From rain to data: A review of the creation of monthly and daily station-based gridded precipitation datasets
Entity
UAM. Departamento de GeografíaPublisher
WileyDate
2021-08-26Citation
10.1002/wat2.1555
WIREs Water 8.6 (2021): e1555
ISSN
2049-1948DOI
10.1002/wat2.1555Funded by
This work was supported by the Government of Aragón through the “Program of research groups” (group H09_20R, “Climate, Water, Global Change, and Natural Systems”). Ernesto Tejedor is partially funded by the NSF-PIRE (OISE- 1743738)Editor's Version
https://doi.org/10.1002/wat2.1555Subjects
grid; interpolation; precipitation; quality control; reconstruction; GeografíaRights
© 2021 The AuthorsEsta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional.
Abstract
Monthly and daily gridded precipitation datasets are one of the most demanded products in climatology and hydrology. These datasets describe the high spatial and temporal variability of precipitation as a continuous surface and for defined periods. However, due to the complex characteristics of precipitation, it is difficult to obtain accurate estimations. Thus, the creation of a gridded dataset from observations requires the comprehensive and precise application of quality control, reconstruction, and gridding procedures. Yet, despite multiple advances, most of the gridded datasets created and published since the mid-1990s to the present use a wide variety of techniques, methods, and outputs, which can completely change the final representativity of the data. It is, therefore, critical to provide general guidelines for the development of future and more robust gridded datasets based on the data characteristics, geographical factors, and advanced statistical techniques. We identified gaps and challenges for near-future perspectives and provide guidelines for implementing improved approaches based on the performance of 48 products. Finally, we concluded that, despite better spatial and temporal resolutions, data access, and data processing capabilities, observational coverage remains a challenge. Moreover, scientists should adopt tailored strategies to improve the representativity and uncertainty of the estimates. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water Extremes Science of Water > Methods
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Google Scholar:Serrano Notivoli, Roberto
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Tejedor, Ernesto
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