热带气象学报2025，Vol.41Issue(6)：859-871,13.DOI:10.16032/j.issn.1004-4965.2025.072
基于LGU-Net的数值天气预报融合订正方法
Fusion Correction Method for Numerical Weather Forecast Based on LGU-Net
WU Kunpeng 1YUAN Jianfu 1ZHAO Yuheng 1WANG Lu1
作者信息
- 1. Chang Guang Satellite Technology Co.,Ltd.,Changchun 130000,China
- 折叠
摘要
Abstract
Numerical weather forecast is the mainstream technique in modern weather forecasting,which has been developing towards higher resolution in recent years,while forecast errors remain unavoidable.This paper proposes a numerical forecast bias correction model,termed LSTM-GAM-UNet(LGU-Net),which introduces the Long Short-Term Memory(LSTM)structure and Global Attention Mechanism(GAM)based on the CU-Net model.The model further integrates various meteorological elements,terrain features derived from"Jilin-1"satellite data,and satellite cloud images,thereby constructing a multi-element fusion correction model.This model is also specifically optimized for meteorological forecasting.An experiment was conducted in northeastern China to correct the biases of the Global Forecast System(GFS)for the 2 m temperature(T2),2 m dew point temperature(D2),10 m wind components(U10,V10),and precipitation.Different models were compared and analyzed for bias correction experiments.By comparing with the original GFS forecasts,as well as the correction results from Anomaly Numerical-correction with Observation(ANO)method and the CU-Net method,it was shown that the LGU-Net model effectively improved the bias correction performance.In addition,the addition of cloud imagery data has a significant positive impact on precipitation correction,with an 80.76%and 76.04%improvement in RMSE and MAE compared to GFS,respectively.This paper provides new technical support for high-precision meteorological element forecasts.关键词
数值天气预报/深度学习/LGU-Net/偏差订正Key words
numerical weather prediction/deep learning/LGU-Net/bias correction分类
天文与地球科学引用本文复制引用
WU Kunpeng,YUAN Jianfu,ZHAO Yuheng,WANG Lu..基于LGU-Net的数值天气预报融合订正方法[J].热带气象学报,2025,41(6):859-871,13.
