Indian Forum for Water Adroit

A review of global precipitation datasets: data sources, estimation, and intercomparisons

Pankaj Dey

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  • Institute : Indian Institute of Science
  • Programming language : MATLAB, R

In this paper, we present a comprehensive review of the data sources and estimation methods of 30
currently available global precipitation datasets, including gauge-based, satellite-related, and reanalysis
datasets. We analyzed the discrepancies between the datasets at daily to annual timescales and found large
differences in both the magnitude and the variability of precipitation estimates. The magnitude of annual
precipitation estimates over global land deviated by as much as 300 mm/yr among the products. Reanalysis
datasets had a larger degree of variability than the other types of datasets. The degree of variability in
precipitation estimates also varied by region. Large differences in annual and seasonal estimates were found
in tropical oceans, complex mountain areas, northern Africa, and some high-latitude regions. Overall, the
variability associated with extreme precipitation estimates was slightly greater at lower latitudes than at
higher latitudes. The reliability of precipitation datasets is mainly limited by the number and spatial coverage
of surface stations, the satellite algorithms, and the data assimilation models. The inconsistencies described
limit the capability of the products for climate monitoring, attribution, and model validation.

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