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基于加权损失函数的我国近海海面风速预报

渠鸿宇 胡海川 钱传海 黄彬

热带气象学报2024,Vol.40Issue(6):931-942,12.
热带气象学报2024,Vol.40Issue(6):931-942,12.DOI:10.16032/j.issn.1004-4965.2024.081

基于加权损失函数的我国近海海面风速预报

Prediction of Sea Surface Wind Speed in China's Offshore Areas Based on Weighted Loss Function

渠鸿宇 1胡海川 1钱传海 2黄彬1

作者信息

  • 1. 国家气象中心,北京 100081
  • 2. 气象与发展规划院,北京 100081
  • 折叠

摘要

Abstract

Sea surface wind speed forecasts based on numerical models often exhibit deviations.Although statistical models based on numerical models can reduce the deviation to a certain extent,their performance in predicting strong winds remains suboptimal due to the scarcity of strong wind samples.This study systematically evaluated the 24-hour sea surface wind speed forecasts from the European Centre for Medium-Range Weather Forecasts(ECMWF)and employed the XGBoost model to develop a correction model tailored for China's offshore areas.This model not only demonstrated good overall forecasting accuracy,but also significantly enhanced the prediction of strong winds through the use of a weighted loss function during training.The model was independently tested using observational data from 14 buoys in China's offshore waters from January 2022 to January 2023.The average error and root mean squared error of the model were 0.11 m s-1 and 1.75 m s-1,respectively.The forecast accuracy of the model for wind speeds classified as levels 7 to 9 was significantly improved compared to that of the ECMWF,with root mean squared errors reduced by 15%,25%,and 24%,respectively.Furthermore,when applied to grid points not included in the training,the model continued to provide more accurate forecasts than the ECMWF.This model is easy to operate and use and can provide reference information for sea surface wind speed forecasting,especially strong wind forecasting,in China's coastal waters.

关键词

海面风速/预报订正/加权损失函数

Key words

sea surface wind speed/forecast correction/weighted loss function

分类

天文与地球科学

引用本文复制引用

渠鸿宇,胡海川,钱传海,黄彬..基于加权损失函数的我国近海海面风速预报[J].热带气象学报,2024,40(6):931-942,12.

基金项目

国家重点研发计划(2022YFC3004204)资助 (2022YFC3004204)

热带气象学报

OA北大核心CSTPCD

1004-4965

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