CWRF performance at downscaling China climate characteristics

XZ Liang, C Sun, X Zheng, Y Dai, M Xu, HI Choi… - Climate Dynamics, 2019 - Springer
XZ Liang, C Sun, X Zheng, Y Dai, M Xu, HI Choi, T Ling, F Qiao, X Kong, X Bi, L Song…
Climate Dynamics, 2019Springer
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 …
Abstract
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.
Springer
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