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Polar WRF V4.1.1.simulation and evaluation for the Antarctic and Southern Ocean 被引量:1

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摘要 A recent version of the Polar Weather Research and Forecasting model(Polar WRF)has been upgraded to the version 4.X era with an improved NoahMP Land Surface Model(LSM).To assess the model performance over the Antarctic and Southern Ocean,downscaling simulations with different LSM(NoahMP,Noah),WRF versions(Polar WRF 4.1.1 and earlier version 4.0.3,WRF 4.1.1),and driving data(ERA-Interim,ERA5)are examined with two simulation modes:the short-term that consists of a series of 48 h segments initialized daily at 0000 UTC with the first 24 h selected for model spin-up,whereas the long-term component used to evaluate long-term prediction consists of a series of 38-41 day segments initialized using the first 10 days for spin-up of the hydrological cycle and planetary boundary layer structure.Simulations using short-term mode driven by ERA-Interim with NoahMP and Noah are selected for benchmark experiments.The results show that Polar WRF 4.1.1 has good skills over the Antarctic and Southern Ocean and better performance than earlier simulations.The reduced downward shortwave radiation bias released with WRF 4.1.1 performed well with PWRF411.Although NoahMP and Noah led to very similar conclusions,NoahMP is slightly better than Noah,particularly for the 2 m temperature and surface radiation because the minimum albedo is set at 0.8 over the ice sheet.Moreover,a suitable nudging setting plays an important role in long-term forecasts,such as reducing the surface temperature diurnal cycle near the coast.The characteristics investigated in this study provide a benchmark to improve the model and guidance for further application of Polar WRF in the Antarctic.
出处 《Frontiers of Earth Science》 SCIE CSCD 2022年第4期1005-1024,共20页 地球科学前沿(英文版)
基金 supported by the Chinese Academy of Sciences(No.XDA20060501) the National Natural Science Foundation of China(Grant No.91937000)to the first two authors The other co-authors were supported by the Office of Naval Research(ONR)(No.N00014-18-1-2361).
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