Predictability of the Great Plains Low-Level Jet and Its Associated Precipitation

Warm-season precipitation in the United States “Corn Belt”, the Great Plains and Midwest, greatly influences agricultural production and is subject to high interannual and intraseasonal variability. Unfortunately, current seasonal and subseasonal forecasts for summer precipitation have relatively low skill. Therefore, there has been an increasing effort to understand hydroclimate variability, particularly through its primary transporter of moisture: the Great Plains low-level jet (LLJ). This study uses the Community Climate System Model, version 4 (CCSM4) July forecasts, made as part of the North American Multi-Model Ensemble (NMME), to assess skill in reproducing the climatology and variability of the monthly Great Plains LLJ and associated precipitation.

Generally, the CCSM4 forecasts can simulate the climatological jet, but has issues rooted in its limit in representing variability past two weeks. In addition, there are large-scale variability predictors identified through linear regression analysis, shifts in kernel density estimators, and case study analysis. A strengthened Caribbean LLJ, negative Pacific-North American (PNA) teleconnection, El Niño-Southern Oscillation, and a negative Atlantic Multidecadal Oscillation have a relatively strong and consistent relationship with a strengthened Great Plains LLJ. In this study, the circulation predictors (positive Caribbean LLJ and negative PNA) present the greatest “forecast of opportunity” for considering and assigning confidence in monthly forecasts.