Application of geographically weighted regression model in the estimation of surface air temperature lapse rate

作     者：QIN Yun REN Guoyu HUANG Yunxin ZHANG Panfeng WEN Kangmin 秦云;任国玉;黄运新;张盼峰;温康民

作者机构：Department of Atmospheric ScienceSchool of Environmental StudiesChina University of GeosciencesWuhan 430074China Laboratory for Climate StudiesNational Climate CenterChina Meteorological AdministrationBeijing 100081China School of Resource and Environmental ScienceHubei UniversityWuhan 430062China 

出 版 物：《Journal of Geographical Sciences》 (地理学报（英文版）)

年 卷 期：2021年第31卷第3期

页      面：389-402页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：The National Key R&D Program,No.2018YFA0605603 National Natural Science Foundation of China,No.41575003 

主　　题：temperature lapse rate geographically weighted regression surface air temperature estimation regression residual 

摘      要：The surface air temperature lapse rate(SATLR)plays a key role in the hydrological,glacial and ecological modeling,the regional downscaling,and the reconstruction of high-resolution surface air ***,how to accurately estimate the SATLR in the regions with complex terrain and climatic condition has been a great challenge for *** geographically weighted regression(GWR)model was applied in this paper to estimate the SATLR in China’s mainland,and then the assessment and validation for the GWR model were *** spatial pattern of regression residuals which was identified by Moran’s Index indicated that the GWR model was broadly reasonable for the estimation of *** small mean absolute error(MAE)in all months indicated that the GWR model had a strong predictive ability for the surface air *** comparison with previous studies for the seasonal mean SATLR further evidenced the accuracy of the ***,the GWR method has potential application for estimating the SATLR in a large region with complex terrain and climatic condition.