Linking Extreme Weather Events and Extreme ENSO States

Abstract:

To what extent are the risks of extreme weather events over the contiguous US, such as heavy precipitation, heat and cold waves, conditioned by the state of tropical east Pacific SSTs? Further, do extreme magnitudes of El Niño and La Niña events exert a unique and particularly strong controlling effect on weather extremes? Here, we utilize both observations and multi-model large ensemble historical simulations to characterize the behavior of 5-day maximum precipitation distributions. We focus on relations between ENSO impacts on seasonal means and weather extremes, and explore the distinction between effects based on ENSO phase and intensity.

For the cold season (November to April), overall ENSO impacts on mean precipitation are shown to be consistent with observations. This signal includes enhanced seasonal mean precipitation over the southern part of the U.S. and central Great Plains during El Niño, and enhanced seasonal mean precipitation over the Midwest during La Nina. We further demonstrate how these signals change under the influence of the most extreme ENSO events, conditions that are difficult to verify from observations owing to small sample sizes, but are modeled via large ensemble methods. The statistics of 5-day maximum precipitation, with a focus on 20-year return levels that characterizes rare but potentially damaging events, are examined. We demonstrate substantial differences in changes in the risk of extreme 5-day precipitation and the seasonal mean precipitation signal, especially in such regions as California, and the western Great Plains including the Front Range of the Rockies from Montana to New Mexico. The plausibility of such behavior is discussed via physical considerations and by examining the structural uncertainty in such outcomes across three different climate models.