青藏高原未来LAI变化情景数据集（2020-2050）

本产品为2020-2050年青藏高原逐年平均叶面积指数产品。本产品基于CESM中CLM模块模拟未来情景下的LAI，产品特色包括：（1）采用了阳坤课题组发表的空间分辨率 0.1°的中国区域地面气象要素驱动数据集（1979-2018）替换模型中空间分辨率 0.5°默认大气强迫数据集。（2）采用了2000-2018年GLASS_LAI数据进行本地化校正。数据集涵盖了未来时期（2020-2050）SSP126和SSP585两种情景下的年均LAI结果。数据为tiff格式，时间分辨率为年尺度，空间分辨率为0.125°。 该数据集可用于深入研究青藏高原地区未来气候情景变化下叶面积指数的趋势和特征，为青藏高原植被变化研究和评估提供支撑。

This product is an annual mean Leaf Area Index (LAI) dataset over the Qinghai-Tibet Plateau spanning the period 2020–2050. It simulates future-scenario LAI using the CLM (Community Land Model) module within the CESM (Community Earth System Model). The key features of this dataset are as follows: (1) The default 0.5° spatial resolution atmospheric forcing dataset in the model was replaced with a 0.1° spatial resolution Chinese regional ground meteorological forcing dataset (1979–2018) published by the Yang Kun Research Group; (2) Localized calibration was conducted using the GLASS_LAI dataset for the period 2000–2018. The dataset covers annual mean LAI results under two Shared Socioeconomic Pathways (SSPs), namely SSP126 and SSP585, for the future period 2020–2050. All data are stored in TIFF format, with an annual temporal resolution and a spatial resolution of 0.125°. This dataset can be utilized to conduct in-depth research on the trends and characteristics of LAI under future climate scenario changes over the Qinghai-Tibet Plateau, providing support for research and assessment of vegetation changes in this region.

搜集汇总

背景与挑战

背景概述

该数据集提供了2020-2050年青藏高原逐年平均叶面积指数（LAI）产品，基于CESM模型的CLM模块模拟，并采用高分辨率气象驱动数据和GLASS_LAI数据进行本地化校正，涵盖SSP126和SSP585两种未来气候情景。数据以tiff格式存储，时间分辨率为年，空间分辨率为0.125°，旨在支持青藏高原植被变化研究和评估。