WRF Forecasts of Great Plains Nocturnal Low-Level Jet-Driven MCSs. Part I: Correlation between Low-Level Jet Forecast Accuracy and MCS Precipitation Forecast Skill

Abstract

AbstractThe Great Plains low-level jet (LLJ) fosters an environment that supports nocturnal mesoscale convective systems (MCSs) across the central United States during the summer months. The current study examines if LLJ forecast accuracy correlates with MCS precipitation forecast skill in 4-km WRF runs. LLJs were classified based on their synoptic background as either strongly forced, cyclonic flow (type C) or weakly forced, anticyclonic flow inertial oscillation driven (type A). Large-scale variables associated with the LLJ were examined. For all LLJs inclusive and the subset of type C LLJs alone, the forecast accuracy of the LLJ total wind direction significantly correlated with MCS precipitation forecast skill. For type C LLJ cases, where predictive skill for MCSs was higher overall, the LLJ ageostrophic wind direction forecast accuracy significantly correlated with MCS precipitation forecast skill during the LLJ and MCS developmental stages, with potential temperature and moisture forecast accuracy correlating well with the forecast skill of mature MCSs. Statistically significant correlations were mainly absent between MCS precipitation forecast skill and LLJ forecast accuracy for type A cases. It is thus suggested that either non-LLJ factors like most unstable convective available potential energy (MUCAPE) or most unstable convective inhibition (MUCIN) fields within close proximity of MCSs, or factors on smaller scales than analyzed (such as gravity waves or bores), may have the greatest potential influence on MCS precipitation forecast skill in LLJ-induced MCS cases in an ambient weakly forced synoptic regime.