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The performance of the regional Climate-Weather Research and Forecasting model (CWRF) for downscaling China climate characteristics is evaluated using a 1980-2015 simulation at 30 km grid spacing driven by the ECMWF Interim reanalysis (ERI). It is shown that CWRF outperforms the popular Regional Climate Modeling system (RegCM4.6) in key features including monsoon rain bands, diurnal temperature ranges, surface winds, interannual precipitation and temperature anomalies, humidity couplings, and 95th percentile daily precipitation. Even compared with ERI, which assimilates surface observations, CWRF better represents the geographic distributions of seasonal mean climate and extreme precipitation. These results indicate that CWRF may significantly enhance China climate modeling capabilities. [ABSTRACT FROM AUTHOR]

This study examines the effects of five cumulus closure assumptions on simulations of summer precipitation in the continental U.S. by utilizing an ensemble cumulus parameterization (ECP) that incorporates multiple alternate closure schemes into a single cloud model formulation. Results demonstrate that closure algorithms significantly affect the summer mean, daily frequency and intensity, and diurnal variation of precipitation, with strong regional dependence. Overall, the vertical velocity (W) closure produces the smallest summer mean biases, while the moisture convergence (MC) closure most realistically reproduces daily variability. Both closures have advantages over others in simulating U.S. daily rainfall frequency distribution, though both slightly overestimate intense rain events. The MC closure is superior at capturing summer rainfall amount, daily variability, and heavy rainfall frequency over the Central U.S., but systematically produces wet biases over the North American Monsoon (NAM) region and Southeast U.S., which can be reduced by using the W closure. The instability tendency (TD) and the total instability adjustment (KF) closures are better at capturing observed diurnal signals over the Central U.S. and the NAM, respectively. The results reasonably explain the systematic behaviors of several major cumulus parameterizations. A preliminary experiment combining two optimal closures (averaged moisture convergence and vertical velocity) in the ECP scheme significantly reduced the wet (dry) biases over the Southeast U.S. in the summer of 1993 (2003), and greatly improved daily rainfall correlations over the NAM. Further improved model simulation skills may be achieved in the future if optimal closures and their appropriate weights can be derived at different time scales based on specific climate regimes. [ABSTRACT FROM AUTHOR]

This study comprehensively evaluates the effects of twelve cumulus parameterization (CUP) schemes on simulations of 1993 and 2008 Central US summer floods using the regional climate-weather research and forecasting model. The CUP schemes have distinct skills in predicting the summer mean pattern, daily rainfall frequency and precipitation diurnal cycle. Most CUP schemes largely underestimate the magnitude of Central US floods, but three schemes including the ensemble cumulus parameterization (ECP), the Grell-3 ensemble cumulus parameterization (G3) and Zhang-McFarlane-Liang cumulus parameterization (ZML) show clear advantages over others in reproducing both floods location and amount. In particular, the ECP scheme with the moisture convergence closure over land and cloud-base vertical velocity closure over oceans not only reduces the wet biases in the G3 and ZML schemes along the US coastal oceans, but also accurately reproduces the Central US daily precipitation variation and frequency distribution. The Grell (GR) scheme shows superiority in reproducing the Central US nocturnal rainfall maxima, but others generally fail. This advantage of GR scheme is primarily due to its closure assumption in which the convection is determined by the tendency of large-scale instability. Future study will attempt to incorporate the large-scale tendency assumption as a trigger function in the ECP scheme to improve its prediction of Central US rainfall diurnal cycle. [ABSTRACT FROM AUTHOR]