DOI: 10.57760/sciencedb.j00001.01573
title: 2001-2024 Daily 1km Precipitation Data Set from Yanshan to Taihang Mountains
title: 2001-2024年燕山-太行山1km逐日降水数据集

description: Yanshan-Taihang Mountain is located in the central and northern part of North China. The precipitation distribution in this mountainous area is affected by various factors such as terrain and landform. While precipitation changes greatly, extreme weather events occur frequently, showing significant spatial and temporal changes. This dataset is based on GPM IMERG V07 precipitation product, combined with multi-source remote sensing environmental variables (vegetation index, surface temperature, slope, etc.), and adopts XGBoost machine learning statistical downscale method to generate a 1 km spatial resolution annual precipitation dataset covering the Yanshan-Taihang Mountains in China from 2001 to 2024; through geo-weighted proportional decomposition and mobile window technology, multi-level downscale processing of annual precipitation to month and day scales is carried out, and a 1 km spatial resolution month-by-day and day-by-day precipitation dataset in Yanshan-Taihang Mountains area was generated, improving the spatial and temporal accuracy of regional precipitation. The dataset time span is from January 1, 2001 to December 31, 2024, with a spatial range of 36°–42° north latitude and 113°–120° east longitude. It adopts a WGS-84 coordinate system, GeoTIFF format, in millimeters (mm). This data set has high spatiotemporal resolution and reliability. After strict accuracy control (correlation coefficient R², average absolute error MAE, etc.), it can be applied in meteorological disaster assessment, ecological environment assessment, extreme climate monitoring and analysis and other fields, providing relevant models with high spatiotemporal resolution and high precision precipitation data.
description: Yanshan-Taihang Mountain is located in the central and northern part of North China. The precipitation distribution in this mountainous area is affected by various factors such as terrain and landform. While precipitation changes greatly, extreme weather events occur frequently, showing significant spatial and temporal changes. This dataset is based on GPM IMERG V07 precipitation product, combined with multi-source remote sensing environmental variables (vegetation index, surface temperature, slope, etc.), and adopts XGBoost machine learning statistical downscale method to generate a 1 km spatial resolution annual precipitation dataset covering the Yanshan-Taihang Mountains in China from 2001 to 2024; through geo-weighted proportional decomposition and mobile window technology, multi-level downscale processing of annual precipitation to month and day scales is carried out, and a 1 km spatial resolution month-by-day and day-by-day precipitation dataset in Yanshan-Taihang Mountains area was generated, improving the spatial and temporal accuracy of regional precipitation. The dataset time span is from January 1, 2001 to December 31, 2024, with a spatial range of 36°–42° north latitude and 113°–120° east longitude. It adopts a WGS-84 coordinate system, GeoTIFF format, in millimeters (mm). This data set has high spatiotemporal resolution and reliability. After strict accuracy control (correlation coefficient R², average absolute error MAE, etc.), it can be applied in meteorological disaster assessment, ecological environment assessment, extreme climate monitoring and analysis and other fields, providing relevant models with high spatiotemporal resolution and high precision precipitation data.