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A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons
Open accessAbstract
In this paper, we present a comprehensive review of the data sources and estimation methods of 30 currently available global precipitation data sets, including gauge‐based, satellite‐related, and reanalysis data sets. We analyzed the discrepancies between the data sets from 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 data sets had a larger degree of variability than the other types of data sets. 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 data sets 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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Cites
The Changing Character of Precipitation
Trenberth, K. E., Dai, A., Rasmussen, R. M., & Parsons, D. B. (2003) · Bulletin of the American Meteorological Society · doi:10.1175/bams-84-9-1205 · Cited by 3,196
Liu, Z., Ostrenga, D., Teng, W., & Kempler, S. (2012) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00152.1 · Cited by 222
Cited by
MSWEP V2 Global 3-Hourly 0.1° Precipitation: Methodology and Quantitative Assessment
Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. G., van Dijk, A. I. J. M., McVicar, T. R., & Adler, R. F. (2019) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-17-0138.1 · Cited by 1,411
High-resolution (1 km) Köppen-Geiger maps for 1901–2099 based on constrained CMIP6 projections
Beck, H. E., McVicar, T. R., Vergopolan, N., Berg, A., Lutsko, N. J., Dufour, A., Zeng, Z., Jiang, X., van Dijk, A. I. J. M., & Miralles, D. G. (2023) · Scientific Data · doi:10.1038/s41597-023-02549-6 · Cited by 917
Asynchronous carbon sink saturation in African and Amazonian tropical forests
Hubau, W., Lewis, S. L., Phillips, O. L., Affum-Baffoe, K., Beeckman, H., Cuní-Sanchez, A., Daniels, A. K., Ewango, C. E. N., Fauset, S., Mukinzi, J. M., et al. (2020) · Nature · doi:10.1038/s41586-020-2035-0 · Cited by 782
Global and Regional Increase of Precipitation Extremes Under Global Warming
Papalexiou, S. M., & Montanari, A. (2019) · Water Resources Research · doi:10.1029/2018wr024067 · Cited by 721
Iturbide, M., Gutiérrez, J. M., Alves, L. M., Bedia, J., Cerezo-Mota, R., Cimadevilla, E., Cofiño, A. S., Di Luca, A., Faria, S. H., Gorodetskaya, I. V., et al. (2020) · Earth System Science Data · doi:10.5194/essd-12-2959-2020 · Cited by 687
Metadata
- Authors
- Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian, S., & Hsu, K.
- Venue
- Reviews of Geophysics
- Publisher
- American Geophysical Union (AGU)
- Published
- 2018-01-05
- Volume
- 56
- Issue
- 1
- Pages
- 79-107
- ISSN
- 0096-1043 (ISSN-L)
- 8755-1209
- 1944-9208
- OpenAlex
- W2773928770
- Cited by
- 1,941
- References
- 2
- FWCI
- 63.04
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian, S., & Hsu, K. (2018). A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons. Reviews of Geophysics. https://doi.org/10.1002/2017rg000574
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