Cool-Season Evaluation of FV3-LAM-Based CONUS-Scale Forecasts with Physics Configurations of Experimental RRFS Ensembles

Abstract

Abstract To help inform physics configuration decisions and help design and optimize a multi-physics Rapid Refresh Forecasting System (RRFS) ensemble to be used operationally by the National Weather Service, five FV3-LAM-based convection allowing forecasts were run on 35 cases between October 2020 and March 2021. These forecasts used ∼3-km grid spacing on a CONUS domain with physics configurations including Thompson, NSSL, and Ferrier–Aligo microphysics schemes, Noah, RUC, and NoahMP land surface models, and MYNN-EDMF, K-EDMF, and TKE-EDMF PBL schemes. All forecasts were initialized from the 0000 UTC GFS analysis and run for 84 h. Also, a subset of 8 cases were run with 15 combinations of physics options, also including the Morrison–Gettelman microphysics and Shin–Hong PBL schemes, to help attribute behaviors to individual schemes and isolate the main contributors of forecast errors. Evaluations of both sets of forecasts find that the CONUS-wide 24-h precipitation > 1 mm is positively biased across all five forecasts. NSSL microphysics displays a low bias in QPF along the Gulf Coast. Analyses show that it produces smaller raindrops prone to evaporation. Additionally, TKE-EDMF PBL in combination with Thompson microphysics displays a positive bias in precipitation over the Great Lakes and in the ocean near Florida due to higher latent heat fluxes calculated over water. Furthermore, the K-EDMF PBL scheme produces temperature errors that result in a negative bias in snowfall over the southern Mountain West. Finally, recommendations for which physics schemes to use in future suites and the RRFS ensemble are discussed.