Education and Outreach Within theModeling Environment for Atmospheric

Discovery (MEAD) ProjectDaniel J. BramerUniversity Of Illinois at Urbana-Champaign

Scott LathropRobert WilhelmsonNational Center for Supercomputing Applications

Steve GordonOhio Supercomputing Center

Susan RaganMaryland Virtual High School

Bob PanoffGarrett LoveShodor Education Foundation

What is MEAD??

The goal of the MEAD expedition is the development and adaptation of Grid and TeraGrid-enabled cyberinfrastructure for mesoscale storm and hurricane research and education. Portal Grid and Web infrastructure will enable launching of hundreds of individual Weather Research and Forecasting (WRF), Regional Ocean Modeling System (ROMS), or coupled WRF/ROMS simulations in either ensemble or parameter mode. Discovery and use metadata coupled to the resulting terabytes of data will then be made available to enable further exploration. Thus, a user of the MEAD workflow will be able to configure and integrate model simulations, manage resulting model and derived data, and analyze, mine, and visualize large model data suites in a research (not predictive) context. Finally, very large domain research fault-tolerant simulations will be enabled through decomposition techniques that can be utilized efficiently on the new TeraGrid architecture. The resulting environment serves both as an example for other research efforts and a cyberinfrastructure proving ground.

MEAD Lite

Develop / adapt Grid and TeraGrid-enabled cyberinfrastructure (CI) for mesoscale storm and hurricane research and education.

You can:Configure, integrate, and launch 100’s of model

simulationsmanage resulting model and derived dataanalyze, mine, and visualize large model data

And more…

Why Education??

Many do not know understand the benefits of ensemble model generation.

MEAD can do this efficiently, but no one will use it unless they understand how it can help them.

MEAD Education Topics

MEAD Education Group Goal: Create models and examples to teach the value of the following topicsParameter Space (different kinds of storms form in

different atmospheric environments)Uncertainty (small changes in model initial

conditions and physical process representations lead to different results)

Prediction (determining probabilities bases on a collection of simulation results)

The Education Group

Scott Lathrop, NCSA-EOTSusan Ragan, MVHS

Hurricane Model in STELLASteve Gordon, OSC

Hurricane Floyd ModelsBob Panoff and Garrett Love, Shodor

Connection ModelsDaniel Bramer, UIUC

Balloon ModelRobert Wilhelmson, NCSA

Hurricane Model in STELLA

What?Help students learn

about hurricane path and strength by giving them a simplified model to play with.

Why?Many factors play a role

in how a hurricane develops as well as where it goes.

Hurricane Model in STELLA

Hurricane ModelInvestigate the role

of sea surface temperature and location of landfall

Note the uncertainty of hurricane paths

Same run may produce different results the second time.

Operate a real model

Hurricane Inland Flood Model

What?Help students use real data

(Floyd, ‘99) to forecast flooding conditions and estimate flood damage.

Why? Inland floding is often a larger

problem than wind damage and is also more difficult to predict (storm path, time exposure, response of complex watersheds).

Hurricane Inland Flood Model

Inland Flood ModelForecast streamflow with

respect to weather and relate to gage height

Use real dataExperience with statistical

techniquesShow forecasting difficulty

for complex environmental events

Connection Models

What?Connection Models can

help introduce students to computational science topics by starting with simple hands-on experiments.

Why?It can be difficult to

introduce students to the world of computational science.

Connection Models

Foam-disc ShooterRelatable to hurricanesSee how predictability and

uncertainty vary with distance

Fun!Hook to get to more

computational topics

Balloon Model

What?Help students see the

usefulness of running multiple simulations by allowing them to release balloons into the atmosphere and view the results.

Why?The variance in flight paths of

balloons is a good allegory to the variance weather system movement.

Balloon Model

Balloon ModelPath variance is similar to

hurricane path forecastsCompare balloon paths to

‘errors’ in the model. Relate uncertainty in balloon

travel to uncertainty in forecasting weather systems.

Predict next balloon’s location.

How does this help??

Many different ways to teach students about importance of uncertainty, predictability, and parameter space.

Leads to discussion of needing to run a model more than once to help get a feel for the potential possibilities.

Take Note

MEAD websitehttp://www.ncsa.uiuc.edu/expeditions/MEAD

See AlsoWilhelmson, et. al MEAD (A Modeling

Environment for Atmospheric Discovery)IIPS Paper 6.2