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An improved daily standardized precipitation index dataset for mainland China from 1961 to 2018.
Wang, Qianfeng; Zhang, Rongrong; Qi, Junyu; Zeng, Jingyu; Wu, Jianjun; Shui, Wei; Wu, Xiaoping; Li, Jianwei.
Afiliación
  • Wang Q; Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environmental & Safety Engineering, Fuzhou University, Fuzhou, 350116, China.
  • Zhang R; Joint Global Change Research Institute, Pacific Northwest National Laboratory and University of Maryland, College Park, MD, 20740, USA.
  • Qi J; Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environmental & Safety Engineering, Fuzhou University, Fuzhou, 350116, China.
  • Zeng J; Earth System Science Interdisciplinary Center, University of Maryland, College Park, 5825 University Research Ct, College Park, MD, 20740, USA.
  • Wu J; Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environmental & Safety Engineering, Fuzhou University, Fuzhou, 350116, China.
  • Shui W; State Key Laboratory of Earth Surface Processes and Resource Ecology/Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
  • Wu X; State Key Laboratory of Earth Surface Processes and Resource Ecology/Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
  • Li J; Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion, College of Environmental & Safety Engineering, Fuzhou University, Fuzhou, 350116, China.
Sci Data ; 9(1): 124, 2022 03 30.
Article en En | MEDLINE | ID: mdl-35354842
ABSTRACT
The standardized precipitation index (SPI), one of the most commonly used drought indicators, is widely used in the research areas of drought analysis and drought prediction in different fields such as meteorology, agriculture, and hydrology. However, its main disadvantage is the relatively coarse time resolution of one month. To improve the time resolution of SPI to identify flash droughts, we have refined the traditional SPI calculation method and developed a new multi-scale daily SPI dataset based on data from 484 meteorological stations in mainland China from 1961 to 2018. SPI data from three different sites (located in Henan, Yunnan, and Fujian Provinces) at the three-month timescale were analyzed by comparing with historically recorded drought events. We found that the new multi-scale daily SPI can effectively capture drought events in different periods and locations and identify the specific start and end times of drought events. In short, our SPI dataset appears reasonable and capable of facilitating drought research in different fields.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article País de afiliación: China