Abstract Submission: Abstract: Customized downscaling and bias-correction of future precipitation projections from General Circulation Models (GCMs) are needed to evaluate potential climate change impacts on regional water supply sources. This study synthesizes an exhaustive performance analysis of models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), focusing on their proficiency in simulating historical precipitation and surface air temperature. Using an enhanced Bias Correction and Stochastic Analog (BCSA) method, a sub-set of CMIP6 GCMs were subjected to further downscaling and bias correction at a 1/8-degree longitude by 1/8-degree latitude scale. The study used historical precipitation data from the Florida Peninsula spanning 1981-2010 as a reference for establishing spatial correlations across varied locations. Compared to the original BCSA method, application of the enhanced BCSA method is no longer limited to one grid box of 1-degree longitude by 1-degree latitude in downscaling to a 1/8-degree resolution. Instead, it simultaneously considers multiple 1-degree grid boxes, resulting in improved spatial correlation of climate variables among neighboring fine-resolution grid boxes. The model outputs were identified for four distinct 30-year future periods: the 2035s (2020–2049), 2060s (2045–2074), and 2085s (2070–2099). The study then explored precipitation characteristics, such as seasonal averages and variability, along with the frequency and intensity of extreme precipitation events. These findings will be instrumental in evaluating the potential impact of climate change on the water supply sources of the Tampa Bay region.
