DOI: 10.57760/sciencedb.cryosphere.00002
title: A dataset of multi-source precipitation fusion in the Xinjiang Tianshan Mountains from 2000 to 2022
title: 2000–2022年新疆天山地区多源降水融合数据集

description: The Tianshan Mountains, known as the “water tower of Central Asia”, are a typical alpine region in China and hold significant importance for both Xinjiang and the broader Central Asian region. With the advancement of remote sensing technology, satellite inversion has become an important method for estimating precipitation in mountainous areas. However, due to the complex terrain and uneven distribution in mountainous areas, there are limitations in the accuracy of precipitation data derived from satellite inversion. To address this issue, this study developed a dataset of multi-source precipitation fusion in the Tianshan Mountains, using GSMaP satellite precipitation data as the initial field and combining with the live precipitation data from 1,065 stations in the same region. And we developed a method for integrating satellite and ground precipitation products based on optimal interpolation. The resulting dataset is a product of daily precipitation in the Tianshan Mountains from 2000 to 2022. During the development of this dataset, strict quality control was implemented on the observed data, and quality assessment was conducted on the daily fused precipitation data. The correlation coefficient increased from 0.44 to 0.53 (passing the significant test at 0.01 level), while the absolute average error decreased from 6.3 mm d-1 to 5.7 mm d-1. This dataset is expected to provide solid data and scientific support for water resource management and efficient utilization in complex terrain areas.
description: The Tianshan Mountains, known as the “water tower of Central Asia”, are a typical alpine region in China and hold significant importance for both Xinjiang and the broader Central Asian region. With the advancement of remote sensing technology, satellite inversion has become an important method for estimating precipitation in mountainous areas. However, due to the complex terrain and uneven distribution in mountainous areas, there are limitations in the accuracy of precipitation data derived from satellite inversion. To address this issue, this study developed a dataset of multi-source precipitation fusion in the Tianshan Mountains, using GSMaP satellite precipitation data as the initial field and combining with the live precipitation data from 1,065 stations in the same region. And we developed a method for integrating satellite and ground precipitation products based on optimal interpolation. The resulting dataset is a product of daily precipitation in the Tianshan Mountains from 2000 to 2022. During the development of this dataset, strict quality control was implemented on the observed data, and quality assessment was conducted on the daily fused precipitation data. The correlation coefficient increased from 0.44 to 0.53 (passing the significant test at 0.01 level), while the absolute average error decreased from 6.3 mm d-1 to 5.7 mm d-1. This dataset is expected to provide solid data and scientific support for water resource management and efficient utilization in complex terrain areas.