Uncovering the vast range of modeling and simulation tools required for accurate weather prediction. Adam Schlosser explains the considerations MIT makes when modeling extreme weather events as the climate changes.
"Weather prediction seems simple nowadays. You just have to summon Siri and ask it if you'll need an umbrella or a sunhat," writes Gemma Church for Scientific Computing World. But the computations that go on behind the scenes to produce these calculations and predictions is more sophisticated and complex than they may seem, including research at MIT.
MIT conducts a range of modelling and simulation research in weather prediction. This work primarily focuses on predicting changes in the occurrence of extreme/damaging weather events that result from the slowly evolving (over the coming decades) continential-to-global scale changes in our climate system. Adam Schlosser, a senior research scientist at the Center for Global Change Science and deputy director of the MIT Joint Program on Science and Policy of Global Change, explained: "The challenge is that models of the climate system are unable to resolve the details of many of the extreme events that we consider a threat. They typically occur at very 'local' scales (i.e. town, city, county). We bridge this gap by taking advantage of 'tell-tale' signs in a number of characteristics in the atmosphere at the larger spatial scales--and we use observations and machine-learning methods to identify what is the 'recipe' of these conditions that have to come together to cause the event."