基于GWR的陕西省夏季GPM降水融合降尺度研究  

Geographically Weighted Regression(GWR)Based Study onDownscaling Summer GPM Precipitation in Shaanxi Province

作　　者：刘名[1] 刘兴忠 杨星 LIU Ming;LIU Xinzhong;YANG Xing(Atmospheric Observation Technical Support Center of Shaanxi Province,Xi’an 710014,Shaanxi;Meteorological Observation Data Center of Sichuan Province,Chengdu 610071,Sichuan;Sichuan Earthquake Administration,Chengdu 610041,Sichuan)

机构地区：[1]陕西省大气探测技术保障中心,陕西西安710014 [2]四川省气象探测数据中心,四川成都610071 [3]四川省地震局,四川成都610041

出　　处：《四川师范大学学报（自然科学版）》2024年第6期786-793,共8页Journal of Sichuan Normal University（Natural Science）

基　　金：中国地震局地震预测开放基金(XH23073D)。

摘　　要：以陕西省为研究目标,基于GWR方法,使用NDVI对GPM降水进行融合降尺度分析,结合87个地面雨量计数据,分析融合前后降水在空间上的差异和原因;同时,考虑陕西省特殊地形,将陕西分为陕北、关中和陕南三部分,利用雨量计数据分析这3个区域的降尺度效果.研究发现:1)GPM和融合降尺度数据均能反映降水在空间上的分布特征,融合降尺度数据更能呈现降水细节;2)参数计算显示,融合降尺度数据与站点数据更接近;3)当具体到某一个较小的范围时,GPM和融合降尺度数据精度仍有待提高;4)GPM和融合降尺度数据能反映陕北、关中和陕南不同的降水特征,且关中和陕南观测质量优于陕北;5)GPM和融合降尺度数据对高降水量的记录更为准确,对小降水量的记录能力有待提高.This study focuses on Shaanxi Province and uses the Geographically-Weighted Regression(GWR)method to analyze the downscaling of GPM precipitation by integrating NDVI data.By combining data from 87 ground rain gauges,the differences and reasons for the spatial distribution of precipitation before and after integration are analyzed.Additionally,taking into account Shaanxi Province’s unique terrain,the province is divided into three regions-northern Shaanxi,central Shaanxi,and southern Shaanxi,where rain gauge data are analyzed to evaluate the downscaling effect in each region.The findings of this study are as follows:1)both GPM data and integrated downscaling data can reflect the spatial distribution of precipitation,with the latter being more detailed;2)the parameter calculation shows that the integrated downscaling data is closer to the station data;3)when the analysis is focused on a smaller range,the accuracy of both GPM data and integrated downscaling data still needs improvement;4)both GPM data and integrated downscaling data can reflect the different precipitation characteristics in northern Shaanxi,central Shaanxi,and southern Shaanxi,with the observation quality in central Shaanxi and southern Shaanxi being better than that in northern Shaanxi;5)both GPM data and integrated downscaling data are more accurate in recording high precipitation levels,while the recording ability for low precipitation levels needs improvement.

关 键 词：GWR方法 GPM NDVI 融合降尺度 

分 类 号：P237[天文地球—摄影测量与遥感]