全球陆地长时序多组分蒸散发与多层土壤水分数据产品（1982-2022）

准确量化陆地蒸散发(ET)和土壤水分动态对全面理解全球水循环和地表能量平衡至关重要。这是一个由新开发的SiTHv2模型生产的全球陆地多组分ET和多层土壤水分长时序数据集。SiTHv2生态水文模型利用多源卫星观测数据和再分析资料中的水文气象变量作为驱动，可提供全球尺度0.1°空间分辨率的每日ET相关估算（包括总ET、植物蒸腾、土壤蒸发和截留蒸发）以及土壤水分动态（多层）。通过与地面观测数据的验证和与其他全球主要ET/土壤水分数据产品的对比显示，SiTHv2数据集在不同尺度上对ET和土壤水分的估算以及时间变化特征都有出色表现。特别是模型对从降水到入渗的水分路径全面表征，使这一数据集特别适用于研究水量平衡和植被对水分限制响应的研究。这个基于卫星遥感的高时空分辨率长时序数据集将持续更新（目前已更新至2022年），为全球水循环研究、干旱评估和生态系统健康监测提供有力支持。

Accurate quantification of terrestrial evapotranspiration (ET) and soil moisture dynamics is critical for a comprehensive understanding of the global water cycle and surface energy balance. This is a long-time series global terrestrial multi-component ET and multi-layer soil moisture dataset produced by the newly developed SiTHv2 ecohydrological model. Powered by multi-source satellite observations and hydrometeorological variables from reanalysis datasets, the SiTHv2 ecohydrological model can provide daily ET-related estimates (including total ET, plant transpiration, soil evaporation, and canopy interception evaporation) and multi-layer soil moisture dynamics at a global scale with a spatial resolution of 0.1°. Validation against in-situ observations and comparisons with other major global ET/soil moisture datasets demonstrate that the SiTHv2 dataset performs excellently in estimating ET and soil moisture across different scales and capturing their temporal variation characteristics. Notably, the model comprehensively characterizes the water pathway from precipitation to infiltration, making this dataset particularly suitable for studies on water balance and vegetation responses to water limitation. This satellite remote sensing-based long-time series dataset with high spatiotemporal resolution will be continuously updated (currently updated to 2022), providing strong support for global water cycle research, drought assessment, and ecosystem health monitoring.

搜集汇总

背景与挑战

背景概述

该数据集是一个全球陆地长时序多组分蒸散发与多层土壤水分数据产品（1982-2022），具有0.05° - 0.1°的空间分辨率和日时间分辨率，数据大小为172.05 GB，开放获取。数据集由SiTHv2模型生产，提供全球尺度的每日ET相关估算和多层土壤水分动态，适用于全球水循环研究、干旱评估和生态系统健康监测。