Using dynamical downscaling to examine mechanisms contributing to the intensification of Central U.S. heavy rainfall events

Keith J. Harding, Peter K. Snyder

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The frequency and intensity of heavy rainfall events have increased in the Central U.S. over the last several decades, and model projections from dynamical downscaling suggest a continuation with climate change. In this study, we examine how climate changemight affectmechanisms related to the development of heavy rainfall events that occur on the scale of mesoscale convective systems over the CentralU.S. Toaccomplish these goals, we incorporate dynamical downscaled simulations of two Coupled Model Intercomparison Project phase 5 models in the Weather Research and Forecasting model that accurately simulate heavy rainfall events. For each model, a set of heavy rainfall events that match the frequency, timing, and intensity of observed events are objectively identified in historical and future simulations. We then examine multimodel composites of select atmospheric fields during these events in simulations of historical and future scenarios, enabling an identification of possible physical mechanisms that could contribute to the intensification of heavy rainfall events with climate change. Simulations show that additional moisture is transported into convective updrafts during heavy rain events in future simulations, driving stronger evaporative cooling from the entrainment of drier midtropospheric air. This results in the formation of a stronger low-level cold pool, which enhances moisture convergence above the cold pool and increases rainfall rates during future heavy precipitation events. In addition, a warmer profile in future simulationsmight allow for heavier rainfall rates as a deeper atmospheric column can support additional collision-coalescence of liquid hydrometeors.

Original languageEnglish (US)
Pages (from-to)2754-2772
Number of pages19
JournalJournal of Geophysical Research
Volume120
Issue number7
DOIs
StatePublished - 2015

Bibliographical note

Funding 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 Modelling, 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 pksny-der@umn.edu. The authors thank Tom Hultquist for reviewing an earlier version of the manuscript.

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