Drought-predicting computer models are not made just so that scientists can say “I told you so” when your favorite lake runs low. From agriculture, to infrastructure, to tourism — major sectors of the economy need a heads-up on what weather conditions are coming down the pipe.
These vitally needed models run on input data, and two Texas A&M University experts are working to improve the precipitation data fed into models, which will in turn help federal agencies such as the National Oceanographic and Atmospheric Administration’s (NOAA) Research Line Office and National Weather Service (NWS) better predict and prepare for droughts.
Brent McRoberts, research assistant professor in the Texas A&M Department of Geography, has received a grant from NOAA’s Modeling, Analysis, Predictions, and Projections (MAPP) program, in partnership with the National Integrated Drought Information System (NIDIS).
“Land surface models are critical in our ability to assess future drought conditions so that we can properly allocate water resources,” McRoberts said. “Precipitation is one of the most important variables driving land surface models, so it is essential to have confidence that the precipitation is accurately depicted.”
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