四川夏季降水量空间插值方法的比较  

Comparative study on spatial interpolation methods of summer precipitation in Sichuan

作　　者：李想 李国平[1] LI Xiang;LI Guoping(School of Atmospheric Science,Chengdu University of Information Technology,Chengdu 610225,China;Collaborative Innovation Center for Meteorological Disaster Forecasting,Early Warning and Assessment,Co-constructed by the Ministry of Finance,Nangjing 210044,China)

机构地区：[1]成都信息工程大学大气科学学院,四川成都610225 [2]气象灾害预报预警与评估省部共建协同创新中心,江苏南京210044

出　　处：《干旱气象》2022年第5期897-907,共11页Journal of Arid Meteorology

基　　金：国家自然科学基金(42175002,42075013,91937301);国家重点研发计划项目(2018YFC1507200)共同资助。

摘　　要：为了研究四川盆地尤其是盆地周围边缘山地夏季降水的主要地理影响因子及降水量的最佳插值方法,基于四川省157个自动气象站点近10 a(2010—2019)夏季降水数据,采用聚类分析进行分区,通过相关性分析和多元回归分析筛选出各区域降水量的地理影响因子。使用协同克里金插值方法的同时,采用传统插值方法进行对比并对插值结果进行交叉检验,结果表明:(1)可用来表征四川夏季降水量的地理影响因子主要有经度、纬度、海拔、坡度和均一化植被指数(normalized difference vegetation index,NDVI);(2)由于四川地形的多样性和复杂性,分区之后的降水量插值效果优于分区前的插值效果;(3)在所选区域降水影响因子数目适中时,采用协同克里金插值方法效果更佳;而在所选区域降水表征因子数目单一或过多时,采用径向基函数插值方法或经验贝叶斯克里金插值方法的效果更佳。In order to study the main geographical influencing factors of summer precipitation and the best interpolation method of precipitation in the complex Sichuan Basin,especially the mountainous area around the basin,Sichuan was divided into four regions by using cluster analysis based on 10 years(2010–2019) summer precipitation data of 157 automatic meteorological stations in Sichuan Province.The correlation analysis and the multiple regression analysis methods were used to screen out the geographical influencing factors of precipitation in each region.In addition to using the cooperative Kriging interpolation method,the traditional interpolation method is used to compare.The interpolation results are tested by cross-validation method.The results are as follows:(1) The geographic influencing factors that can be used to characterize the summer precipitation in Sichuan were mainly longitude,latitude,altitude,slope and normalized difference vegetation index.(2) Due to the diversity and complexity of the topography in Sichuan,the effect of precipitation interpolation after the division was better than that before the division.(3) When the number of precipitation influencing factors in the selected area was moderate,the coKriging interpolation method was better,and when the number of precipitation characterization factors in the selected area was single or too many,the radial Basis function interpolation method or empirical Bayesian Kriging interpolation method were more effective.

关 键 词：插值方法 山区 四川 夏季降水 影响因子 

分 类 号：P413[天文地球—大气科学及气象学]