Summer rainfall variability over the Southeastern United States in the 21st century as assessed by the CMIP5 Models

Journal Article (Academic article)

The variability of the Southeast (SE) United States (U.S.) summer precipitation in current and future climate is analyzed using phase 5 of the Coupled Model Intercomparison Project (CMIP5) models. By comparing the simulated historical precipitation variability with the observations, we categorize the CMIP5 models into two groups: Group 1 (G1) models that simulate the summer precipitation variability reasonably well, and Group 2 (G2) models that need further improvements. Our analysis suggests that the relatively higher skill of G1 models is attributed to their ability to represent the dynamical linkage between SE U.S. summer precipitation variability and North Atlantic Subtropical High (NASH) western ridge position. In contrast, the inability of G2 models to represent such linkage leads to biases in their simulations of the SE U.S. summer precipitation variability. According to our analysis, the ensemble projection of CMIP5 models suggests that under the Representative Concentration Pathway (RCP) 4.5 scenario, the SE U.S. summer precipitation variability will intensify and this intensification is more pronounced among the G1 models. Our analysis further suggests that this intensification is most likely because of the projected pattern shift of the NASH western ridge in a warming climate. Under the RCP4.5 scenario, the NASH western ridge will extend further westward leading to more frequent occurrences of the Northwestward and Southwestward ridge patterns that are respectively related to dry and wet summers in the SE U.S. Consequently, more frequent occurrence of summer precipitation extremes would be expected over the SE U.S. in the future.

Full Text

Duke Authors

Cited Authors

  • Li, L; Li, W; Deng, Y

Published Date

  • 2013

Published In

Volume / Issue

  • 118 /

Start / End Page

  • 340 - 354

International Standard Serial Number (ISSN)

  • 2169-897X

Digital Object Identifier (DOI)

  • 10.1002/jgrd.50136