Understanding Simulated Extreme Precipitation Events in Madison, Wisconsin, and the Role of Moisture Flux Convergence during the Late Twentieth and Twenty-First Centuries

Abstract

nderstanding extreme precipitation events in the current and future climate system is an important aspect of climate change for adaptation and mitigation purposes. The current study investigates extreme precipitation events over Madison, Wisconsin, during the late twentieth and late twenty-first centuries using 18 coupled ocean?atmosphere general circulation models that participated in the Coupled Model Intercomparison Project (CMIP3). An increase of ~10% is found in the multimodel average of annual precipitation received in Madison by the end of the twenty-first century, with the largest increases projected to occur during winter [December?February (DJF)] and spring [March?May (MAM)]. It is also found that the observed seasonal cycle of precipitation in Madison is not accurately captured by the models. The multimodel average shows a strong seasonal peak in May, whereas observations peak during midsummer. Model simulations also do not accurately capture the annual cycle of extreme precipitation events in Madison, which also peak in summer. Instead, the timing of model-simulated extreme events exhibits a bimodal distribution that peaks during spring and fall. However, spatial composites of average daily precipitation simulated by GCMs during Madison?s wettest 1% of precipitation events during the twentieth century strongly resemble the spatial pattern produced in observations. The role of specific humidity and vertically integrated moisture flux convergence (MFC) during extreme precipitation events in Madison is investigated in twentieth- and twenty-first-century simulations. Spatial composites of MFC during the wettest 1% of days during the twentieth-century simulations agree well with results from the North American Regional Reanalysis dataset (NARR), suggesting that synoptic-scale dynamics are vital to extreme precipitation events.