Spatio-Temporal Analysis of Precipitation Patterns in Xinjiang Using TRMM Data and Spatial Interpolation Methods: A Comparative Study

Abstract

Amidst global climate change, regional climate pattern studies are essential for grasping climate variability and shaping water resource management. This research delves into the spatial and temporal aspects of precipitation in China's Xinjiang region. By analyzing TRMM 3B43 V7 satellite precipitation data from 1998 to 2019, alongside ground-based observations, the study examines the efficacy of four spatial interpolation methods - inverse distance-weighted, kriging, radial basis function, and thin-plate spline. The goal is to evaluate their accuracy in mapping Xinjiang's annual precipitation distribution. Findings indicate that the inverse distance weighting method, when used with TRMM data, yields the most accurate results. Notably, precipitation in Xinjiang has generally increased over the study period, with the northern region experiencing markedly higher precipitation, particularly in summer, compared to the south. Over 63% of Xinjiang exhibited this increasing precipitation trend, predominantly in the north. These insights are vital for comprehending water resource dynamics and climate change in Xinjiang, offering significant guidance for water management and agricultural planning.