The Climate Change group addresses real problems related to climate and environment by using mathematical and statistical tools. Current research interest includes studying the impacts of climate change at local spatial scales and at fine time resolution and also extreme events. This entails exploring the various methodologies of downscaling meteorological variables from global climate models (GCM) or regional climate models (RCM). Among the methods used are regression-based statistical downscaling methods (SDSM), canonical correlation analysis (CCA), artificial neural networks.

Research Alliance: Resource Sustainability.

Focus area: Statistical modeling of the climate system with a particular emphasis on extreme events and their future evolution and interdisciplinary climate impacts research that links to the physical, health,  environmental, biological, economic, and social sciences.