基于Stefan方程的多情景多模型青藏高原土壤冻结深度数据集（1950-2099）

土壤冻结深度(SFD)是评估冻土区水资源平衡、地表能量交换和生物地球化学循环变化所必需的，是冰冻圈气候变化的重要指标，对季节性冻土和多年冻土都至关重要。受气候变暖的影响，青藏高原的冻土发生了显著的变化，主要表现为地温升高、多年冻土退化和土壤冻结深度降低。未来土壤冻结深度的进一步降低将对青藏高原的生态环境、水文和工程设施产生重大影响。基于Stefan方程和多模型（BCC-CSM2-MR、CanESM5、CESM2、CMCC-ESM2和CNRM-CM6-1等）不同情景（Historical，SSP126，SSP245，SSP370和SSP585）下降尺度的CMIP6数据集，模拟获得了1950-2099年青藏高原年平均土壤冻结深度数据集，其空间分辨率为0.25°。该数据集对预测冻土的变化，灾害防治，环境评估有支撑作用。

Soil Freezing Depth (SFD) is essential for evaluating changes in water balance, surface energy exchange and biogeochemical cycles in permafrost regions, and serves as a critical indicator of cryospheric climate change, which is vital for both seasonally frozen ground and permafrost. Affected by climate warming, permafrost on the Qinghai-Tibet Plateau has undergone significant changes, mainly manifested as elevated ground temperature, permafrost degradation and reduced soil freezing depth. Further reduction of SFD in the future will exert substantial impacts on the ecological environment, hydrology and engineering facilities across the Qinghai-Tibet Plateau. Based on the Stefan Equation and downscaled CMIP6 datasets from multiple models (including BCC-CSM2-MR, CanESM5, CESM2, CMCC-ESM2, CNRM-CM6-1 and others) under different scenarios (Historical, SSP126, SSP245, SSP370 and SSP585), this study simulated and produced the annual mean SFD dataset over the Qinghai-Tibet Plateau spanning 1950–2099, with a spatial resolution of 0.25°. This dataset provides critical support for permafrost change prediction, disaster prevention and mitigation, and environmental assessment.

搜集汇总

背景与挑战

背景概述

该数据集是基于Stefan方程和多模型多情景CMIP6数据模拟的青藏高原1950-2099年土壤冻结深度数据，空间分辨率为0.25°，旨在预测冻土变化并支持灾害防治和环境评估。数据集覆盖历史时期和未来四种共享社会经济路径情景，反映了气候变暖对冻土的影响。