The 30-year TAMSAT African rainfall climatology and time-series (TARCAT) dataset

Maidment, R. I. ORCID: https://orcid.org/0000-0003-2054-3259, Grimes, D., Allan, R. P. ORCID: https://orcid.org/0000-0003-0264-9447, Tarnavsky, E. ORCID: https://orcid.org/0000-0003-3403-0411, Stringer, M., Hewison, T., Roebeling, R. and Black, E. ORCID: https://orcid.org/0000-0003-1344-6186 (2014) The 30-year TAMSAT African rainfall climatology and time-series (TARCAT) dataset. Journal of Geophysical Research: Atmospheres, 119 (18). pp. 10619-10644. ISSN 2169-8996 doi: 10.1002/2014JD021927

Abstract/Summary

African societies are dependent on rainfall for agricultural and other water-dependent activities, yet rainfall is extremely variable in both space and time and reoccurring water shocks, such as drought, can have considerable social and economic impacts. To help improve our knowledge of the rainfall climate, we have constructed a 30-year (1983–2012), temporally consistent rainfall dataset for Africa known as TARCAT (TAMSAT African Rainfall Climatology And Time-series) using archived Meteosat thermal infra-red (TIR) imagery, calibrated against rain gauge records collated from numerous African agencies. TARCAT has been produced at 10-day (dekad) scale at a spatial resolution of 0.0375°. An intercomparison of TARCAT from 1983 to 2010 with six long-term precipitation datasets indicates that TARCAT replicates the spatial and seasonal rainfall patterns and interannual variability well, with correlation coefficients of 0.85 and 0.70 with the Climate Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) gridded-gauge analyses respectively in the interannual variability of the Africa-wide mean monthly rainfall. The design of the algorithm for drought monitoring leads to TARCAT underestimating the Africa-wide mean annual rainfall on average by −0.37 mm day−1 (21%) compared to other datasets. As the TARCAT rainfall estimates are historically calibrated across large climatically homogeneous regions, the data can provide users with robust estimates of climate related risk, even in regions where gauge records are inconsistent in time.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/37236
Item Type	Article
Refereed	Yes
Divisions	Interdisciplinary Research Centres (IDRCs) > Walker Institute Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO) Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	American Geophysical Union
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