HSPEI：2001 至 2022 年中国大陆 1 公里空间分辨率 SPEI 数据集

IF 3.3 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Geoscience Data Journal Pub Date : 2024-10-04 DOI:10.1002/gdj3.276

Haoming Xia, Yintao Sha, Xiaoyang Zhao, Wenzhe Jiao, Hongquan Song, Jia Yang, Wei Zhao, Yaochen Qin

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引用次数: 0

摘要

标准化降水蒸散指数（SPEI）是公认的监测气象干旱的有效工具。然而，现有的 SPEI 数据集存在空间不连续性或空间分辨率较低的问题，限制了其在地方干旱监测研究中的应用。因此，我们结合全球降水测量（GPM）降水量（Pre）、中分辨率成像光谱仪（MODIS）陆地表面温度（LST）、ERA5-陆地短波辐射（SR），计算了气象站的 SPEI 指数、在此基础上，利用航天飞机雷达地形图任务（SRTM）数字高程模型（DEM）数据集和随机森林回归（RFR）模型，建立了 2001-2022 年中国大陆多时间尺度的高空间分辨率（1 公里）SPEI（HSPEI）数据集。与其他 SPEI 数据集相比，HSPEI 数据集具有更高的空间分辨率，能够有效识别 2001 至 2022 年中国大陆干旱的详细特征。总体而言，HSPEI 数据集可有效地应用于 2001 至 2022 年中国不同旱情的研究。

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HSPEI: A 1-km spatial resolution SPEI dataset across the Chinese mainland from 2001 to 2022

The Standardized Precipitation Evapotranspiration Index (SPEI) is a widely recognized and effective tool for monitoring meteorological droughts. However, existing SPEI datasets suffer from spatial discontinuity or coarse spatial resolution problems, which limits their applications at the local level for drought monitoring research. Therefore, we calculated the SPEI index at meteorological stations, combined with the Global Precipitation Measurement (GPM) Precipitation (Pre), Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST), ERA5-Land Shortwave Radiation (SR), Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) datasets and Random Forest Regression (RFR) model, developed a high spatial resolution (1 km) SPEI (HSPEI) datasets with multiple time scales in mainland China from 2001 to 2022. Compared to other SPEI datasets, the HSPEI datasets have higher spatial resolution and can effectively identify the detailed characteristics of drought in mainland China from 2001 to 2022. Overall, the HSPEI datasets can be effectively applied to the research of different droughts in China from 2001 to 2022.

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来源期刊

Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES

CiteScore

5.90

自引率

9.40%

发文量

审稿时长

4 weeks

期刊介绍： Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.

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