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A New Approach for Using Web
Services, Grids and Virtual
Organizations in Mesoscale Meteorology
Sponsored by the National Science Foundation
We Live in a Highly Vulnerable
World…
…That Requires Adaptation
Why is Meteorology the Exception?
Observing Systems Do Not Sample
the Atmosphere When/Where Needs
are Greatest
We Teach Using Current Weather Data But
Students Don’t Interact With It
Forecast Models Run Largely on
Fixed Schedules in Fixed Domains
The Nation’s
Cyberinfrastructure is Virtually
Static
The LEAD Vision
Revolutionize the ability of scientists, students, and
operational practitioners to observe, analyze,
predict, understand, and respond to intense local
weather by interacting with it dynamically and
adaptively in real time
Making it Happen
Adaptive weather tools
 Adaptive sensors
 Adaptive cyberinfrastructure

In a User-Centered
Framework
Where Everything
Can
Mutually Interact
How Does LEAD Do It?
The Notion of a Web Service


Web Service: A program
that carries out a specific
set of operations based
upon requests from
clients
The LEAD architecture is
a “Service Oriented
Architecture” (SOA),
which means that all of
the key functions are
represented as a set of
services.
The LEAD Service-Oriented
Architecture
Service A
(Analysis)
Service B
(Model)
(Radar Stream)
Service D
(Work Space)
Service E
(VO Catalog)
Service F
(Viz Engine)
Service G
(Monitoring)
Service H
(Scheduling)
Service I
(Decoder)
Service J
(Repository)
Service K
(Mining)
Service L
(Decoder)
Many others…
Service C
LEAD can Solve Broad Classes of Problems
by Linking Services Together in Workflows
Service D
(Work Space)
Service C
(Radar Stream)
Service L
(Decoder)
Service A
(Analysis)
Service B
(Model)
Service K
(Mining)
Service J
(Repository)
A LEAD Weather Prediction Workflow
LEAD Data Query System
LEAD Visualization and Analysis
Unidata Users Workshop in Summer 2006
“I spent days last summer learning how to install,
configure, run and display output from the WRF
model. With LEAD, I was able to do virtually the same
thing in part of an afternoon, and I needed far less
computer expertise to do it.”
-Professor David Dempsey
San Francisco State University
Research to Operational Practice:
NOAA Hazardous Weather Test Bed

LEAD produced on-demand
forecasts for experimental
evaluation by operational
forecasters at SPC
– Fully automated
– Forecaster-initiated

Mid-April – early June
(severe weather season)
2007, 2008
Centers of On-Demand LEAD Forecast Grids Launched During
the 2007 Spring Experiment of the NOAA Hazardous Weather
Test Bed
Launched automatically in response to hazardous weather messages
(tornado watches, mesoscale discussions)
Launched based on forecaster guidance
Graphic Courtesy Jay Alameda and Al Rossi, NCSA
Forecaster-Initiated Predictions
Brewster et al. (2008)
The Value of Adaptation: ForecasterInitiated Predictions on 7 June 2007
Observed Composite
Reflectivity
20 hr Pre-Scheduled
WRF-ARF
Brewster et al. (2008)
5 hr LEAD Dynamic
WRF-ARF With Radar
Data Assimilation
Adaptive Observing
Technologies
Other LEAD-Related Activities
The Future of LEAD

5-year NSF base funding ended in fall 2008
– Now in a 1-year no-cost extension
NSF support being sought to keep basic
LEAD services going through fall, 2009
 Proposal now being developed to support
long-term deployment as community facility

– Must increase community familiarity with LEAD
to make the case