Precipitation scale effect of the TRMM satellite in Tianshan,China  

作　　者：NING Shan ZHOU Hong-wu ZHANG Zheng-yong BAI Shi-biao LIU Lin 

机构地区：[1]College of Marine Sciences and Engineering,Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing Normal University,Nanjing 210000,China [2]College of Sciences,Shihezi University,Shihezi 832000,China

出　　处：《Journal of Mountain Science》2023年第5期1349-1368,共20页山地科学学报（英文）

基　　金：supported by the National Natural Science Foundation of China(Grant No.41941017 and 41877522);the National Key Research and Development Program of China(Grant No.2021YFE0116800);Jiangsu Province Key R&D Program(Social Development)Project of China(Grant No.BE2019776)。

摘　　要：High-resolution precipitation data is conducive to objectively describe the spatial-temporal variability of regional precipitation,and the study of downscaling techniques and spatial scale effects can provide technical and theoretical support to improve the spatial resolution and accuracy of satellite precipitation data.In this study,we used a machine learning algorithm combined with a regression algorithm RF-PLS(Random Forest-Partial Least Squares)to construct a downscaling model to obtain three types of high-resolution TRMM(Tropical Rainfall Measuring Mission)downscaled precipitation data for the years 2000-2017 at 250 m,500 m,and 1km.The scale effects with topographic and geomorphological features in the study area were analysed.Finally,we described the spatial and temporal variation of precipitation based on the optimal TRMM downscaled precipitation data.The results showed that:1)The linear relationships between the TRMM downscaled precipitation data obtained by each of the three downscaled models(PLS,RF,and RF-PLS)and the precipitation at the observation stations were improved compared to the linear relationships between the original TRMM data and the precipitation at the observation stations.The accuracy of the RF-PLS model was better than the other two models.2)Based on the RF-PLS model,the resolution of the TRMM data was increased to three different scales(250 m,500 m,and 1 km),considering the scale effects with topographic and geomorphological features.The precipitation simulation effect with a spatial resolution of 500 m was better than the other two scales.3)The annual precipitation was the highest in the areas with extremely high mountains,followed by the mediumhigh mountain,high mountain,medium mountain,medium-low mountain,plain,low mountain,and basin.

关 键 词：TRMM data Scale effect LANDFORM Tianshan Mountains 

分 类 号：P426.6[天文地球—大气科学及气象学] TP181[自动化与计算机技术—控制理论与控制工程]