In coming decades, changing climate and an ever-growing population will put unprecedented strains on our nation’s natural resources, agriculture, and environment. Predicting and preparing for shifting temperatures, changing growing seasons and rain patterns, extreme weather events, increased drought, flooding, wildfires, and changes in plant and animal populations are among the most important roles of scientific computing.
The Center for Robust Decision Making on Climate and Energy Policy (RDCEP) at the Chicago Computation Institute integrates climate, agricultural, and economic models to help inform policy decisions.
For example, researchers there recently modeled the effects that climate change – such as hotter, drier summers experienced in 2012 – will have on U.S. corn crops.
The iPlant project at the University of Texas at Austin brings researches together with vast databases of plant genomic information and tools that may help develop and adapt agricultural crops, among other uses.
At the University of California, Berkeley, researches are using robotic floaters to transmit information about the Sacramento River delta into real time models that may someday help resource planners balance increasing demands and competing pressures on this waterway.
Louisiana State University’s Center for Computation and Technology and UT Austin researchers are modeling the destructive water rises (storm surges) caused by tropical Atlantic tempests and passing that information on to emergency officials who rely on the information to direct evacuations and other responses.
And, of course, climate models are growing more sophisticated and more important in understanding and predicting the changes underlying all this work.
Climate Models are becoming more detailed and more accurate.
The simulation was created to test a new version of climate modeling software (the National Center for Atmospheric Research’s Community Atmospheric Model). Using historical weather data, Lawrence Berkeley National Laboratory researchers Michael Wehner and Prahbat found the model spontaneously spawned tropical cyclones in line with the actual storms from that period.