Ensemble data assimilation and prediction of typhoon and associated hazards using TEDAPS:evaluation for 2015-2018 seasons

作者：Hong LI,Jingyao LUO,Mengting XU

摘要：The initial condition accuracy is a major concern for tropical cyclone(TC)numerical forecast.The ensemble-based data assimilation techniques have shown great promise to initialize TC forecast.In addition to initial condition uncertainty,representing model errors(e.g.physics deficiencies)is another important issue in an ensemble forecasting system.To improve TC prediction from both deterministic and probabilistic standpoints,a Typhoon Ensemble Data Assimilation and Prediction System(TEDAPS)using an ensemble-based data assimilation scheme and a multi-physics approach based on Weather Research and Forecasting(WRF)model,has been developed in Shanghai Typhoon Institute and running realtime since 2015.Performance of TED APS in the prediction of track,intensity and associated disaster has been evaluated for the Western North Pacific TCs in the years of 2015-2018,and compared against the NCEP GEFS.TED APS produces markedly better intensity forecast by effectively reducing the weak biases and therefore the degree of underdispersion compared to GEFS.The errors of TED APS track forecasts are comparative with(slightly worse than)those of GEFS at longer(shorter)forecast leads.TEDAPS ensemble-mean exhibits advantage over deterministic forecast in track forecasts at long lead times,whereas this superiority is limited to typhoon or weaker TCs in intensity forecasts due to systematical underestimation.Four case-studies for three landfalling cyclones and one recurving cyclone demonstrate the capacities of TEDAPS in predicting some challenging TCs,as well as in capturing the forecast uncertainty and the potential threat from TC-associated hazards.

发文机构：Shanghai Typhoon Institute Key Laboratory of Numerical Modeling for Tropical Cyclones

关键词：ENSEMBLEdataASSIMILATIONENSEMBLEforecastingTROPICALCYCLONES

分类号： P44[天文地球—大气科学及气象学]