A Better Way to ID Extreme Weather Events in Climate Models

You'd think that spotting a category 5 hurricane would never be difficult. But when the hurricane is in a global climate model that spans several decades, it becomes a fleeting wisp among mountains of data. That's a problem. As scientists develop ever-more sophisticated computer models to predict the effects of climate change, one of the things they'll look for are changes in the frequency of extreme weather events such as hurricanes and heavy precipitation. The more data generated by models, however, the more difficult it is to quantify these rare but potent events. What's needed is an automated way to quickly comb through a climate simulation's huge dataset and tally the weather events that spell big trouble. A team of researchers that includes scientists from Lawrence Berkeley National Laboratory (Berkeley Lab) are developing techniques to do just that.