Understanding the influence of ENSO on the Great Plains low-level jet in CMIP5 models

Abstract

The Great Plains Low-Level Jet (GPLLJ) is an important driver of precipitation and severe weather outbreaks over the US Great Plains and undergoes large interannual variability. Therefore, to reliably make predictions and projections of Great Plains precipitation, it is essential for the observed influence of ENSO on the GPLLJ to be understood and simulated accurately by global climate models. This study uses four reanalyzes and an ensemble of 42 historical simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to investigate the accuracy of the simulated ENSO–GPLLJ teleconnection. From observations, winter ENSO has a significant negative correlation with the GPLLJ in the following spring and a significant positive correlation with the GPLLJ in the following summer. Here, it is shown that the influence of ENSO is on the frequency, not intensity, of GPLLJ events in the spring, while both the frequency and intensity of GPLLJ events are affected in the summer. However, although the majority of CMIP5 historical simulations exhibit the observed significant negative ENSO–GPLLJ correlations in the spring, nearly all of them fail to simulate the significant positive correlation in the summer. The ability of the models to simulate the ENSO–GPLLJ relationship is attributed to the strength of simulated ENSO events and the associated effects on geopotential heights and atmospheric circulation. These results have implications for the predictability of weather and climate in the Great Plains and suggest that the variability of the GPLLJ will not be reliably captured in future climate simulations if the magnitude of ENSO events and their impacts are not well represented.