2006 Unidata Users Workshop

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2006 Unidata Users Workshop

• Expanding the Use of Models as Educational Tools
• in the Atmospheric Related Sciences
• 10 July 2006
• Boulder, CO
• Dr. Mohan Ramamurthy
• Unidata Program Center
• UCAR Office of Programs
• Boulder, CO

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Welcome!

• Welcome to Boulder, UCAR, Unidata, and this new
  facility.
• Thank you for your enthusiastic participation in
  this important gathering of our community.
• We have 82 registered participants possibly a
  record for a Unidata Users Workshop.
• A great program is ahead for the rest of the
  week, with a terrific line up of speakers and
  instructors (once I get off the stage!)

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Importance of Users Workshops

• Have been held every three years since 1988
• This speaker is a veteran of all seven workshops!
• Written into the Users Committee charter
  facilitating the exchange of ideas among users
  on the Unidata Program and its systems
• Over the past 18 years, the workshops have
  brought the community together to address a range
  of issues related to atmospheric/geo science
  education
• Integration of Research and Education is a core
  Unidata value.

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Acknowledgements

• I wish to thank the Users Committee, Gary
  Lackmann and Chris Herbster - the Co-Chairs of
  this workshop, the entire Workshop Organizing
  Committee, and the UPC staff for their hard work
  in organizing this meeting.
• Sincere thanks to NSF/ATM (Cliff Jacobs and
  Bernard Grant in particular) for their continued
  and strong support of Unidata and these
  workshops.
• Finally, I wish to thank all speakers, lab
  coordinators, and other individuals who have
  shaped the agenda and helped to develop a very
  exciting program for the days ahead.

When you get a chance, be sure to thank these
individuals for their diligent work and support.
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Expanding the Use of Models as Educational Tools
in the Atmospheric Related Sciences
Data is the linchpin of scientific process (July
17, 2002)

• Having spent over a quarter of a century in
  working with atmospheric prediction models and
  teaching those topics, this years workshop topic
  is particularly near and dear to my heart.
• As Chair of Board of Higher Education, last year
  I led the team that drafted the current AMS
  statement on Bachelors Degree in Atmospheric
  Sciences.

Observations
Data
Theory
Models

• More than ever, educators, students and their
  future employers recognize the importance of
  computer literacy and information technology (IT)
  skills. To meet those expectations, atmospheric
  science programs must help students build a
  seamless pathway from the classroom to productive
  careers in atmospheric and related fields and
  prepare them for todays increasingly IT-driven
  and global society. Specifically, computer
  programming and other computer-related skills
  should be integrated, as appropriate, into as
  many atmospheric science courses as feasible.

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Expanding the Use of Models as Educational Tools

• Workshop Goals
• Defining the extent to which modeling concepts
  should be incorporated into atmospheric science
  curricula
• Provide a means to expand the use of models in
  traditional undergraduate and graduate courses.
• Facilitate the sharing of existing resources that
  have been developed in the community as well as
  develop new materials and resources inspired by
  interactions at the workshop.
• Generate a dialog to identify those aspects of
  modeling which are most critical to teach at
  various levels (i.e., freshman to graduate
  students).

The introduction of models as an evolutionary
development from simple to more complex but a
related one fosters learner acceptance, resulting
in an orderly development of thought process.
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One of the Most Widely Used Models in Science
Education
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Pedagogical Effectiveness
Dempster, 2004
Data, tools for analysis and visualization, and
models play a critical role in this
hierarchy. Workshops like this provide an in
important venue for community discussions that
help to transform the academic culture.
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Democratization of Access to Data and Tools
Unidata has made great strides in establishing
the underpinnings of a worldwide data sharing
network Over 170 institutions are now
participating in the IDD. The democratizing and
transformative effects of data and knowledge
sharing cannot be overstated. Students and
faculty are using the very databases and tools
used by researchers. It is having a profound
impact on education, research, and operations.
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Tools for Analysis and Visualization
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Unidata Modeling

• The modeling community has always been an
  important group within the larger Unidata
  community for us.
• Unidata was at ground zero when the CONDUIT
  project, a USWRP-led effort, was started. CONDUIT
  distributes high-resolution model grids from NCEP
  to promote local modeling at universities.
• Over 50 institutions are receiving
  high-resolution CONDUIT data
• Over 100 institutions are receiving operational
  model grids
• Unidata was a founding partner in the CRAFT
  project, led by Kelvin Droegemeier, to bring
  real-time WSR 88-D Level II data to universities
  for model initialization.
• The success of CRAFT led to the adoption of the
  LDM by NWS for operational use
• Today over 60 institutions are receiving Level II
  radar data
• With TIGGE (THORPEX Interactive Grand Global
  Ensemble), Unidata is involved in bringing output
  from 10 operational prediction models around the
  world to archive centers at NCAR, ECMWF and CMA
  (Beijing).
• LDM was able to transfer 17 GB/hour of data in
  tests
• Data flowing from ECMWF to NCAR since April 2006
• We are working to gain permission to distribute a
  subset of TIGGE data to community in real-time

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Unidata Modeling - continued

• Easy, transparent and remote access to model
  output
• COMMON Data Model (e.g., GRIB2 support) and
  related web services
• IDV advancements (WRF support, subsetting
  subsampling features, seige client connection,
  etc.)
• NetCDF advancements CF conventions, staggered
  grids, etc.
• GIS integration WCS Gateway for THREDDS Data
  Server

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In the Beginning...
Coming soon...
Now..
a dizzying volume of information on the order
of 100 MB/day, aggregate (Davis and Rew, 1990)
20 TB
LDM-6 Internet2 bandwidth use Typically 21
TB/week (4-5) growing
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UIUC Experience

• Built hierarchy of models for various courses
• Lorenz 3 variable model
• Linear and nonlinear shallow water models
• Non-divergent barotropic equivalent barotropic
  models
• Quasi-geostrophic model developed it as a class
  project in Howie Bluesteins Synoptic Met. course
• Plethora of interactive Java models
• Balance of forces in the boundary layer
• VGEE concept models
• MEAD model to illustrate uncertainties
• http//www.atmos.uiuc.edu/courses/atmos100/program
  _lists/jnlp/mead.jnlp

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A Few QG Model Applications
Q-Vectors
Baroclinic Lifecycle
Monsoon Depression
Case Studies
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STELLA Models Powerful Tools for Learning at all
Levels
Carbon Cycle
Hurricane Simulation
Water Cycle
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VGEE The Visual Geophysical Exploration
Environment

• An inquiry-based curriculum to guide student
  exploration
• A learner-centered interface to a scientific
  visualization tool
• Concept models to help students understand
  scientific principles and their role in data
• A suite of El Niño-related data sets adapted for
  student use (and connections to distributed,
  real-time data)

Using the Visualization tool and data sets,
students notice that the Western Pacific is
considerably warmer than the East.
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VGEE Relate, Explain Integrate
Concept models are used to explore and explain
relations in an idealized context.
Concept models can also be used to probe the
data. This helps students apply the basic physics
toward understanding geoscience data.
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Service-Oriented Science Education

• Web Services are self-contained, self-describing,
  modular applications that can be published,
  located, and invoked across the Web.
• XML based Web Services are emerging as tools for
  creating next generation distributed systems that
  facilitate program-to-program interaction without
  the user-to-program interaction.
• Besides recognizing the heterogeneity as a
  fundamental ingredient, these web services,
  independent of platform and environment, can be
  packaged and published on the internet as they
  can communicate with other systems using the
  common protocols.

Source Ian Foster, Science, 6 May 2005
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Grid Computing

• Refers to an infrastructure that enables the
  integrated, collaborative use of computers,
  networks, databases, and scientific instruments
  owned and managed by distributed organizations.
• The terminology originates from a crude analogy
  to the electrical power grid most users do not
  care about the details of power generation,
  distribution, etc, but your appliances work when
  you plug them into the socket.
• Grid applications often involve large amounts of
  data and/or computing and require secure resource
  sharing across organizational boundaries.
• Grid services are essentially web services
  running in a Grid framework.

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TeraGrid A 250M NSF Facility
Capacity 20 Teraflops 1 Petabyte of
disk-storage Connected by 40GB network
NCAR has now joined the TeraGrid
150 Million TeraGrid Award actually, a second
installment Heralds New Era for Scientific
Computing Researchers and educators around the
country can now access a range of computing
resources that will accelerate advances in
science and engineering. (NSF Press Release,
August 19, 2005)
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Traditional NWP

• Analysis/Assimilation
• Quality Control
• Retrieval of Unobserved
• Quantities
• Creation of Gridded Fields

Prediction/Detection PCs to Teraflop Systems

• Product Generation,
• Display,
• Dissemination

• STATIC OBSERVATIONS
• Radar Data
• Mobile Mesonets
• Surface Observations
• Upper-Air Balloons
• Commercial Aircraft
• Geostationary and Polar Orbiting Satellite
• Wind Profilers
• GPS Satellites

The Process is Entirely Serial and Static
(Pre-Scheduled) No Response to the Weather!

• End Users
• NWS
• Private Companies
• Students

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LEAD Linked Environments for Atmospheric
Discovery

• A large Information Technology Research project
  involving nine institutions, including Unidata
• Goal Lower the barrier to entry for numerical
  weather prediction
• LEAD is changing the paradigm for using
  state-of-the-art prediction models
• With LEAD you can now do in six minutes what
  normally took a researcher six months to do!!

Kelvin will have A LOT to say in his talk(s)!
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NWP as chained Grid services
NCSA
Prediction Service
UAH
Product Generation Mining Service
User running local analysis and display tools
User Orchestrates Web Services to Create
Regional Forecast
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LEAD Goal Solve NWP Problems by Linking Services
Together in Workflows
Service L (Catalog)
Service D (Data Stream
Service C (Decoder)
Service A (Data Assimilation)
LEAD Mantra Everything is a service
Service L (Mining)
Service B (WRF)
These servicescan also be used as
stand-alonecapabilities.
Service J (Visualization)
Service K (Archival)
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Bridging between the TeraGrid the Unidata
grid

• Bridging Communities with range of computing
  capabilities and needs
• Many technological, cultural and systemic
  challenges remain in connecting departmental and
  PI computing systems with high-end Grid
  environments like the TeraGrid
• With our LEAD work, we are beginning to build a
  bridge between the traditional Unidata community
  and high-end computing communities.

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Concluding Remarks

• We live in an exciting era in which the
  confluence of science and technology is reshaping
  the conduct of education.
• A new generation of data and information services
  are enabling the use of innovative education
  strategies.
• Cyberinfrastructure, including data, tools,
  models, and services, is playing a crucial role
  in geoscience education and research.

I wish you all a most productive workshop. And
be sure to have fun along the way!