Thursday, July 21, 2016

Peter Webster, The Meteorologist Who Saves Lives

How does Big Data enable you to do that?
To do a one- to two-day forecast for a country like India, you just need to develop a forecasting model that covers India and its immediate neighbors. But as the forecast horizon increases, the influence of weather events thousands of miles away also become important. So for a 10-to 15-day forecast, we have to use a global model. We use the rainfall forecasts from the European Center for Medium Range Weather Forecast model in the United Kingdom. The model has grid points every 25 km over the globe and 130 levels in the vertical. Each day, the model is run twice and integrated out to 15 and 30 days. At these two points, the model is run 51 times with slightly different initial data to simulate the uncertainty in what we know about the state of the atmosphere and the physics of how the atmosphere works. Terabytes of data are generated each day and streamed to Georgia Tech where we stream it to obtain a regional forecast over Bangladesh, where we eventually stream the data via cellphone.

Do you have trouble convincing people who might not understand these complex models?

These people are living on the edge. They realize how vulnerable they are, so they’re accepting these forecasts.

It also helps that you’ve been correct?

In our first year there, 2007-08, we forecast all three major floods. There were no false positives. More importantly, there were no false negatives—a flood never came when we didn’t predict one.


You can’t talk about Big Data without talking about privacy, can you?

There are issues with privacy when it comes to meteorological data. Some nations sell their data. Some nations believe that data belongs to them. We wanted to give India a flood forecasting scheme for the entire Ganges, and all we needed was their river data at a few points, and they wouldn’t give it to us. They wouldn’t give us sea-level data. That makes it very difficult.

Yet you’ve been able to help India, right? 

Ahmedebad, a city of 4 million people, is impacted adversely by extreme heat waves that occur in the months before the monsoon rains. They wanted to be able to forecast these waves in advance so that they could allocate their scant resources optimally and develop a heat action plan.

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