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CONDITIONAL NONLINEAR OPTIMAL PERTURBATIONS: APPLICATION IN TROPICAL CYCLONE FORECASTS
作者姓名:田洪军  李泽椿  王栋梁  王 斌
摘    要:Considering the feature of tropical cyclones (TCs) that strong positive vorticity exists in the lower layers of troposphere, this study proposed to use vorticity at 850 hPa as cost function to find the conditional nonlinear optimal perturbation (CNOP), which was largely different from those previous studies using total energy of perturbed forecast variables. The CNOP was obtained by an ensemble-based approach. All of the sensitive areas determined by CNOP with vorticity at 850 hPa as cost function for the three cases were located over the TC core region and its vicinity. The impact of the CNOP-based adaptive observations on TC forecasts was evaluated with three cases via observational system simulation experiments (OSSEs). Results showed obvious improvements in TC intensity or track forecasts due to the CNOP-based adaptive observations, which were related to the main error source of the verification area, i.e., intensity error or location error.

关 键 词:Conditional  Nonlinear  Optimal  Perturbations    tropical  cyclone    intensity    track
修稿时间:2019/8/15 0:00:00

CONDITIONAL NONLINEAR OPTIMAL PERTURBATIONS: APPLICATION IN TROPICAL CYCLONE FORECASTS
TIAN Hong-jun,LI Ze-chun,WANG Dong-liang and WANG Bin.CONDITIONAL NONLINEAR OPTIMAL PERTURBATIONS: APPLICATION IN TROPICAL CYCLONE FORECASTS[J].Journal of Tropical Meteorology,2019,25(4):421-436.
Authors:TIAN Hong-jun  LI Ze-chun  WANG Dong-liang and WANG Bin
Institution:;1.Nanjing University of Information Science and Technology;2.Shanghai Central Meteorological Observatory;3.National Meteorological Centre;4.Shanghai Typhoon Institute
Abstract:Considering the feature of tropical cyclones(TCs) that strong positive vorticity exists in the lower layers of troposphere, this study proposed to use vorticity at 850 hPa as cost function to find the conditional nonlinear optimal perturbation(CNOP), which was largely different from previous studies using total energy of perturbed forecast variables. The CNOP was obtained by an ensemble-based approach. All of the sensitive areas determined by CNOP with vorticity at 850 hPa as cost function for the three cases were located over the TC core region and its vicinity. The impact of the CNOP-based adaptive observations on TC forecasts was evaluated with three cases via observational system simulation experiments(OSSEs). Results showed obvious improvements in TC intensity or track forecasts due to the CNOP-based adaptive observations, which were related to the main error source of the verification area, i.e.,intensity error or location error.
Keywords:Conditional Nonlinear Optimal Perturbations  tropical cyclone  intensity  track
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