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Climatology of Severe Local Storm Environments and Synoptic-Scale Features over North America in ERA5 Reanalysis and CAM6 Simulation

Authors :
Daniel T. Dawson
Funing Li
Daniel R. Chavas
Kevin A. Reed
Source :
Journal of Climate. 33:8339-8365
Publication Year :
2020
Publisher :
American Meteorological Society, 2020.

Abstract

Severe local storm (SLS) activity is known to occur within specific thermodynamic and kinematic environments. These environments are commonly associated with key synoptic-scale features--including southerly Great Plains low-level jets, drylines, elevated mixed layers, and extratropical cyclones--that link the large-scale climate to SLS environments. This work analyzes spatiotemporal distributions of both the environmental parameters and synoptic-scale features in ERA5 reanalysis and in Community Atmosphere Model version 6 (CAM6) during 1980--2014 over North America. Compared to radiosondes, ERA5 successfully reproduces SLS environments, with strong spatiotemporal correlations and low biases, especially over the Great Plains. Both ERA5 and CAM6 reproduce the climatology of SLS environments over the central United States as well as its strong seasonal and diurnal cycles. ERA5 and CAM6 also reproduce the climatological occurrence of the synoptic-scale features, with the distribution pattern similar to that of SLS environments. Compared to ERA5, CAM6 exhibits a high bias in Convective Available Potential Energy over the eastern United States primarily due to a high bias in surface moisture, and to a lesser extent, storm-relative helicity due to enhanced low-level winds. Composite analysis indicates consistent synoptic anomaly patterns favorable for significant SLS environments over much of the eastern half of the United States in both ERA5 and CAM6, though the pattern differs for the southeastern United States. Overall, results indicate that both ERA5 and CAM6 are capable of reproducing SLS environments as well as the synoptic-scale features and transient events that generate them.<br />25 pages, 15 figures

Details

ISSN :
15200442 and 08948755
Volume :
33
Database :
OpenAIRE
Journal :
Journal of Climate
Accession number :
edsair.doi.dedup.....16a1c2e06dd2a657987654d3a11448b5