Climate change is expected to increase the frequency of hydrological extremes, producing more droughts and heavy rainfall events globally. How warm-season precipitation extremes will change over the Central U.S. is unclear because most coarse spatial resolution global climate models inadequately simulate hydrological extremes resulting from convective precipitation. However, the higher spatial resolution from dynamical downscaling potentially enables improved projections of future changes in extreme rainfall events. In this study, we downscaled two models from the Coupled Model Intercomparison Project-Phase 5 (CMIP5) using the Weather Research and Forecasting model for one historical period (1990–1999), two future periods (2040–2049, 2090–2099) in a midrange emissions scenario (Representative Concentration Pathway (RCP) 4.5), and one period (2090–2099) in a high emissions (RCP8.5) scenario. The diurnal cycle, extremes, and averages of precipitation in historical simulations compare well with observations. While the future change in the total amount of precipitation is unclear, model simulations suggest that summer rainfall will be less frequent, but more intense when precipitation does occur. Significant intensification of the heaviest rainfall events occurs in the models, with the greatest changes in the early warm season (April). Increases in total April–July rainfall and the enhancement of extreme rainfall events in the RCP8.5 2090s are related to a stronger Great Plains Low-Level Jet (GPLLJ) during those months. Conversely, late warm-season drying over the North Central U.S. is present in nearly all future simulations, with increased drought in August–September associated with a slight weakening of the GPLLJ. Simulated trends generally increase with stronger greenhouse gas forcing.
Bibliographical noteFunding Information:
Support for this study was provided by the U.S. National Science Foundation under grant 1029711. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute. We acknowledge the World Climate Research Programme?s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy?s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The WRF model used herein can be acquired from the WRF home page at http://www2.mmm.ucar. edu/wrf/users/download/get_source. html. The parent climate model data that were downscaled can be obtained from the Earth System Grid Federation at http://pcmdi9.llnl.gov/. All other data and programs used to replicate the results in this study are available upon request from the corresponding author at email@example.com. The authors thank three anonymous reviewers for their comprehensive and thoughtful suggestions on this manuscript.