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1. REPORT DATE (DD-MM-YYYY)
10-02-2011
2. REPORT TYPE
3. DATES COVERED (From - To)
Technical Paper
FEB 2011 - MAR 2011
4. TITLE AND SUBTITLE
5a. CONTRACT NUMBER
FA8720-05-C-0002
European and U.S. Perspectives on the Sharing
and Integration of Weather Information
into ATM Decisions
5b. GRANT NUMBER
5c. PROGRAM ELEMENT NUMBER
6. AUTHOR(S)
5d. PROJECT NUMBER
David Pace, Thomas Ryan, Aaron Braeckel, Dennis Hart, Oliver
Newell, and Kajal Claypool
5e. TASK NUMBER
5f. WORK UNIT NUMBER
7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)
8. PERFORMING ORGANIZATION REPORT
NUMBER
MIT Lincoln Laboratory
244 Wood Street
Lexington, MA 02420
9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES)
10. SPONSOR/MONITOR’S ACRONYM(S)
Federal Aviation Administration
800 Independence Avenue, SW
ATO-P
Washington, DC 20591
FAA
11. SPONSOR/MONITOR’S REPORT
NUMBER(S)
12. DISTRIBUTION / AVAILABILITY STATEMENT
DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited.
13. SUPPLEMENTARY NOTES
14. ABSTRACT
Weather is a major source of operational air traffic delays, accounting for 25 to 70 percent of all delays
dependent of the geographical region. In today 's Air Traffic Management (ATM) systems, a variety of
weather information is available to help tactical and strategic planners better anticipate weather events
that impact airspace capacity. Regretfully, the information is not always shared amongst all the
stakeholders involved or well integrated into the existing ATM environment. This paper describes the
high-level concepts for an improved sharing and integration or weather information into Air Traffic
Management Decisions, as well as the current state and anticipated capabilities or the underlying
information Management infrastructure.
15. SUBJECT TERMS
16. SECURITY CLASSIFICATION OF:
U
a. REPORT
U
b. ABSTRACT
U
c. THIS PAGE
U
17. LIMITATION
OF ABSTRACT
18. NUMBER
OF PAGES
SAR
6
19a. NAME OF RESPONSIBLE PERSON
Zach Sweet
19b. TELEPHONE NUMBER (include area
code)
781-981-5997
Standard Form 298 (Rev. 8-98)
Prescribed by ANSI Std. Z39.18
Ninth USA/Eu ro pe Air Traffic Manage ment Research and Development Seminnr (ATM20 I I)
European and U.S. Perspectives on the Sharing
and Integration of Weather Information
Contract Aoproved
into ATM Decisions' FA!\~
-2- !(o (((
David Pace
Aviation \\feather Group, FAA
\Vashington, D.C.
da vid.pace@ faa.gov
Dennis Hart
Eurolltrol
Brussels
Denn is. [email protected]
Thomas Ryan
Aviatio n Weather Group , FAA
Washington , D.C.
thomas.e .ryan @faa.go v
Oliver Newell and Kajal Claypool
Weather Sensing Group
MIT Lincoln Laboratory
Lexington , MA
01 ivern @II.lllit.edu
Aaron Braeckel
Research Application Laboratory, NCAR
Boulder, CO
[email protected]
Abstract- ""eat her is a major sOlll"Ce of operationnl air
trarric delays, accounting for 25 to 70 percent of all delays
dependent of the geographical region. In toclay 's Air
Traffic Management (ATl\1) systems, a variety of weat her
information is available to help tactical and strntegic
planners better anticipate weather even ts that impact
airspace cnpacity. Regretflilly, the infol"ll1ntion is not
always shared amo ngst all the stakeholders involved or
well integrated into the existing ATM environment. This
paper describes th e high-level concepts for an improved
sharing and integration or weather information into Air
Traffic NIanagement Decisions, as well as the current state
and anticipated capabilities or the und erlying inrormation
nHlnagement infrastrllcture.
I.
INTEGRATtO N OF WEATH ER INFORMATtON IN ATM
U.S. Perspective
\\fea th er hns a tremendous impact on aviatio n operntions. A
study o r ncc iclcnl reports fro m the y e~H s 1994 th ro ugh 2006
revea led tha t 20 percent or aviati on acc idents and 23 percent of
raw l lI viatioll accidents we re wcather related. \Veather delays
acco unt for 70 perccnt or the $41 bi ll ion anllua l cost of air
traffi c c1clnys with in th e Un ited Stmes Na ti onnl Ai rspace
Sys te m (NAS ), or $28 billion annuall y. Approxi mately tlVO
thirds ($ 19 billion) of th ese delays are considered to be
1\ .
*'111is wo rk was sponso red by lhe Federal Aviation Ad mi nistrati on under Air
f'"o rcc Contran
No. FA8 72 I ~OS·C.OO02 .
Opinions, inteqJretations,
concl us ions, and rt'" co mmcndmions !I re lhose of the aUlhors and are nOI
llI:ccssarily endorsed by (he Un it ed Sta les Govelll menL
avoidable. The Weather-Air Traffic Management (ATM )
IntegI:ation Working Group of the NAS Operati ons
Subcommittee of the Federal Aviation Admini stration ' s
(FAA 's) Research, Engineerin g and Deve lopment Ad visory
Committee conducted a 12- lllonth stud y to examine the
potential benefits of integrating weather and ATM. The report
of thi s committee mnde several recommendatio ns regarding
integration of weather and th e potentin] for weather integration
to hclp reduce deln ys . The wn y to mitigate these dela ys and
eliminate those that are avo ida ble is to impro ve the qual ity and
method of use of weather information and integrate the weather
support into NAS dec isions. At th e same time, the acl vnntages
nnd potential benefits of integratin g wea th er and air traffic
manage ment will , in all likeli hood, ass ist in reducing the
number of weather relnted acc idents.
The FAA has produced a Nex tG en An 'l-Weather
Integratio n Plan which prov ides the npproac h, sco pe. and
implementati on road rnap to achieve th e NextGcn vision: to
enab le dec isio n makers to identify areas where and when
ni rcrn ft cn n ny safely with wea th er assimil ated into th e
dec ision makin g. It nlso addresses age ncy ro les ancl
responsibilities and includes reso urce requ irements. The pl an
es tab lishes an npproach to deal wi th the in tcgrnt ioll of weat her
information into the ATM dec ision-mak ing process.
Integration as used here rete rs to th e inclusio n of weat her
information into the logic of a decision process or a decision
nid sllch that weather constraints are taken into accou nt when
the dccision is mnde or recommend ed. The goal of weath cr
integration is to minimi ze the need for humans to ga uge NAS
weather constraints and to dete rmine th e optir11LlIl1 miti g.a tion of
these constraints.
The ATM~wetllhe r
fo ll owing problems:
Integratio n concep t addresses
the
•
Most weather support to ATM is manual , wit h wea ther
disp lays that Tllllst be interpreted by the lIser.
•
Weather products do no t ha ve the maturity req uired for
d irec t inserti on with out inte rpretation nor are they
tra nsl ated into constrai nt information.
•
Rule s for interpretation and LIse of weather data are
generally based on the expe ri ence of the user.
•
ATM decisions based upon today's weather produc ts
are inconsisten t from user to user.
Figure I below illustra te s the process of mov in g from raw
current and forecast weat her data through the creatio n of
wea ther in for matio n that re la tes weather data to aviat ion
const raint s and on to the generatio n of rules for decisions to be
mad e by ATM operators and other users and ult imately to the
creation of auto mated Decision Support Tools (DSTs) .
An analysis o f the current stale of weather integration was
conduc ted and found weathe r integrat ion opportuniti es in the
NextGen Solu tion Sets: Initiate Trajectory Based Operatio ns,
Increase Arri vals/Departure s at High Dens ity Airports, Increase
Flexib il ity
in
the
Term ina l
Env ironme nt , Improve
Collaborative
ATJ'vI,
In crease Safety, Security,
and
Environmental Performance, and Transform Fac ilit ies. Each
so lut ion set was broken down into Operational Impro vements
(OIs), wi th level Mid-Term capabilities, Mid-Term operat io nal
scenarios, and Mid -Term wea ther integration and needs
ana lysis.
ATM wi ll require DSTs that can access info rmati on from
the 4- D Weather Data Cube (4-D Wx Data Cube) that has been
Weather
Information
translated into NAS co nstraints a ncl provid e ATM wit h best
choice opt io ns. The translation can be obtained by a network
service for common lise or by im bedd in g the transla tion
capab ilit y in the DST for unique needs. The rAA ATMWeather Integration Plan provides an overview o f
for evaluatio n of the
methodologies. th e strategy
methodologies, and the initial ident ifi cati on of the best nearterm strategies for further development. An appendix to the
Plan provides a survey iden tify in g technologies and
methodologies for trans lat in g .weathe r information into ATlv[
co nstrai nts in the NAS and for usi ng that infor ma tio n. The
survey includes approaches for addressing weathe r-re lated
uncertainty in ATM decision making and risk management
processes.
The Plan presents a summary of each of th e surveyed ATM
cons traint and impact models stan in g with models th at were
derived primarily for co nvect ion, and endin g with a wid e
var iety of models for severa l types of aviat io n hazards. It also
co ntains an assessment of the maturity of the ATM cons train t
and impact models presen ted , and id en tifie s gaps in
technologies that mll st be addressed for NextGen.
Further research is required on the COil vers io n o f weath er
data into spec ific ATM co nst ra ints. It is expec ted that th is
researc h will be a collaborati ve e ffo rt in vo lvi ng the
govern ment, the private secto r, and acade mi a.
The execution of thi s Plan will occur in four steps. The
steps will be execu ted in sequential orde r from the start, but the
steps will be repeated many time s as new weathe r techniques
and ATM too ls are devel o ped and may be occ urrin g
simultaneous ly at some point in the future. The steps are as
follows:
A"tM
Oecision
Suppor.t
Weather
Translation
Observations
"
Forecasts
"
I •
Analyses
_t
<I-
I
iWrWfltl'trl11
~
Translation of
weather data
into:
Constraints
Threshold
Events
Conversion
into:
NASlmpac\s
State Changes
DSTs use
'impacts to
developTFM
solutions
NextGen 4D
Wx Data
Cube
,p-- ------------
Weather Co mmunity
-------- -----------------
:1-Primary
: NWS
FAA Met
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ __ _
Figure
J
ATM Community
FAA ArM
__________________________
Convers ion of weather infonnation into ATi...f decisions.
._------------,
:
_ _ _ _ _ _ _ _ _ _ ____ I
I.
Align teams with each solution set and analyze
wc,lIhe r integration requ iremeTHs for a scrvice- and
performance-based approach for weather integrati on as
associated with operational relevance.
interoperability. This is especiall y tr ue in a European selling
where MET Informat ion and Services available for av iation
today are almost exclusively di ctated by the Slated ICAO
provisions.
2.
Idcntify the specific weather in tegration insert ion
points, including performance criteri a and va lue, into ATM tool
or dccision platform functionality.
Besides developing new ca pabilities. rccent ad vances in
meteorological observat ion and forecasting techn iques ha ve
already raised the levels of accuracy of the predicted
information at a European level significantly. But the lise of
these products by the European ATM commun ity continues to
be low. The reasons for this underutil ization are far from clear.
There is circumstantial evidence thut a lack of awareness is a
significant cause. However, the root cause could be that ATM
today, with respect to weather, applies a reactive rather than
proactive approach to decision making. ' Wait and see' appears
to be the norm, as the perceived leve l of associated risk is
considerably lower than in the proactive alternative.
3.
Iden tify and recommend the specific weather
integration techniques and technologies that best fit the
requirements of a particular traffic flow management tool under
development and in particular, the insertion points identified in
the previous step.
4.
Serve as the Subject Matter Expert for the ATM tool
development team to ass ist in integration of the weather
methodologies and to evaluate test results.
To downl oad the f'AA ATM-Wea ther Integrat ion Plan, go
to hup://www.jpdo.gov/ and then in the to p ri ght corner choose
"Knowledge Cente r" and "Library." From there, look under
"Technical Documents" to find "Air Traffic Manageme ntWeather Integration Plan v2.0."
B.
European Perspective
Today 's and future European ATM Network (EATMN) is
little different to the US NAS and will continue to be subject to
the same vagaries of weather phenomena that affect air
transport today . EUROCONTROL's Performance Review Unit
(PRU) and its Centra l Flow Management Unit (CFMU)
est imated that over recent years, 25% of the airport and enrou te delays in the EATMN were attributable to weather.
Translating this to Airport performance, aroll nd 45% of delays
had a direct relationship with the wea ther on or in the vici nity
of airpons. Whilst less imp ressive than the es timated associated
costs in the US, the average annual costs for weather related
delays in Europe is an estimated €900 million.
Within the contex t of the futu re EATMN, this considerable
impact of wcathe r on safeLY, capacity and efficiency and the
potcntial to mitigate some of the environment impaci of
av iat ion Illust be examined in detail. The importance of timely,
accurate and easily available meteorological information for
dec ision support is emphasized in European ATM Master Plan
and th e Si ngle European Sky ATM Research (SESA R)
Programme.
Identified by all stakeholders arc a number of key chan ges
in support of the notion of utilization, management and
interchange of metcorological information relevant for the
fUlu re European and Global ATM system. These key changes
idc nti lied arc very si milar to the US ones and add ress iss ues
such as requirements for improved means to fo recast and report
wind shear, low level turbu lence, wake vo rtex, low visibility
procedure conditions, winter conditions, severe wea ther
phenomena and similar OCC UITences to support lIser needs. In
ge neral. these products and se rvices are in addition to the
tradit io nal requiremen ts 1'0 1' Meteorological (MET) Information
and Services as spec ified ill leAO Annex 3. This in itself
req uires a key change ill how MET is harmonized, regulated
and all stakeh o lders conjointly work towards global
To change this norm, it is clea r that a significantl y higher
degree of understanding and cooperatio n between the user and
supplier communities is req uired. The ch all~ nge is to ide ntify
the key data attributes required 10 ass ure a hi gh degree of
confidence in the information and the platform for dec ision
making. Moreover, 10 stan to wo rk 0 11 this conversion of
weather data into specific ATM constraints, it is crucial to
understand, foster and develop the notion of uncertainty in
ATM decision makIng.
The aim is to 1110V~ towards the much desired holistic,
cooperative and collaborative decision-making environment.
In such an environment the diverging expectations and interests
of all members of the Air Transport co mmunity are balanced to
achieve equity, access and system efficiency. It is essential for
the effic iency of ATM thm a know ledge-based decision
making is made inclusive of weat her. Therefore the existing
knowledge on the uncert aint y of MET Info rmation throu ghou t
the th is decis ion making environment for ATM must be
qui ckl y and full y incorporated into operati onal proced ures ..
It is observed that in many domains of Ai r Transport and
ATM, a state of ha ving lim ited knowled ge and where il is
impossi ble 10 exactly descr ibe th e future o utcome of th ings can
be handled. Risk manage ment meth odologies inclusive of costlost anal ys is provide the mec hanisms to nddress ullcertaint y in
decision making processes. It is accep ted that a transat lan tic
fli ght approac hin g th e outer bounds of radar coverage will
appear 011 the ATCO scree n in defin ed space and time but not
exactl y on position A, or time B. However, ATM find s it
diffi cult 10, for instance. incorporate a spot wind forecast of 2
meier per second at FL350. int o the calculation of the
associated intended track.
It should be recognizcd th at the level of ullcertainty in
do mains other tha n meteorology is in 1110st eases of a different
order. Therefo re, it could be perce ived as d ifficul t to apply in a
straightforward manner by ATiVI. This comes back to the
inlrinsic stochastic nature or weat her -thus meteoro logycompared to other infor matio n types and doma ins lIsed by
ATM. These are potentiall y reasons why it is 110t poss ible 10
handle the uncertainly associated wit h meteo rol ogica l
information in an ATM contex t across the EATMN. The exact
reasons are however not co mpl etely understood.
Further resea rch is required to improve the level of
understanding and confidence within the MET and ATM
communities to tackle issues assoc iated with meteorological
uncertainty. It is expected that this research will be a
collaborative effort throughoLit the SESAR Programme.
II.
WEATHER
INFORMATION
MANAGEMENT
I NFRASTRUCTURE
The U.S. and European plans for integration of weather
information into ATM in the 2013-2025 time frame presume
the existence of a robust ATM information ma na gement
infrast ru cture inclusive of weather information. At a high-level,
both the FAA and EUl"Ocontl"01 and the regional ATM
impro vement programmes NextGen and SESAR are addressing
the iss ue using a similar, Service-Oriented Architecture (SOA)
approach that· relies on standardized data exchange models and
data access services. A key goa l is to move away from stovepiped weather systems that are ntH inherent ly interoperable and
are, as a consequence, difficult to maintain and extend and
moreover hindering cOlllmon situational awareness amongst all
rele va nt stakeho lders.
The need for standardized data models and data access
services is certa inly not unique to the weather domain, or the
FAA or EUROCONTROL as organizations. In the U.S.,
numerous other governmcnt agencies, suc h as the Department
of Defense (DoD), Department of Homeland Security (DHS),
are pursuing a similar strategy. In Europe, organiza tions such
as the Infrastruc ture for Spatial Information in Europc
(INSP1RE), serve a sim ilar ro le.
A.
Dow models
The focus over the last few years has been on creatin g data
models tha t leverage exist ing standards, such as the spatial data
standards supported by the International Standardization
Organization USO ) or the Open Geospatial Consortium
(OGC). The weat her information exchange mode[ (WXX'1-.1),
developed jointly by the FA A and EUROCONTROL, is an
exa mple of a modular data model based on core components
defined by the ISO and OGC standards. The benefits of
standards include interoperabilit y between a wide variety or
Eurocont ro! ~
FAA
Extensions
Extensions
['J ..
Otller
Extensions
weather data providers and co nsumers. as well as shared
software component libraries .
Following guidance in the NextGen and SESAR Enterprise
Architectures, \VXXM separates the abstract conceptual model
from the physical implementation(s) of the 1110del. In WXXM ,
the abstract conceptual model is defined lIsing Universal
Modeling Language (UML) and is commonly referred to as the
Weather Information Conceptual Model (WXCM). Currently,
WXX1v1 includes a physical implementation of the conceptual
model in the form of an Extensible Mark-up Lan guage (XML)
schema, which itself leverages XML schema components
available from 1S0 and OGe and is automatically generated
from the UrvtL model. This XML schema is referred to as
WXXS. The 1110dular, component-based design of the WXXM
Xl'vlL schema is shown below in figure 2. Note that the XML
schema is one physical realizarion of the conceptual model, and
other representations are possible.
The layered, modular nature of th e model provides obviolls
benefits in the form of software reuse. Less obvioLls is the faci
that design also allows for modular governance of the model.
This is particularly useful in the context of the more rapidly
changing aspects of the model driven by new NextGen or
SESAR requirements. Community-specific extensions provide
the necessary ag ility for organizations such as the FAA and
Eurocontrol to independently innovate, while still remainin g
true to the overall \VXXM framework.
It is interesting to contrast the \VXXM data model with the
aeronautical information exchange model (AIXM) and other
models under development for data typical used in the ATM
environment (Fli ght Objects, etc.) from the perspecti ve of
Weather-ArM integration. As for \vXXM , A1XM is based on
GML and the ISO/OGC spatial standards stack. A diagram
illustrating the composition of the AIXM XML schema is
shown below in figure 3.
The leveraging of common underlying standards between
WXXM, AIXM and other data domains under development
provides a number of benefits to the ATiVr community. Shared
software infrastructure and tooling across the weatller and
aeronautical information domains wi l[ simplify application
development and red uce overal l development costs. For
example, a single GML software library can be lIsed, assLlm ing
that the models are synchronized to use the same version of
GNfL. Also cross-references between domains, such as a
reference to an AIXl'vl runwa y description from a \VXXfVl
airport weather report, also become more straightforward due
Aviation-Specific Weatller Components
General-purpose Weather Components
Observations
& Measurements I
ISO t9123
Eurocontrol
Extensions
~
FAA
Extensions
rJ . . .
.
Other
Extensions
Aeronaulicallnformalion Core Components
Geograplly Markup Language (GML)
Geography Markup Language (GM L)
ISO 19139 Metadala
ISO 19139 Metadata
XML
XML
Figure 2
Ln ycreo. composnblc.
WXXivl XML Schcnw
Figure 3 AIXM
XivlL Schemn Componen ts
to the cOlllmon upproac h shared by the two models. The use of
cross references is important LO minimize duplication of duta,
with its associated bandwidth requ irements and qua lity
assu rance issues. Within the SESAR Programme, these
commonali ties which respec t to common rules and common
components for all the models used in the different data
domains is also made abstract. This COlllillon layer is
represented as an abstract Information model inclusi ve of a set
of rules with respect to the underpinning data domains. Th is
model is referred to as the ATM Information Reference Model
(AIRM).
The shnring of XML components at the physica l exchange
level is, however, not a magic bullet in terms of providing
seamless interoperability between two or more information
domains. In practice. there is still a fair amount of manual
doma in-s pecific labor involved, plac ing limits on software
component reuse. Weat her information, for example, tends to
be highly dyna mic when compared with aero nautical
information sllch as runway and airspace geometries. The
temporality models of AIXM and WXXM evolved somewhat
separately, and are quite different. As a result, software
components llsed to hand le the tempora l aspects of weather
data cannot curre ntly see significant rellse with respect to
hand li ng the tempora l aspecls of AIM data. The possibility of
increased alignment of the models with respect to temporality
and other features will be the subject of ongoing research in the
201 1-2015 time-fram e, so me of wh ich wil l be conducted under
the auspices of the OGe interoperability program.
B.
Flat-File, eLc.) to be used in support i t variety of data Iypes.
such as weather, aeronautical information, and Ilight da ta.
Add itional information on the NNE\y program can be
found
on
the
NNEW
Wik i
at :
http,:!lwiki.lIcar.edli/displayINNEWDffhe+NNEW+W iki
The SESAR Information Management activi ties inclusive
of
meteorology
can
be
found
at:
ht10://www.sesa rju.eu/prngramm(./wnrkpackaf!.es/wpR
Ill.
CONCLUS tON
The challenges associated with the globa l integration of
weather into ATM decision making are signi fi cant not least
from the institutional side. EUROCONTROL and the FAA are
working closely together to ensure harmonization across the
Atlantic and to support ICAO at the globa l and regional levels.
This collaboration is reflected in Action Plan P29 of the
Euroco ntrollFAA Memorandum of Cooperation whic h has
already delivered WXXM. Wo rk is ongo ing with respect to the
4 D Weather Cube and the many other facets of av iation
meteorology which are cLIITently being considered or deli ve red.
Harmonization is forma ll y organized through biannual
Technical Interchange Meetings (TIM) and the essent ial needs
of global harmonization are not being ignored. ICAO, WMO
and a limited number of States from other ICAO regions are
inv ited to participate in the TIMs
In/omwrioll Services
The second major piece of the interoperability puzzle is the
set of interfaces, or services, used to access the data, History
has shown Ihat large-scale intcroperability is best achieved by
leveraging a re latively sma ll number of interfaces that arc, to
thc ex tent possible, data type agnostic (analogo us to the lise of
HTTP and ITP on the Internet). The OGe Web Feature
Service (WFS) and Web Coverage Service (\YCS) have been
selecled as a set of sti.lIldardized interfaces for access of nongridded :lI1d gridded weat her data products, when lIsed in near
real time user applications. These interfaces provide
standardized query semantics to allow data to be filtered by
product type, as well as by spec ifying spatial and temporal
constraiJlls.
Ne ither the \~lCS or WFS services, as currentl y specified by
the OGC, support pub Iish/subscribe message exchange
semantics. Thi s is cons idered to be an imporlant service pattern
in an ATtvl environment. A ke y activity wi thin Nex lGen has
been [0 develop publish/subsc ri be ex tensions fo r \YCS and
WFS, based on the OAS IS WS-Notification speci fi cat ion. This
capnbility has been sllccessfull y demonstrated, and the
responsible NNE\V team will be working on standardi zing the
:lpproach wi thin the aGe over the next two yea rs.
The
OGC
inte rl~tces,
including
the
pl an ned
publish/s ubscribe extensions, arc nOI spec ific to the wea ther
domain, and are capable of supporting spatial and temporal
query access 10 othe r data types such as aeronautical
information, night informat io n or other relevant information
for ATM. The \VFS and \YCS interfaces serve as an abstraction
layer, allowing for a variety of underlyin g data stores (SQL,
AUTHOR BtOGRAPHtES
Dav id J. Pace was born in Norfolk. Virginia. USA. He .lItcndcd the
Univcrs ity of Virginia, Chilrlottesville VA (BA mathematics 1969), SI. Louis
University, St Louis Missouri (grndUale studies in mcteorology t970). and
San Diego Slate Univers ity, Sail Diego Ca ti fo m ia (MS Astronomy 1974).
He has had an extensive career ill avi:ltion mcteorology in the US
Ai r Force and for FAA aviation wcather programs and the Next Gener:lIion
Ai r Transportation System at FAA Headquallcrs in Washington DC.
Mr. Pace is a member of the Amcrica Mcteorologicat Society
(aviation committec chair) .md the National Weather Associa tion ..
Dennis ( L3vt.) Halt was bom in Amsterdam. the Netherlands. He allendeu the
Roya l Nether lands Ai r Force Academy (r-.'1cteorology, 19S9). Bcsicks
ex perience in operational (aviation) meteorology hot h s uppol1ing mititary
operations alld civil use, he has an CX \l'nsive career in the 1Il,1Ilagelllcnl alld
inlcl11:lliona l eooperatioll aspects of 1IIeh,!orologica l service provision.
He joined EUROCONTROL ill 2008 as the Agency's sen ior
aviation meteorology expert.
Mr. Hart is a member of the Dutch Mett'orological Society
(NVBM), member of regional and In\el1lationat Civil Av i:H ioll Organi7ation
([CAO) groups working on r-. IET support to ATt'.,1. Observer to tht! World
ivleteorological Organization (WMO) Aeronautica l Program. advisor to
European institutions on aviation meteorology and active in OGe.
TIlomas E. Ryan was bOI11 in Pellh Am1.l0y. New Jersey. USA He auended
Frostburg Sta te University or i\h.ryland ( B.S. i\ lalhcmatics. 1982).
He has e:-.; tens i\'c Program t\ tanagemen t e,\ peril'ncc in the US Air
Force. the computer industlY, the US Agency for Intemat ional Developmcn t.
and thc US Federal Aviation Ad minist ration. His wide r.lIlging program
e:<; peri enees include wide-area network management. a 50.000 scat ellIail
system, building constnlctiol1. runway sa fel Y, ami the Ff\}\ ·s NNEW progra m.
Mr. Ryan is a member of the Alilcrican Meteorological Sm:lt.:t)' and
the Air Traffic Control Associatioll.
Oliver J. Newel l was bom in Boston, Massachuseus. USA. He attended the
Univers ity of fvlassachusens. Amherst (B.S. civ il engineering. 1984).
He is a staff member at MIT Lincoln Laboratory in Lexington.
MA. Since 1988. he has worked on a variety of weather radar and aircraft
survei llance sensor research programs for the FAA. Recently he has been
addressing information managemeTlt challenges associated with Nex tGen.
Mr. Newell is a technica l committee member in the Open
Geospatial Consolliutn and the OAS IS ebXML Regisll)'/Rcpos itory working
group.
K;tia l Claypool was bam in New Delhi. In dia. She received her B.Tech.
degree in Computer Engin eering from M;mipal Ins titute of Technology.
Kamala ka, India. and a Ph .D. degree in Computer Science from Worces ter
Polytechnic In stilute. Worcester. Massachuse tts. USA .
She was a facu !! y member post her Ph.D al the University of
Mass:lchllsell s. Lowell. :lnd a staff member at Oracle Corporation.
Dr. Claypool is :In assistant group leader at MIT Lincoln
Labori\lory in Lexi ngton. Mi\. Since 2007, her rese:lrch is focused on data
management. pall i1:11larly in information integration and modeling. and stream
data management.
Aaron D. Braecke l was bam in Denver Colorado. He anended Evergreen Slate
College (B .S. compu ter science. 1999), and Un iversi ty of Colorado (M.S.
computer sc ience. 20 10).
He is a soft ware engineer wit h the National Center for
Atlllospheric Researc h. in Boulder, Colorado. He began his work at NCAR
on the Aviation Digi tal Data SClvice (ADDS ) in 2002. and has been worki ng
in aviation weat her dissemi nation and visu alization ever since. He is cU ITen(]y
the techn ical lead for the NCAR NNEW team.
Mr. I3rat:ckel is active in the Open Geospatial Consortium and is a
found ing member of the OGC Web Services PublishJSubsclibc Standards
Working Group.