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Comparison of different land-surface perturbation methods in short-range ensemble forecasts
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作者 Zhibo Gao Jiangshan Zhu +4 位作者 Yan Guo Xiaodong Yan Xiujuan Wang Huoqing Li Shuwen Li 《Atmospheric and Oceanic Science Letters》 CSCD 2021年第3期60-65,共6页
In order to compare the sensitivity of short-range ensemble forecasts to different land-surface parameters in the South China region,three perturbation experiments related to the land surface model(LSM),initial soil m... In order to compare the sensitivity of short-range ensemble forecasts to different land-surface parameters in the South China region,three perturbation experiments related to the land surface model(LSM),initial soil moisture(ISM),and land–atmosphere coupling coefficient(LCC)were designed,and another control experiment driven by the Global Ensemble Forecast System(GEFS)was also performed.All ensemble members were initiated at 0000 UTC each day,and integrated for 24 h for a total of 40 days from the period 1 April to 10 May 2019 based on the Weather Research and Forecasting model.The results showed that the perturbation experiment of the LSM(LSMPE)had the largest ensemble spread,as well as the lowest ensemble-mean root-mean-square error among the three sets of land-surface perturbed experiments,which indicated that it could represent more uncertainty and less error.The ensemble spread of the perturbation experiment of the ISM(ISMPE)was generally less than that of LSMPE but greater than that of LCCPE(the perturbation experiment of the LCC).In particular,although the perturbation of the LCC could not produce greater spread,it had an effective influence on the intensity of precipitation.However,the ensemble spread of all the land-surface perturbed experiments was smaller than that of GEFSPE(the control experiment).Therefore,in future,land-surface perturbations and atmospheric perturbations should be combined in the design of ensemble forecasting systems to make the model represent more uncertainties. 展开更多
关键词 Short-range ensemble forecast Land-surface parameter South china region
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