节点文献

Evaluation of Tropical Cyclone Intensity Forecasts from Five Global Ensemble Prediction Systems During 2015-2019

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 辛佳洁余晖陈佩燕

【Author】 XIN Jia-jie;YU Hui;CHEN Pei-yan;Chinese Academy of Meteorological Sciences;Shanghai Typhoon Institute of China Meteorological Administration;Key Laboratory of Numerical Modeling for Tropical Cyclones of China Meteorological Administration;

【通讯作者】 余晖;

【机构】 Chinese Academy of Meteorological SciencesShanghai Typhoon Institute of China Meteorological AdministrationKey Laboratory of Numerical Modeling for Tropical Cyclones of China Meteorological Administration

【摘要】 This study presented an evaluation of tropical cyclone(TC) intensity forecasts from five global ensemble prediction systems(EPSs) during 2015-2019 in the western North Pacific region. Notable error features include the underestimation of the TC intensity by ensemble mean forecast and the under-dispersion of the probability forecasts.The root mean square errors(brier scores) of the ensemble mean(probability forecasts) generally decrease consecutively at long lead times during the five years, but fluctuate between certain values at short lead times.Positive forecast skill appeared in the most recent two years(2018-2019) at 120 h or later as compared with the climatology forecasts. However, there is no obvious improvement for the intensity change forecasts during the 5-year period, with abrupt intensity change remaining a big challenge. The probability forecasts show no skill for strong TCs at all the lead times. Among the five EPSs, ECMWF-EPS ranks the best for the intensity forecast, while NCEPGEFS ranks the best for the intensity change forecast, according to the evaluation of ensemble mean and dispersion.As for the other probability forecast evaluation, ECMWF-EPS ranks the best at lead times shorter than 72 h, while NCEP-GEFS ranks the best later on.

【Abstract】 This study presented an evaluation of tropical cyclone(TC) intensity forecasts from five global ensemble prediction systems(EPSs) during 2015-2019 in the western North Pacific region. Notable error features include the underestimation of the TC intensity by ensemble mean forecast and the under-dispersion of the probability forecasts.The root mean square errors(brier scores) of the ensemble mean(probability forecasts) generally decrease consecutively at long lead times during the five years, but fluctuate between certain values at short lead times.Positive forecast skill appeared in the most recent two years(2018-2019) at 120 h or later as compared with the climatology forecasts. However, there is no obvious improvement for the intensity change forecasts during the 5-year period, with abrupt intensity change remaining a big challenge. The probability forecasts show no skill for strong TCs at all the lead times. Among the five EPSs, ECMWF-EPS ranks the best for the intensity forecast, while NCEPGEFS ranks the best for the intensity change forecast, according to the evaluation of ensemble mean and dispersion.As for the other probability forecast evaluation, ECMWF-EPS ranks the best at lead times shorter than 72 h, while NCEP-GEFS ranks the best later on.

【基金】 National Key R&D Program of China(2017YFC1501604);National Natural Science Foundation of China (41875114);Shanghai Science&Technology Research Program (19dz1200101);Fundamental Research Funds of the STI/CMA (2020JB06)
  • 【文献出处】 Journal of Tropical Meteorology ,热带气象学报(英文版) , 编辑部邮箱 ,2021年03期
  • 【分类号】P444
  • 【被引频次】1
  • 【下载频次】42
节点文献中: 

本文链接的文献网络图示:

本文的引文网络