status
In June 2011 the Aquarius was launched. This
is a focused effort to measure Sea Surface
Salinity and will provide the global view of
salinity variability needed for climate studies.
The mission is a collaboration between NASA
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and the Space Agency of Argentina (Comisión Nacional de Actividades Espaciales). In
October 2011, the Suomi National Polar-orbiting Partnership was launched and collects
and distributes remotely-sensed land, ocean, and atmospheric data to the meteorological
and global climate change communities as the responsibility for these measurements
transitions from existing Earth-observing missions such as Aqua, Terra and Aura, to the
NPOESS. It will provide atmospheric and sea surface temperatures, humidity sounding,
land and ocean biological productivity, and cloud and aerosol properties.
B. Enterprise Accomplishments
The U.S. IOOS Blueprint 1.0, http://www.ioos.gov/about/governance/welcome.html ,
employs an architectural framework for describing IOOS full operating capability (FOC),
partnership roles and responsibilities, and implementation requirements. An architectural
framework was chosen to provide a structured approach for organizing and describing
discrete activities and components of IOOS that can be uniformly and repeatedly applied to
all IOOS-related capabilities and participants. The architectural guidance and
documentation in the Blueprint are used to do the following:
• Establish initial requirements
• Describe what needs to be accomplished, who executes it, and in what order
• Provide functional descriptions, including working relationships among IOOS
components
Core Functional Analysis
Significantly, the Blueprint’s architectural framework does not prescribe specific system
or technical solutions, infrastructure/facility material solutions, detailed business process
steps, funding mechanisms or an organizational/management structure for the U.S. IOOS
Program Office. The U.S. IOOS Program office conducted an assessment of the Federal
Agencies that are part of IOOS and the RAs determine which functions and activities are
currently being performed by which IOOS Federal and non-Federal partners, and which
activities remain to be developed. The Blueprint identifies core functional areas (CFA) that
describe the U.S. IOOS Program management products and services. The CFAs were
derived from stated or implied requirements in the ICOOSA and the IOOS Development
Plan. CFAs are the minimum capabilities required for an effective IOOS and represent, at a
high level, the contribution required of U.S. IOOS to produce a cohesive suite of data,
information, products, and services related to our coastal waters, Great Lakes, and oceans.
Each core functional activity has subordinate activities.
The U.S. IOOS Program Office used a system of capability readiness symbols, Figure 2, to
represent the assessment of the ability of IOOS to perform required activities at a given
point in time. The symbols do not convey any information about the effectiveness or
efficiency with which the activity is conducted. These symbols are focused on the readiness
to perform an activity, not the characterization of the actual execution of that activity.
Figure 2: Definitions of the Readiness symbols
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Figure 3 shows the results of the analysis of the Federal Agencies.
Will need to explain this better
What this tells us is there are opportunities to pursue growth in IOOS capability through
partner contributions. For example:
Observing Subsystem: Pursue partnership agreement opportunities with USACE and
Navy/ONR in core functions within the Observing Systems subsystem in the area of
optimization studies and asset management.
DMAC Subsystem: Pursue partnership agreement opportunities with USACE, USGS, and
NOAA in core functions within the DMAC subsystem such as utility services development
and configuration control.
Modeling & Analysis Subsystem: Pursue partnership agreement opportunities with
USACE and USGS in assessment and management of sponsored models.
R&D Subsystem: Pursue partnership agreement opportunities with USACE, USGS, NOAA,
Navy/ONR, and BOEM in core functions within the R&D subsystem for requirements
determination, coordinated pilots.
Figure 4 shows the results of the Regional Association Assessments.
From this we assess that Regions are active in all of the subsystems. Overall the Regions
have capability in some of the sub-activities in each subsystem. No Region has “full
capability” in any subsystem. The Regions collectively display a solid foundation of IOOS
capability.
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Observing Subsystem:
The IOOS Blueprint was unable to fully evaluate the subsystems because the end state
has not been determined therefore the assessments asked the Federal agencies to identify
their contributions. Below are the results of the Observing, DMAC and Modeling and
Analysis subsystems. The GOOS system, to which the US IOOS global component provides
50% the funding, has determined an initial end state. Figure 5 depicts that progress.
GOOS has achieved a number of milestones. OceanObs’09 provided an opportunity for
us to evaluate the decade of progress since OceanObs’99. From an observing perspective
the number of observations grew from 4.5 million oceanographic reports to more than 16
million. The Tropical Ocean-Atmosphere (TAO) array, a legacy of the Tropical OceanGlobal Atmosphere program, has expanded to be the TAO-TRITON (Triangle Trans-Ocean
Buoy Network) array in the Pacific with a series of standard moorings, flux reference sites,
CO2, and biochemistry sites, and expanded PIRAT array in the tropical Atlantic, and the
beginnings of a Research Moored Array for the African-Asian-Australian Monsoon Analysis
and Prediction (RAMA) array in the tropical Indian Ocean. With the development of the
profiling float technology under the World Ocean Circulation Experiment (WOCE), ARGO
reached its target of 3000 floats in 2005. A new observing platform has been added – the
OceanSITES (OCEAN Sustained Interdisciplinary Time series Environmental observation
System) program. OceanSITES consists of approximately 100 moorings, considered
sentinel sites, providing high quality air-sea flux data in key, unique, or strategic portions of
the global ocean.
Technology innovation has enabled the sharing worldwide of ocean information. The
Global Ocean Data Assimilation Experiment (GODAE), Array for Realtime Geostrophic
Oceanography (ARGO) and the Global High Resolution Sea Surface Temperature (GHRSST)
programs have shown that it was possible to reach consensus on common standards. With
the emergence of portals that can serve data to users in real-time, a number of Global Data
centers such as GHRSST, ARGO, Global Ocean Surface Underway Data (GOSUD) and the
Joint Technical Commission for Oceanography and marine Meteorology (JCOOM) Observing
Platform Support Center exist. We have seen the emergence of global solutions to facilitate
the sharing of biodiversity data that include the Global Biodiversity Information Facility
(GBIF) and the International Ocean Biogeographic Information System (OBIS. The
associated regional nodes, (e.g. OBIS-USA) and focused taxonomic nodes (e.g. OBISSeamap) have developed worldwide infrastructure to publish and therefore share their
data.
This same identification of systems does not exist for the coastal component of IOOS;
therefore the Assessment collected information on candidate observing, data management
and research infrastructure from the Federal Agencies. Figure 6 depicts the observing
systems and programs, as part of the Blueprint assessment, as contributing to IOOS but the
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DRAFT IOOS Summit Report: September 18, 2012
next steps of identifying how they fit together and where the gaps are has not been
completed. Appendix XX identifies the specific systems.
Figure 6
While the Bureau of Ocean Energy Management (BOEM) does not list specific observing
system, they have played an important role in regard to increasing observing assets. BOEM
required oil & gas platforms to collect and transmit current data in near real time is
because the BOEM Regional Director and his Environmental Program leadership were
convinced that the Integrated Ocean Observing System was the way of the future. The
agency then issued a Notice to Lessees (NTL) requiring the data collection and its nonproprietary transmission in to the federal data stream. In his role as a dedicated IOOS
supporter he began a sea change in attitude of the oil & gas industry contribution of data
into the federal data stream. Further, through their ocean studies program, BOEM, has
been funding the University of Alaska scientist to provide HF Radar, drifters and gliders in
the Arctic in anticipation of drilling.
The RAs have the responsibility for not only deploying observing assets but also
providing access to ocean, coastal and Great Lakes data collected by State, Local, Tribal
governments, academia, industry and non-governmental organizations. The RAs provided
an initial inventory of assets, have stood up Regional Data Assembly centers, and have
completed Regional Build Out Plans. The RAs identified priority user needs in four primary
categories: marine operations; coastal, beach and near shore hazards; ecosystems,
including fisheries, and water quality; and long-term trends in ocean and Great Lakes
conditions. These broad themes and specific user needs associated with them are based on
many years of interaction by the RAs with users in their regions and nationwide. The
process for developing the Regional Build Out Plans out plan began with each individual
RAs identifying user needs, products and required assets for their own region. This
information was then synthesized to identify common elements across the nation as well as
unique regional circumstances. A draft, national synthesis document,
http://www.usnfra.org/buildout.html, defines 29 common products and services that
should be provided in all the regions after a 10-year implementation period. Figure 7
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DRAFT IOOS Summit Report: September 18, 2012
represents the assessment of the observing requirements laid out in the Regional Build Out
Plans.
Figure 7
A foundation for all IOOS activities and products are effective, accurate, precise and
reliable in situ and remote sensing instruments to quantify key parameters and to
document environmental conditions and changes over time. The Alliance for Coastal
Technologies (ACT) was developed, in large part, to fulfill one aspect of these IOOS
technology requirements, by providing an understanding of sensor performance and data
quality, while facilitating the maturation of novel technologies. Since 2004, ACT has
evaluated 49 sensors from 25 international companies; overall, ACT has conducted 235
tests of instrument performance in the laboratory and in the field, under a wide range of
environmental conditions and in different deployment applications. These Technology
Evaluations have helped manufacturers improve their technologies and users make
informed technology choices. The online Technology Information Clearinghouse now
connects users with over 300 companies and nearly 4,000 commercial instruments.
DMAC subsystem:
DMAC is the central mechanism for integrating all existing and projected data sources.
Historically, data providers recorded and transmitted data in a variety of ways that, while
satisfactory for their own purposes, were often not consistent in content or format with
other providers of the same data. Figure 8 represents the Federal contribution to DMAC.
Figure 8
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DRAFT IOOS Summit Report: September 18, 2012
At the Global level individual programs such as AGRO, OceanSITES have global data
assembly centers. In addition to the efforts of the US IOOS Program Office to provide a
national consistent data management picture of IOOS, the data must also be provided in
formats that serve communities. For example, the World Meteorological Organization and
national meteorological services rely on the Global Telecommunications System for ocean
data to support atmospheric modeling, for IOOS NOAA’s National Data Buoy provides this
service. Since 2002 the amount of data annually going to the GTS has risen from less than
500K in 2003 to over 11 million in 2011. At the Regional level, each of the RAs has stood
up Data Assembly Centers (DAC) and significantly increasing access to data. For example
Central and Northern California (CeNCOOS) provides real-time ocean and coastal
information from 183 assets and 23 partners while the Northwest Association of
Networked Ocean Observing Systems (NANOOS) provides information from 167 assets and
25 partners.
Coastal and Ocean Modeling
Need text from CSDL on how far they have come since 2001, need to evaluate Regional
modeling
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DRAFT IOOS Summit Report: September 18, 2012
In 2010, U.S. IOOS established the Coastal and Ocean Modeling Testbed (COMT) to
accelerate the transition of scientific and technical advances from the coastal and ocean
modeling research community to improve identified operational ocean products and
services. Initially addressing chronic issues of high relevance in the Atlantic and Gulf
regions such as flooding from storm surge and seasonal depletion of oxygen in shallow
waters, this project has established a robust infrastructure to facilitate model assessment
and detailed scientific investigation of both model output and data. Through the COMT,
methods will also be explored for effectively delivering model results to regional centers,
scientists, and managers relying on U.S. IOOS. Results from phase I of that effort include:
•
Development of skill metrics for specific issues of societal importance;
•
Development of standards, web services and standards-based tools that work across
a variety of different model types and conventions, enabling interoperability and software
reuse by following IOOS DMAC principles.
•
Improvements to all models through comparisons with others. For example, the
Estuarine Hypoxia team reported that the CHESROMS model realized a 40% overall
reduction in RMS difference between predicted and observed bottom dissolved oxygen
concentration due to improvements identified during the Testbed project;
Research and Development
One of the most exciting developments has been the funding of the National Science
Foundation’s Ocean Observatories Initiative (OOI). The OOI is a long-term, NSF-funded
program to provide 25-30 years of sustained ocean measurements to study climate
variability, ocean circulation and ecosystem dynamics, air-sea exchange, seafloor
processes, and plate-scale geodynamics. The OOI will enable powerful new scientific
approaches for exploring the complexities of Earth-ocean-atmosphere interactions, thereby
accelerating progress toward the goal of understanding, predicting, and managing our
ocean environment. The OOI can foster new discoveries that will, in turn, move research in
unforeseen directions.
C. Delivering the benefits:
IOOS is a vital tool for tracking, predicting, managing, and adapting to changes in our
coastal and ocean environment. IOOS addresses :
 Safety: helps ensure the safety and security of citizens now and into the future
 Economy: unlocks economic and business benefits of the ocean
 Environment: key to protecting our environment for generations to come.
Safety:
Increased observations to National Weather Service: NOAA’s NDBC has increased
observation information provided by NOAA and US IOOS partners for use globally in
atmospheric modeling by 1000 percent. RA observing platforms provide unique support to
NOAA’s NWS. NERACOOS buoys provide the only wave observations in Long Island Sound
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DRAFT IOOS Summit Report: September 18, 2012
and the only ocean visibility observations in the Gulf of Maine, CariCOOS provides 100% of
the coastal buoys for Puerto Rico and US Virgin Islands, PacIOOS operates 100% of the
wave buoys in the region and GLOS buoys provide data in faster report cycles than NDBC
which is valuable because conditions along the coastline change very rapidly and are
different than at the central lake positions of the NDBC buoys. SECOORA buoys increased
forecast verification by NWS by 7%. HF Radar uniquely provides surface currents along the
coast. NHC uses HF Radar data for wave forecasts in the Florida Straits. RAs have
augmented coastal meteorological stations in sparse areas, specifically AOOS has funded
RCOOS are funding coastal met stations in sparse areas: AOOS funds 9 weather stations in
Prince William Sound; CariCOOS funds 15 coastal stations.
Deep Water Horizon: The U.S. IOOS response to the April 2010 Deepwater Horizon oil spill
in the Gulf of Mexico was threefold; observing technologies used in new ways to aid
response; immediate access to non-federal data in the region impacted by the spill, and a
project that tracked surface and subsurface oil. The use of satellite data and gliders
represented new technologies to support response. Coordinated data management made
the information collected instantaneously usable but also revealed that the sufficient
baseline information was not there available. Had a fully realized US IOOS that includes
historical characterization of the environment had been in place, the understanding of the
oil spill effects would have been vastly improved. It is a testament to the IOOS partnership
that assets were brought from across the United States and that the data streams, and
models were immediately usable in the Federal emergency response.
Japanese Tsunami – March 2011: IOOS played a part in the warning and information flow of
the tsunami wave’s reach to the United States. Nationally the DART buoys and tide gauges
provided vital information for adequate warning. At the Regional level RAs saw five to tenfold increases in web-traffic proving that the public trusts and look to their IOOS RA for
local guidance during national and international distress. Pacific Island Ocean Observing
System (PacIOOS) provided the only real-time water level (tsunami arrival) and turbidity
(debris) measurements for Waikiki. The Northwest Association of Networked Ocean
Observing System (NANOOS) featured their “Tsunami Evacuation Zones for the Oregon
Coast,” which has now been expanded to the Pacific Northwest Tsunami Evacuation Zones
online portal and free app that provides an at-a-glance view of tsunami hazard zones along
the coasts of Oregon and Washington. Southern California Coastal Ocean Observing System
(SCOOS) measured the tsunami signal documented by the NOAA tide gauge on the Scripps
Institution of Oceanography pier and by pressure sensors at the four SCCOOS Automated
Shore stations: Scripps Pier, Newport Pier, Santa Monica Pier, and Stearns Wharf. Central
and Northern California Ocean Observing System (CeNCOOS) captured the tsunami passage
using the Monterey Accelerated Research System, Humboldt, San Francisco, and Morro
Bays. CODAR SeaSonde radars located in Japan and California detected and measured
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DRAFT IOOS Summit Report: September 18, 2012
tsunami current flows, representing the first such tsunami observations occurred with any
radar, between 10 and 45 minutes prior to its arrival at neighboring tide gauges.7
Hurricane Irene: As Hurricane Irene moved through the Caribbean and along the East
Coast of the United States in August 2011 the non-Federal partners of US IOOS augmented
NOAA’s observing and forecasting capabilities. NOAA used the buoys from Caribbean
Regional Association (CARA), Southeast Coastal Ocean Observing Regional Association
(SECOORA) and Northeastern Regional Association of Coastal Ocean Observing Systems
(NERACOOS) to track the Hurricane, initialize and verify forecasts. The United States Coast
Guard (USCG), NOAA’s National Hurricane Center, and NOAA’s Weather Forecast offices in
New England all used RA models to support local forecasts. As Irene progressed up the
East Coast the Mid-Atlantic Regional Association of Coastal Ocean Observing Systems
(MARACOOS) collected and distributed a dedicated hurricane blog http://maracoos.org/irene/ - with updates on the storm, especially with regard to high
frequency radar data, glider routes and the phytoplankton bloom monitoring. The
MARACOOS site also delivered new forecasts to the New Jersey Board of Public Utilities.
Underwater glider RU-16 collected data during the hurricane. The RU16 glider which was
deployed by the U.S. Environmental Protection Agency, the N.J Department of
Environmental Protection, and Rutgers was directed offshore to survive the hurricane. It
rode out the storm in deeper waters and collected an unprecedented dataset from Irene
that which will inform forecast model development well into the future.
Storm Surge Display Program Improved: The National Hurricane Center (NHC) runs a
computerized model, the Sea, Lake, and Overland Surges from Hurricanes (SLOSH), to
predict storm surge. Through a U.S. IOOS customer project within NOAA, real-time water
level and wind data were incorporated into the SLOSH Display Program. As of the 2010
hurricane season, forecasters have access to time series graphs of water level observations,
predictions, and winds, and are able to display these along with surge information from the
SLOSH model. In addition, improvements provide additional Geographic Information
System capabilities and options for displaying roads, populated areas and city boundaries.
Search and Rescue: USCG has the mission for Search and Rescue. The USCG has added U.S.
IOOS surface current monitoring data and forecasting to their Search and Rescue Optimal
Planning System (SAROPS) and estimates that search areas can be reduced by as much as
two-thirds over a 96 hour period with this data, thereby leading to a greater number of
lives saved and significantly reducing search costs.
Reducing Rescue incidents: A “Bar Forecast” that uses critical U.S. IOOS wave data has
dramatically reduced the number of USCG rescue incidents in the San Francisco area of
California. In 2005, the National Weather Service in Monterey started broadcasting the Bar
Forecast, providing information on sea conditions, for marine operators entering and
Lipa, Belina, et all; Japan Tsunami Current Flows Observed by HF Radars on Two Continents, Remote Sens.
2011, 3, 1663-1679; doi:10.3390/rs3081663, 3 August 2011
7
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departing San Francisco. Since the Bar Forecast was introduced, there has been a 50
percent decrease in the average number of annual U.S. Coast Guard rescue incidents in the
vicinity of the San Francisco bar.
Support to Local First Responders: When USAIR 1549 landed in the New York Harbor it was
MARACOOS partners’ real-time oceanographic information provided critical information to
New York’s Office of Emergency Management (OEM). Due to the nature of the crash
location, emergency teams realized that rescuing passengers from the slowly sinking plane
would be complicated due to the swift river currents. With surface water temperatures of
32F, timing was critical for removing passengers from the ice-cold waters, particularly
those passengers who had fallen into the water and those who had walked out on the
wings. Within 30 minutes of the crash, MARACOOS partners were working with New York’s
OEM regarding the water conditions. In the days following the crash, Stevens provided
around the clock on-call assistance to the various emergency agencies including the NTSB
in order to assist with the aircraft salvage operations.
Harmful Algal Bloom: NOAA has been a national leader in responding to Harmful Algal
Blooms (HAB) for over a decade. In response to a severe HAB event in the southeast in
1988, NOAA started the CoastWatch program—the first national capability to provide nearreal-time satellite imagery to state and federal managers. Today there is an operational
HAB bulletin for the Gulf of Mexico and pre-operational bulletins in the Northeast, Great
Lakes and Northwest United States. On the west coast the California Harmful Algal Bloom
Monitoring and Alert Program, in collaboration with CeNCOOS and SCCOOS have jointly
developed pier-based monitoring networks to complement existing monitoring provided
by the California Department of Public Health. Similar observations exist for Oregon and
Washington but are not currently linked to HABMAP. In 2005, the outbreak of HAB in the
Northeast was devastating. Through NOAA’s Gulf of Maine HAB program, scientists at the
Woods Hole Oceanographic Institution (WHOI) have developed a coupled
biological/physical oceanographic model to identify (1) whether the HAB will occur and
(2) where it will move once it occurs. In 2007 used this model and observations from
NERACOOS to predict that the season would be bad. This triggered additional sampling
and better tracking. Closures decreased and saved a good deal of money. Technologies
such as the Optical sensor on AUVs to detect Karena brevis and Environmental Sample
Processor (ESP) exist in research programs or are under development, and are
approaching transition to operations but currently have not been routinely incorporated
within IOOS.
Safe Drinking Water: The Great Lakes provides drinking water to 22 million people. The
resources provided by the Huron Erie Corridor face multiple conflicting uses including
waste disposal, water withdrawals, shoreline development, shipping, recreation, and
fishing. The Macomb / St. Clair Inter-County Watershed Management Advisory Group, a
local group of township and county officials, sought to expand their real-time water quality
monitoring/notification system to include a hydrodynamic model that could assist with
pollutant spill response planning. The Great Lakes Observing System (GLOS) worked with
this group and researchers at NOAA-GLERL and CILER to implement the Huron to Erie
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DRAFT IOOS Summit Report: September 18, 2012
Connecting Waterways Forecasting System and developed a tool for managers to use when
planning for spill events.
Storm Water Plume Tracking: The City of San Diego, Department of Environmental Health,
conducted simulation of particles tracking using near real-time HF radar derived surface
currents. The city uses the Tijuana River Plume Trajectory to help guide decisions about
sampling and beach closures. Ocean Outfall Impacts – SCCOOS responds to ocean outfall
diversions providing local views of near real-time surface currents, modeled surf zone
waves and currents, and meteorological observations. SCCOOS is able to initiate a plume
tracking simulation at the diverted inshore location to track discharge during the event.
This information proves beneficial for city managers deciding where to conduct intense
sampling for contamination, and presenting to present information to the public.
Economy:
Shellfish Industry Saved: The immense value of integrated Earth observations, and how
even small monitoring and observation efforts can make a huge difference, is evident in the
Pacific Northwest where oyster hatcheries on the verge of collapse just a few years ago are
again major contributors to the $111 million West Coast shellfish industry. The US IOOS
and NOAA’s Ocean Acidification Program, are helping to restore commercial hatcheries and
expected to reap an estimated $45 million for coastal communities in Oregon and
Washington. Real-time data from offshore U.S. IOOS buoys act as an early warning system
for shellfish hatcheries, signaling the approach of cold, acidified seawater one to two days
before it arrives in the sensitive coastal waters where larvae are cultivated. The data enable
hatchery managers to schedule production when water quality is good. Armed with better
information about the ocean conditions that oysters can and cannot tolerate, Taylor
Shellfish Farms in Washington State was able to adapt its operations, resulting in its best
year since 1989. Whiskey Creek Shellfish Hatchery in Oregon, a major supplier to the
majority of West Coast oyster farmers, also enjoyed substantial increases in its oyster
harvest. In 2008, productivity for Whiskey Creek was at just 20 percent of its normal level;
by 2010, it had risen to 70 percent.
Saving business money: The data from a PacIOOS buoy has saved fuel barge companies
from having to return to Honolulu full of fuel because the ocean conditions in the harbor
were too rough to safely discharge. Prior to the deployment of the buoy, two or three
barges a year would be forced to return to Honolulu at a cost to the barge companies of
approximately $22,000 per event. With the buoy in place since 2007, the barge companies
now have the ability to know ahead of time when they can safely make the drop off, and
have not had to return a single ship. In addition to saving the barge companies
approximately $66,000 per year, there is the benefit of improved safety and efficiency of
importing oil to the island, increasing crew safety, and reducing threats of damage to the
barge and risk of oil spill.
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DRAFT IOOS Summit Report: September 18, 2012
Safe and Efficient Shipping: The Physical Oceanographic Real-Time System (PORTS®) is
making shipping safer and more effective. NOAA developed the PORTS which integrates
and delivers environmental observations in real-time and through nowcasts and near-term
forecasts to users in many of the nation’s major ports. Studies in three different ports have
shown over a 50% decrease in groundings following the installation of a PORTS. Further
the realized quantifiable benefit from Columbia River PORTS data is about $7.4
million/year.8
Return on Investment: Dr. Kite-Powell has developed an economic framework for the
design, evaluation and enhancement of ocean observing systems. He employed this
framework within NEARACOOS. Dr. Kite-Powell estimates that the annual value generated
by NERACOOS data are about $6 million based on a 2.0M investment, or a 3 fold return on
investment9
Environment
Tagging and Telemetry: Aquatic animal telemetry technology, the science of analyzing
animal behavior with tracking devices known as “tags”, is operational and the community
is developing a strategic plan to establish a U.S. Animal Telemetry Network for the Nation
under U.S. IOOS. As part of this effort, U.S. IOOS collaborated with the Office of Naval
Research, the Naval Oceanographic Office (NAVOCEANO), the National Weather Service’s
National Centers for Environmental Prediction (NCEP), and the Tagging of Pacific
Predators (TOPP) Program at Stanford University’s Hopkins Marine Station on a 6-month
project with the goal to make data from tagged marine mammals more accessible to ocean
modelers from NAVOCEANO and NCEP. These targeted scientists expressed enthusiasm
about results after processing more than 8,000 historical and current observations from
TOPP that they could not access before. It turned out that these marine animals (elephant
seals) indeed sample areas of the ocean where there is poor or no data at all. This project is
part of an IOOS commitment to facilitate broader access to animal telemetry observations
for the nation’s ocean science community.
The Great Lakes Acoustic Telemetry Observation System (GLATOS) was launched by GLOS
to answer fisheries management and ecology questions in the Great Lakes. The system will
track more than 1,700 fish of four species – lake trout, walleye, sea lamprey, and lake
sturgeon – tagged between 2010 and 2013. Tracking information will influence a range of
fish population restoration actions, including improved sea lamprey control, better data for
fish stocking decisions, and enhanced understanding of fish spawning behavior.
Kite-Powell, Dr. Hauke Kite-Powell; Estimating Economic Benefits from NOAA PORTS® Information: A Case
Study of the Columbia River, June 2010, http://tidesandcurrents.noaa.gov/pub.html
9 Kite-Powell, Dr. Hauke and Morrison, Dr. J. Ruairidh, Observing System Infrastructure and Economic Value,
US IOOS summit white paper, July 2012
8
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Another example comes from the Mid-Atlantic region, where a new habitat model is being
used to help fishermen reduce the number of butterfish caught unintentionally while
trawling for squid. IOOS partners at the University of Delaware are combining satellite
data with radar information on ocean currents to develop a model predicting where
butterfish populations are most likely to be on any given day. The study is a collaborative
effort with the Garden State Seafood Association, the National Marine Fisheries Service, and
Mid-Atlantic Regional Association Coastal Ocean Observing System (MARACOOS) scientists.
Researchers recently tested the accuracy of predictions with an eight-day field experiment,
sending daily reports to a fishing vessel roughly 200 miles offshore. Overall, the model
pointed the boat in the right direction based on features of the ocean’s surface. The
fishermen’s initial feedback on the model is that they could use it in a similar way to
weather forecasts, in providing general guidance on when and where to drop nets. The
collaboration between the fishing industry, academia, and government demonstrates how
real-time ocean observing can help fisheries and aid ecosystem management
D. Partnerships
International
Through the GOOS umbrella, there have been a number of milestones. OceanObs’09
provided an opportunity for us to evaluate the decade of progress since OceanObs’99.
From an observing perspective the number of observations grew from 4.5 million
oceanographic reports to more than 16 million. The Tropical Ocean-Atmosphere (TAO)
array, a legacy of the Tropical Ocean-Global Atmosphere program, has expanded to be the
TAO-TRITON (Triangle Trans-Ocean Buoy Network) array in the Pacific with a series of
standard moorings, flux reference sites, CO2, and biochemistry sites, and expanded PIRAT
array in the tropical Atlantic, and the beginnings of a Research Moored Array for the
African-Asian-Australian Monsoon Analysis and Prediction (RAMA) array in the tropical
Indian Ocean. With the development of the profiling float technology under the World
Ocean Circulation Experiment (WOCE), ARGO reached its target of 3000 floats in 2005. A
new observing platform has been added – the OceanSITES (OCEAN Sustained
Interdisciplinary Time series Environmental observation System) program. OceanSITES
consists of approximately 100 moorings, considered sentinel sites, providing high quality
air-sea flux data in key, unique, or strategic portions of the global ocean.10
Technology innovation has enabled the sharing worldwide of ocean information. The
Global Ocean Data Assimilation Experiment (GODAE), Array for Realtime Geostrophic
Oceanography (ARGO) and the Global High Resolution Sea Surface Temperature (GHRSST)
programs have shown that it was possible to reach consensus on common standards. With
the emergence of portals that can serve data to users in real-time, a number of Global Data
Busalacchi, A., Celebrating a Decade of Progress and Preparing for the Future: Ocean Information for
Research and Application. In Proceedings of OceanOBS’09; Sustained Ocean Observations and Information for
Society (Vol.1), Venice, Itlay,doi:10.5270/OceanObs09. pp 45
10
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centers such as GHRSST, ARGO, Global Ocean Surface Underway Data (GOSUD) and the
Joint Technical Commission for Oceanography and marine Meteorology (JCOOM) Observing
Platform Support Center exist. We have seen the emergence of global solutions to facilitate
the sharing of biodiversity data that include the Global Biodiversity Information Facility
(GBIF) and the International Ocean Biogeographic Information System (OBIS. The
associated regional nodes, (e.g. OBIS-USA) and focused taxonomic nodes (e.g. OBISSeamap) have developed worldwide infrastructure to publish and therefore share their
data.11
International collaboration takes many forms. Through GOOS and the Global Climate
Observation System (GCOS) international efforts such as those described above take place.
There is also direct contact between national observation systems such as US IOOS and
Australia’s Integrate Marine Observing System (IMOS) that allows for the exchange of
information on the implementation of the national system. Emerging ocean observing
systems such as the United Kingdom’s Integrated Marine Observing Network (UK-IMON)
plan to take lessons learned from both US IOOS and IMOS as they establish their network.
Partnerships are about peoples and the following example on the RAMA network
exemplifies this wonderfully. Sid providing example for Indian Ocean partnership
GOOS is a participating organization to the Group on Earth Observations. Within the
workplan 2012-1016 for the Global Environmental Observation System of Systems the
contribution of the ocean is recognized under the societal benefit area titled Blue Planet.
GEO is another construct in which the importance of ocean observing can be articulated in
the context of global earth observations. The emphasis under Blue Planet is sustained
ocean observations and information, improve the global coverage and data accuracy of
coastal and open-ocean observing systems, and developing a global operational ocean
forecasting network. The tasks in the Blue Planet build continue the work of GOOS and
introduce some new programs such as the Global HF Radar initiative. The United States
has been working many years to transition its HF radar network to an operational system
and has succeeded in moving from individual radars to clusters of radars to a
omprehensive national networked tied together through a common data architecture, set
of practices and a national plan. Many other nations have begun to deploy HF radars and
there is a tremendous amount of informal coordination and collaboration that is taking
place. We believe that we can all capitalize on this coordination by coming together more
formally under GEO and accelerate the transition of operations of all HF radars through this
effort.
Industry
Industry is an important stakeholder for IOOS and is involved as providers, intermediate
users and end-users. As providers of observing system infrastructure there are a number
11Pouliquen,
S;,Hankin, S.,Keeley, R., Blower, J.,Donlon,C.,Kozyr, A.,Guralnick, R., The Development of the Data
System and Growth in Data Sharing. In Proceedings of OceanOBS’09; Sustained Ocean Observations and
Information for Society (Vol.1), Venice, Itlay,doi:10.5270/OceanObs09. pp 31.
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of industries that are worldwide leaders and have grown as a result of GOOS, IOOS and the
National Ocean Partnership Program. While a comprehensive inventory has not been done,
three areas include HF Radar, Gliders and marine instruments. The work on HF Radar
began within NOAA research laboratories in 1968, led by Don Barrick. In 1984, the core
team left the Government to form CODAR Ocean Sensors, California. As the US HF Radar
network grew in the 2000, it provided a launching pad for sales globally. Today the CODAR
SeaSonde® comprises 95% of the US HF radar network and make up 80% of all HF radars
built worldwide. For Gliders, US companies make up 95% of the market. There are 3 US
profiling gliders in production. Teledyne Webb Research, now part of Teledyne Benthos,
invented and builds the Slocum glider. University of Washington developed the Seaglider
and continues to build the research version; IRobot has the commercial license. Scripps
Institute of Oceanography builds the Spray gliders which were licensed in 2004 to Bluefin
Robotics. Liquid Robotics has developed the first surface glider powered by waves. SeaBird Electronics, Inc., Seattle Washington, is the largest manufacturer of marine
instruments for the measurement of salinity, temperature, pressure, dissolved oxygen, and
related oceanographic variables. Customers include research institutes, ocean observing
programs, national and local government agencies, engineering firms, and navies
throughout the world. (http://www.seabird.com/about_seabird/aboutsbe.htm) ))
A challenge identified by the US IOOS summit white paper – Options for Integrating Private
Sector Oceanographic Data, is that as government budgets face increasing downward
pressures, innovation allows for lower cost ocean observing technologies, thereby
increasing the likelihood of expanded private sector capacity. There area a range of
opportunities and challenges IOOS faces in balancing the policy of open access to data,
generating the most economic activity and ability for these companies to be part of IOOS
and still maintain profitability.
The open access to weather data has spawned many intermediate users/companies. IOOS
desires to b a similar foundation for ocean related value add companies.
Surfline/Wavetrak, Inc. ("the Company") was incorporated on September 10, 2001 and is
aareare provider of surf report, forecast and editorial content to consumers, businesses
and government agencies worldwide. In 2003, the Company acquired buoyweather.com
("Buoyweather"), a popular website for boaters, sailors, anglers and divers. Buoyweather is
unique from its network of "Virtual Buoys" that provide focused marine data for coastal
and offshore areas in the world. From each virtual buoy point, users are able to gauge
current wind speeds and swell heights, as well as garner a seven-day marine forecast for
that precise location. Surfline relies on government observing system and model output for
their work. Roffer's Ocean Fishing Forecasting Service, Inc. (ROFFS™) is a scientific
consulting company based in Miami and West Melbourne, Florida (U.S.A.) that is involved
with fisheries oceanography and environmental science. ROFFS is both a user and provider
of ocean information to US IOOS. Many of the sources of their information are based on
government funded remote sensed and in situ data. ROFFS remains active in both the
scientific community, as well, as the fisheries resource management community locally,
regionally, nationally and on an international basis. They are currently funded by the
National Aeronautics and Space Administration (NASA) to study the effects of climate and
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ocean variability on pelagic fish resources and to develop easy-to-use tools for resource
managers. They are a member of NASA’s Biodiversity & Ecological Forecasting Science
Team.
E. Introspection
Significant progress has been made on delivering the promise of US IOOS but both
external and internal factors have inhibited our progress. This workshop presents an
opportunity to reflect on those circumstances and establish a realistic vision for moving
forward. We note first that, externally, the fiscal environment during the previous decade
did not lend itself to large infusions of resources for IOOS and that the present budget trend
is, at best, level. Thus, significant increases in discretionary spending for IOOS® are
unlikely. We have also however been and remain impacted by internal factors over which
we do have some ability to influence and the list below provides representative examples
of those:
 The ICOOS Act provides a comprehensive definition of US IOOS that includes
contributions by all civilian Federal Agencies but it is not clear that this definition is
fully embraced in a budgetary or staffing sense by these agencies
 The US IOOS Program office is a good start on an interagency office but it is not truly
an inter-agency Program Office funded and enabled, i.e. possessing inter-agency
authority? Influence?, to implement national IOOS plans
 A consensus among stakeholders on IOOS priority goals has yet to be achieved, i.e.,
IOOS proponents have failed to develop a consensus view as to what is most urgent,
what can be done now, what can wait, what has large payoff in the near-term;
 A leadership team of committed people in key positions inside and outside the
federal government has yet to develop;
 Although there have been many attempts to quantify economic costs and benefits of
IOOS, the results have not been compelling to date, in part because many benefits
are for the public good and are not established in the marketplace.
 The ocean research community has yet to recognize the value to the research
enterprise of establishing an IOOS, and, ironically, the proponents of IOOS are still
perceived to champion an academic-researcher focus on science questions instead
of research applications and the potential economic benefits of IOOS®;
 There are many examples of Regional successes and we have demonstrated that the
enterprise has the ability to maintain a national network (e.g Hf Radar) and respond
to crisis but we are perceived as pursuing too many priorities and therefore taking
too long to make progress.
 Interdependcies between Fed, State, Local, Academia and NGO are expressly
encouraged – this is a valuable position but its adoption presents a very complex
business model. If one funding stream (primarily the Federal) is decreased than we
lose exponential capability because no-one can make up that funding stream
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Chapter 2:
Users Requirements
I. Introduction
In common with the wider frameworks of GOOS and GEOSS, IOOS delivers a number of key
benefits to users. Through federation of common requirements IOOS permits more
effective and timely delivery to existing users of marine data and information. Through
better integration of their needs, and the use of common data infrastructure, analyses and
models IOOS enables improvements to existing uses through better quality core data and
information. Finally, IOOS enables a range of new uses by virtue of delivering better
understanding and prediction of open ocean, coastal and great lakes processes.
At the Airlie House meeting the needs of users were only poorly understood and this
meeting concentrated on formulating a scientific, technical and governance structure for a
US IOOS. Later, the nascent IOOS structure that emerged from this vision moved towards a
focus on delivery of core data and information required to meet a specific set of uses. In the
next decade IOOS must move towards delivering a comprehensive range of core data and
information needed to fully support the common data and information needs of all users
and able to respond quickly and effectively to emerging needs. To do so IOOS must develop
a clear understanding of the stakeholders engaged in the IOOS enterprise securing their
continuous engagement as beneficiaries and advocates.
Stakeholders in planning, construction operation and use of IOOS comprise three main
categories:

Providers of observing system infrastructure and outputs;

Intermediate users who take U.S. IOOS data or information and tailor it for a
specific end-use;

End-users whose activities or businesses benefit from U.S. IOOS data and
information.
Providers of observing system infrastructure include manufacturers of sensors,
instruments and platforms; operators who deploy, run, and maintain the in situ observing
stations; those building, launching and operating satellite systems; those providing the
cyberinfrastructure that interconnects the U.S. IOOS components; and organizations that
develop and maintain the data management systems, software tools and models that are
used to turn U.S. IOOS data into useful information. Intermediate users are organizations
that add value to U.S. IOOS outputs tailoring them for specific end-uses. End-users are the
ultimate beneficiaries of U.S. IOOS. They use value added products generated in whole or in
part from U.S. IOOS data and information as an input to their activities or businesses to
derive specific scientific, societal or business benefits.
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End-users of U.S. IOOS data and information fall into four main types:

Operational end-users who make use of ocean data and information to support
decision making related to safety, economic efficiency and protection of the
environment;

Science end-users who undertake research activities that rely in whole or in part
on sustained measurement and observation of the oceans. These include academic
scientists, modelers, mariners, commercial fishermen, and others needing access to
data most usually in near real time for business decision-making;

Policy end-users who require sustained ocean data and information to support
policy formulation, monitoring of policy compliance, and assessment of policy
effectiveness;
Public end-users who are primarily interested in accessing products that
synthesize or analyze data to provide specific information relevant to their leisure
activties (e.g, recreational boaters, divers, and fishermen; beachgoers; surfers).

To understand how the various user groups and their requirements have evolved over the
last decade, we turn first to an understanding of the identification of the diverse
contributors of infrastructure, including data and products, and the determination of the
core variable requirements for the integrated system. It is significant to note that the
providers of data, products, and information are actually the first users with requirements
for those data, products, and information because the data collection and product
development is done to meet specific mandates and responsibilities of those
user/providers.
A broad consensus was achieved at the Airlie House Workshop regarding the vision and
direction for U.S. IOOS including identifying twenty16 high priority core variables necessary
to meet the seven societal goals. This variables was codified in the US IOOS development
plan, the IGOOS Coastal Theme Report and the GOOS – Coastal Module Implementation.
These variables were increased to 26 in the US IOOS Blueprint. There are two important
caveats about the requirements that came out of the Airlie House Workshop:

There was not a good balance among groups with interests in ocean observations.
There was too much emphasis on physics and user groups other than scientists
were not well represented.

Workshop participants acknowledged that there were many variables that were
important for detecting and predicting changes in coastal marine and estuarine
ecosystems, but that not all of these variables were appropriate for implementation
on a national scale. Rather, these variables and time-space scales were to be
considered by regional observing systems based on priorities established by
16 Bathymetry, Bottom character, Contaminants, Dissolved nutrients, Dissolved oxygen, Fish abundance, Fish species, Heat flux,
Ice distribution, Ocean color, Optical properties, Pathogens, Phytoplankton species, Salinity, Sea level, Surface currents, Surface
waves, Temperature, Zooplankton abundance, Zooplankton species. Note that an additional six variables have been added to the
U.S. IOOS core variable list (GOOS No. 125, 148); these are: Acidity (pH), Colored dissolved organic matter, Partial pressure of
carbon dioxide (pCO2), Total suspended matter, Wind speed and direction, Stream flow.
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stakeholders in each region.
This background is relevant to clarify that it was these providers-users whose
requirements informed the Airlie House workshop, and whose goals did not include
explicit identification of other users and their requirements.
What did we know about user requirements 10 years ago and how does it compare to
today? A decade ago, the community of people interested in the Global Ocean Observing
System had accepted the seven societal goals determined through the discussions and
negotiations of nations during the formulation of the international GOOS. In 2002, the
planning participants focused on identifying and prioritizing the core variables required to
address those seven societal goals. They also recognized the need to have regional
organizations that would gather information from the regional stakeholders on the regionspecific needs—the birth of the concept of the Regional Associations.
In the ensuing ten years, the Regional Associations have been established with a strong
focus on regional engagement. They have engaged with users in many different ways, as
described in Section 2. Today, we see that the decade of engagement with users of all types
has resulted in a much improved and stronger understanding of the wide range of users,
their interests, and the types of data, products, and information they may need to improve
their decision-making both for their communities and themselves. But the engagement
needs to go further to have truly integrated users that are also providers and advocates for
U.S. IOOS.
The engagement has brought the benefits of a sustained, integrated ocean observing
system into the greater awareness of many of the identified user communities. They are
seeing that the mature U.S. IOOS will deliver benefits in multiple ways that otherwise are
not available. The mature U.S. IOOS will ensure that users are fully aware of what is
available through a consolidation of information on resources, data, products and
information and seamless linkages between the providers and the users. It will ensure that
data are available in consistent and easily used formats and are of reliable quality through
standardizations made possible by the Data Management and Communications subsystem.
U.S. IOOS will provide benefits to users by:
1) making use of observations, measurements, and model outputs in a structured way to
generate gridded data sets and other integrated products needed for decision-making,
2) filling gaps in observations both as to type of variable and location,
3) insure the continuity of datasets, and
4) delivering data products of known quality in machine-to-machine or other user-selected
formats.
Yet the U.S. IOOS is not mature, but is still in its adolescence. Over the next decade, the
engagement process must continue unabated to ensure that new providers continue to be
entrained into the U.S. IOOS, the engagement with users continues to provide the
information on changing requirements as the oceanic and Great Lakes’ states change, and
the information on providers, users, and requirements continues to be consolidated and
used to inform the decisions on the development of the U.S. IOOS to meet the user
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requirements. In all these engagement activities, the Regional Associations will remain at
the forefront of the effort to evolve the coastal module of U.S. IOOS to meet the needs of our
nation and its regions.
Section 2 provides the information on what we have learned about the user engagement
process and the types of users and their requirements for their activities associated with
the coastal ocean and Great Lakes. It also provides examples of successful user engagement
efforts to guide future engagement activities. Section 3 examines the challenges involved
with understanding and meeting user requirements. It also discusses the opportunities
these challenges present to shift in the current paradigm for resource allocation and data
sharing. Section 4 summarizes the recommendations.
II. Users and Their Requirements
Significant progress has been made in the last decade by the U.S. IOOS enterprise and
global ocean observing communities in defining user requirements. These advances are
accompanied by an increase in scientific understanding, sensing capability, and
information technology. These advances add complexity to the task of maintaining an
effective user engagement system, in which defining requirements are but one component.
A. Hallmarks of Successful User Engagement
Successfully defining user requirements is an iterative process characterized by mutual
understanding, commitment, and trust between the user and provider. The "corporate
culture" of the U.S. IOOS must be one where engagement is a top priority; ; if the
organization's culture does not have an interest in building the U.S. IOOS, a mere change in
personnel can undermine previously positive engagement. Building understanding,
commitment and trust takes efforts that must necessarily be funded at a significant enough
level to make a difference.
At the level of the Global Module of U.S. IOOS, engagement is usually conducted within the
spheres of federal agencies and their consultants and contractors, with some reasonable
level of funding supporting the efforts due to the international characteristic of the
engagement.
At the level of the Coastal component, the U.S. IOOS Program Office and the agencies of the
Interagency Ocean Observing Committee are serving in effect two masters. In many cases
the contributions by the Federal agencies are assets that support the agencies mission and
US IOOS needs to create those overarching user requirements where the contributions
create a situation where one plus one equals three. These need to be better integrated into
the U.S. IOOS—both to more fully represent all the user groups and to improve entrainment
of the data, products, and information from these agencies into the System of Systems.
There is some level of funding for the IOOC agencies to engage with each other in the U.S.
IOOS enterprise, and this Summit is one example.
The U.S. IOOS Regional Associations (RAs) operate on the local, regional, and even national
scales of user interfaces. The RAs have devoted significant resources, including voluntary
efforts by partners, to user engagement. As a result, the RAs have established strong
relationships with many users and have worked to define the requirements of those users
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over the last decade. This progress, however, needs improvement and an infusion of
additional resources if we are to substantially increase the value and support for the U.S.
IOOS infrastructure.
The level of engagement of users, in the way originally envisioned for the U.S. IOOS
enterprise, has ranged from excellent to mediocre. A few examples are given below.
Example 1: eMOLT17, developing a solution to a data deficiency
There is always a shortage of in-situ data for the assimilation and validation of coastal
ocean circulation models. In the Northeast Region, the Environmental Monitors on Lobster
Traps (see http://emolt.org) project has been developed to address that problem by
working with lobstermen to place sensors on their traps. Start-up funds were provided by
NOAA’s Northeast Consortium, maintaining the program requires a minimal investment for
low-cost replacement probes approximately every five years and a few months of
personnel time each year to process the data. There is now more than a decade of hourly
bottom temperatures at dozens of fixed locations as a result of this program. Salinity
sensors, bottom-current meters, acoustic listening devices, tide-gauges, and underwater
cameras have also been deployed on the traps and have provided valuable data. The
cameras, in particular, are popular with the fishermen and can provide a time series of
biological activity. The fishermen also assist with deployment and recovery of student-built
satellite-tracked drifters in order to help document surface current flow (see
http://www.nefsc.noaa.gov/drifter). In addition to providing data for assimilation and
validation of coastal ocean circulation models, the project has engaged many fishermen in
the process of monitoring their environment. These fishermen spend their days at sea,
have the biggest stake in preserving our coastal marine resources, and are most
knowledgeable of the local waters. This is an excellent example of developing a solution to
a data deficiency, which resulted in engaging users by turning them into data providers.
Example 2: A successful R2O process involving USCG Search & Rescue
The US Coast Guard (USCG) requirements for its Search and Rescue Optimal Planning
System (SAROPS) include timely and accurate nowcast and forecast fields of surface winds
and sea surface currents.18 While providing these data to meet the user requirement seems
straightforward, requirements for the operational information technology that supports
SAROPS are quite robust, and the time and resources required to operationally ingest sea
surface currents are significant. Introducing new observing technologies into the SAROPS
requires substantial testing and the USCG had to be convinced that a new technology was
worth considering. MARACOOS has a substantial High-Frequency Radar capacity in the
mid-Atlantic region; engaging with the USCG and the U.S. IOOS Office, their scientists
worked to demonstrate the viability of these data sets for use in Search and Rescue. The
results of a four-day test in July 2009 showed that when HF radar data were ingested into
the Search and Rescue system, the search area was decreased by 66%, allowing crews to
17
Manning CWP
18
Art Allen CWP …
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DRAFT IOOS Summit Report: September 18, 2012
focus their efforts and save more lives. Significant investments were and continue to be
made by the USCG, U.S. IOOS Office and RA partners, and the use of this data is currently
being integrated in to SAROPS on a national level. This example illustrates the time (years)
it can take to fully transition from research to operations, and the commitment of all
involved parties that is required to pursue the project to successful conclusion. Yet even
this successful project that saves lives has not resulted in an expansion in the HF Radar
assets distributed across the country; so the positive feedbacks of even a successful R2O
process do not necessarily translate into additional resources.
Example 3: Changing “corporate culture”
Early in the formulation of the U.S. IOOS vision, the National Data Buoy Center (NDBC)
became committed to the concept. As part of that commitment, NDBC took on the task of
becoming the U.S. IOOS Data Assembly Center (DAC). As the IOOS DAC, NDBC collects data
from regional ocean observing systems, quality controls the data, and distributes it via the
Global Telecommunications System (GTS) in realtime. NDBC also makes the quality
controlled data available on their web site and via netCDF files. NDBC applies automated
quality control algorithms before releasing the data in realtime and also performs
additional quality assessments on daily and monthly views of the data. As a result of the
NDBC efforts on behalf of U.S. IOOS, there are ~400 additional, non-federal observing
stations in the coastal ocean and Great Lakes that are part of the federal data stream that
goes out over the GTS (Figure 1). This compares to the ______ federal stations that are in this
data stream. These data are part of the data that are ingested by operational and other
forecast modeling communities. Operational agencies that are accessing the GTS are users
of these non-federal U.S. IOOS data, but most of them are not aware that they are
substantial users of U.S. IOOS data. The NDBC early on became engaged in the U.S. IOOS
vision as a user and a provider; it committed itself to undertaking a substantial role in the
IOOS data streams and it has remained fully engaged in this effort. This example illustrates
how a federal agency changed its "corporate culture" to entrain itself into the vision for the
benefit of the nation.
Figure 1. Stations in the IOOS DAC operated by NDBC. Showing stations at
2200 CT on 8/26/12 (available at <http://www.ndbc.noaa.gov/obs.shtml>
by selecting "IOOS Partners" in the Program Filter).
Example 4: Data is not enough, it needs to be analyzed?
The Gulf of Maine buoy array of the Northeastern Regional Association of Coastal Ocean
Observing Systems (NERACOOS) has provided continuous oceanographic measurements
for over a decade. Currently there are seven buoys in the array sited at coastal shelf depths
ranging from 50 to 250 m and providing temperature measurements at 3-7 depths
throughout the water column. Analysis of this time series shows statistically significant
warming trends at all depths for all locations, providing the first depth-resolved rates of
temperature variability for the U.S. East Coast from continuous data (need to cite CWP).
Ecosystem data, however, are lacking so there is no telling what impact this warming
condition will have on the ecosystem. The key requirement for climate scientists is long,
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continuous data sets, to enable statistically significant analysis, that measure both
biological and physical parameters. However maintaining support for long-term datasets,
especially ecosystem data, is difficult. But the data in and of themselves are not enough to
reap the full benefits of U.S. IOOS; data integration into products useful to business and
informational end-users is important. Although data sets are products, the impact of the
data is limited without human resources dedicated to analyzing the data and pushing
results found to other, engaged users. User engagement is successful when the data are
integrated together in new ways to provide new understandings or new information for
decision-making. Some value added products will be produced by businesses, others will
be produced for the general public by Regional Associations and/or governmental
agencies.
Example 5: Catastrophes radically change users requirements
Sudden catastrophic events, such as Hurricane Katrina and the Deepwater Horizon oil spill
that occurred in the Gulf of Mexico can have profound and sudden impacts on user
requirements. Twice in just five years, the GCOOS-RA stakeholder engagement effort was
altered from a steady pace of engagement, entrainment and building solid commitments
with users and providers to an on-demand, urgency-driven engagement process with
myriad new stakeholders entering the Gulf in the wake of these events. Ongoing projects,
such as the development of a HAB Integrated Observing System, were postponed in order
to deal with these emergency situations. Engagement personnel, many of whom were
volunteers facing their own major issues of losses associated with these and similar events,
were stretched thin. The dramatic changes in stakeholder needs caused by these events
reverberate in the engagement process still today. Both of these events effectively imposed
a prioritization scheme on a response and monitoring system that had no mechanism for
establishing priorities. The responses to both of these events emphasizes how powerful
and effective prioritization can be. (can we say anything about how the system had
evolved since Katrina, and that it was thereby better able to deal with the Deepwater
Horizon oil spill?)
In addition to extreme events like Hurricane Katrina and the Deepwater Horizon oil spill,
other changes in the environment and climate, such as such as increases in hurricane
intensity, habitat losses from sea level rise, new invasive species, and increases in HABs
will also impact user needs for data, products, and information. It is imperative that the
system be designed to be able to recognize and response to changing user needs.
B. User Engagement Steps
To understand user requirements with the specificity needed to transition from the
research stage to operations, users, in addition to providers (of data, products, etc.), must
be fully engaged. Successful user engagement is an iterative process. The eight user
engagement steps presented here demonstrate the scope of an engagement process geared
to integrating users and making them advocates. While applicable to most user
engagement processes, these steps are described as they apply to U.S. IOOS. The steps
emphasize the resources necessary to generate user pull, which is largely lacking in the
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current U.S. IOOS infrastructure. In the next section, the challenges involved with each of
these steps are discussed in detail.
1. Identify the users. This seemingly straightforward step has been a major undertaking.
Considerable progress has been made over the last decade to identify and build
relationships with the users both of a nascent U.S. IOOS and a mature U.S. IOOS. See
subsection C immediately following for identification of these users.
2. Prioritize the users and/or the products. Existing and potential users of U.S. IOOS are
extensive, which follows from U.S. IOOS having a purposefully broad scope and impact.
However, limited resources require that we prioritize who we are going to serve and/or
what the system will serve, in terms of products or services.
3. Define user requirements. Defining user requirements is an iterative step that can
only be executed if adequate human resources are committed to the process. Each
user's decision processes and operational needs must be fully understood Users
requirements also extend to data access and dissemination, and are not restricted to
just the data.
4. Develop Solutions. This is the iterative development stage marked by partnering of the
RAs and IOOC agencies with private enterprise, non-governmental organizations,
and/or local, tribal, state, and federal agency partners. A key to success in this step is
keeping the user engaged and understanding that several options, iterations, or
versions will likely be necessary before users are satisfied. Additionally, since this
process can take months and years, user requirements will evolve requiring adjustment
to solutions.
5. Conduct Outreach. In the private sector, this step is called marketing. Products will
not be used if users are not aware and interested in trying them. This is the step that is
most often cut from public section development programs. It is a highly important step
to achieve, but requires infusion of human resources and funding to keep moving
forward.
6. Assess and Maintain Products. Follow-up assessments are required to ensure the
data, product, or service continues to meet the user's need. Maintenance is critical to
keep the user groups, their requirements, and the associated human and other
resources necessary to meet the requirements up-to-date with the changing states of
the ocean and Great Lakes. When accounting for resource needs to meet requirements,
the long-term cost of maintenance of the system must be included.
7. Provide Training. Training of the technicians, programmers, scientists, educators, and
others who will be needed for a mature U.S. IOOS is required. This step in engagement
is often overlooked and hence under-planned with needed advances in training
capabilities being under-funded.
8. Enable Advocacy. Through outreach (step 5), the users will better understand what
the U.S. IOOS enterprise is trying to accomplish as a whole and for them as a user group.
This understanding, coupled with successful provision of data, products, and
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information needed by users will lead to user-initiated advocacy for the enterprise,
effectively turning end users into U.S. IOOS advocates.
An obvious conclusion from this discussion is that significant, well-qualified human
resources are necessary to maintain effective user engagement. The U.S. IOOS enterprise
must recognize importance of this process, and support implementation of a user
engagement infrastructure in order to successfully become the envisioned System of
Systems delivering critical and unique products to diverse users.
C. Current Knowledge of User Requirements
An exhaustive discussion of what is known of existing user requirements is beyond our
scope. Table 1 presents a condensed list, and illustrative examples. Today, as opposed to
ten years ago, sources of information on users requirements are extensive, and include
1. U.S. IOOS Summit community white papers (For requirements associated with SAR,
HABs, waves, offshore renewable energy, and ocean acidification, see Allen,
Anderson, Bailey, Birkemeier, Hall, and Gledhill papers, respectively.)
2. Regional Associations' Ten Year Build Out Plans (See
http://www.usnfra.org/buildout.html for a synthesis of user needs and 29 common
products identified in the RA Plans, grouped by societal themes).
3. National Operational Wave Observation Plan (March 2009), which includes plans for
a surface-wave monitoring network to meet the maritime user community’s needs.
4. Plan to Meet the Nation’s Needs for Surface Current Mapping (September 2009),
which delineates plans for a national network of high-frequency radar stations to
support search-and-rescue efforts and oil-spill response, among other societal
needs.
5. U.S. Integrated Ocean Observing System: A Blueprint for Full Capability Version 1.0
(November 2010), which “identifies, describes, and organizes the specific functional
activities to be developed and executed by U.S. IOOS partners”. Additionally, the U.S.
IOOS Office is developing a series of perspective papers, including one on user
requirements and gap analysis.
6. Requirements for Global Implementation of the Strategic Plan for Coastal GOOS, Panel
for Integrated Coastal Observation (PICO-I) (July 2012)
Systematic organization of the requirements from these and other sources is in progress
and will begin to address some of this chapter’s key recommendations. The RAs have made
an effort to begin the task of organizing the requirements, both for products and data, of
four major user categories that tie into the seven societal goals: Marine Operations19 ,
Coastal Hazards20, Ecosystems, Fisheries, and Water Quality21, and Long-term Variability22.
hyperlink to Table __ in RA Build-out Plan (BOP) Synthesis
hyperlink to Table __ in BOP
21 hyperlink to Table – in BOP
22 hypelink to Table __ in BOP
19
20
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These requirements were summarized from the 10-year Build-out Plans of the 11 RAs,
which in turn derived their requirements from their extensive engagement with their
regional communities and user groups. Note that the RA engagement included the regional
offices of many federal agencies.
III. The Current Challenges
Below we discuss the challenges associated with each of the user engagement steps just
outlined. Many of these challenges are related to communication and coordination. How
can the requirements of users and stakeholders be better documented and communicated
to data providers and those developing the infrastructure of U.S. IOOS? How can the public
and other potential users be made more aware of the data available through U.S. IOOS?
How can different federal agencies, different countries and different RAs coordinate to
meet the diverse array of user requirements? How can we prioritize activities to address
user requirements? How can we ensure that users are properly engaged in the transition
from research to operations for observational data streams and models?
There are also technological, financial and ideological challenges involved with meeting
user requirements. For example, many users want biochemical measurements, but the
system has been primarily focused on physical measurements. Due to lack of resources,
users are often asked to supply funds in order to see their requirements fulfilled, which
alienates that user community. Lastly, there are ideological or cultural challenges involved
with different communities working together: the research/academic and operational
communities, the public, private and university sectors, different federal agencies and
different countries. Each of these different entities or communities have a different
attitude or perception on what user requirements are. These challenges are discussed in
further detail below.
Challenge 1: How can we identify the users of U.S. IOOS?
This challenge has been met. In fact, we have possibly been too successful since the range
of users that are and could be served by U.S. IOOS is so extensive it is difficult to know how
to tackle serving them.
Recommendation 1: Organize information about users, their requirements and available
products into a “marketplace” that will serve to match users and producers, incite efficiency
through sharing of products and decreased duplication, and result in an evolving list of users.
Among the 11 Regional Associations, work has been done to identify which products are
common to all the RAs. This could serve as a starting point for the “marketplace.”
Additional information on users and requirements is included in the references listed in
Section C. However, this recommendation for a marketplace is NOT a recommendation for
a bureaucratic, burdensome, rigidly controlled requirements database.
Challenge 2A: How can different federal agencies, different countries and different RAs
agree on priorities since resources are not available to meet all user requirements?
Setting priorities for an enterprise with the scope of U.S. IOOS is a daunting task.
Cooperating can be difficult within different parts of a single federal agency, and even more
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so between different federal agencies. However, businesses and agencies and RAs are all
establishing priorities now, although they might not explicitly acknowledge that is what
they are doing. The current economy requires that choices be made about where money
will be spent. However, the rules governing U.S. federal agency budget development
present seemingly impossible obstacles to developing U.S. IOOS-wide priorities.
At the global scale, there is increasing recognition that the U.S. will have to rely on foreign
sources of satellite data in the coming years to meet our requirements for environmental
satellite data. The Committee on Earth Observation Satellites (CEOS23, part of GEO24) is
coordinating environmental satellite observations of the Earth. While these are high level
issues discussed elsewhere in this report (Chapter 3), they are pertinent to users
requirements because different agencies or entities have different mandates, and therefore
different priorities. With limited resources, if we can only meet 2 of 3 requirements, who
gets left out? And who decides? And who explains the process to the user whose
requirements are not being met? There are also cultural challenges associated with
different agencies and communities working together, which are discussed in Challenge 2B
Prioritization should not stifle creativity or entrepreneurship. Given the structure of U.S.
IOOS with its global, federal, and coastal (which includes national and regional) levels,
priorities will be needed at each of these levels. Leadership, partnership and commitment
from each of the U.S. IOOS levels would be required to 1) agree to a priority setting process,
and 2) establish meaningful priorities. In this context, meaningful priorities are ones that
guide budget decisions. The framework and process for establishing priorities must
respect the diversity of the key stakeholders in U.S. IOOS, which includes unique regional
and mission-agency interests. Additionally, care must be exercised to assure that the
priorities are not defined so broadly, i.e. marine operations, ecosystem management, etc.,
that they fail to clarify how available funding and other resources should be directed.
Recommendation 2A(i): Develop an “Action Agenda” for U.S. IOOS that prioritizes nearterm investments and steps along the path to a fully operational system.
Rather than attempt to get unanimous consent on some small number of priorities across
the entire U.S. IOOS enterprise, we propose a smaller scale effort to begin to organize
current organization/individual-specific priorities into shared priorities. This
recommendation suggests that U.S. IOOS priorities are not necessarily the same as NOAA or
Weatherflow or NFRA priorities, as examples. However, we should be able to identify some
priorities to which several, maybe not all, U.S. IOOS stakeholders will commit resources.
Recommendation 2A(ii): Devote a portion of each IOOC meeting agenda to resolving
coordination issues delivered unfiltered and confidentially (i.e. not passed through
multiple levels of approval) from any user or stakeholder, to the IOOC.
A mechanism is needed to begin to chip away at the coordination issues that will obviously
plague an enterprise like U.S. IOOS. We believe that the IOOC is the proper place to vet
these issues, and to provide a safe mechanism for discussion.
23
24
http://www.ceos.org/
http://www.earthobservations.org/
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DRAFT IOOS Summit Report: September 18, 2012
Challenge 2B: There are cultural challenges associated with different communities
working together, and each has a different attitude or perception on user
requirements.
In 2012, it is safe to say that the United States’ ocean observing community has never been
as organized, collaborative and disciplined towards common national goals and objectives.
However, challenges remain at the interface of the various sub-communities, for example,
operational programs, research, academia, industry, physical scientists, different
disciplines of science (physics versus biochemical), etc. Cultural differences can limit our
effectiveness when dealing with operational users. For example, many federal agencies
have operational needs that could be addressed by other U.S. IOOS partners. A mechanism
is needed to make it easy for both those with data streams or other potential solutions and
operational programs to engage with each other. Another example is the different value
system between academia, which prioritizes publication and grantsmanship, and the
operational community, which prioritizes meeting user requirements. Since the nonfederal observing system is being implemented mostly through academic institutions, the
academic value structure needs to shift, or we risk disengagement from academic partners
if their professional advancement is hindered by their collaboration with U.S. IOOS.
Recommendation 2B: The IOOC agencies should provide recognition and/or rewards for
partnerships across cultural interfaces. For example, rewarding operational programs for
publishing requirements and entraining academic or other communities with new
products (data, models, technology) effectively into their development processes. Another
reward would provide prestigious scientific recognition to academic and other scientists
who have contributed substantial time and effort to helping to build the U.S. IOOS, making
sure the reward is structured so it will be recognized within the academic and university
structures. .
Challenge 3A: How can the requirements of users be better documented and
communicated to U.S. IOOS stakeholders?
It is a legislative mandate for U.S. IOOS to be based on the needs of users25; however
documenting user needs is not necessarily straightforward. Which users should be
included? How should their requirements be determined and which should be prioritized?
(See Challenge #2.) How should the requirements be distributed among providers? The
Federal Agencies and the RAs play important roles in fostering user engagement and
documenting user requirements, and are themselves intermediate users.
The timing of engaging with end-users to try to understand their needs must also be
considered. Requirements have a shelf life. If the capabilities, i.e. resources, are not
available to act on the requirements and develop solutions, then documenting them may
have negative impacts: 1) raising expectations of users when nothing can be done, and 2)
wasting time because the requirements may change and will have to be revisited at a time
when they are actionable. However, these impacts can be ameliorated by communicating a
prioritization schema. If requirements are documented, funding opportunities can be more
25
Airlie House report, 2002.
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DRAFT IOOS Summit Report: September 18, 2012
readily realized. Additionally, it is important to recognize that user requirements also
extend to the data dissemination process, and active communication between users and
data providers is crucial to establish efficient, user-friendly data distribution systems.
Since user requirements will also change with time and with changing technology, the
documentation process needs to be able to accommodate this. Especially difficult is dealing
with episodic, catastrophic events, which cause users requirements to change dramatically
over short time periods, without necessarily an increase in resources (i.e. Hurricane
Katrina and the Deepwater Horizan oil spill). Different types of users (see Section 1) have
very different requirements, and varying levels of ease in documentation of those
requirements. For example an operational user running an operational model has a very
constrained set of parameters that it needs in a continuous near real-time stream, whereas
the needs of the public are more episodic and varied and often require data interpretation
(is it safe to swim at the beach today?) rather than a data stream.
An organizational mechanism is needed to bring together user community needs with the
expertise of the research communities to bridge the valley of death to produce meaningful
products as well as to shorten the life cycle of transitioning research to operations.
Recommendation 3A: Building on Recommendation 1 for a marketplace, U. S. IOOS should
enable more systematic engagement with users by establishing a structure for this
engagement that fosters efficiency, and provides awareness of changing needs as
conditions users face change through time. The structure must also enable two-way
dialogue between users and providers. This interaction between users, intermediate users,
and providers and will also result in the identification of new directions for research and
technology developments.
The structure should encourage intermediate users, including those in the private sector
who specialize in bridging between providers and users, to engage. We need better
mechanisms to foster private enterprise activity that can fill gaps in the current U.S. IOOS
system.
Challenge 3B: There is a mismatch between many of the user needs and the technical
capabilities of the observing system.
The present system has been built largely around collecting and modeling physical
oceanographic parameters, which is useful to users such as those involved in marine
operations and search and rescue. However, a larger segment of the potential user
community is interested in observing biological systems and the biogeochemical exposures
that drive them. The observing system was logically initiated around developing physical
measurements and models because they provide a required foundation for these other
uses. Early investment in physical oceanographic models was a conscious decision for this
reason. Some physical circulation products, such as larval dispersal models, have gained
favor with the biological user community. There have even been efforts to incorporate
biological measurements, such as fluorescence sensors to describe algal density, but these
have been driven largely by a desire to leverage available technology rather than as direct
responses to the highest priority user needs. The investment in sensor development or the
modeling necessary to optimize the observing system toward biological or chemical
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DRAFT IOOS Summit Report: September 18, 2012
process questions, such as what are the nutrient sources driving algal blooms or predictive
models of when the next bloom is likely to occur, are still lacking. Such investment towards
products beyond the purely physical models will be required to capture the interest of the
larger user community.
There is also a spatial mismatch between the observing system capabilities and many
desired applications. The observing system has been built as an expansion of large scale
oceanographic assimilation models, such as GODAE and HYCOM. These generally operate
at kilometer scale resolution and the coastal shelf serves as a boundary condition. In
contrast, many of the user needs are located close to shore and operate on much smaller
spatial scales. For instance, the water quality user community is interested in how land
based sources are transported along the coast, even to the point of needing to examine
longshore transport within the surf zone for beach water quality modeling. While the
spatial resolution of the models continues to improve and there are some nascent efforts to
move the model's boundary conditions closer to shore, there is still much fundamental
technical work to be done before many user community needs can be addressed. The gaps
between capabilities and requirements are discussed in detail in Chapter 3.
Recommendation 3B: To meet established user requirements U.S. IOOS needs to invest in
the development of (1) the necessary biological and chemical sensors and (2) higher –
resolution coastal models.
Challenge 4: How can we ensure that users are properly engaged in the transition from
research to operations for observational data streams and models?
The Research to Operations (R2O) transition process has always been difficult, earning it
the nickname of the “Crossing the Valley of Death”. It is a fundamental part of U.S. IOOS, as
research and data products are delivered by providers to operational communities and
subsequently applied in various operational contexts. Traditionally, successful R2O is a
balance between the research side “pushing” research results to the operations side, along
with the operations side “pulling” the focus of research (and products) toward its
operational needs. Today, U.S. IOOS can point to many examples of a strong “push” from
research communities, and to a lesser extent occasional “pull” from the operations side.
However, no organized approach exists foster a strong and consistent “pull” from the
operational communities to complement the existing “push” from the research side.
Improvements are required for R2O transition to occur at the level needed for a successful
IOOS.
The “pull” from the operational communities represents the needs and applications of end
users and other stakeholders—a common goal or set of objectives around which U.S. IOOS
partners can congregate and work toward. To ensure timely translation of research into
operations, not only are substantial informatics systems required, but also a formal
infrastructure for user-driven, product development. It will result in a greater balance
between the push and pull of R2O and more meaningful product development. An example
of a working R2O process is given by the Navy example in section X. It is crucial to
maintain active user engagement in the R2O process.
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DRAFT IOOS Summit Report: September 18, 2012
The Regional Associations have significant experience in user-driven, product development
approaches. (See http://www.usnfra.org/products.html for 71 RA created products.) The
RAs often serve as the linchpin between data generators and data product developers and
users in the region, including with federal agency representatives in the region. However,
improvements are needed to shift current individual RA and other U.S. IOOS stakeholder
collaborations from a cooperative approach (working together toward independent goals)
to a more coordinated approach (working together toward common goals).
The infrastructure for the product development process could include a number of
supporting structures, including user councils, thematic product working groups, a
stakeholder engagement service, and leveraged use of existing stakeholder networks. This
will result in new observing opportunities, invigorate the ongoing user network feedback
loop, provide the foundation for the implementation of the U.S. IOOS RA 10-year Build Out
Plans, and ultimately lead toward the vision of U.S. IOOS.
Recommendation 4: Building on Recommendation 1 for a ‘marketplace’, organize existing
U.S. IOOS user engagement efforts into an ad hoc User Engagement Council to foster efficiency
and establish a R2O path. To initiate this activity, hold a National Forum charged with
developing an U.S. IOOS R2O strategy.
A partnership of the U.S. IOOS Program Office and NFRA could engage all IOOS agencies and
RAs to populate and support a User Engagement Council. The Council would be charged
with responsibility for defining and fostering a U.S. IOOS R2O strategy, and should include
key members of all U.S. IOOS stakeholder groups including federal agencies, private
industry and the RAs. This Council should be coordinated with the existing U.S. IOOS
Advisory Committee.
Challenge 5: How can the public and other potential users be made more aware of the
data available through U.S. IOOS?
The RA education and outreach specialists already work with many different types of
stakeholders26. U.S. IOOS data have been utilized in developing innovative undergraduate
curriculum that allows students to be active participants in innovations and partake in the
active exploration of the world’s oceans27. There needs to be more work and investment in
building a community of informal education specialists who can promote the use of U.S.
IOOS information to achieve ocean literacy. Future scientific discoveries and innovation
necessitate collaboration beyond traditional boundaries to include multiple perspectives,
skill sets and expertise. U.S. IOOS must utilize existing tools and facilitate the development
of new strategies for virtual social structures that encourage communication and sharing of
ideas across disciplines28. For outreach to the general public, data dissemination must
move beyond webpages and take advantage of expanding media technologies, such as
26
27
28
[Simoniello]
[Glenn et al]
[Thouroughgood et al.]
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DRAFT IOOS Summit Report: September 18, 2012
smart phone apps and twitter feeds, to make data and products more easily available to
individuals.
There are proven government engagement programs, for example in the Department of
Agriculture (specifically the 50 Land-Grant-based Agricultural Experiment Stations and
Extension Services) as well as the Department of Commerce’s Sea Grant extension services.
These extension services provide agents with expertise who interact directly with specific
stakeholder group types. These examples can serve as models for stakeholder engagement
within U.S. IOOS as well as a partnership leveraging opportunity in some cases.
Additionally, IOOC agencies could provide a base of ‘friendly’ end users from their agencies
able to engage at the regional level with non-agency efforts to contribute to data streams,
products, and information that could meet their agencies’ needs.
Recommendation 5A: Building on Recommendation 5, the User Engagement Council should
be charged with development of an Outreach Strategy as a component of the overall R2O
path.
The existing NFRA Education and Outreach Council should be a component of this effort.
Additional resources would allow for an increase the level of its activity in the planning for
and execution of outreach activities to formal and informal educators, undergraduate and
graduate level students, and the general public. The outreach subsystem, which puts
understandable information into the hands of the public, is, in many ways, just as
important as the DMAC subsystem that puts quality data into the hands of users.
Recommendation 5B: Provide a detailee with an education and outreach background to the
U. S. IOOS Program Office to staff the User Engagement Council and ensure cooperation
with ongoing Federal and RA and other stakeholder activities.
Challenge 6: How can we ensure that U.S. IOOS products continue to meet user needs?
Many ‘levels’ of products are/could be available from U.S. IOOS stakeholders. These
product range from minimally processed data to decision support tools. Some products
transition to operational users after development, while others are ‘maintained’ by various
IOOS stakeholders such as RAs, private industry or federal agencies. The challenge is to
build assessment, maintenance and product updates into the U.S. IOOS structure.
Currently, if these activities are undertaken they occur on a case-by-case basis.
OR
Challenges 5, 6 and 7 represent steps along the continuum of user engagement from
outreach to assessment to training/demonstration. Once a product is developed, an
assessment effort is required to assure products are functioning as designed and meeting
user needs. This step is needed to assure user satisfaction and to gather metrics on use.
Additionally, someone must be available to maintain or service the product, make sure
links remain operational and be available to support user inquiries, and to update the
product to ingest new data streams, etc. For the products that are currently served via the
web by RAs, some of these services are provided by DMAC personnel. However,
Recommendation 6: Require that product metrics be developed for all U.S. IOOS branded
products???.
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DRAFT IOOS Summit Report: September 18, 2012
Challenge 7: How can we ensure that U.S. IOOS products are used?
Dedicated human resources are required to conduct meaningful marketing (outreach) and
training.
As mentioned previously, Department of Agriculture Extension Services as well as the
Department of Commerce’s Sea Grant extension services can serve as models for
stakeholder engagement within U.S. IOOS as well as a partnership leveraging opportunity
in some cases. Agricultural Experiment Stations have a cadre of agriculture specialists who
serve as linchpins between scientists and farmers; these specialists scale up lab bench
research projects to pilot scale to demonstrate the viability of a new agricultural product or
process for the operational farmer. The adoption of this new product or process is more
likely after the conduct of a successful demonstration process. The Agricultural Extension
Service is also made up of educational liaisons that undertake topic-driven workshops and
programs to disseminate the latest relevant agricultural advances to agribusiness
operators. It is also important to insure that data dissemination meets user requirements
and is user-friendly.
Recommendation 7: Provide marketing and training …
Use the IOOS marketplace and User Engagement Council …
Challenge 8A: Developing and maintaining advocacy.
Although U.S. IOOS is a line item in the NOAA budget, it is largely an unfunded federal
mandate. Many naysayers continue to question the value of integration, believing that
agency programs supported with agency-unique budgets and supporting requirements are
adequate. Clearly, this argument does not address the inefficiencies of this fragmented
approach, and fails to support U. S. IOOS as a national ocean enterprise. This current state
of play makes it difficult for the U.S. IOOS efforts to be taken seriously by Federal partners.
Challenge 8 lies at the heart of U.S. IOOS’ ‘failure to thrive’. What is needed are users and
requirements that can help make the case why improved, coordinated funding must occur
to enable an effective, integrated Federal backbone. In an effort to try to emphasize that we
all benefit through the contributions of many, the U.S. IOOS has sometimes been called a
National Ocean Enterprise. However, the coastal, estuarine and Great Lakes communities
can feel excluded by the “ocean” terminology, which makes this branding effort counter
effective.
By meeting all the previously identified challenges, advocacy will develop naturally if the
stakeholders and users are actively engaged and their requirements are being met.
However, a proactive advocacy strategy that addresses federal agency, RA, private
industry, and NGO roles and limitations is needed. Federal agencies obviously would have
a very different role in this strategy than other stakeholders.
Recommendation 8A: NFRA should coordinate with private industry, the Consortium for
Ocean Leadership and other stakeholders to develop an advocacy strategy. One element of
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DRAFT IOOS Summit Report: September 18, 2012
the strategy should be to incorporate advocacy elements into the R2O process
recommended for Challenges 4 through 7.
Challenge 8B: Lack of proper funding can lead to user alienation and loss of existing
observational resources.
There is often an awkward interaction between users and the observing community that is
trying to develop the U.S. IOOS because the conversations mix discussions about technical
needs with those of financial support. The observing community has an earnest desire to
define and fill user needs, but often cannot, having inadequate funds to achieve the desired
data stream, integrated product, or other informational assets. In this situation, the issue of
finances may be brought into the conversation prematurely, before the observing
community has created credibility for their products. Such interactions create a perception
that the U.S. IOOS entity is more interested in obtaining money than in meeting user needs.
At the other end of the interaction spectrum, there are many users that have come to rely
on observing system products without providing financial or political support for the
system. The observing system community is not adept at culminating that supportive
relationship into advocacy or funding even when the timing is appropriate.
Recommendation 8B: NFRA, in coordination with the private sector stakeholders in U.S.
IOOS, should coordinate training for advocates of U.S. IOOS, particularly those advocates
with limited business experience.
Business partners have experience in knowing how best to develop and market products,
especially in the current governmental fiscal environment at local, state, and federal levels.
IV.
Future Opportunities and Recommendations
We need to envision a future with users, like NOAA NCEP and the Governor’s South Atlantic
Alliance and the Sportfishing Association of California, queuing up to talk to their local U.S.
IOOS representative because they, the user, know that U.S. IOOS gets problems solved. We
need a National User Engagement Plan, something analogous to the national Operational
Wave Observation or Surface Current Mapping plans. We need a systematic framework for
not only enabling, but also inciting user pull. The question, as always, is how to get there.
A. Recommendations
Below are concise versions of the recommendations associated with each of the challenges
discussed in the previous section. This takes a high-level view of the program, and does
not get into detailed recommendations tied to specific datasets. Several Community White
Papers outlined requirements for specific user communities and are listed in Appendix X.
Recommendation 1: Organize information about users, their requirements and available
products into a “marketplace”.
Recommendation 2A(i): Develop an “Action Agenda” for U.S. IOOS that prioritizes nearterm investments and steps along the path to a fully operational system.
Recommendation 2A(ii): Devote a portion of each IOOC meeting agenda to resolving
coordination issues delivered unfiltered and confidentially to the IOOC.
Recommendation 2B: The IOOC agencies should provide recognition and/or rewards for
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DRAFT IOOS Summit Report: September 18, 2012
partnerships across cultural interfaces.
Recommendation 3A: U. S. IOOS should enable more systematic engagement with users by
establishing a structure for this engagement that fosters efficiency.
Recommendation 3B: U.S. IOOS needs to invest in the development of (1) the necessary
biological and chemical sensors and (2) higher –resolution coastal models. development of
the necessary biological and chemical sensors to meet established user requirements.
Recommendation 4: Organize existing U.S. IOOS user engagement efforts into an ad hoc
User Engagement Council and hold a National Forum to define an R2O path for U.S. IOOS.
Recommendation 5A: Charge the User Engagement Council with development of an
Outreach Strategy as a component of the overall R2O path.
Recommendation 5B: Provide a detailee with an education and outreach background to
the U. S. IOOS Program Office to staff the User Engagement Council and ensure cooperation
with ongoing Federal and RA education and outreach activities.
Recommendation 6: Require that product metrics be developed for all U.S. IOOS branded
products??
Recommendation 7: Provide marketing and training using the IOOS marketplace and User
Engagement Council.
Recommendation 8A: NFRA should coordinate with private industry, the Consortium for
Ocean Leadership and other stakeholders to develop an advocacy strategy.
Recommendation 8B: NFRA, in coordination with the private sector stakeholders in U.S.
IOOS, should coordinate training for advocates of U.S. IOOS.
continued engagement with professional societies like AMS and MTS,
building on the success stories of how the RAs have developed their
user engagement strategies,
continuing to collect lessons learned from successful operational
ocean observing programs,
Appendix X, Specific user requirement recommendations
Ocean & Coastal Build out Plan (UNDER DEVELOPMENT)
This list is not exhaustive, but represents the start of a “user requirements database”. The
products and services listed in the Regional Build Out Plan synthesis were used as a
starting guide. which should have at least two subsections – requirements, and known
gaps, and this would fall into the latter category.
HF Radar
• _Assimilate HF radar data into physical and ecological models to enhance model
performance.
o Integrate HF radar data into decision support tools for marine operations (e.g., search
and rescue, oil spill response, and tsunami warnings).
• _Proactively address the HF radar network health, balancing operations and maintenance
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DRAFT IOOS Summit Report: September 18, 2012
(O&M) activities of existing radars with expansion of the network. Seek new methods for
lowering the O&M for the HF radar network.
• _Develop a plan for the long-term stewardship of HF radar data to develop climate data
records for use in climate science, adaptation, and mitigation strategies.
• Work with NOAA’s Center for Operational Oceanographic Products and Services to
incorporate HF radar surface currents data into PORTS® and the National Currents
Program.
water quality
• _Enhance U.S. IOOS interagency and regional collaboration with the National Water
Quality Monitoring Council to improve data integration and monitoring coordination to
better meet local needs for timely water quality information and decision support.
biological observations
• _Enhance U.S. IOOS’ ability to collect, deliver, and use biological data towards the goal of
full integration by implementing the recommendations from the 2010 report, Attaining an
Operational Marine Biodiversity Observation Network (BON) Workshop
(http://www.nopp.org/wp-content/uploads/2010/03/BON_SynthesisReport.pdf). Initial
steps to advance sample processing, taxonomic identifications, data management, and
training should be pursued through the initiation of a multi-agency integrated marine BON
demonstration project.
• _Advance the recommendations from the March 2011 Toward a National Animal
Telemetry Observing Network (ATN) Workshop Synthesis Report (http://www.U.S.
IOOS.gov/observing/animal_telemetry/workshop/mar2011/atn_synth_wrkshp_rprt_jul20
11.pdf) to develop a collaborative project designed to support ecosystem science and
management requirements by demonstrating the utility of the ATN to fisheries and habitat
management communities.
6
REFERENCES – UNDER DEVELOPMENT (TO INCLUDE LINKS)
Relevant International Documents
GOOS-125: The Integrated Strategic Design Plan for the Coastal Ocean
Observations Module of GOOS (2003)
GOOS-148: An Implementation Strategy for the Coastal Module of GOOS (2005)
GOOS-193: Requirements for Global Implementation of the Strategic Plan for
Coastal GOOS (2012)
http://www.earthobservations.org/
http://www.ceos.org/
Relevant NOPP and Ocean.US Documents
Toward a U.S. Plan for an Integrated, Sustained Ocean Observing System, Report
to Congress 1999.
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DRAFT IOOS Summit Report: September 18, 2012
C-GOOS Workshop: An Integrated Ocean Observing System: A Strategy for
Implementing the 1st Steps of a U.S. Plan, 1999.
Building Consensus: Toward an Integrated & Sustained Ocean Observing System,
2002 (Airlie House Report)
An Integrated Sustained Ocean Observing System (U.S. IOOS) for the U.S.: Design
and Implementation, 2002
Relevant U.S. IOOS Office, IOOC Agency, and Regional Association Documents
Regional Associations' Ten Year Build Out Plan Synthesis, NFRA 2011.
http://www.usnfra.org/products.html
National Operational Wave Observation Plan (March 2009).
Plan to Meet the Nation’s Needs for Surface Current Mapping (September 2009).
U.S. Integrated Ocean Observing System: A Blueprint for Full Capability Version
1.0 (November 2010).
Informational Document for General Release, U.S. IOOS HF radar data and its
use by the United States Coast Guard for Search and Rescue
http://marinesciences.uconn.edu/News%20Articles/SAROPS_HFR_Informat
ional_3Jul2012.pdf
Rapid detection of climate scale environmental variability in the Gulf of Maine,
J.R. Morrison, NERACOOS, Rye, NH, N.R. Pettigrew, University of Maine, J.
O’Donnell, University of Connecticut, J.A. Runge, University of Maine and Gulf
of Maine Research Institute (2012)
Enhancing Stakeholder Engagement: Toward Next-Generation Product
Development in the R2O Process, Carolyn Thoroughgood, MARACOOS /
University of Delaware, Newark, DE, USA, Gerhard Kuska, Peter Moore,
MARACOOS, Newark, DE, USA
Community White Papers:
U.S. IOOS STAKEHOLDERS AND BENEFICIARIES BY RALPH RAYNER
IMPLEMENTATION of a NATIONAL Dual-USE HIGH FREQUENCY RADAR
NETWORK SUPPORTING UNITED STATES COAST GUARD REGUIREMENTS
FOR SEARCH AND RESCUE & MARITIME DOMAIN AWARENESS, S. Glenn,
Rutgers University, New Brunswick, NJ, and D. Barrick, CODAR Ocean
Sensors, Mountain View, CA
THE U.S. IOOS PROGRAMOFFICE PERSPECTIVE ON OBSERVING SYSTEM
CAPABILITIES: GAP ASSESSMENT, JULY 2012
Art Allen
Don Anderson
Bailey
Birkemeier
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DRAFT IOOS Summit Report: September 18, 2012
Hall
Gledhill
Send
Simoniello
Thoroughgood
Lankhorst et al. CWP: DATA QUALITY CONTROL IN THE U.S. IOOS
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DRAFT IOOS Summit Report: September 18, 2012
Chapter Three:
Observing System Capabilities- Gap Assessment and Design
I. Introduction
This chapter examines the challenges, issues and opportunities in developing a
comprehensive design of the Integrated Ocean Observing System. It is important to
acknowledge that a vision for IOOS, and priorities and requirements that flow from that
vision, are prerequisites of a design for IOOS. Consistency of vision, priorities and
requirements from global to local scales is a challenge to achieve. Priorities will vary
regionally, by design, and will require ongoing refinement, but should conform to the
overarching vision. Identification of specific capabilities in each of the system components
of IOOS that are essential to satisfying the requirements of IOOS can provide common
threads of design. This chapter assesses the status of the IOOS enterprise in developing a
comprehensive design and highlight steps that need to be taken to achieve this objective.
Reference to GOOS and its development are included to ensure consistency across all scales
and to identify strategies or pitfalls that may be applicable to IOOS.
A comprehensive design is an important step towards detailed costing and implementation
planning. It can be viewed as an opportunity to align interests and methodologies prior to
significant expenditures. The design process will also naturally lead into discussion of
implementation and appropriate roles and responsibilities for participants and should be a
venue for refining these next steps.
Design and gap analyses are needed for each of the observing system subsystems:
observing (in-situ and remote sensed), modeling & analysis and data management and
communication.
2. Overarching Issues
Unifying a design across the breadth of scales of interest to IOOS relies on commonalities in
vision at differing scales. The IOOS Strategic Plan (ref) provides a vision for the governance,
design and implementation of IOOS. It identifies an initial set of priorities and core
variables that support them. The OceanObs’09 Conference resulted in a revised vision for
GOOS and a framework (Task Team, 2012) for establishing it emphasizes requirements for
essential ocean variables (EOVs). These approaches are similar to that of Ocean.US in its
initial depiction of IOOS (Airlie House report) and its articulation of core variables, and the
subsequent expansion of the list of core variables to better capture the interdisciplinary
observations needed to address priority topics in the IOOS Blueprint. The recent build-out
plan synthesis developed by the IOOS Regional Associations also resulted in a revised list of
core variables. The similarity of approaches suggests that given an alignment of priorities,
a common set of variables can be identified for which requirements can be developed that
span the full range of scales the IOOS aspires to cover.
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The Global Climate Observing System (GCOS) and GOOS have developed detailed design
and implementation plans and these continue to be refined and updated. The
internationally agreed plan for the initial global ocean observing system was revised in
2010 and is described in GCOS (193)/GOOS(184), and the most recent summary for an
ecosystem based management approach to the coastal component of the global system is
described in GOOS (193). More detail on needed sustained satellite observing activities
was most recently updated in 2011 and is given in GCOS (154). Progress against the initial
global ocean plan was most recently described in 2009 in GCOS (128). Both the global
ocean and global coastal system plans advocate for significant national activities along the
coasts and in coastal waters. GOOS (193) invites, in particular, national participation in a
set of Global Coastal Network activities (see section 5.4). A major issue for all these plans is
working to agreed common standards and to timely free and open observation exchange.
Identification of a limited set of variables that are to be observed, modeled, and used in the
development of information products and deliverables that directly address the priorities
has been found to streamline the requirements process. GCOS(193) provides the list of
GCOS Essential Climate Variables for the ocean (and atmospheric and terrestrial) domain.
GOOS(193) offers a set of essential ocean variables (Table 14) for the Global Coastal
Network; GCOS(193) offers a set of essential climate variables for the ocean domain. For
state estimation and prediction, requirements will specify the spatial resolution,
observation frequency and duration, accuracy, and speed of distribution needed. The
requirements may then be met based solely on observations, or may be met through data
synthesis which may use data assimilative modeling. Products derived from the variables
will impose certain analysis and processing requirements. Information management will
be required to support the variables through standards development and exchange
protocols that facilitate aggregation from all observing platforms and with modeling and
product development systems. It should be expected that requirements will change over
time. The space/time/accuracy requirements for the ocean Essential Climate Variables of
GCOS/GOOS are revised routinely and are listed in the WMO Observing Requirements Data
Base (http://www.wmo-sat.info/db/). The recent GOOS (193) report is a noteworthy
example of a process that can be followed to translate priorities into observing system
requirements and the use of these requirements in design.
Ongoing challenges of uniting ocean observing efforts into an integrated system of systems
is the patchwork of existing systems of limited interoperability and the limited financial
support available for integration activities and new observing component programs. For
example, the GOOS initial global physical and carbon climate observing system remains
only partially deployed due to lack of national commitments to sustained investment. The
governance for coastal IOOS has matured significantly since the Airlie House meeting but
support for implementation has largely been absent. Regional associations have formed
and demonstrated the utility of integrating available observing system components but
have lacked the resources to implement systems that can fully address the set of initial
priorities. IOOS stands at a crossroad of development – if it is to meet the expectations for
the coming decade, significant growth of the system will be needed. At issue is how can
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growth be undertaken in the most efficient and complementary fashion to existing efforts?
And is there the political will for investment?
Observation and prediction of some variables are already reasonably advanced, such as
water temperature and sea level, whereas others, such as species-specific harmful algal
bloom toxins, are much less so. A balance of investment in mature observing systems
components and in pilot programs to demonstrate new capabilities is needed to ensure
that an interdisciplinary system is developed and sustained.
After agreement on requirements a census of the present state of observing system
components is a necessary starting point for gap assessment. For federal agency
participants in IOOS the identification of programs and assets that are considered part of
IOOS has begun with the U.S. IOOS Blueprint for Full Capability (IOOS PO CWP on gap
assessment). This critical step requires self-identification of relevant programs by agencies,
and presumably a commitment to sustain the contribution to IOOS. Regional IOOS has
recently completed a build-out plan that includes a census of most of the non-federal US
contributions that exist at present. Within GOOS the 2009 summary of progress lists the
initial in-situ global system to be about 60% implemented, with year to year variation in
the extent of deployment of many of its subsystems; little progress in overall in –situ
system implementation has been achieved over the past several years. The satellite
component has been well implemented. Both the in-situ and satellite systems lack national
commitments to sustain the present levels.
Gap assessment is the comparison of requirements for the observing system with its
present state to establish what is missing and must therefore be added to the observing
system to improve its functionality. Statement of requirements for the observing system,
derived from a synthesis of societal and scientific priorities and likely in the form of
specification of resolution and accuracy of essential or core variables, is challenging
because of the necessary translation from a set of specific objectives into observing system
component needs. An agreed upon framework for the observing system and its
components, or design, facilitates this task by providing a finite number of ways to
implement the system. A high-level design of IOOS, of 3 major subsystems – observing,
modeling and analysis, and data management and communications – has existed for
decades (ref to early system description), but a more fine-grained consensus description is
now needed. Gap assessment and system design are complementary efforts and must both
evolve to provide a detailed depiction of the observing system to be built.
Assessing a gap between the existing system and requirements for its envisioned
performance relies on definition of adequacy. Because IOOS strives to address multiple
objectives with a single system, numerous specifications of adequacy for a given
component will arise. Deciding on a specific measure of adequacy will involve balancing
costs, weighting of requirements derived from various priorities and objectives, and
implications for other system components. The time frame in which adequacy is evaluated
is also important. There may be differing expectations for near-term objectives than for a
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design that describes the expected state of the system a decade from now. These temporal
considerations are likely more of an issue for implementation planning.
Once gaps in the components of the observing system have been identified the design of a
revised system that fills the gaps can begin. A number of approaches to the design process
exist; indeed there is a subfield of engineering (systems engineering) dedicated to this
topic. Needed is a blend of more qualitative expert knowledge, to inform the types of tools
available and the ways in which they can be employed to meet requirements, and more
quantitative assessment tools, such as simulation experiments, which provide an objective
method for evaluating a particular design. The former can produce specific designs while
the latter can be used to optimize its structure. The design of the global system has
depended heavily upon expert opinion, feasibility and available resources, with model
studies useful for some components. As the breadth of priorities the system addresses
increases so does the complexity of the design effort, and it should be expected that an
ongoing design and evaluation program must be mounted to enable the growth of the
system through infusion of new technologies in an efficient manner. The adequacy of the
global ocean system is assessed periodically and will be revisited soon (probably by 2014)
through the GCOS process. A similar practice should be adopted for IOOS.
How the design process addresses the multi-scale nature of IOOS is an outstanding
question. Priorities at global, regional and local scales are likely to differ and lead to
designs that may not be closely aligned, at least at certain phases of implementation.
Careful consideration of the implications for interactions across scales may help identify
priorities that cut across scales and provide overarching goals that define implementation
timelines. A recent exploration of these issues has been undertaken by the NSF Arctic
Observing Network Design and Implementation Task Force (Eicken, 2012).
IOOS is often described as a system with three functional subsystems (Observing, DMAC
and Modeling/Analysis) and three cross-cutting subsystems (Governance,
Education/Training, and Research/Development). At a high level this abstract framework
(or logical or abstract architecture) encompasses the concepts in the IOOS adequately.
However, as it is currently implemented (the physical or implementation architecture) this
system model does not quite fit. In reality IOOS more closely resembles a System of
Systems and not a single monolithic system. This distinction is only important if we can
apply it to better designing, implementing and managing IOOS.
A System of Systems (SoS) differs from a single system in a few key ways. It is typically
characterized by geographic, operational, and managerial separation of the component
systems (Maier, 1998). The components have been prioritized, funded and built
independently (managerial separation) and do not depend on each other for their existence
(operational separation). Importantly, geographic separation implies that the primary
artifact that is transmitted between systems is information, emphasizing the importance of
a cyberinfrastructure capable of propagating all the necessary information. Consistency of
approaches to gathering and generating information will also facilitate connectivity
between systems. Systems of Systems evolve incrementally and iteratively because, given
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the managerial separation of the components, it is unreasonable to think that even the
most collaborative or coordinated SoS will effect change in lock step. However, for all the
difficulties in building a SoS, it is the last characteristic that provides the promise for IOOS.
Systems of Systems exhibit emergent properties which is a systems engineering term
expressing the well known cliche, “the whole is greater than the sum of its parts”. The IOOS
should carefully consider how best to mount a comprehensive design that encompasses the
full breadth of scales and topics the system is envisioned to address.
3. Subsystems
Given the considerations of the process of gaps assessment and system design presented
above we here review the subsystems of the observing system, focusing on the status of
existing systems, gap assessment and design considerations.
Observing subsystem: a large number of observing programs exist, some of which are
discussed below. A useful distinction is drawn between observations made in-situ and
those made remotely. A further breakdown based on whether an observing platform is
fixed or mobile begins to provide the granularity necessary to support a detailed system
design. The sensing that a given platform can support varies widely, and it is the
combination of platform characteristics and sensor load that are critical to design
considerations. Ideally the analysis can be done essential variable by variable, but in
practice it is often necessary to consider activity by platform.
In-situ observing almost always depends upon access to ships, either to make the
observations directly or to deploy autonomous platforms (moorings, drifters, profiling
floats or gliders). Access to ships is a critical infrastructure need and requires considerable
coordination among observing components as well as between national research vessels
and between commercial shipping for the global system. Talley and Feely (CWP) note that
ship-based repeat hydrography is the only existing method to measure and track ocean
carbon inventories, observe the global ocean below 2000 m, measure and track overall
ocean heat changes, or provide the highest quality in situ validation data for autonomous
sensors. Autonomous platforms, if their arrays can be adequately maintained offer the
ability to collect observations routinely throughout much of the global ocean. Moorings
offer the unique ability to sample the full time spectrum of variability with high accuracy.
Autonomous platforms have revolutionized our knowledge of the ice-free global open
ocean over the past decade, and much development is underway to make these systems
capable of sustained operation under ice. The motivations for these autonomous systems
are reduced cost of operations and continuous, unobtrusive all-weather observing. The
ability to collect observations in conditions too harsh for vessel operations (e.g. storms or
under ice) and at high frequency for extended periods of time has significantly improved
the statistics of ocean observations and permits greater confidence in state estimation and
hence predictability.
It is essential to increase the observing capabilities of surface drifters, gliders and profiling
floats beyond their present physical variables. Work is ongoing to improve the ability of
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biogeochemical sensors on these platforms, as well as to develop profiling floats capable of
sampling the full ocean depth. There are power, stability, calibration and data system
implications for every new sensor, which require sustained community engagement to
address.
In coastal settings buoys have served as the principal automated observing platform.
Moorings are also an essential component of the global system, both to provide information
in critical regions like the tropics and to provide reference quality observations at selected
global reference sites. These fixed platforms have enabled collection of long time series of
largely near-surface physical variables, sufficient in some instances to define seasonal
climatologies and anomalies from them. Routine collection of subsurface observations
using subsurface moorings has increased in recent years but subsurface observations in
coastal areas, and the use of these platforms to host a wider variety of sensors, are a
significant gap (Virmani CWP). It has not been practical to document the smaller spatial
scales of variability characteristic of the coastal waters with these systems.
Regions with limited depths and strong currents pose challenges for drifters and deepwater profiling floats. Underwater gliders are a promising mobile platform for observing
some parts of the coastal ocean because of the ability to capture smaller scales of variability
and because of the ability to direct sampling patterns and protocols. Ruddick et al. (CWP)
present a plan for implementing a routine glider observing program covering coastal
waters and providing a link to global observing. A number of other navigable platforms
(wave gliders, autonomous underwater vehicles, autonomous ships) and volunteer
observing platforms (e.g. ferry-based systems, see Codiga et al. CWP) are finding use in
coastal waters, including those areas no accessible by gliders (e.g. estuaries and the
nearshore) and should be considered for inclusion in an observing subsystem design.
Commercial vessels have played the primary role in the historical collection of met-ocean
observations and support ocean observing in other ways. In particular, some vessels
deploy drifters and profiling floats and XBTs and tow plankton collection systems. Others
support underway sampling systems for SSS and pCO2, and a variety of other variables
potentially could be observed. The industry has indicated a willingness to support ocean
observing, within agreed limits of responsibility, and it is important to follow up on recent
interactions to expand the type of variables observed and the spatial coverage.
The collection of platforms best suited to a given region is expected to vary due to differing
environmental conditions (e.g. water depths, current strength, stratification, intensity of
human activity, accessibility), payload needs, and will change over time as new capabilities
become available. A comprehensive observing system makes the best use of the qualities of
each of the available platforms in different regions. No single platform offers a costeffective strategy for all observing needs. The global system has long depended upon a mix
of platforms to obtain global coverage at minimum cost. An important aspect of a coastal
design will be accommodating flexibility in platform use regionally and temporally to adapt
to changing needs and to maximize the efficiency of operations.
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Dedicated observing networks have already been considered in IOOS planning, notably the
surface current mapping plan (HFR plan) and waves plan (Birkemeier, CWP). These plans
consider either how best to employ a specialized observing technology (e.g. high-frequency
radar) on a national scale or a specific variable of interest (directional wave field) and the
best mix of platforms and sensors to enable its observation nationally. It is likely that a
mix of approaches to the observing subsystem design, considering both dedicated systems
and more overarching approaches that consider a broader scope (e.g. ecosystem observing
network) will need to be employed.
Routine collection of biogeochemical variables is probably the greatest recognized gap in
the observing subsystem. Typical methodologies require laboratory analyses at some stage
of processing and have been ship-based. However there is in explosion in automated
sensing development, as well as development of indicators or proxies of ecosystem state,
that if fostered holds the promise of addressing this large gap in observing capability. The
GOOS report #193, mentioned earlier, explores how a balance of routine and measurement
techniques at various states of readiness can be employed to acquire the needed
observations.
There is keen interest in developing new observing technologies as evidenced by the large
number of community white papers submitted on this topic. Gledhill et al. (CWP) describe
observing needs to assess ocean acidification and its impacts in coastal regions and note
that carbon chemistry and ecosystem response changes need to be measured together.
Wanninkhof et al. (CWP) examine the Integrated Ocean Carbon Observing System and
describe a series of augmentations to existing programs that will enable improved
estimates of carbon inventories and impacts.
Acoustics-based monitoring of fisheries and marine animals, from use of existing or
innovative platforms to host active acoustic survey equipment (Greene et al., CWP, Horne
et al., CWP) to continental shelf wide acoustic arrays (Welch et al., CWP; O’Dor et al., CWP),
have been examined. Leveraging the Animal Tracking Network to enhance monitoring of a
broad range of variables is also considered (Block et al., CWP), and inclusion of line
transects for observer-based biological data is promoted (Fornhall et al., CWP). Passive
acoustics monitoring of biological and human activity may be possible from a wide variety
of platforms (Southall et al., CWP). HAB monitoring and forecasting will require
integration of a range of variables, as well as observation of select toxins, at a spatial
resolution that requires further investigation (Anderson et al., Kudela et al., CWPs).
The role of industry partnerships deserves further exploration. A number of CWPs explore
possible industry roles and relationships to IOOS (Rossby et al., Woll et al., Holthus, Manly
et al.). Given the funding challenges system build-out faces, industry collaboration may be
a vital mode of capitalization.
It will also be important to consider US involvement and investment in GOOS regional
programs. Of particular note is the Arctic, a region experiencing unprecedented change,
and in dire need of a broad range of enhanced observing capabilities (see Auad et al., Calder
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et al., Stabeno et al., Hicks et al., CWPs). Priority should be given to GOOS regions that
impact US waters (the Artic, Gulf of Mexico, Carribean, Pacific) and exploring opportunities
to leverage international programs to meet gap assessment and design needs.
Remote sensing (electromagnetic) can be space-based (i.e. satellites) and land-based and
provides a unique ability to map surface ocean properties. Satellites in particular are
expensive to develop and maintain. A number of studies have examined the adequacy and
future of the US (e.g. NRC, 2011) and international (e.g. GCOS(154)) satellite programs and
express concern about the vitality of this component of the observing subsystem. It is
important to define the role of IOOS in advocating for satellite remote sensing capabilities,
and to ensure that needs across all scales are communicated.
The most widely used land-based remote sensing technology is surface current mapping by
high-frequency radar. A national plan for broad-scale coverage around the US is an
example of a design employing a dedicated technology. A review of the plan to consider
nested, more high-resolution systems, and additional observational capabilities, would be
appropriate. There should also be consideration of other land-based remote sensing
technologies that may provide efficient or novel methods to observe the oceans.
Challenges:
1. How is the adequacy of the existing collection of observing assets best assessed
and gaps best defined? Should it be done by variable? By priority? By geographic
location? Some mix of these?
2. how should the technologies to fill gaps be identified? Should we advocate for
standards, or common practices, across scales as a way to improve efficiency and
reduce cost? Or will this stifle innovation?
3. how do we promote bringing new technologies into IOOS while maintaining an
operational output? Given a large gap in biogeochemical and ecosystem automated
observing, should a dedicated effort be made to advance these technologies?
Modeling: The need to have model simulations and forecasts, on appropriate time and
space scales, for processes including waves, ocean circulation, weather, inundation,
ecosystems, and water quality, has been identified as a core requirement that should be
available in all 11 regions ten years from now. Presently, different types of models may be
run independently to simulate these different properties, but some of these model types
are now coupled together, and it is expected that more will be in the future.
The relevant time scales for model predictions range from minutes or hours for processes
such as storm surge, to weeks, months or years for ecosystem or fisheries forecasts.
Increasingly, there is a call for models to shed light on regional impacts due to climate
change, thus calling for predictions on time scales of decades to centuries. These efforts
may take the form of down-scaling forecasts of global sea level rise to the predicted effects
on a specific city or regional infrastructure. Other examples would be assessments of the
consequences of long-term changes in water quality parameters such as pH or dissolved
oxygen, on ecosystem diversity, fisheries, or aquaculture.
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Unlike the DMAC and parts of the observational subsystems, there is no explicitly stated
vision and implementation strategy developed for the IOOS modeling subsystem. There is
a wide range of modeling approaches among the various regional observing systems, and
there is only ad hoc communication between the federal agencies involved in ocean
modeling and regional modeling system providers. A design effort for modeling that
considers the critical role of modeling in the design and evaluation of the overall observing
system and in the analysis, synthesis and prediction of ocean and ecosystem state is
imperative.
In addition to the need for larger-scale ocean models to provide boundary conditions on
sea level, temperature, salinity, and velocity, regional models also require atmospheric
forcing including all the relevant air-sea fluxes, at appropriately fine spatial resolution.
Accurate freshwater input, from stream/river gauges and hydrological models, is also
necessary.
The regional models should assimilate observations made within their domains. The
frequency with which the models should run, and the temporal resolution of their output,
depends on the type of model and its intended use. For instance, forecasts of salmon
abundance might only be needed every few weeks or months, while forecasts of coastal sea
level might be needed at intervals of hours or minutes.
With an understanding of how model results are to be used, based on knowledge of
customer needs, models should be used for Observing System Simulation Experiments
(OSSEs), to help optimize observing systems by revealing which types of measurements at
which locations are most important in producing a forecast of sufficient accuracy over a
given area. Then, given the range of needs to be met and the budget available, the
observing array can be optimized based on dynamics and known assumptions, a more
rigorous and quantifiable method than just relying on experience and intuition. This
should increase the accountability of observing systems, as well as expected performance.
As in atmospheric prediction, more reliable forecasts may be produced by taking advantage
of ensembles - i.e. by analyzing together the results from several similar, though not
identical, models. The ensembles may be constructed from a single model run with varied
initial conditions or forcing, or from multiple models that have different physics and
parameterizations. Ensemble forecasts also provide an estimate of uncertainty, which is
vital for decision-makers. In order to be most useful, all regional models should be
objectively assessed and results should be communicated with a measure of uncertainty.
This will better allow model results to be formulated into products that meet stakeholder
needs.
In order for ocean models to meet their full potential within the integrated framework of
ocean observing systems, considerations relating to end-user needs and the unique
properties of model-produced data (e.g. large size, unusual coordinate systems) must be
incorporated into the modeling, and associated, systems. Model output requires special
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attention within IOOS data management efforts. Modelers and ocean forecasters will need
to work with observationalists and observing system and data managers throughout the
development and implementation process to ensure that user-driven products and services
are developed and delivered.
We are entering a new era of coastal observation where advanced coastal modeling
systems can: (1) provide dramatically improved data-driven simulations and (2) determine
optimal observing networks for stated societal goals and available resources. In the past,
many simulation models used data assimilation techniques which simply force models
to look like the data in the vicinity of the data. Now with more sophisticated models that
take advantage of known physical, biological and chemical relationships, data can impact
even remote regions that are dynamically connected. By using inverse techniques, these
relationships can be further exploited to determine the impact that different observations
have on defined metrics. Thus once we have stated what quantities we want the models to
simulate, we can determine the optimal sensing network for an available amount of
resources. We can thus move from an era of best guesses to an era of defensible,
optimized sensing networks based on established goals.
Recommendations:
View IOOS as prediction system.
Incorporate assessment as an essential component of modeling and analysis. How well can
issues be addressed with the present system? What metrics are appropriate for a specific
issue? How is a modeling component that addresses multiple issues assessed?
Use modeling to inform design and/or augmentation of the system.
Data Management and Communications (DMAC): Previously we discussed the “design”
of the observing system to be a result of articulating a vision, identifying priorities and
requirements and suggesting a physical system implementation that would satisfy the
requirements given certain constraints. In the field of system engineering this design is
referred to as an architecture and applying some architecture principles provides a
framework for describing and discussing gaps. Prior efforts to characterize a fully
functional DMAC system have included elements from the entire data lifecycle (Hankin,
2005; Blueprint, xxx; PICO, 2012). The envisioned system delivers data, collects metadata,
provides analysis and visualization tools and provides for the long term preservation and
reuse of all of this information and it does so seemlessly across regional, national and
global boundaries as well as across disciplinary boundaries. The currently enacted system
falls short of this vision in many ways. Some of these gaps between the existing system and
the envisioned system are identified herein, and some suggestions for filling the gaps are
made. Like others before we note that the suggestions for filling gaps address solving
organizational change issues more than technical issues (Hankin et al., 2010).
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Web Services are the interface between systems
Since information is the primary artifact that flows between subsystems, a
cyberinfrastructure is key to enabling this information exchange. The means by which
information is exchanged is over a network and the network of choice is the public internet.
Currently, the most effective means to exchange information between computers on the
public internet is by utilizing web services. We use the term web services generally to
mean a mechanism or protocol for web applications to exchange information over a
network. There are several types of web services that have been successfully applied to
oceanographic and atmospheric data and products in numerous limited scale projects
(Blower et al., 2010). But, these applications aren’t limited to pilot projects. Full national
scale implementations of spatial data infrastructures based on web services are emerging
(Proctor et al., 2011, Inspire ????) . To many people data systems still rely on old web
browsing and/or ftp solutions. This will never result in the desired level of functionality
from the system. (Cite Ch.4 example of CO-OPS web services)
Web services work: use the quote from Rob Bassett CO-OPS about increases to the volume
of data served by CO-OPS. Verify with him. In 2007 the NOAA Center for Operational
Oceanographic Products and Services began a development effort in collaboration with the
IOOS program office to implement web services interfaces to their data. At that time, COOPS data was distributed primarily as files linked to static web pages. By 2011, with three
types of web services in place, the volume of data distributed by CO-OPS was evenly split
between web services and traditional web pages, and in 2012, the ratio has grown to 3:1.
How should IOOS DMAC be structured?
The Blueprint identifies a number of functions that must be fulfilled by DMAC and
describes nodes that satisfy these roles. Data assembly centers (DAC) are viewed as a
central part of the DMAC architecture, yet the form these take and the roles and
responsibilities within the system, especially with respect to discrete elements of the data
ifecycle, are not yet certain. How should they be organized and funded? What are their
responsibilities with respect to data content? Some DACs are regional and others are
thematic and still others focus on specific observing systems. Data flows through the
system and at each exchange there is the possibility for information loss.
It may be useful to compare/contrast IOOS DMAC with IMOS. Data Fabric is a common
resource for all of IMOS. National Centers are integrated by a single data management
framework mandated by a central governance facility. IOOS does not have that level of
control of any one node so there must be a more collaborative commitment to the
information needs of the whole system. But, in order to commit, the information needs
must be known and documented. At this point they are not well known.
Archives are a particular type of DAC. Archiving is an essential element of good data
stewardship and of the IOOS data lifecycle. The standards for IOOS DMAC data
dissemination are the same as those that the archive needs. The interface between a data
provider and the archive is the same as that between a data provider and the public.
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Archive also distributes data according to the same protocols thereby (potentially)
alleviating some of the data serving burden on the data provider. Archive process relies on
metadata further emphasizing the critical role data documentation plays in enabling all the
functions of the system. We need to think of the scope of the information system as
encompassing much more than just the environmental observations themselves but
includes the entire lineage. (Rutz et al CWP)
Open Data/Open Software Development/Open Standards
In a collaborative SoS such as IOOS openness is a well-known enabler of successful system
development. First, open data is essential to provide the information upon which all of the
desired IOOS capabilities can be built. But, open data need not be synonymous with free
data (Woll et al CWP).
Beyond sharing data, sharing experience is critical to advance IOOS. An emerging and
viable business model driven by open source software development practices is resulting
in profitable companies. But open source development is much more than a willingness to
share code. It is a commitment to collaboration across the entire software development
cycle and is enabled by tools such as online code repositories, wikis blogs and other
information sharing portals. With a commitment to open source development coupled
with training in using open source tools effectively, many of the software needs of DMAC
will be developed faster and with higher quality than could otherwise be accomplished
(Howlett CWP). Developers within the IOOS Regional Associations have recently begun
publishing software on open source code sharing sites and as a result the level of
collaboration and code reuse across the RAs has increased significantly.
Finally, the standards on which DMAC is built are themselves open. They evolve according
to requirements from new communities and participants. Maintaining this commitment to
open standards development is important to building trust in the user community.
(Probably don’t want to go down this road but there is a strong push for a data publishing
enterprise similar to the journal system. Unless and until publishing data is an element of a
scientist’s career progression, we will continue to experience resistance to sharing data.)
Example of a journal that provides a venue for publishing data that includes a peer review
process and links explicitly to papers. Motivation for scientists to embrace open data
sharing.
http://onlinelibrary.wiley.com/journal/10.1002/%28ISSN%292049-6060
Quality Control and Quality Assurance
An essential role of cyberinfrastructure is to provide tools to discover and access
information about the ocean and achieving that goal is a difficult task. It must be assumed
then that the information that is delivered to users is of sufficient quality to be useful.
Assessing, documenting and improving the quality of the observations and derived
products that result from IOOS activities is a responsibility that applies to all elements of
the system. Observing system operators have an obligation to keep their instrumentation
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and methods inline with the state of the science practices and data users in the modeling
and analysis subsystem have a responsibility to view the data in light of their inherent
uncertainties and when anomalies are discovered to communicate that information back to
the observing system operators. As with other elements of the system the DMAC
cyberinfrastructure has responsibility for delivering this information between system
nodes using technologies the enable machine to machine interaction and unambiguous
interpretation of the information. DMAC operators are unlikely to develop quality control
algorithms or quality assurance protocols for instrument calibration, but they do have a
role to ensure that this information is captured and codified using relevant IT standards.
QARTOD (quality assurance of realtime observational data; Howard CWP) has been an
effective grass-roots effort to establish best practices in QA over the last decade, and it has
recently been endorsed and supported by the IOOS Program Office. It is an appropriate
model for development of variable-specific QA procedures that can be adopted by IOOS
providers.
RECOMMENDATIONS:
Web services distribution should become the de facto standard for disseminating
information and the requirement rolled into funding management. NOAA is currently
pursuing a Data Access procedural directive stating something very similar.
Develop a detailed framework for DMAC that builds on the Blueprint and DMAC 1.0 by
exploring the types, functionality and number of DACs that should logically constitute the
IOOS DMAC.
Promote open source approaches to infrastructure development and support it through
establishment of readily found clearing houses, repositories and encourage/reward use of
the system.
Adopt QARTOD as a starting point for QA development within IOOS
Reference white papers: Lankhorst et al.
Interoperability: More important than the way information is requested and received over
the internet (i.e. web services), is the content and structure of that information (i.e. the
structure of the data in files, the conventions used to identify the data elements, and the
linkages between information in a file to information resident somewhere else on the
network). The ability for a system on the internet to convey information to another system
is only successful if the receiving system understands the information. An often overlooked
implication is that interoperability is defined with respect to multiple systems, not as an
attribute of a single subsystem, and it is therefore not only a consideration for DMAC but
for the system as a whole. Argo float data files are not interoperable in and of themselves.
The Argo data system as a whole may be interoperable with the modeling efforts of a
university if and only if modelers at the university can 1) locate the particular Argo data of
interest and 2) request and receive the data of interest, and 3) understand the data such
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DRAFT IOOS Summit Report: September 18, 2012
that it is used in the modeling efforts in a scientifically appropriate way. The
cyberinfrastructure must evolve according to requirements from both the observational
systems and the modeling systems.
The data storage and access component of DMAC is well defined for data sources including
in-situ buoys, HR Radar, and gridded data from satellites and models (Howlett CWP).
However, there has been in large part not enough involvement from the operational
modeling centers to help prioritize DMAC requirements. Too often they operate as a
separate system. Clearly the operational centers assimilating data are a vital client. Other
groups that must have ready access to information for the system to function smoothly
include scientists, data assimilation systems, weather forecasting offices and product
developers.
Another way to promote interoperability is to broaden the interaction between instrument
manufacturers to instrument operators. Metadata generation starts with the manufacturer.
Placing the responsibility for digitizing instrument specifications and factory calibration
results on the instrument operator is inefficient and error prone. One possible way to
address this issue is to write a standardized metadata document from manufacturers to
users into contracts and purchase agreements. A self registration goal for automated
introduction of new sensors to the system is an ambition of the NSF OOI.
Interoperability is enhanced through judicious use of standards but conversely, adopting
standards does not guarantee interoperability (Blower et al., 2010; Hankin et al., 2010b).
Decisions on the application of standards involves input from observations, modeling and
data management systems. More work on tools for clients is needed (this will drive
compliance). netCDF is a standard today because the software libraries exist for so many
client applications (Howlett et al CWP).
As an example consider the flow of metadata from the observations subsystem through
the cyberinfrastructure to the modeling and analysis subsystem. Metadata or more
accurately, documentation about the life cycle of data, is crucial for understanding the
applicability of data to a situation or science problem. The origin of the data lifecycle
begins at the sensor manufacturer. Sensor manufacturers often provide digital
information about the sensor but do so in their own proprietary formats. If manufacturers
were to publish this information using the same data standards that are being
implemented within the cyberinfrastructure then the entire IOOS data lifecycle would be
made more efficient (because humans wouldn’t need to transform or transcribe metadata
manually) and information loss would be lessened (because humans make mistakes).
RECOMMENDATIONS:
Enumerating the clients and the recipients of data is as important as defining the protocols
by which DACs will distribute data.
Contribute all possible data to GTS
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DRAFT IOOS Summit Report: September 18, 2012
Community pushes the manufacturing sector to embrace interoperability in the same way
we are. Wherever possible and at every stage of the data lifecycle strive for automated
collection of metadata.
Product development: without products that directly address user needs IOOS may fail to
demonstrate its utility. Explicit planning for this subsystem is vital and yet it is seldom
included as a functional component of IOOS. It is instead included in modeling and
analysis, yet its roles and responsibility are distinct from what is typically the
responsibility of modelers and analysts. Recognition of the interested parties and
coordination among them is an important first step. This type of user engagement is not
typical of modeling components, nor of analysis centers. Funding to support product
development and its evaluation and refinement is essential to ensuring the observing
system is truly end-to-end. Industry may find an important niche in product development.
This topic it addressed clearly in Chapters 2 and 4 but we mention here because a
comprehensive design should better recognize the need for this subsystem and find
appropriate ways to support it.
Aggregated Recommendations
In summary we present the following recommendations and challenges.
From the overarching issues:
 Accommodate differing priorities, variables, and design approaches at differing
scales.

Establish essential/core variables as a unifying design element that cuts across all
scales.

Consider a system-of-systems approach that ensures the ability to exchange
information at acknowledged bounds of the system (e.g. global, regional, local).

Consider an end-to-end design that incorporates existing components and identifies
any components/subsystems that are under-developed. Examine whether product
development falls within the modeling and analysis subsystem or should be
considered as an additional subsystem.
Observing challenges:
 How is adequacy of an existing collection of observing assets best assessed and gaps
best defined? Should it be done by variable? By priority? By geographic location?
Some mix of these?

How should the technologies to fill gaps be identified? Should we advocate for
standards, or common practices, across scales as a way to improve efficiency and
reduce cost? Or will this stifle innovation?
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DRAFT IOOS Summit Report: September 18, 2012

How do we promote bringing new technologies into IOOS while maintaining an
operational output? Given a large gap in biogeochemical and ecosystem automated
observing, should a dedicated effort be made to advance these technologies?
Modeling:
 View IOOS as prediction system.

Incorporate assessment as an essential component of modeling and analysis. Assess
how well issues can be addressed with the present system? What metrics are
appropriate for evaluating a specific issue? How is a modeling component that
addresses multiple issues assessed?

Use modeling to evaluate design and/or augmentation of the system.
DMAC:
 Web services distribution should become the de facto standard for disseminating
information and the requirement rolled into funding management. NOAA is
currently pursuing a Data Access procedural directive stating something very
similar.

Develop a detailed framework for DMAC that builds on the Blueprint and DMAC 1.0
by exploring the types, functionality and number of DACs that should logically
constitute the IOOS DMAC.

Promote open source approaches to infrastructure development and support it
through establishment of readily found clearing houses, repositories and
encourage/reward use of the system.

Adopt QARTOD as a starting point for QA development within IOOS
Interoperability:
 Enumerating the clients and the recipients of data is as important as defining the
protocols by which DACs will distribute data.

Contribute all possible data to GTS

Community pushes the manufacturing sector to embrace interoperability in the
same way we are. Wherever possible and at every stage of the data lifecycle strive
for automated collection of metadata.
References/Reading List
CWPs
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DRAFT IOOS Summit Report: September 18, 2012
Priorities For Governance Of Data
Management And
Communications For Ocean
Observations
Alexander, C.
J. Thomas, K. Bennedict, W. Johnson,
R. Morrison, J. Andrechik, E.
Stabeneau, M. Gierach, K. Casey, R.
Signell, H. Norris, R. Proctor, K.
Kirby, D. Snowden, J. de
LaBeaujardiere, E. Howlett, S.
Uczekaj, K. Narasimhan, E. Keys, M.
Trice, and J. Fredericks
The Need For Improved MetOcean Data To Facilitate: Offshore
Renewable Energy Development
IOOS Data Assimilation:
Connecting Regional Associations
and the National Backbone
Revising the IOOS National Wave
Observation Plan
Toward a US Animal Telemetry
Observing Network (US ATN) for
our Oceans, Coasts and Great
Lakes
Bailey, B.
M. Filippelli, M.Baker
Bayler, E.
F. Aikman, Y. Chao, and A. Mehra
Birkemeier, W.
L. Bernard, R. Jensen, R. Bouchard
Block, B.
K. Holland, D. Costa, J. Kocik, D. Fox,
B. Mate, C. Grimes , A. Seitz , H.
Moustahfid, M. Behzad, C. Holbrook,
S. Lindley, C. Alexander, S. Simmons,
J. Payne, M. Weise and R. Kochevar
P. McEnaney, G. Leshkevich
Developing a Great Lakes Remote Colton, M.
Sensing Community in Support of
IOOS/GLOS
Building Coastal IOOS for the Next Crowly, M.
Decade: Following up on the
Regional Build Out Plans
Design Of The Great Lakes
Observing System Enterprise
Architecture
Requirements for Global
Implementation of the Strategic
Plan for Coastal GOOS
Expanding Biological Data
Standards Develement Processes
for US IOOS: Visual Line Transect
66
Dekker, T.
H. Seim, A. Jochens, J. Quintrell, D.
Hernandez, J. Kohut, R. Morrison, M.
McCammon, H. Price, L. Rosenfeld, S.
Skelley, J. Thomas
J. DePinto, S. Ruberg, M. Colton, J.
Read, D. Schwab, N. Booth
DiGiacomo, P.
T. Malone
Fornwall, M.
R. Gisiner, S. Simmons, H.
Moustahfid, G. Canonico, P. Halpin, P.
Goldstein, R. Fitch, M. Weise, N. Cyr,
DRAFT IOOS Summit Report: September 18, 2012
Observing Community for
Mammal, Bird, and Turtle Data
Outreach and Collaboration Emerging Activities
Connecting National Initiatives:
Sharing Best Practise In
Integrating Ocean Observing
Systems
Smart Ocean/Smart Industries:
Scaling Up Of Ocean Data
Collection By Industry
Integrating Active Acoustics in
Observing Systems
Quality Assurance of Real-Time
Ocean Data
IOOS DMAC Challenges and
Successes
The U.S. IOOS Program Office
Perspective On Observing System
Capabilities: Gap Assessment
The U.S. IOOS Program Office’s
Perspective On Integration
Challenges And Opportunities
Usage Tracking for OOS
Evaluation and Enhancement
Data Quality Control In The U.S.
IOOS
Identifying Stakeholder Driven
User Needs in the Southeast
Large Regional Testbeds:
Bridging The “Valley Of Death”
Great Lakes Observing System
Enterprise Architecture Design
Report Summary
Linking The IOOS Animal
Tracking Network With The
Ocean Tracking Network
The Observing System Monitoring
67
D. Palka, J. Price, D. Collins
Fredericks, J.
Hill, K.
Arko, Chandler, Maffei, Pearlman,
Smith, Stocks, Waldmann
D. Mills, T. Moltmann, R. Rayner, Z.
Willis
Holthus, P.
Horne, J.
Howard, M.
J. Jech, H. Moustahfid , W. Michaels,
R. O’Dor
R. Crout, R. Toll Jr.
Howlett, E.
K. Wilcox, A. Crosby, G. DeWardener
IOOS PO
IOOS PO
Kite-Powell, H.
R. Morrison
Lankhorst, M.
F. Bahr, E. Boss, P. Caldwell, O.
Kawka, M. Vardaro
J. Dorton, D.Porter, J.Virmani
Leonard, L.
Mooers C.
No Author
O’Dor, R.
F. Whoriskey, D. Fox, J. Kocik, K.
Holland, J. Payne, H. Moustahfid
O'Brien, K.
S. Hankin, T. Habermann, K. Kern, M.
DRAFT IOOS Summit Report: September 18, 2012
Center: Moving Toward An
Integrated Global Ocean
Observing System
The NOAA National Data Buoy
Center Contributions to the US
Integrated Ocean Observing
System
IOOS Stakeholders and
Beneficiaries
IOOS Modeling Subsystem: Vision
and Implementation Strategy
A National Glider Network For
Sustained Observation Of The
Coastal Ocean
A Vision of the Data Cycle within
the IOOS Observing Subsystem
Enhancing Stakeholder
Engagement: Toward NextGeneration Product Development
in the R2O Process
Interagency Collaboration For
Operationalizing Datums
Standards
The Ocean Observatory Initiative
Options For Integrating Private
Sector Oceanographic Data
Little, R. Mendelsohn, D. Neufeld, B.
Simons
Portmann, H.
L. Bernard, J. Swaykos, R. Crout
Rayner, R.
Rosenfeld, L.
Y. Chao, R. Signell
Rudnick, D.
R. Baltes, M. Crowley, C. Lee, C.
Lembke, O. Schofield
Rutz, R.
R. Ragsdale, E. Kearns, V.
Subramanian, K. Wilcox, R. Crout, K.
Witcher, T. Ryan, M. Biddle, K.
Arzayus, C. Alexander
G. Kuska, P. Moore
Thoroughgood,
C.
Tronvig, K.
J. Dunnigan, J. Kolva
Weller, R.
Woll, S.
T. Cowles
M. Roffer, S. Root
Other References
Blower, J.D., Hankin, S.C., Keeley, R., Pouliquen, S., de la Beaujardière, J., Berghe, E.V., Reed, G.,
Blanc, F., Gregg, M.C., Fredericks, J., others, 2009. Ocean data dissemination: New challenges
for data integration, in: Plenary Talk at OceanObs. pp. 21–25.
de La Beaujardière, J., Beegle-Krause, C.J., Bermudez, L., Hankin, S., Hazard, L., Howlett, E., Le, S.,
Proctor, R., Signell, R.P., Snowen, D., Thomas, J., 2010. Ocean and Coastal Data Management,
in: Proceedings of OceanObs’09: Sustained Ocean Observations and Information for Society,
ESA Publication WPP-306. Presented at the OceanObs’09: Sustained Ocean Observations
and Information for Society, European Space Agency, Venice Italy, pp. 226–236.
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DRAFT IOOS Summit Report: September 18, 2012
Hankin, S.C., Bermudez, L., Blower, J.D., Blumenthal, B., Casey, K.S., Fornwall, M., Graybeal, J.,
Guralnick, R.P., Habermann, E., Howlett, E., others, 2010. Data Management for the Ocean
Sciences–the Priorities and Considerations for the Next Decade.
Hankin, S.C., Blower, J.D., Carval, T., Casey, K.S., Donlon, C., Lauret, O., Loubrieu, T., Srinivasan, A.,
Trinanes, J., Godoy, O., others, 2010. NetCDF-CF-OPeNDAP: Standards for ocean data
interoperability and object lessons for community data standards processes, in: Oceanobs
2009, Venice Convention Centre, 21-25 Septembre 2009, Venise.
Hankin, S.C., Integrated, U.S.N.O. for, Observations, S.O., Integrated, U.S.N.O. for, Management,
S.O.O.D., Committee, C.S., 2005. Data Management and Communications Plan for Research
and Operational Integrated Ocean Observing Systems: Interoperable Data Discovery,
Access and Archive. National Office for Integrated and Sustained Ocean Observations.
Keeley, R., Woodruff, S., Pouliquen, S., Conkright-Gregg, M., Reed, G., 2010. Ocean data:
collectors to archives, in: OceanObs’ 09: Sustained Ocean Observations and Information for
Society (Vol. 1), Venice, Italy, 21-25 September 2009.
Panel for Integrated Coastal Ocean Observations (PICO), 2012. “Requirements for Global
Implementation of the Strategic Plan for Coastal GOOS” (No. GOOS-193), GOOS Reports.
Intragovernmental Oceanographic Commission.
Stein, L., 2008. Towards a cyberinfrastructure for the biological sciences: progress, visions and
challenges. Nature Reviews Genetics 9, 678–688.
U.S. IOOS Program Office, 2010. U.S. Integrated Ocean Observing System: A Blueprint for Full
Capability ( No. 1.0).
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Chapter Four:
Integration Challenges and Opportunities
I. Introduction
A truly integrated ocean observing system is still an aspiration, and will remain so unless
and until we as a community address INTEGRATION in all of its forms. Certainly, there is
strong consensus that the envisioned integrated system should provide ocean state
estimates (past, present, and future) to a known degree of accuracy based on the integrated
use of ocean observing networks, data assimilative model predictions, and data
management and communication tools. These estimates should produce “actionable”
information regarding physical, chemical, and biological characteristics delivered to the
various user communities. Such information can range from scientific findings, to
operational products to support safe navigation, and products in support of public
education and public policy, to name a few examples. Importantly, and as envisioned from
the outset of IOOS, these parameter measurements and ocean state estimations should be
incorporated – integrated – into programs that quantify the meteorological, terrestrial, and
human impact/human influence drivers of change across time scales from seconds to
centuries.
But this is not enough. An integrated system must engage all providers and all consumers
of relevant data and data products at the local, regional, national, and global scales. It must
effectively address both the physical and ecological components of the ocean state. And it
must bridge the gap between basic & applied research and technology development, and
between operations and technology products. Certainly, we can point to several successes
in the latter respect over the last 10 years. The transition of satellite products to
operational use in coastal zone management (including, e.g., response to HABs and oil
spills), and the rapid introduction of HF Radar-derived surface current maps and data
assimilative high resolution coastal models are striking examples of successful, integrated
action across academia, government, and industry. But these achievements were not the
result of formal and sustained partnering between the research and the operational
segments of our community. There have in fact been very few opportunities for truly
integrated activities where new knowledge and new technologies inform and enhance
operational observing and prediction systems via well-understood transition pathways,
and where conversely, requirements and and lessons-learned from the observing and
prediction system operators inform and guide research and development. There is a need
to more effectively integrate the activities of the R&D community and the operational
community across all sectors (public, private, and academic) and across all scales of
interest (local, regional, national, and global). Only in this fashion can we unlock the
energy, expertise and creativity of our community to successfully address the rapidly
increasing societal needs for informed, safe, responsible, secure, and sustainable utilization
of our ocean resources.
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II. The “I” in IOOS
The late Admiral James D. Watkins, Chairman, U.S. Commission on Ocean Policy and CoChair, Joint Ocean Commission Initiative, stated in 2007 “It is now obvious that enhanced
and integrated observing systems are a key element underlying a robust ocean and climate
science strategy…A sustained, national Integrated Ocean Observing System (IOOS), backed
by a comprehensive research and development program, will provide invaluable economic,
societal, and environmental benefits, including improved warnings of coastal and health
hazards, more efficient use of living and nonliving resources, safer marine operations, and a
better understanding of climate change. However, the value of this system will be fully
realized only if an adequate financial commitment is also provided to support integrated,
multidisciplinary scientific analysis and modeling using the data collected, including
socioeconomic impacts. Unfortunately, support for the lab and land-based analysis of the
data derived from these systems is often inadequate, diminishing the value of these
programs, while support for socioeconomic analysis is virtually nonexistent.” Admiral
Watkins also pointed out: “While there is a continuing effort to integrate programs and
activities, it is the exception not the rule. In addition, the budget process often discourages
interagency cooperation as funding for multi-agency programs is subject to cuts or
reductions during internal agencies budget negotiations, compromising the integrity of the
broader strategy and promoting further competition among federal and nongovernmental
players.” (Testimony before the Committee on Commerce, Science, and Transportation,
Subcommittee on Ocean, Atmosphere, Fisheries, and Coast Guard, U.S. Senate, Washington,
D.C May 10, 2007)
This call for strengthened integration among disciplines; among observations, modeling,
analysis, and data product dissemination; between the research and operational
communities; and among the various federal and nongovernmental organizations, still
resonates in today’s ocean observing and prediction community. For example, there is
widespread acceptance that a defining feature of a successful operational system is a full
integration of its observing and prediction sub-systems. There is a very simple reason for
this: it is not possible now, nor in the foreseeable future, to monitor (measure) the ocean
with high enough spatial and temporal resolution to provide the various user communities
with the data products they require. And even if we were able to populate the ocean with
an adequate number of sensors, the present-state conditions tell us very little about future
conditions. Computer models enable us to fill gaps in the 4D information domain, providing
estimates of ocean state variables at locations and times where we possess no direct
measurement, as well as predictions of how these variables will change over time. On the
other side of this integrated system, direct ocean measurements provide models with
initial and boundary conditions, as well as real-time constraints, to significantly improve
model performance and to enable a reasonable understanding of model skill. The
remaining component of this integrated observing & prediction system is the data
management and communication sub-system. Without the capacity to access, verify
(QA/QC), and combine data and data products across multiple information types and
sources, IOOS cannot function as a user-driven operational system. For this reason, ocean
data integration has been a central goal of IOOS from the start, and Data Management and
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DRAFT IOOS Summit Report: September 18, 2012
Communications (DMAC) efforts were some of the first projects supported in the early days
of IOOS.
The question before us is whether the integrated observing-prediction-data management &
communications system as presently envisioned by U.S. IOOS and implemented via
partnerships across the academic, public, and private sectors can achieve a sustainable
user-driven, operational system. It is appropriate to first note some leading attributes of
such operational systems:
● Composed of three component subsystems: observing, modeling and data
assimilation (prediction and data analysis), and data management and
communications;
● Certified to meet evolving user requirements expressed as standard metrics with
known error attributes, which in turn may vary over time and space;
● Documented sustained sponsorship for application-dependent, real-time product
delivery AND ongoing R&D with clear transition pathways;
● Demonstrated robust and resilient operations;
● Designed to support experiments as well as rapid response to marine crises
Success will require that we commit to the necessary periodic introspection and ensuing
community-wide effort to ensure that the U.S. Integrated Ocean Observing System moves
away from a cooperative enterprise with numerous partners striving for their individual
goals to a coordinated enterprise striving for a single, integrated system. Such an enterprise
should include the following attributes:
(1) global, national, regional, and local components;
(2) ecological, biogeochemical, and physical (oceanographic, meteorological, and
hydrological) components, including coupled components (e.g., coastal ocean and
atmosphere);
(3) observing, modeling, data assimilation, and data management and
communication components;
(4) academic, public, and private systems;
(5) data/information providers and users (many are both);
(6) “flexible” (adaptive? responsive?) observations, predictions, and products;
(7) multiple uses/multiple users/multiple sponsors of observation and prediction
components and platforms;
(8) active partners in the 17 sponsoring U.S. federal agencies; as well as regional,
state, and local agencies;
(9) processes and funding to ensure R&D-to-Operations and Operations-to-R&D;
(10) processes to validate and prioritize requirements at the global, national,
regional and local levels to inform funding and long term planning decisions;
(11) integration of all requisite disciplinary fields – technical and non-technical – to
enable widespread and effective dissemination and use of data and data products;
(12) integration of remotely-sensed data with in-situ observations and model
output;
(13) integration of real-time data management with maintenance of long-term
archives;
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(14) integration with ocean science and engineering workforce development, STEM
education, public policy, and public outreach.
In the following we describe the challenges and opportunities associated with achieving a
comprehensively integrated U.S. ocean observing system.
III. Opportunities for, and Challenges to Integration
The past 10 years have provided valuable lessons in the power of integration. We have
witnessed dramatic improvements in coastal ocean prediction systems as a result of data
assimilation across a variety of in-situ and remotely-sensed data types. We have seen the
impact of coordinated multi-agency and multi-university action in response to pressing
national needs, such as occurred during the Macondo oil spill in the Gulf of Mexico.
Throughout, we have also observed the power of using ocean observations and predictions
to inspire and educate the next generation of STEM professionals.
Success has occurred most often when efforts were made to ensure interoperability among
the various public, private, and academic observing, prediction, and data management &
communication systems. Our eventual, long-term sustained success will require that we
make integration and interoperability across systems and organizations the top priority for
U.S. IOOS. This must necessarily include interoperability within the IOOS network (that is,
between the 11 Regional Associations (RAs), the 17 sponsoring US federal agencies, private
industry, and a growing number of governmental and nongovernmental organizations) and
interoperability of IOOS assets with the international Global Ocean Observing System
(GOOS) and Global Earth Observation System of Systems (GEOSS). This, in essence, is our
challenge.
A. Overall
One could argue that achieving Integration in all its aspects must begin and end with the
integration of programs and activities across federal and non-federal (local and state
governments; private; academic) organizations. This integration will require cultural
changes on all sides. For example, the federal government cannot own sufficient platforms,
sensors, models and computational and analysis systems to comprehensively and at
adequate resolution cover the entire U.S. coastal ocean and Great Lakes. Academic and
private industry partners must play a role, as active providers of data and data products,
that is to say, as “operators”. This evolution will require trust-building, experiments,
failures, and joint action to address weaknesses. It will require that the community address
head-on the longstanding issues related to data and data product liability, and the use of
proprietary data. Once this evolution is complete and we have moved from cooperative to
coordinated in our work together, the community will be in a much stronger position to
deal with the very difficult issues that challenge all S&T programs, in particular:
 understanding the user needs – and therefore the requirements - for products and
services and
 the development of transition pathways for new technologies to address those
requirements.
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This process, informed from the outset by the various user communities, will require that
our operational systems be multi-disciplinary and adaptive, and that they deliver a clear
return-on-investment, including, in addition to economic (operational) and scientific
benefits, contributions to public safety and security, STEM education, public outreach, and
policy making.
B. Observations
The existing U.S. coastal ocean observing system was built with the support of a wide range
of sponsors and users, and with applications as varied as safe navigation and beach water
quality monitoring. Platform locations and sensor types therefore arose as a “mission
dependent”, uncoordinated collection of sensors that bears little or no resemblance to a
carefully designed, multi-sensor, multi-user observing system. This is not to say that we
should consider dismantling the present system; only that we need to examine the existing
system of sensors and sensor platforms with a view to identifying the opportunities for
improvements. This could come from the facilitation (and permitting) of co-located sensors
on existing platforms, or perhaps even re-locating existing platforms based on scientific or
operational need. The wise use of increasingly scarce resources will guide many of these
decisions, but in all cases the assurance of meeting an identified scientific/societal need
should be paramount. And herein lies an important but often misunderstood or
unrecognized point – scientific and societal needs should be one and the same and should
be adopted as such in the years ahead as a fundamental principle of IOOS. The ocean
sciences community understands the limitations of existing observation and prediction
systems to deliver all of the required information at all locations in real time. As mentioned
earlier, we employ models and data assimilation to fill the very large gaps in our direct
observations. Although we need to do more to understand the skill of these combined
systems, we have seen their impact in providing real-time and near real-time information
to users, addressing important societal goals. The scientific community in all sectors –
public, private, and academic – must act in a coordinated fashion to improve and expand on
these successes. This will necessarily involve experimentation, as will be described in a
later section.
As mentioned earlier, our existing observing systems are an amalgam of federal, state and
local government, academic, and private systems. The integration of the data and data
products from these systems into a single report of ocean conditions is impeded by a
number of issues, including liability concerns (or at least the perception of liability
concerns) on the part of academic institutions, and the desire to protect in some fashion
the proprietary data and data products delivered by private industry. Here we should
mention the Meteorological Assimilation Data Ingest System (MADIS), established by the
National Weather Service (NWS) to collect, store, and disseminate observations from nonfederal weather observing networks. MADIS has several categories that designate how
contributed data will be handled, including a category for proprietary data (usually from
private network operators) that is authorized for use within NOAA, but is not authorized
for further distribution outside of NOAA. Under the National Mesonet Program (NMP) and
through the use of restricted licenses, MADIS currently receives observations from nearly
10,000 professional grade private sector weather stations. Given the success of the NMP in
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facilitating access to large numbers of high quality weather observations via restricted
licensing and the MADIS data architecture, implementing a similar data policy and
architecture for IOOS should be given serious consideration. Likewise, a data policy of
unrestricted licensing and an unrestricted data architecture should also be considered. This
is a long-overdue conversation that should be pursued immediately. Failure to act will
threaten continued investment by non-governmental organizations in future platforms and
systems.
Quality control is recognized by the community as a key requirement but remains a
challenge due to the lack of definition of processes and – perhaps most significantly limited funding to support the implementation of mature quality control procedures. In
this regard, it would be helpful to ensure close coordination between the RAs and centers
of data at multiple federal agencies such as NOAA, EPA, USGS, USACOE, etc., to ensure that
consistent QA/QC and archiving procedures are employed across the nation. We must
recognize that this issue will only increase in importance and complexity as the volume of
data and data products expands dramatically in the years ahead. Ultimately, we as a
community need to convey the critical importance of QA/QC – it is the process that ensures
that our data and the derived products are reliable, and therefore confidently usable by the
user. Usability imparts value, ensuring a return-on-investment and contributing to the
sustainability of the IOOS enterprise.
Since its inception, IOOS has struggled with the challenge of incorporating biological
observations into the IOOS architecture. The difficulty of enabling biological data
interoperability within IOOS is twofold: (1) building consensus among the many different
communities of practice within ocean biology and (2) the adoption by these communities
of DMAC standards that will link their data collections to the larger integrated ocean data
architecture that is IOOS. There has been progress. Under the Census of Marine Life, Ocean
Biogeographic Information System (OBIS) a standard was implemented that would allow
for integration of species observation data. This standard, Darwin Core is a biogeographic
data standard that allows for sharing of data that are spatially, temporally and
taxonomically resolved. Furthermore, the standard is extensible to address other richer
biological data including absence, abundance, movement, life stage, behavior and others.
To that end, IOOS has recently completed, in partnership with the US Geological Survey’s
OBIS-USA program, an application of Darwin Core that captures fish abundance. Similar
efforts are under way for the high frequency active acoustic systems used for fish and
zooplankton surveys, and for biological data from tagged animals (physical oceanographic
data from tagged animals carrying CTD and similar sensors are already being imported into
IOOS).
The USGS OBIS-USA team is responsible for developing biological data standards within the
IOOS DMAC infrastructure, as well as contributing to the international standards for
biogeographic data, Darwin Core. The result is a Marine Biogeographic (MBG) standard
that that is consistent with the global Darwin Core standard while serving US and IOOS
priorities. This standard enables data collectors to render their data maximally useful - the
data can be located, understood (easily viewed and evaluated for suitability of use) and
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accessed (via web services) by colleagues, other members of the ocean science community,
decision makers, and planners. One of the great challenges of securing biological data for
IOOS has been the diversity of methods used to gather biological data. The OBIS-USA and
the MBG standards process offers communities of practice a means of creating benchmark
documentation of their methods that also ensures that their data will mesh well with other
IOOS data. While considerable challenges remain within the realm of ocean biological data
collection and ocean ecosystem modeling, uncertainties about the data themselves and the
ability to synthesize the rich variety of biological information within IOOS are being
addressed through the MBG process.
A final note with respect to observations is the need to ensure that we as a community
commit to the education and training of the next generation of ocean observing
professionals. Operational systems ultimately are as effective, robust, and resilient as the
people who design, deploy, maintain and operate them. These are highly specialized skills
gained only by doing. And some of the skills, e.g., programming and data management
skills, are highly valued in other fields. Certainly, the integration of operational systems
into K-12 STEM education provides opportunities to inspire young people to pursue
careers associated with ocean observing.
C. Models
We have already discussed the value – actually, the absolute necessity – of numerical
models for the purpose of filling observational gaps in the 4D information domain, using
data assimilation to provide estimates of ocean state variables at locations and times where
we possess no direct measurements. Predictive algorithms provide estimates of how these
variables will change over time. Models therefore provide us with the ability to deliver realtime nowcasts as well as forecasts. They can also be useful in the reconstruction of past
conditions (hindcasts) and in the conduct of hypothetical scenarios (simulations), both of
which can be valuable tools in, e.g., emergency response and coastal ocean resource
management.
Yet, despite the critical importance of models to the ocean observing enterprise, it is clear
that there has not been balanced investment among the observing, modeling and
information management subsystems of U.S. IOOS. A more holistic approach is needed,
with usable, actionable information being the end goal. In this context, perhaps the most
important consensus resulting from the IOOS Modeling and Analysis Steering Team (MAST)
effort (see Ocean.US, 2008) was recognition that the academic R&D community and the
federal operational forecast centers should work cooperatively on such matters as skill
assessment, observing system design, prediction system experiments, etc. The committee
recommended the establishment of a system of sustained but evolving regional testbeds,
where ‘regional’ may include the domains of two or more of the IOOS RAs. The significant
coordination and information sharing that would be required to achieve the design and
operation of such testbeds and the conduct of comprehensive experiments, would move
the community much further along toward the integrated public-private-academic system
alluded to several times in this chapter. The assessment of model skill and the
communication of model uncertainty would, in addition to improving the state of the
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science, help to inform the public and the various user communities of the accuracy and
reliability of integrated sensor, prediction & analysis systems. Transparency and
information sharing builds trust among all stakeholders, an essential ingredient to ensure
credibility and both return-on-investment and sustainability of the IOOS enterprise.
Future coordinated model development activities must support an expanded effort to
couple existing ocean and atmosphere models. Several IOOS RAs have demonstrated the
importance of ocean surface boundary conditions to improved atmospheric forecasts.
These improved atmospheric forecasts can in turn dramatically improve the skill of coastal
ocean models.
Future coordinated model development activities will also provide the opportunity for
experiments with ensemble modeling of the ocean and atmosphere. We should take
advantage of the existing global, national, regional, and in some RAs, local scale models.
This ensemble approach would spur increased collaboration and coordination across
government and non-government organizations, and would provide valuable products for
use in both model enhancement and forecast skill improvement. The community
witnessed first-hand the impact of ensemble modeling during the Macondo oil spill, when
several models were employed in support of the response, and observations were used to
inform first responders as to which models were performing best at different times and in
different locations.
One final note with respect to the opportunities afforded by prediction and analysis
systems. We spoke in an earlier section about the need to re-examine the sensor types and
placement locations across the entire IOOS (government and non-government) enterprise,
with the aim of optimizing the system’s usability, reliability, robustness, and resiliency.
Prediction and analysis systems can guide this process by identifying critical ocean
parameters and observing locations that would improve model skill and therefore the
ocean state estimates employed by virtually all of our user communities.
D. Data Management & Communications
As mentioned earlier, ocean data integration has been a central goal of IOOS from the
outset, and Data Management and Communications (DMAC) efforts were some of the first
projects in the early days of IOOS. This focus on DMAC is understandable, since a userdriven, reliable and robust observing system cannot exist without the capacity to access,
verify (QA/QC), and combine data and data products across multiple information types and
sources. Users must be able to search for and retrieve the data they need, ingest these data
into their analysis or visualization software and decision-support tools, and understand the
source, quality, applicability and limitations of the data. Future use and reuse of these data
make similar demands of data stewardship and archiving. In practice, this generally
translates into a set of recommended or required standards and protocols. These standards
and protocols, employed and evaluated through a compliance and certification process,
form the framework for the DMAC activity.
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NOAA CO-OPS (Center for Operational Oceanographic Products and Services), NDBC
(National Data Buoy Center) and the U.S. IOOS Office have been collaborating for several
years on a data integration project that aims to increase interoperability between data
providers and the user community. The joint effort has recently focused on the
implementation of NDBC and CO-OPS’ Sensor Observational Service (SOS), as part of a suite
of web services, offering various new protocols, formats, and an expanded set of sensor
variables. This suite of new web services enhanced the data and services that CO-OPS and
NDBC was already providing through traditional web pages and facilitated machine-tomachine data transfer over the internet. Both organizations have made their SOS
observational data available as a collection of stations and in multiple data formats.
Previously these data could only be accessed for one station at a time. Since launching this
new capability, CO-OPS’ collections service has decreased the end users’ data processing
time by 70% and increased their data retrieval speed by 50%. In addition, NDBC and COOPS SOS services are available in CSV, TSV, XML and KML formats. KML is especially
important because it is used by a variety of GIS and mapping applications to display
geospatial data of interest to the oceanographic community. These integration efforts have
increased data interoperability, which translates to delivering their ocean data to a wider
customer base; faster, better and with less effort. For example at CO-OPS in 2011, fully half
of the 30 terabytes of data served were discovered, accessed and delivered by this suite of
web services which did not exist only five years earlier. At NDBC, these services are used to
automatically transmit archive data to the National Oceanographic Data Center.
The use of open standards and technologies has been at the core of the IOOS DMAC
philosophy. This has allowed the academic, federal, and industry partners to retain the use
of their individual tools and approaches, but also collaborate on a unified system of data
sharing and access. There has been a strong focus on the development and implementation
of standards to enhance interoperability, with significant progress in enabling the sharing
of observations and model output between the RAs, the federal agencies, and the user
community. The components of the DMAC architecture can be summarized by:
 Storage and Data Formats
 Catalogs, Data Discovery, Metadata, and Vocabularies
 Quality Control
 Data Access
 Data Products
Of the components listed above, Data Access has been the priority within IOOS as resources
and budgets have been reduced. The Data Integration Framework (DIF) pilot project was
carried out by the IOOS Program Office during fiscal years 2007-2010. This engaged the
RAs in making observations of seven core variables available via a specific web service
protocol. The exercise was successful in that it provided very specific targets for the RAs. It
did not define specific technologies to be used but defined specific web services (OGC SOS,
WMS, WCS ) or data transport protocols (DAP). While successfully engaging the RAs, the
approach also highlighted the challenges in allowing each RA to select its own path to a
solution. Depending on the skill sets available in each of the organizations, new solutions
were developed independently with different toolsets ranging from Java to C. Theoretically,
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this approach should be successful - the standards are well defined and as long as each
development team delivered a tool that complied with the standard specification, they
would meet the requirement. In practice however, the approach has faced numerous
challenges, including the development of stovepipe solutions. There has been progress
recently, including the establishment of the SOS Reference Implementation Working Group
to develop a single SOS standard based on SWE (Sensor Web Enablement).
In the past year, there has been a shift in the focus from the development and
recommendation of standards to the implementation of the technologies that deliver and
consume compliant standards. This is a breakthrough as a smaller subset of technical
teams now focus on the solution, which frees up the DMAC teams in the RAs to focus on the
implementation of these maturing technologies and the other DMAC requirements. The
IOOS Coastal Ocean Modeling Testbed (COMT) was a unique opportunity to implement and
evaluate many of the widely used technologies. A few notes on these technologies:
- Although they are open-source and intended to be community-based, they generally
have one individual developer responsible for the development and maintenance of
the tool. While the community may regularly provide feedback to the developer,
very rarely does the community contribute to the source code. The developers are
capable, but there is a limit to how much one person can manage.
- Due to the lack of funding and staffing, we do not have reliable pathways for ongoing
development and transition, including rigorous testing procedures.
- The technologies have not been tested for how they may scale to manage issues
such as very large data volumes.
Clearly, the challenge ahead of us is the maturation and testing of the selected technologies.
The data storage and access component of DMAC is well defined for data sources including
in-situ buoys, HF radar, and gridded data from satellites and models, and is evolving for
glider data. The availability and use of IOOS data from the RAs in the USCG SAROPS system
demonstrates the power of defined data sharing protocols, but incorporates a brokering
layer that also provides flexibility and a robust environment for mission critical
applications.
There continue to be significant challenges related to the successful population of metadata
and registration and subsequent discovery of metadata, data and associated web services.
New catalog systems that have been developed in the traditional GIS community are being
adopted for use in the ocean community, but these catalog systems are not a perfect match.
These systems were designed to generally manage temporally static GIS-style data of
feature classes and raster datasets. The ability of these catalog systems to handle timevarying point collections (e.g collections of buoys), unstructured grids and other complex
time-varying datasets is still evolving. These catalog systems also require intensive work to
set up and maintain and this requires a considerable commitment in terms of personnel
and budgets.
As mentioned earlier, quality control is recognized by the community as a key requirement
but remains elusive due to the lack of definition of processes and – perhaps most
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significantly - limited funding to support the implementation of mature quality control
procedures.
In the years ahead, and in view of continued and rapid changes in information technology,
DMAC should be driven with real-world use cases, emphasizing training and support for
existing technology and standards, and then building incrementally as use cases dictate.
The community should also take advantage of significant partnering opportunities such as
exist with the National Science Foundation’s Earthscope and Ocean Observing Initiative
(OOI), in part to ensure that the standards and protocols we use are indeed the best
practices available and to enable a common trust in our data assets.
Social media offers tremendous opportunities for communicating in innovative ways and
enabling broader community participation. It should be exploited within IOOS, providing
users a place in which to share techniques and experiences. This will both raise awareness
of the enterprise and hasten its development.
Finally, as we move forward with innovate strategies to meet the community’s needs with
respect to data management and communication, remaining flexible to new developments
in information technology, we should be mindful of the explosive growth of data and data
products in the years ahead. This growth has the potential to overwhelm both the
generators and the users of the information we seek to share. The solution will require
close coordination among all information providers and all users, and will likely include a
reduction in the information volume, e.g., via automated (autonomous) data processing and
filtering.
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IV. The Way Forward
In charting our course for the next 10 years, it is critical that we once again confirm and
commit to our destination. We understand that as a community we have committed to the
creation and operation of an ocean observing and prediction system that will support the 7
societal goals of the IOOS program. Achievement of these goals requires that we provide
reliable, credible, and understandable estimates of the space and time-varying physical and
ecological state of the ocean, in a fashion that will support the informed, safe, secure, and
sustainable utilization of our ocean resources. In essence, we are working together to build
and operate an information system, a system that can provide estimates of present
conditions while also providing the opportunity to look backward and forward in time.
Borrowing lessons learned from complex network design and decision-making, we should
consider adopting the perspective of “Valued Information at the Right Time” (see e.g.,
Hayes-Roth, 2005, 2006). This perspective requires that we answer the question Who
needs What information When? And further, How do we best deliver that information?
As has been stated numerous times in this chapter, it is our view that a coordinated effort
among public, private, and academic “producers” of information will be needed to fully
achieve the vision of IOOS. The effort must be informed by the “consumers” of this
information; it must be sustainable, multi-disciplinary and adaptive; it must bridge the
operational and research communities; and it must deliver a clear return-on-investment,
including, in addition to economic (operational) and scientific benefits, contributions to
public safety and security, STEM education, public outreach, and policy making.
A. Overall
Within the next 10 years, a first-generation information system that delivers valued
information at the right time to each and every consumer should become well-established
and sustained. This information system should link the (1) global, national, regional, and
local components; (2) ecological, biogeochemical and physical components; and (3)
observing, modeling and data assimilation (prediction and data analysis), and data
management and communications components. There should be ongoing and objective
assessments of both the technologies and the information products provided to the various
user groups, coupled to a vigorous R&D effort that addresses the next-generation system
requirements. These future requirements may include new observing system sensors and
networks, new information delivery systems, new modeling systems, and new applications.
Thus, the following vision will be realized by 2022:
● Research scientists, engineers, and technologists will approach their daily
R&D challenges with a 4D view (complete with known error attributes) of the
synoptic U.S. coastal ocean at their fingertips.
● These ocean state estimates will be based on observing networks and data
assimilative model predictions.
● All relevant disciplines will be engaged, across government and nongovernment organizations.
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●
The information delivered will be highly valued by a broad array of
consumers, and will support the informed, safe, secure, and sustainable
utilization of our ocean resources and the education of our students, the
general public, and policy makers.
B. Observations
As mentioned earlier, many of our legacy observing sensors and sensor platforms were
chosen and located based on specific scientific and/or operational needs. There needs to
be a system-wide assessment of the utility of these existing sensors and platforms, with a
view to a system-wide optimization (e.g., via the addition of new sensors to existing
platforms and/or the re-location of existing platforms). This optimization must consider
only the scientific and/or operational requirements associated with the data being
delivered in each instance. One avenue for this assessment process is the conduct of a
carefully designed series of observing system experiments - Observing System Simulation
Experiments (OSSEs) - to help optimize observing systems by revealing which types of
measurements at which locations are most important in producing a forecast of sufficient
accuracy over a given area. These experiments would likely employ data assimilation and
inverse techniques to assess the impact of the individual sensors on specific metrics (to be
developed in cooperation with the user communities). The array of sensors can then be
optimized. These experiments should be comprehensive and multi-scale (including across
Regional Associations), and they should be designed to challenge the ability of the suite of
sensors and data assimilative prediction models to provide estimates of the ocean state to a
known degree of accuracy. The experiments must be designed in a fashion that does not
guarantee success; these are NOT demos.
We need a community-wide discussion of data policy (and the supporting data handling
architecture) to optimize the integration of private sector data into the IOOS enterprise.
It is noteworthy that within the Meteorological Assimilation Data Ingest System (MADIS),
established by the NWS to collect, store, and disseminate observations from non-federal
weather observing networks, private sector stations represent approximately 90% of the
combined (private, government, university) inventory of professional grade weather
stations. Although a comparison of the two systems is not entirely appropriate, we note
that within NDBC, private sector stations represent less than 5% of the combined inventory
of professional grade oceanographic and coastal meteorological stations.
There should be continued support for enabling biological data interoperability within
IOOS. This will require consensus-building among the many different communities of
practice within ocean biology and adopting DMAC standards that will link their data
collections to IOOS. Work has begun in this area, using the standard (Darwin Core)
developed under the Ocean Biogeographic Information System (OBIS), to enable the
integration of species observation data. Specifically, IOOS has partnered with US Geological
Survey’s OBIS-USA program to develop an application of Darwin Core that captures fish
abundance. Similar efforts are underway for the high frequency active acoustic systems
used for fish and zooplankton surveys, and for biological data from tagged animals.
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Physical oceanographic data from tagged animals carrying CTD and similar sensors are
already being imported into IOOS, capitalizing on recent advances in miniature, low power
“bio sensors”. The anticipated outcome of these efforts is a Marine Biogeographic (MBG)
standard that that is consistent with the global Darwin Core standard while serving US and
IOOS needs. Success will require that this process for standards development will support
the biology community across all methods of biological data gathering, and that it provide
an understanding of the uncertainties associated with the data. The integrated use of these
physical and biological sensors has great potential for applications to marine ecosystem
assessment and management.
The existing IOOS infrastructure contains the technology and observations relevant to
offshore renewable energy development on the U.S. Atlantic and Pacific coasts and in the
Great Lakes. Real-time wind velocity data at requisite heights, planetary boundary layer
data, ocean current data, and wave measurements are all necessary for informed decisionmaking related to offshore renewable energy development. This represents a relatively
new user community in IOOS, and the activities outlined here should make provisions for
ensuring that relevant data products are generated.
During the next ten years, BOEM (US Department of the Interior’s Bureau of Ocean Energy
Management) will continue to perform analysis and planning for oil spills in coastal and
offshore waters along the U.S. coasts. NOAA’s Emergency Response Division will continue
to provide scientific support, including oil trajectory forecasts, when oil and hazardous
materials spills occur. All proposed lease areas for oil and gas or renewable energy will
require accurate information about the wind and ocean current fields and the environment
for the analysis of potential impacts, as well as potential requirements for monitoring
during construction, operations and decommissioning. IOOS regional observing systems
can and should provide some of the required data and information necessary for these
requirements. The RAs should also examine opportunities to develop data products useful
for resource agencies, states, and industry tasked with making operational decisions
concerning offshore energy development. This activity could be an outcome of the
Observing System Simulation Experiments in those regions where offshore energy
development is active or planned.
C. Models
As mentioned earlier, there has not been balanced investment among the observing,
modeling and information management subsystems of U.S. IOOS. A more holistic approach
is needed in the years ahead. This approach can and should be guided by the type of multiscale experiments (OSSEs) alluded to earlier in the context of observations. In fact, if we are
to achieve the long-term goals outlined in this chapter, we should assume that the
experiments will employ integrated observing and data assimilative predictive modeling
sub-systems. It is critical that all IOOS RAs possess this integrated capability. As
recommended in the 2008 MAST report, the design and conduct of the experiments will
require the cooperation of the federal operational forecast centers and the R&D
community. Outcomes from these experiments would include:
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




Assessment of model skill and the communication of model uncertainty;
Information sharing among all stakeholders, across all disciplines, including user
communities;
Coordinated model development, including coupled (e.g., ocean-atmosphere)
models;
Examination of ensemble modeling for various applications;
Improved capability to rapidly mobilize in support of responses to marine crises.
The type of coordinated model development and experimentation described above cannot
and will not occur until there is community-wide recognition of the role that the RAs can
play in the development and operation of regional ocean models. The significant R&D
capabilities resident within each and every RA can contribute in significant and unique
ways to this coordinated activity, including:
 The development of new types of models and modeling techniques;
 The operation of special-purpose models for applications that do not lie within the
scope of federal agencies;
 The education and training of the marine forecaster workforce;
 The insertion of local knowledge into the model development and forecast process.
IOOS must lead in the transition of these regional modeling systems from the research
world to the operational realm. There are some encouraging developments in this regard.
The initial success of the U.S. IOOS super-regional model test bed, which objectively
compares modeling components and approaches in order to transition new understanding
and technologies to operations, has led to NOAA’s National Center for Environmental
Prediction (NCEP) and IOOS planning for a sustained coastal prediction test bed. This
initiative should be fully funded and accelerated, with test beds covering all of the U.S.
coastal ocean and Great Lakes domains. Importantly, these test beds should be configured
and operated in such a manner that they can serve as transition pathways for new
observation and modeling technologies, and as education and training platforms for future
workforce development.
D. Data Management & Communications
The recent focus of the IOOS DMAC activity on technologies that deliver compliant
standards shows great promise. The IOOS Coastal Ocean Modeling Testbed (COMT) was a
unique opportunity to implement and evaluate several of these technologies. Going
forward, the DMAC process should be driven by real-world use cases. Applications – which
may vary from RA to RA – will drive the (local or regional) selection of technologies, and
will also provide opportunities for training at the local and regional levels. Here again, the
formal and rigorous testing environment provided by the multi-scale experiments (OSSEs)
alluded to earlier would afford an opportunity to evaluate existing and emerging
technologies.
The experiments should be designed to examine the scalability issues associated with the
expected significant increase in data volumes. Here again we mention the approach of
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“Valued Information at the Right Time” - understanding Who needs What information
When? - before we seek solutions to this challenge. As mentioned earlier, the experiments
will require the cooperation of the federal operational forecast centers. They should also
include the participation of centers of data at multiple federal agencies such as NOAA, EPA,
USGS, USACE, etc. to share information and best practices with regard to QA/QC and data
archiving.
A compliance and certification process should be developed that allows IOOS to ensure that
our systems meet the needs of our stakeholders while complying with regulatory
requirements related to the data. IOOS should also encourage the development of social
media that expands both our user community and the functionality of our information
products. A “bottom-up” approach to data management and information delivery will
ensure that we gain maximum advantage of the significant and diverse skill sets across our
community.
As part of the US IOOS DMAC core services, the US IOOS Program Office has initiated a
sustainable, community-based project to establish authoritative procedures for QA/QC
procedures for each of the 26 US IOOS core variables (http://www.iooc.us/oceanobservations/variables/), including detailed information about the sensors and procedures
used to measure the variables. This project will be based on the QARTOD (Quality
Assurance of Real Time Ocean Data) effort, existing community-based QA/QC efforts, and
existing QA/QC standards developed by federal agencies and the US IOOS Regional Coastal
Ocean Observing Systems (RCOOS). This effort will also facilitate QA/QC integration with
the Global Ocean Observing System (GOOS) and other international ocean observation
efforts.
Throughout all of the activities suggested here, it is critical that the IOOS community
pursues close coordination with the NSF Ocean Observatories Initiative (OOI).
V. Success Stories
As we consider our future path, it is useful to reflect on past and current applications and
activities that can help guide our actions in ensuring a fully-integrated IOOS, and that can
demonstrate the significant benefits that can arise from such applications and activities. We
here outline several examples.
SAROPS and IOOS
The United States Coast Guard considers search & rescue (SAR) as one of its primary
missions. A critical component of the SAR process takes place well before a helicopter can
arrive on scene. This is the activity of Search Planning. Search planning is largely concerned
with "where things are", “where things may have been” and “where things will be” so a
search plan can be created effectively. The US Coast Guard has developed SAROPS, a system
that allows the search planner to define the scenario; to access environmental data (winds
and currents) via web services from an Environmental Data Server (EDS); and to develop
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near optimal search plans given the amount of searching resources available. The system
was deployed throughout the U.S Coast Guard in 2007, and has successfully been used to
find missing persons and save lives.
In the event of a SAR case, the EDS provides the appropriate wind and current forecast for
the region of interest so the search planner can efficiently make a prediction of where
missing objects will move, and create a probability map that is used to set up search plans
for search & rescue units (SRUs). The EDS can be considered as a “brokering” system that
harvests and caches vast amounts of coastal and ocean data, including both observations
and model results. The data are collected from a variety of sources including NOAA NCEP,
NDBC, NOS, U.S Navy (NAVO and FNMOC), IOOS Regional Associations, and international
partners. The EDS is based on using open standards with a focus in the use of CF Compliant
NetCDF data as both a storage and data delivery format. Where available, the EDS harvests
data from providers in NetCDF and GRIB leaves the data in their native formats. For data
providers that do not have compliant data formats or access services such as DAP, the EDS
ingests the data in custom formats and converts to CF compliant NetCDF. SAROPS
interfaces to the EDS using REST and SOAP-based web services and EDS delivers subsetted
NetCDF to SAROPS for the region and time of interest.
Search & Rescue incidents represent a challenging use case because:
- They need data immediately available for open ocean and coastal areas throughout
the world – no single dataset or provider can offer a solution so there is need for
integration of a wide variety of data from different providers
- SAR controllers need to make decisions in a matter of minutes, and so issues related
to the efficient and reliable transfer of data are of high priority
- SAR cases include a hindcast component (e.g if a person went missing 5 days ago)
and a forecast component – e.g where will the object drift to by tomorrow morning
to allow for deployment of search units. This requires that the EDS can aggregate
hindcast, analysis, or observation data with forecast data
- Defining the uncertainty or error associated with the data is required to estimate
the size of the search area. As uncertainty estimates are not readily available with
most data sources, the system must perform analysis against observations such as
drifting buoys, HF radar, and other measurements to support error estimates
associated with the model forecasts.
Initially, SAROPS only had access to global and large scale models available from
national centers such as NCEP and NAVO. The evolution of IOOS’s regional observing
and modeling efforts, and importantly, the availability of these data in standard formats
and services, has dramatically increased the regional coastal data now available to the
U.S Coast Guard. Sources now included in the EDS include:
- National HF Radar Network
- Short Term Predictive System (STPS) based on the HF Radar data
- GLOS/GLERL Great Lakes Meteorology and Circulation Models
- NOS regional models
- Stevens Institute of Technology’s NYHOPS
- UMASS NECOFS
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This success story is notable in that it required an array of data providers to work with
a data brokering system to ensure that a collection of disparate data could be made
standards-compliant and fed into a standards-compliant application. As the IOOS
enterprise grows in size and complexity, such brokering may prove the optimal path to
success for many applications.
SAROPS using aggregated coastal and ocean models to generate search areas with
associated probabilities.
Center for Operational Oceanographic Products and Services: A Tale of Two Partnerships
Establishing successful partnerships can be challenging due to a number of key factors such
as accountability, added value, expectations, learning curves, resources and trust. Over the
past 20+ years, CO-OPS has participated in a number of partnerships with varying levels of
success. Two of these collaborative efforts help illustrate the motivation, benefits and
challenges associated with these endeavors. The similarities and differences from these
examples may be useful as additional partnerships are forged within U.S. IOOS.
The first case involves a partnership where a specialized expertise at the Federal level can
address a Regional need. For the Texas General Land Office (TGLO) in the late 1990’s, that
need centered on the determination of tidal datums and property boundaries in the coastal
waters of Texas. Through a sustained program of technology transfer to TGLO and its
contract personnel by CO-OPS, Texas developed an organic capability to conduct its own
water level data collection, analysis, and datum computations using National/NOS
procedures and standards. Over time, the TGLO contractor, the Conrad Blucher Institute
for Surveying and Science (CBI) at Texas A&M University, Corpus Christi, built the expertise
to install, operate, and maintain the Texas Coastal Ocean Observation Network (TCOON)
and provides products and services that address the needs of stakeholders regionally,
nationally and internationally. CBI and TCOON have successfully attracted funding from a
number of sponsors that have enabled it to sustain and continually improve its operations
and product delivery.
There have been several tangible benefits of this partnership. The partnership efficiently
leverages the Regional field resources and combines them with the Federal IT
infrastructure. TCOON data (water level and meteorological) from over 25 stations are
transmitted via satellite, permitting direct ingest into the NOS database for subsequent
data QA/QC and dissemination. TCOON stations fill gaps in the National Water Level
Observation Network (NWLON) and provide data for Physical Oceanographic Real Time
System (PORTS®) to support safe and cost-efficient navigation. The data directly provide
local NWS Weather Forecast Offices with real-time water level and meteorological data
critical for storm warnings, storm surge modeling, evacuation planning, and protection of
lives and property. The USACE depends on these data for planning coastal engineering
projects, maintenance of navigation channels and dredging operations.
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Of course even successful partnerships face challenges that vary through time. Chief
among these are sustaining a high level of engagement, incorporating emerging
technologies, leveraging limited resources and the ongoing communication and
coordination of programs to achieve the maximum benefit for a wide variety of
stakeholders.
The second case involves a partnership where a distributed expertise at the Regional level
is being harnessed to address Federal needs. Over the past 20+ years, a national HighFrequency Radar (HFR) network has been created, almost exclusively by academia, from
centers of expertise distributed throughout the RAs. Although the efforts were distributed,
HF radar researchers began gathering initially to exchange information and then meeting
regularly via Radiowave Oceanography Workshops. This collaboration led to the eventual
creation of standardized data formats, quality control parameters, and a central repository
for the data at the National Data Buoy Center. These many partnerships along with IOOS
support and guidance has fostered the coalescence of these regional and federal efforts into
a national capability.
The development of this National capability provided a key link to the use of HFR in a
number of applications such as coastal search and rescue, oil spill response, water quality
monitoring, and safe and efficient marine navigation. In 2005, CO-OPS began a
collaboration with Rutgers University and Stevens Institute of Technology to measure the
2-D ocean surface current velocity fields in Raritan Bay and begin development of a
prototype product for the maritime community. Although the effort has been focused in
specific regions with Regional partners, the goal for CO-OPS is to develop a product with
the same look and feel for mariners throughout the country. At the same time, it may
provide a base product that RAs could tailor to local needs.
While facing similar challenges to the previous case, some challenges are a bit more
nuanced. Leveraging resources among multiple partners and various funding sources i.e.
state, local, research, etc., can be quite daunting and poses considerable risks to
maintaining an operational capability. Compounding this management hurdle is the
significant amount of in-kind resources provided on a “voluntary basis” usually as added
tasks for assigned personnel. While a portion of funding is provided from national sources
via U.S. IOOS, customers on both a national and regional scale will likely need some
assurances that an operational capability is sustainable.
BOEM and IOOS
1) Gulf of Mexico
The Gulf of Mexico Office of BOEM (US Department of the Interior’s Bureau of Ocean Energy
Management) has engaged IOOS and its Regional Association, GCOOS, since its initial
meeting in 2000. With the formalization of GCOOS, the Office has been part of the board of
directors and has participated in the products and services committee. The BOEM
Environmental Studies Program has also contributed to GCOOS. The Program’s historical
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databases have become part of GCOOS data portals and are made available to the
community for use in the validation of models and to provide background information. For
example, oceanographic programs funded by BOEM that have provided important insights
into the Gulf’s circulation include the Louisiana-Texas Shelf Physical Oceanography
Program (LATEX) and numerous deep water studies, including the ongoing “Dynamics of
the Loop Current” study. The knowledge acquired through this program has been
employed to guide design of observational arrays planned by GCOOS in the shelf and EEZ
regions.
Perhaps the single most significant contribution of BOEM was the array of deep-water
current measurements from oil and gas platforms resulting from regulations. This
regulation (Notice to Lessees, NTL 2007-G17 ) called for companies to install and maintain
Acoustic Doppler Current Meters on fixed platforms and mobile drilling ships and the near
real-time reporting of such measurements to the public at large via the National Data Buoy
Center website. A follow-on ocean current monitoring regulation (NTL 2009-G02) applied
only to floating mobile drilling units (MODUs) and production facilities in water depths
greater than 400 m.
The BOEM Environmental Studies Program has consistently worked to use observations to
improve ecosystem models in the Gulf of Mexico, which is also in line with one of GCOOS’
major goals in the Gulf. BOEM’s primary focus has thus far been on improving the
understanding of the physical circulation. Extensive physical-oceanographic field
programs and modeling efforts support of BOEM’s oil spill modeling program and National
Environmental Protection Act (NEPA) responsibilities.
2) Alaska
Several factors are currently contributing to BOEM’s information needs in the Alaska Outer
Continental Shelf (OCS) Region. In addition to a warming climate trend, and an
approximate doubling of the state’s population over the last 35 years (Alaska Department
of Labor, 2010), the BOEM Alaska OCS Region needs to maintain and expand its
environmental knowledge in order to feed BOEM’s regulatory process. These growing
information needs are, in turn, a response to a growing national need for increased
domestically-produced energy. Alaska’s OCS is one such resource. While BOEM’s Alaska
OCS Region has been contributing to the Alaska Ocean Observing System (AOOS), BOEMfunded scientists often gather information from the AOOS portal. It is important that this
two-way flow of information not only continues, but also that the AOOS capabilities adapt
to keep up with the growing needs for environmental information in response to a
changing climate, increased population and ship traffic, and a more present and active oil &
gas industry. From the operational perspective, due to tight environmental requirements,
BOEM has an increased need for real-time observations.
The Alaska OCS presents unique challenges in terms of recent and present environmental
changes. The magnitude and present pace of many of these trends call for an organized,
relatively rapid investment of resources, dedication and response if we hope to be effective
in addressing the environmental issues at stake. Understanding and quantifying stressors
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and corresponding environmental responses are relevant to successful ecosystem
management and overall protection of the natural and cultural resources. Along these lines,
the AOOS has a key role in the region. Expanding and adapting its capabilities to upcoming
challenges and opportunities would need to be carried out dynamically and with flexibility.
As offshore energy exploration and development makes its way into the Alaska OCS and as
rapid environmental changes increasingly draw our attention and physical presence to the
region, expanded data file availability, addition of new variables (e.g., vessel position) and
two-way real-time data transfer are some of the observing system capabilities expected to
be increasingly in demand over the next decade and beyond.
VI. Coastal IOOS and Global GOOS
Although the global ocean and coastal ocean components of IOOS & GOOS have progressed
along separate paths, there is significant value to linking the two activities. The global
ocean observing community, for example, must provide information regarding coastal
ocean conditions to maximize societal benefit. The coastal community on the other hand
requires information at the global scale to provide lateral boundary conditions for higherresolution coastal circulation and ecosystem models.
There are many initiatives aimed at facilitating the essential collaboration and coordination
to link ocean observing and prediction researchers around the world. These include Earth
Cube, created over the past year by the Office of Cyberinfrastructure (OCI) and the GEO
sciences program office of NSF, and the Research Coordination Network, also funded by
NSF. A new EU-initiated project called the Ocean Data Interoperability Platform (ODIP) is
forming to enable a US, EU and Australian collaboration to foster the development of
common standards across existing oceanographic programs. IOOS is already a partner in
the activity. Another initiative, COOPEUS, is underway to create a framework for data
exchange within the environmental research infrastructures of the EU and US. COOPEUS is
intended to facilitate a sustainable, collaborative working environment between the US OOI
and the European counterpart EMSO.
Title: Requirements for Global Implementation of the Strategic Plan for Coastal GOOS
Authors: Paul M. DiGiacomo (NOAA-NESDIS Center for Satellite Applications and Research)
and Thomas C. Malone (University of Maryland Center for Environmental Science)
(Note: Following is the Executive Summary from GOOS Report #191: Requirements for Global
Implementation of the Strategic Plan for Coastal GOOS. Authors: GOOS Panel for Integrated
Coastal Ocean Observations; in press)
Meeting the terms and conditions of international conventions and agreements on the oceans,
living marine resources and biodiversity (e.g., United Nations Convention on the Law of the
Sea, Convention on Biological Diversity, Global Program of Action for the Protection of the
Marine Environment from Land Based Sources) require adaptive, ecosystem-based
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approaches (EBAs) to sustainable development, including marine spatial planning and
management. Sustainable development depends on the continued provision of ecosystem
goods and services valued by society. EBAs require the sustained provision of multidisciplinary
data (biogeochemical and ecological as well as geophysical) and information on ecosystems
states, especially in the coastal zone where goods and services are most concentrated.
While considerable progress has been made by developed countries in implementing those
elements of GOOS and the Global Climate Observing System (GCOS) that require geophysical
observations and models of the ocean-climate system (emphasizing improved predictions of
natural hazards and climate change), implementation of those elements requiring
observations and models of biological and biogeochemical states has been slow and uneven
geographically, especially in the coastal waters of developing nations and emerging
economies. Developing the capacity for sustained provision of these data and information as
an integral part of GOOS is the focus of this report. The goal is to expand GOOS to inform EBAs
for managing human uses of ecosystem goods and services and adapting to climate change on
local to global scales. Thus, our emphasis is on the provision of data and information needed
for rapid detection and timely anticipation of the effects of the major drivers of change on
estuarine and marine ecosystems (human expansion, climate change and natural hazards).
Building on analyses and recommendations of the Coastal Ocean Observing Panel (COOP), the
Coastal Theme of the Integrated Global Observing Strategy (IGOS), OceanObs’09, A
Framework for Ocean Observing, and An Assessment of Assessments of the United Nations, a
plan for expanding the Global Ocean Observing System (GOOS) to include biogeochemical and
ecological elements is offered herein. Our recommendations are intended to complement and
leverage those aspects of the ocean-climate system addressed by the Ocean Observations
Panel for Climate (OOPC) and existing operational programs for predicting extreme weather
events and tsunami, changes in physical states of the upper ocean, and coastal flooding.
The following are critical to effective implementation of EBAs: (1) frequent, routine and
integrated ecosystem assessment (IEAs) and (2) continuous provision of data and information
on meteorological, geophysical, biogeochemical and biological states (indicators) needed for
timely IEAs that inform decision makers. To these ends, a rationale and framework for EBAs
to managing, mitigating and adapting to changes in ecosystems states and their impacts are
given in Chapters 1 and 2. A description of a set of end-to-end observing systems for high
priority phenomena of interest is provided in Chapter 3; Chapter 4 presents a framework for
integrating these systems into a global system of systems; and Chapter 5 updates the list of
essential variables for coastal GOOS, specifies a set of key indicators, recommends the
ingredients for a global coastal network and procedures for implementing regional observing
systems, and describe international collaborations and partnerships needed to implement
regional ocean observing systems globally. Our report concludes by recommending four
complementary approaches to accelerating the delivery of coastal GOOS (Chapter 6).
The following priority indicators of ecosystem states (health) are identified to guide the
specification of end-to-end observing systems (Chapter 3) that are the building blocks of a
system of systems for coastal observations and predictions:
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Surface phytoplankton biomass and subsurface oxygen fields,
Distribution and abundance of waterborne pathogens and toxic phytoplankton,
Spatial extent of living benthic habitats (coral reefs, seagrass beds, mangrove forests
and tidal marshes) and ecological buffers to coastal flooding,
● Distribution and condition of calcareous organisms (cold and warm water corals,
coccolithophores and pteropods), and
● Distribution and abundance of exploitable fish stocks.
●
●
●
Although the emphasis of the COOP strategy is on coastal marine and estuarine ecosystems
within territorial waters and Exclusive Economic Zones (EEZs), the strategy also recognizes
that EBAs must consider external pressures on ecosystems, as well as changes in ecosystem
states and the impacts of such changes, that occur on local to global scales from coastal
catchment basins (watersheds) to the ocean basins. In this context, the essential variables to
be monitored include at least the following:
External Pressures
○ Atmospheric (ocean surface vector winds, heat flux, precipitation, incident
solar radiation);
○ Land-based inputs (freshwater, sediments, nutrients, pathogens, chemical
contaminants);
○ Extraction of living marine resources (e.g. fishing);
○ Sea level rise, ocean warming and acidification;
○ Coastal flooding;
○ Natural ocean-atmospheric climate modes; and
○ Basin scale migrations of large pelagic predators.
● Ecosystem states (surface and subsurface)
○ Geophysical (fields of temperature, salinity, suspended matter, sea surface
roughness, waves, and currents, sea level, shoreline position);
○ Chemical (fields of dissolved nutrients, dissolved oxygen, pH, fCO2, total
alkalinity, aragonite saturation state, and colored dissolved organic matter);
○ Biological (fields of phytoplankton biomass, toxic phytoplankton, waterborne
pathogens, calcareous plankton, copepod indicator species, fish eggs and
larvae; extent of living benthic habitats, coral skeletal density, species diversity,
abundance and diet of exploitable fish stocks, bycatch, abundance and size of
apex predators); and
○ Biophysical (water leaving radiances and downwelling irradiance).
●
Impacts of changes in these ecosystem states include declines in fish and shellfish catch (food
security), increases in human illness and death rates, loss of income due to beach and shellfish
bed closures, increases in the extent of and vulnerability to coastal inundation (due to both
storm surges and sea level rise), mass mortalities of iconic marine animals, loss of coastal real
estate and infrastructure, and losses of aesthetic value and tourism.
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In terms of real-time, operational readiness, current and potential observing system
capabilities for the essential biological and chemical ecosystem state variables generally fall
into two broad categories:
●
The required technologies are mature but implementation on regional to global scales
is limited by lack of (1) funding for widespread and rapid repeat assessments, (2)
common standards and protocols, (3) and/or calibrated and validated algorithms for
translating data into useful products, e.g., nutrients, phytoplankton, dissolved oxygen,
fCO2, and pH fields; spectral diffuse attenuation of downwelling irradiance, spatial
extent of biologically structured benthic habitats and ecological buffers to flooding).
●
Technologies for rapid detection are under research and development (not operational
but in a concept or pilot level of readiness), e.g., waterborne infectious microbes and
many toxic phytoplankton species and their toxins; biodiversity; aragonite saturation
state, macro- and meso-zooplankton, abundance, abundance of size classes of
exploited fish stocks and apex predators, species diversity, and iconic species.
With these deficiencies in mind, implementation priorities (Chapter 6) are as follows:
●
Support national and international programs that target priority infrastructure
described in chapters 3 and 5 for observations and predictions.
Successful expansion of GOOS to incorporate biological and chemical observations required
for EBAs depends on sustained national support of regional “pioneer” ocean observing and
predictions systems in, for example, Australia (Integrated Marine Observing System), Europe
(EuroGOOS and Global Monitoring for Environment and Security) , and the United States
(Integrated Ocean Observing System). Priority infrastructure includes data management and
communications systems, remote and in situ observations, and modeling and analysis as
described in Chapter 5. As indicated by their operational readiness, priority essential variables
are chlorophyll-a, dissolved inorganic nutrient, dissolved oxygen, fCO2, and pH fields; spectral
diffuse attenuation of downwelling irradiance, and spatial extent of biologically structured
benthic habitats and ecological buffers to flooding
●
Establish data management and communications systems for interoperability among
monitoring systems and data integration within and among regions.
Designing and implementing the data management and communications link in end-to-end
observing systems is a critical step toward integration and should be the highest immediate
priority. Such a system must provide rapid access to multidisciplinary data from all sources.
●
Support capacity building and research and development to fill priority spatial and
temporal gaps in the global coastal network.
Capacity building projects that fill gaps in the GCN are needed. This will involve a review of
existing and planned programs, identification of critical spatial gaps, and allocation of
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resources to fill those gaps. The Coastal Zone Community of Practice (CZCP) of the Group on
Earth Observations (GEO) could oversee such a gap analysis.
●
Facilitate regional implementation of a pilot project in a priority “super site” domain
to demonstrate the value added of an end-to-end system of systems (e.g., multiple
applications of data and information needed to guide EBAs derived from a common set
of observations and models).
Implementation of a regional demonstration project at a “super site” through a sustained and
iterative life cycle for designing, implementing, evaluating, and improving a Regional Coastal
Ocean Observing System (RCOOS) over time has the potential to address all four priorities. In
terms of the value-added of an integrated system of systems, highest priority for regional
implementation should be given to “super sites” with the largest number of sentinel and
reference sites. A global analysis identified three regions that are subjected to the greatest
number of pressures and have multiple sites with high risks of flooding and exposure to
waterborne pathogens. One of these, the Indonesian Archipelago-South China Sea domain, is
unique in terms of its high species diversity and the presence of sentinel sites for human
pressures and state changes for all of the phenomena of interest. This region also has two
Large Marine Ecosystem (LME) programs funded by the Global Environmental Facility (GEF),
a large number of marine reserves (~ 65), and several institutional networks that could
facilitate implementation. Such a demonstration project could begin with the establishment of
the required facilities (e.g., the Australian approach to implementing IMOS) in support of an
international coastal ocean data assimilation experiment (modeled, for example, after a
hybrid of the Integrated Marine Biogeochemistry and Ecosystem Research [IMBER] program
and the Global Ocean Data Assimilation Experiment [GODAE]) with the goal of providing data
and data-products required to inform adaptive, EBAs to marine spatial planning and coastal
zone management for the region as a whole.
Through an international coalition of data providers (scientists and technicians) and users
(managers, conservation groups, shipping and tourist industries, and fishers) from developed
countries (e.g., Taiwan, Australia and New Zealand), emerging economies (e.g., China) and
developing countries (e.g., Philippines, Vietnam, Cambodia, Thailand, Malaysia, Indonesia,
East Timor), this could become the prototype for both regional capacity building and
developing an integrated system of systems globally, i.e., phased implementation of the system
achieves the goal through capacity building.
Addressing the priorities above will require investments by developed nations to ensure the
coordinated establishment of a global network of national and regional observing systems
that are locally relevant and interoperable in terms of data and information exchange. Such
mechanisms must (1) engage groups that use, depend on, manage and study marine systems
in the design, operation and evolution of a coastal GOOS that meets their data and
information needs on local to global scales; (2) build on and leverage existing programs with
common goals and objectives; (3) promote the development of regional observing systems
and services in regions populated by developing countries; (4) promote the development of a
Global Coastal Network (GCN) through coordinated regional development worldwide; and (5)
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effectively interface with the existing planning, oversight and implementation bodies of the
Global Earth Observing System of Systems (GEOSS), GOOS, GCOS, the Global Terrestrial
Observing System (GTOS), and other organizations as appropriate.
The Joint Commission for Oceanography and Marine Meteorology (JCOMM) is the
coordinating body for implementing the ocean-climate observing systems of GOOS and GCOS.
No such body is in place for coordinating the global implementation and evolution of coastal
networks of observations, data management, and modeling that includes the full spectrum of
required geophysical, biophysical, chemical and biological variables. This is a major gap in the
current GOOS governance structure that must be addressed for coastal GOOS to become a
reality.
There is an immediate need to estimate the costs of capitalization, implementation and
sustained operations of coastal GOOS. PICO was not adequately resourced in terms of funding,
time or the diversity of experts needed to formulate realistic estimates of implementation
costs in terms of observations and data telemetry, data management and communications,
and modelling and analysis. This important task could likewise be executed under the
auspices of the GEO-CZCP, in coordination with the GOOS Steering Committee.
Successful implementation also depends on more effective collaboration with the OOPC as
well as on effectively engaging stakeholders (data providers and users) across the land-sea
interface in the process. The CZCP was established by GEO to do the latter. Thus, we
recommend that the CZCP be charged, and jointly resourced by the IOC, GEO member
countries, and GEO Participating Organizations, to oversee both the gap and cost analyses
described above.
We also endorse the recommendation of the Joint JCOMM-IOC-GRA ad hoc Task Team that an
expert panel such as the Joint Panel for Integrated Coastal Observations (J-PICO), or
alternatively the CZCP, be tasked and resourced to provide scientific and technical guidance
and ensure the coordinated evolution of ocean and terrestrial observing systems across the
land-sea interface. Should the CZCP be given this important responsibility, this would have the
added benefit of establishing an important and direct link between IOC-GOOS and GEO-GEOSS
(and the GEO Ocean Monitoring Task advocated by POGO and Oceans United). Finally,
successful implementation of the priorities set forth herein as an integral part of GOOS and
GEOSS depends on developing international partnerships and collaborations, in active
coordination with sustained coastal observing system efforts within and across the GRAs.
References
Glenn, S.M., W. Boicourt, B. Parker and T.D. Dickey. 2000. Operational observation
networks for ports, a large estuary and an open shelf. Oceanography, 13: 12-23.
Glenn, S.M., T.D. Dickey, B. Parker and W. Boicourt. 2000. Long-term real-time coastal
ocean observation networks. Oceanography, 13: 24-34.
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Hayes-Roth, F. 2005. Model-based Communication Networks and VIRT: Filtering
Information by Value to Improve Collaborative Decision-Making," 10th Intl. Command and
Control Research and Technology Symposium: The Future of C2, McLean, VA.
Hayes-Roth, F. 2006. Model-Based Communication Networks and VIRT: Orders of
Magnitude Better for Information Superiority. MILCOM 2006, Washington, DC, IEEE.
Ocean.US, 2002. Building Consensus: Toward an Integrated and Sustained Ocean Observing
System (IOOS). Ocean.US, Arlington, VA. 175pp
Ocean.US, 2008. The integrated ocean observing system (IOOS) Modeling and Analysis
Workshop report. Ocean.US Publication No. 18, The National Office for Integrated and
Sustained Ocean Observations.
Some additional concepts on integration that we might want to address
In understanding US IOOS means truly understanding the critical dependencies and
successful partnerships with non-Federal observing networks and achieve a greater degree
of interagency coordination to improve the efficiency, efficacy, and costs of leveraging the
observation networks of non-Federal entities.
The Nation’s Earth-observing requirements are met through a combination of systems, including
those that are entirely owned and operated by the Federal Government as well as “extramural” systems sustained by a complex patchwork of funding arrangements from both Federal and nonFederal sources. In many cases, Federal mission-driven agencies have become reliant on data from
extramural systems for their operations. Often these are long-term, time series data needed to support scientific understanding of climate change. Funding streams for extramural Earth observation
systems are often interconnected, requiring the perpetual agreement of all parties that funding not
be arbitrarily withdrawn from the observational system. Nevertheless, the stability of even the
most important of these systems is routinely challenged by threats to their partial funding arrangements, from both Federal and non-Federal partners. The “partial” nature of the funding arrangements often implies, incorrectly, that such systems are not important. On the contrary, many
represent outstanding examples of doing more with less and achieve substantial cost savings for
Federal and non-Federal entities engaged in the partnership. The new governance mechanism for
the NEO Strategy will engage in a routine review of such partnerships and dependencies, to increase visibility for the best arrangements and ensure they are preserved and sustained.
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Figure XX: Relationships between Federal, non-Federal, and international stakeholders.
From an IOOS perspective some examples:
The M. J. Murdock Charitable Trust aims to strengthen the Pacific Northwest’s educational, spiritual, and cultural base in
creative and sustainable ways. Coastal water conditions are of interest to scientists studying the ocean and weather
conditions that lead to water with lower than normal pH -- often called acidified waters -- as well as the creation of lowoxygen waters, like those that have plagued Hood Canal in recent years. NANOOS in teaming with the University of
Washington’s Applied Physics lab was successful in winning an award from the M.J. Murdock Charitable Trust to deploy a
buoy array in part because the IOOS region – NANOOS would be able to sustain this buoy array for years to come.
OOI/IOOS – I have inserted the picture from NANOOS that shows we have thought about the process
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Than there is the interdpencency on funding – you can user the MARACOOS pie chart.
What are the challengers with this
 Leveraging resources yields positive results
 Multi-sector approach is a hallmark of IOOS but adds complexity
As we are now interdependent both from a fiscal, science and operational perspectives
loss of any 1 funding stream means significant risk to the entire enterprise
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Chapter Five:
A Vision for the Integrated Ocean Observing System
I. The year is 2022 ...
 The owner of a fleet of charter fishing boats in Oregon contacts his customers to
tell them that the departure time for their albacore trip next week will be an hour
earlier to ensure they get to the best fishing grounds. That call is based on the
predictions that he gets as part of his subscription to an ocean information
service.
 The Chief Operating Officer of a global shipping line reviews quarterly revenue
projections based on a change in optimal track ship routing for the fleet. A
reliable tailored projection of when passage will be possible for six weeks
through the Northern Sea Route of the Arctic Ocean, has been made available to
him in March of that year.
 A public health warning has been issued to hotels, chambers of commerce,
hospitals and clinics, in three coastal counties of Florida. They are informed of a
harmful algal bloom, with potential health impacts, which will occur next week.
Emergency medical supplies are shipped to the area, and alternative vacation
options are sent to prospective travelers.
 Immediately upon the grounding of a New Panamax class container ship in an
Asian port, a fleet of unmanned surface vehicles, gliders and autonomous
underwater vehicles is deployed to monitor the release and dispersion of fuel oil.
The vehicles are operated by, and their data collected by a commercial marine
response service.
 A major canoe and kayak tournament is scheduled to take place from Maine to
Rhode Island during the last summer months: this is a major outdoor recreation
and tourism event drawing 30,000 visitors from around the continent. Weather
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These vignettes are stories from our future – the not too distant future. Parallel ongoing
revolutions in communications, knowledge processing and transportation are realigning
the standing of countries all over the world, including the relative position of the United
States among the leading societies and economies of the 21st century. Indeed, some have
characterized the challenge of the future in terms of defining the role of a “Blue Economy”
in addressing the key applications of water, food, coastal real estate, and energy (Michael B.
Jones, “Promoting the Blue Economy: The Role of Maritime Technology Clusters”, Mains’l
Haul, V. 38: 138-147, 2012). The dramatic rate and scale of this change that formerly
played out over multiple decades can now be seen within a few years.
II. Drivers For A New Decade Of Ocean Observing
During just the initial decade of design and implementation of IOOS, the world has been
shaken with change affecting economies, security and environment. Data processing
measurement has moved from kilobytes to yottaflops. Pocket-sized smartphones are
ubiquitous, and social networks connect people around the globe instantaneously. The
awesome power of nature, as seen from ocean-based earthquakes and associated tsunamis,
along with notable environmental disasters such as large oil spills, have affected trillions of
dollars of wealth and commerce. Ever larger merchant ships deliver greater cargoes to
more destinations, and the capacity of the Panama Canal is about to double. The relatively
open access of ports and the low cost of maritime commerce leave large gaps in security
protocols for most of the world’s most intensely populated and commerce-filled areas.
In short, the drivers that inspired the development of IOOS ten years ago have largely acted
as anticipated, except that change has been greater and faster than projected. With the
world working to come out of a global recession, there is no reason to doubt the pace and
rate of this change to continue to increase. The drivers listed below will continue to
influence the speed and direction of development. Moreover, each of these sets of drivers
is intertwined with the others.
A. People and Culture
The world population today is 7 billion people – up a billion over the last ten years, and
projected to increase by another billion in the next ten. As anticipated, people have
increased their movements towards coastal areas all over the globe. In addition, the rate of
increase in household wealth around the globe is much greater than the rate of increase in
population. However, the United States is seeing only low-to-medium growth. Emerging
large economies such as China, India, Brazil and Indonesia are leading the way; and many
smaller economies are experiencing strong growth. As a result of instantaneous
communications, people around the world are more aware of other societies and cultures,
contrasting value paradigms, and inequality of prosperity.
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In this world of change, information will become an increasingly valuable commodity. And
because of the role of maritime commerce, vulnerability to ocean-related natural disasters
and the need to provide security for coastal populations, and food and water for a larger
population, information about the oceans becomes just as critical as other data.
B. Commerce and Economy
The role that maritime commerce plays in our national economy is often underappreciated.
The role that it plays in coastal economies is essential to the vitality of our largest
communities. 99% of the volume of U.S. foreign trade, and 62% by value, enters or leaves
on a ship. Movement of goods through ports is inextricably linked to national supply chains
for virtually every type of goods and merchandise.
One of the hallmarks of the new economy is the fluid, rapid and enormous flow of capital
around the globe. Information primes the pumps of capital flow. Investments in oceanrelated services depend on reliable data and information, and private capital will thus
require ocean and coastal observation products. In this kind of world, data becomes a
commodity with economic value to investors; and ocean observing data are no different.
The focus of investment in oceans and coastal resources is broadening beyond petroleum
exploitation, fisheries, recreation and tourism. While these sectors continue to be
important, new technology and increased demand are fueling the growth of the ocean
energy sector, including wind, wave and tidal power – all requiring reliable and sustained
ocean data. And the growth in all of these sectors places greater emphasis on insurance
products that can only be priced properly when sufficient ocean information is readily
available.
C. Technology and Communications
The ability to take advantage of the knowledge, intellect and experiences of billions of
people is a key driver, made possible by improvements in technology and communications.
Information visualization and real-time access to an explosively increasing set of products
and services (think of Yelp, GoTo Meeting, and Groupon on steroids!) means IOOS data will
be accessible and interpretable by a vastly diversified user base. Community open source
platforms and crowd sourcing will take cloud computing capabilities to a “new normal” of
data analysis, adaptive sampling and product development
D. Politics and Governance
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It is widely acknowledged that our national governance system is having significant
difficulty determining the direction that policy should take relative to economic
intervention, regulation, and the role of government in public and private life. The
economic downturn/Great Recession during the past 5-10 years has raised the priority for
job creation. For more than a decade, national policy has also focused on security. Jobs,
economic policy and security have been the drivers for high priority initiatives.
The private sector will play an increasing role in ocean observing. As the various economic,
technical and political drivers become more influential, the importance of ocean and
coastal data and information will be driven by demand from the private sector, and the
relative burden for funding will shift accordingly. But private sector investments will
require a greater ownership of the ocean, coastal and Great Lakes observing enterprise, in
the sense of being able to influence the structural and policy decisions that govern the
system, while ensuring that the public good is held paramount.
E. U.S. Public Policy Drivers
Over the last ten years, the national government in the United States has recognized the
importance of ocean and coastal observing, and codified its commitment to a sustained and
integrated system. Over the next ten years, public policy will extend this attention to a
demand for accountability. Congress and local jurisdictions will ask for measures of
effectiveness in safety, security, economic development and general public welfare.
Advances in scientific understanding will increasingly be subject to political manipulation.
Just as the seemingly esoteric analyses of carbon cycling of years past have become fodder
for partisan policy dialogue, the observations of coastal and oceanic phenomena may also
fall subject to exaggerated and inaccurate misinterpretations. As a community we should
proactively preempt such developments.
II. The Challenge
For years information service providers have acknowledged that 'content is King'. If a
service provider has the technology and the employee base to deliver services but has no
content, that service provider will soon be out of business. The boom in content providers
has shown that people are consumers of all types of information and this data explosion is
continuing. Social media has become a leading source of information for people to make
decisions quicker than they have ever done so before. At issue, however, is the accuracy
and reliability of the information that travels so quickly. Consequently, many decisions are
made in error because of inaccurate information. So while 'content is king' reigns true to
many information services providers, further clarification is needed to describe the content
as 'accurate'. Without accurate information being provided to drive decision making,
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confidence in information service providers would plummet and drive them out of
business.
Like any successful business the supply chain must be managed well in order to keep
commerce flowing. This supply chain also applies to information relating to the ocean, its
state and forecasts of its condition. The accuracy of this information is critical to enable
international trade, transportation and protection of our coastlines. Since ocean-related
and near-ocean commerce accounts for so much of our nation's GDP, the more we know
about the ocean the more our nation can maximize its potential and grow our economy.
People need technology and access to the right information so they can make the best
decisions possible, wherever they are and whenever they need it. Most people do not know
when they will need critical information or what kind of information they will need until
they get into a situation where decisions (perhaps life-saving) need to be made. Many times
whatever situation develops or hazard presents itself a complete decision tree has not
been thought through in advance.
Today’s complex environment is being monitored by satellites, sensors on the ground, and
in the ocean by drifting, moored, and autonomous vehicles. Atmospheric profile
measurements are collected by planes, balloons and unmanned aerial vehicles being
launched and radars catching just about every storm that develops. The amount of
observations that are collected on the state of the ocean and atmosphere is impressive. Yet
as storms develop and intensify, they sometimes unleash unexpected power that affects
millions of people in a short period of time. The public may even express themselves as
frustrated that they never received any warning that this storm was headed their
way…even if the information was out there…it just didn’t reach them in time or at all. The
information delivery pathway to serve citizens is incomplete.
Weather forecasters still have a difficult time determining precisely when a tropical
system, spinning up in the tropical ocean, evolves into a tropical storm or transitions from
a tropical storm into a hurricane – we have yet to understand fundamental questions about
such intensifications. It takes observations from both satellite and airplanes flying into the
storm to accurately determine its strength and a future IOOS® should offer proactive alerts
and messages when certain criteria are met to satisfy the needs of a broad base of users.
This is a system that evolves with technology and is responsive to the needs of the
people.
The need for real-time, actionable information is critical during day-to-day and emergency
response operations where multiple jurisdictions and disciplines interact. Plenty of
homeland security-related information exists at the local, tribal, state, and Federal levels,
but since equipment investment decisions have been made based on the specific
operational needs of individual agencies without benefit of a national strategy or
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standards, this information is often trapped in silos. As a result, potentially critical
information often does not make it into the hands of the people who need it the most.
In short, our challenge is to build a system that is:




Operationally reliable
Economically sustainable
Politically defensible
Technologically evolvable
IV. The Vision
The world defined by the examples at the start of this chapter will be enabled by the
drivers that we've defined, and guided by the policies that pertain to environmental
data and information. However, the realization of this vision can take many shapes.
Just as over a hundred different countries deploy different forms of national weather
services, we expect that many different paradigms can emerge successfully. We know,
however, that certain 'boundary conditions' must exist to define a successful enterprise
of ocean observing. We believe that vision will be defined by the following
characteristics:
The ocean observation services that are provided will be "full spectrum": There's a quip
that it’s easy to establish a weather service since you only need to monitor three kinds
of data: pressure, temperature and moisture! Valid or not, this perspective calls to the
fore the need to attend to scores of variables in a robust ocean observing system. While
the value of real-time observations of ocean surface pH might be less relevant to
commercial shippers, those same data will be of paramount importance to coastal
shellfish hatcheries. The enterprise of services dependent on ocean information will
demand that the full array of relevant observations be operationalized. The priorities
for tailored observations will be driven by market demands, but all observation types
will have the potential for full transition to market.
The ocean observing system will be a public-private enterprise: Public sector support will
be insufficient to support all applications, and private investment will not tolerate
footing the bill for what is arguably largely a public good. In this context, substantial
national public investment will remain needed to ensure a core set of measurements of
baseline variables remains intact. In addition to this continued federal investment,
partnerships of new sorts will emerge, allowing a legal co-mingling of resources (with,
of course, concomitant authorizations through revised economic policies and
regulations). A risk-tolerant foundation of individual ('angel') and collective (venture
capital, or crowd funding) investors will recognize a meaningful return on investment
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for the added value contribution to a publicly funded foundation of observations and
services. Forms of industry cooperatives (as exist in many natural resource industries
such as forestry) will form to support those sector-specific capabilities needed to
enhance their bottom line. These private investment-backed activities will initially
establish a broad array of creative business plans, a handful of which will become
standard models for the industry (not unlike the evolution seen in information services
over the last two decades). Ultimately a commercial enterprise of equity valuation in
excess of $10B will emerge, with a workforce exceeding 10,000 in the United States
alone (this is compared to data regarding the cost and value of the weather enterprise,
as shown for example at www.sip.ucar.edu). This will, by necessity, be a global
commercial enterprise of data acquisition, assimilation and application, information
dissemination, and ocean product derivation, with full international interoperability for
those who succeed - think of the telecommunications example as an analog, in which
independent solutions ultimately had to become integrated to satisfy the needs of the
market.
The ocean observing enterprise will be expressed through a new system of governance: A
wholly different concept will have to emerge, that engenders sustained operations and
investment value. Several concepts will need to be invoked to ensure operational
configuration control, requirements validation and management, research oversight,
infrastructure recapitalization priorities and system refresh, as well as basic operations
and maintenance. Several governance concepts will be adopted such as the use of IDIQ
acquisition tools, establishment of public corporations’, deployment of GOCO
(Government Owned Contractor Operated) principles, not to mention traditional
corporate oversight. The governance system will provide accountability to the
taxpayers and the stockholders.
The ocean observing system will promote the establishment of new models for workforce
development: The breadth of skill sets, combined with the logistical challenges of
operating to full ocean depth, at all times, throughout the globe will demand some
special approaches to education, as well as access to knowledge. The community can
tap into decades of experience in training weather forecasters and sensor engineers,
while the capabilities for knowledge transfer enabled by broad band communications
will open up opportunities for on-site educational opportunities (envision a systems
engineer at an ocean observations site on the Pacific coast getting trained on buoy
operations through a teleconnection to an oceanographic institution in Florida)
V. Conclusion
Our society is at a seminal point in the development of a class of products and services
based on ocean observations. We envision an enterprise of ocean observations that
builds on extraordinary successes to date, and merges with expected developments.
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Ultimately, we foresee a capability utilizing and delivering products from ocean
observations that are fully integrated into the culture of our society, and is considered a
non-negotiable component of our ability to enhance the lives, livelihoods and quality of
life of future generations.
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