Dan Cooley and a team of collaborators were recently awarded a joint National Science Foundation (NSF) and Department of Energy (DOE) funded grant investigating extreme weather changes as a result of natural and anthropongenic forcings. The team is comprised of statisticians, climate scientists, and social scientists based at CSU, UC-Berkeley, Lawrence Berkeley National Labs, and UNC Chapel Hill. Cooley serves as PI for the 5-year grant, which totals $4.9M.
At this project's core is a goal to address three areas which are critical to understanding extreme events, but whose methods are not yet developed enough to answer impact-relevant questions. First, the investigators will advance and develop multivariate statistical methods which can describe and model extreme events which arise from a combination of meteorological factors which may or may not individually be extreme. Second, the investigators will advance spatial downscaling methods to be applicable to studying extreme phenomena which occur at spatial scales not resolved by climate models. Third, the investigators will put the study of detection of changes in extremes and attribution of extreme events on a solid statistical foundation, and to apply the spatial and multivariate techniques to this area. The participants will collaborate with social scientists in incorporating the improved methodology developed into models that analyze the impact of extreme weather events on agricultural production and the forestry sector for specific regions of the US. They will also develop risk assessment measures that take into account possible increases in the frequency of extreme weather events.