Simulation of Precipitation Extremes Using a Stochastic Convective Parameterization in the NCAR CAM5 Under Different Resolutions

Abstract

AbstractWith the incorporation of the Plant‐Craig stochastic deep convection scheme into the Zhang‐McFarlane deterministic parameterization in the Community Atmospheric Model version 5 (CAM5), its impact on extreme precipitation at different resolutions (2°, 1°, and 0.5°) is investigated. CAM5 with the stochastic deep convection scheme (experiment (EXP)) simulates the precipitation extreme indices better than the standard version (control). At 2° and 1° resolutions, EXP increases high percentile (>99th) daily precipitation over the United States, Europe, and China, resulting in a better agreement with observations. However, at 0.5° resolution, due to enhanced grid‐scale precipitation with increasing resolution, EXP overestimates extreme precipitation over southeastern U.S. and eastern Europe. The reduced biases in EXP at each resolution benefit from a broader probability distribution function of convective precipitation intensity simulated. Among EXP simulations at different resolutions, if the spatial averaging area over which input quantities used in convective closure are spatially averaged in the stochastic convection scheme is comparable, the modeled convective precipitation intensity decreases with increasing resolution, when gridded to the same resolution, while the total precipitation is not sensitive to model resolution, exhibiting some degree of scale‐awareness. Sensitivity tests show that for the same resolution, increasing the size of spatial averaging area decreases convective precipitation but increases the grid‐scale precipitation.