构建准实时海面风场的一种智能算法
An intelligent algorithm for constructing quasi-real-time sea surface wind field
刘晓燕 1宋晓姜 1郭安博宇 1郝赛 1彭炜1
作者信息
- 1. 国家海洋环境预报中心,北京 100081;自然资源部海洋灾害预报技术重点实验室,北京 100081
- 折叠
摘要
本文基于深度学习U-Net网络构建了CMA-GFS数值模式风场订正模型,并以此订正模型订正后的风场为背景场(CMA-GFS_Unet),以HY-2B/2C/2D以及MetOp-B 4颗卫星的散射计海面风资料为观测资料,采用插补法快速完成准实时海面风场的构建.此智能算法可实现滞后 3 h准实时生成空间分辨率为 0.25°、时间分辨率为 6 h的全球海面融合风场(Fusion_QRT).分别使用CCMP融合风场数据和中国近海浮标 10 m风矢量数据对CMA-GFS、CMA-GFS_Unet和Fusion_QRT 3组风场资料进行了评估,结果表明,CMA-GFS_Unet风场质量得到显著提升,Fusion_QRT风场风速质量得到进一步改善,但风向质量略有降低:相较于CCMP,3组风场的风速平均绝对误差(MAE)分别为 1.13 m/s、0.89 m/s和 0.84 m/s,CMA-GFS_Unet和Fusion_QRT相较于CMA-GFS分别提升了 21.3%和 25.7%;风向MAE分别为 17.5°、15.5°和 16°,分别提升了 11.3%和 8.6%;而相较于浮标,风速MAE分别为 1.50 m/s、1.36 m/s和 1.28 m/s,分别提升了 9.3%和 14.7%;风向MAE分别为 23.3°、22.7°和 24.0°,分别提升了 3.0%和-3.9%.
Abstract
In this paper,the correction model of CMA-GFS numerical model wind field is constructed based on the deep learning U-Net network,and the construction of the quasi-real-time sea surface wind field is rapidly accom-plished by interpolation method using the corrected wind field with the correction model as the background field(CMA-GFS_Unet),and using the scatterometer sea surface wind data from the four satellites,namely,HY-2B/2C/2D and MetOp-B as the observation data.This intelligent algorithm can realize the generation of global sea surface fusion wind field(Fusion_QRT)with a spatial resolution of 0.25° and a temporal resolution of 6 hours in quasi-real time with a lag of 3 hours.The CMA-GFS,CMA-GFS_Unet and Fusion_QRT wind fields are evaluated using the CCMP fusion wind field data and the 10 m wind vector data from the Chinese offshore buoys,respect-ively.The results show that the quality of the CMA-GFS_Unet wind field has been significantly improved,and the quality of the wind speed of the Fusion_QRT wind field has been further improved but the quality of the wind direc-tion has been slightly reduced.The mean absolute errors(MAEs)of wind speed are 1.13 m/s,0.89 m/s and 0.84 m/s for the three wind fields by using CCMP data as reference,and the CMA-GFS_Unet and Fusion_QRT wind fields have improved by 21.3％and 25.7％compared to the CMA-GFS,respectively;while the MAEs of wind direction are 17.5°,15.5° and 16°,and have improved by 11.3％and 8.6％,respectively.The MAEs of wind speed are 1.50 m/s,1.36 m/s and 1.28 m/s for the three wind fields by using buoy data as reference,and have improved by 9.5％and 14.7％,respectively;while the MAEs of wind direction are 23.3°,22.7° and 24.0°,and have improved by 3.0％and-3.9％,respectively.
关键词
U-Net/CCMP/CMA-GFS/HY-2B/2C/2D/MetOp-B/准实时/海面风场Key words
U-Net/CCMP/CMA-GFS/HY-2B/2C/2D/MetOp-B/quasi-real-time/sea surface wind field引用本文复制引用
基金项目
国家重点研发计划(2023YFC3107901)
自然资源部空间海洋遥感与应用研究重点实验室开放基金(202102004)
出版年
2024
NETL
NSTL
万方数据