大地测量与地球动力学2025，Vol.45Issue(8)：791-795,5.DOI:10.14075/j.jgg.2024.08.401
基于RF_Adaboost神经网络的中国区域ZWD偏差改正模型
A Bias Correction Model of ZWD Based on RF_Adaboost Neural Network over China
摘要
Abstract
Previous ZWD models over China only consider the effects of elevation,latitude and meteor-ological parameters,without taking into account the impact of monsoon climate and ocean water vapor transport on ZWD estimation.To solve this problem,we take bias correction as the breakthrough point,analyze the spatial distribution of RMSE and bias of ERA5-ZWD estimation value obtained by the ERA5 data integration method and inversion method over China from 2016 to 2019.Then,the re-gional bias correction model over China based on RF_Adaboost neural network is established using the ERA5 and radiosonde data from 2016 to 2018.The results show that the bias of ERA5-ZWD estima-tion value in 2019 is significantly reduced after correction,and the RMSE is significantly reduced in the eastern coastal areas and southern regions of China.关键词
ERA5/天顶湿延迟/RF_Adaboost/偏差改正Key words
ERA5/zenith wet delay/RF_Adaboost/bias correction分类
天文与地球科学引用本文复制引用
彭祥天,张露露,林买金,徐庆兵,刘俊文,谢劭峰..基于RF_Adaboost神经网络的中国区域ZWD偏差改正模型[J].大地测量与地球动力学,2025,45(8):791-795,5.基金项目
广西自然科学基金(2023GXNSFAA026434). Guangxi Natural Science Foundation,No.2023GXNSFAA026434. （2023GXNSFAA026434）
