Grid Meter » Why Meteorologists Care About Grid

September 12, 2005 | Comments: (0)

Why Meteorologists Care About Grid

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When we discuss Grid computing's role in mass-scale data crunching and predictive analysis scenarios, many of us associate the discussion with the financial services industry - where Grid powers complex Monte Carlo models to help large brokerages glean real-time insights / predictions for capital market performance.

Another world of data that's even more volatile and dynamic than today's capital markets is weather prediction.

Today, 142 NEXRAD (next generation) Doppler radars are sitting around the country, scanning the atmosphere 24/7 and collecting the finest-scale, highest temporal resolution data of any observing system yet deployed. But the systems which use these data -- to both detect hazardous weather using real time decision support systems as well as predict its evolution via numerical models, operate in static configurations independent of the weather. And for the most part so do the NEXRADs, with no ability to zero in on a specific region of a thunderstorm and scan it intensely in order to verify the presence of a tornado.

Kelvin Droegemeier, Director for Analysis and Prediction of Storms at the University of Oklahoma, is part of a research team called LEAD (Linked Environments for Atmospheric Discovery) -- which is figuring out how to leverage a Grid cyberinfrastructure to bring more real-time intelligence to the data collection, analysis and numerical prediction.

"The LEAD project aims to Grid-enable a lot of the capabilities of the numerical models, so they can dynamically adapt themselves to new weather patterns," said Droegemeier. "As the data comes in from the radar, we want the models themselves to adapt to the atmosphere, reconfigure themselves to concentrate on new areas of interest, and yield more optimal results to predict specific types of weather events, like thunderstorms."

In order to get to this new level of autonomic computing to support weather prediction, the LEAD project is developing a Grid service infrastructure, built on the Globus Toolkit and GGF standards and protocols.

"The idea here, and the connection to Grid, is that we would like to be able monitor these radars in real time and have data-mining services that are looking at their output," said Dennis Gannon, Professor of Computer Science at Indiana University (one of 9 institutions participating in the program). "The data mining, if it's well done, can actually take that radar stream and pinpoint interesting things developing, automatically. And when that happens, it will trigger a particular simulation workflow on the Grid. That workflow will do a number of what we call 'data assimilation tasks' and assimilate all the observable weather data that they've got in a given region and prepare it for a set of simulations. So we then might use TeraGrid or a large grid to launch maybe a 100 different simulation scenarios for a single county in Oklahoma."

Posted by Greg Nawrocki on September 12, 2005 07:59 AM

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