Atmospheric Rivers Effects on Severe Convective Storm Environments from 1979 to 2023

Abstract

This study investigates the role of Atmospheric Rivers (ARs) in modulating Severe Convective Storm Environments (SCSEs) in the Mid-South United States from 1979 to 2023, leveraging ECMWF Reanalysis v5 reanalysis and the practically perfect hindcast dataset. AR detection was performed using seven different Atmospheric River Detection Techniques (ARDTs), varying in corridor length and meridional-to-zonal orientation thresholds with a base Integrated Vapor Transport, IVT, criteria of IVT ≥ 500 kg m-1 s-1 . AR presence was compared against the region's top 30 SCSE days for six perils (tornado, significant tornado, hail, significant hail, wind, significant wind). Results indicate that broader, less restrictive ARDTs captured a higher frequency of AR Peril days particularly for tornado and wind related events, whereas hail events showed weaker association with AR presence. Linear regression analyses reveal generally weak relationships between IVT and severe weather probabilities, with significant tornadoes displaying the strongest positive IVT correlation on AR Peril days of R2= 0.56. Hail related perils exhibited negligible IVT dependence, reinforcing their thermodynamic sensitivity. These findings suggest ARs enhance environmental moisture but are not singular predictors of SCSEs. Moisture transport via ARs acts as a contributory rather than deterministic factor, emphasizing the need for multivariate approaches in severe weather forecasting and climatology