Impacts of New Implementing Strategies for Surface and Model Physics Perturbations in TREPS on Forecasts of Landfalling Tropical Cyclones  

作　　者：Xubin ZHANG 

机构地区：[1]Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction,Institute of Tropical and Marine Meteorology,CMA,Guangzhou 510640,China

出　　处：《Advances in Atmospheric Sciences》2022年第11期1833-1858,共26页大气科学进展（英文版）

基　　金：sponsored by the National Key R&D Program of China through Grant No. 2017YFC1501603;the National Natural Science Foundation of China through Grant No. 41975136;the Guangdong Basic and Applied Basic Research Foundation through Grant No. 2019A1515011118。

摘　　要：To improve the ensemble prediction system of the tropical regional atmosphere model for the South China Sea(TREPS) in predicting landfalling tropical cyclones(TCs), the impacts of three new implementing strategies for surface and model physics perturbations in TREPS were evaluated for 19 TCs making landfall in China during 2014–16. For sea surface temperature(SST) perturbations, spatially uncorrelated random perturbations were replaced with spatially correlated ones. The multiplier f, which is used to form perturbed tendency in the Stochastically Perturbed Parameterization Tendency(SPPT) scheme, was inflated in regions with evident convective activity(f-inflated SPPT). Lastly, the Stochastically Perturbed Parameterization(SPP) scheme with 14 perturbed parameters selected from the planetary boundary layer, surface layer, microphysics, and cumulus convection parameterizations was added. Overall, all these methods improved forecasts more significantly for non-intensifying than intensifying TCs. Compared with f-inflated SPPT,the spatially correlated SST perturbations generally showed comparable performance but were more(less) skillful for intensifying(non-intensifying) TCs. The advantages of the spatially correlated SST perturbations and f-inflated SPPT were mainly present in the deterministic guidance for both TC track and wind and in the probabilistic guidance for reliability of wind. For intensifying TCs, adding SPP led to mixed impacts with significant improvements in probability-matched mean of modest winds and in probabilistic forecasts of rainfall;while for non-intensifying TCs, adding SPP frequently led to positive impacts on the deterministic guidance for track, intensity, strong winds, and moderate rainfall and on the probabilistic guidance for wind and discrimination of rainfall.

关 键 词：ensemble forecasting MESOSCALE TC forecasting surface perturbations perturbations for model physics 

分 类 号：P457.8[天文地球—大气科学及气象学]