{"title":"HSPEI: A 1-km spatial resolution SPEI dataset across the Chinese mainland from 2001 to 2022","authors":"Haoming Xia, Yintao Sha, Xiaoyang Zhao, Wenzhe Jiao, Hongquan Song, Jia Yang, Wei Zhao, Yaochen Qin","doi":"10.1002/gdj3.276","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":"11 4","pages":"479-494"},"PeriodicalIF":3.3000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.276","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscience Data Journal","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/gdj3.276","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
Geoscience Data JournalGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
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.