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TAMSAT

Maidment, R. ORCID: https://orcid.org/0000-0003-2054-3259, Black, E. ORCID: https://orcid.org/0000-0003-1344-6186, Greatrex, H. and Young, M. (2020) TAMSAT. In: Levizzani, V., Kidd, C., Kirschbaum, D. B., Kummerow, C. D., Nakamura, K. and Turk, F. J. (eds.) Satellite Precipitation Measurement. Advances in Global Change Research, 1 (67). Springer, pp. 393-407. ISBN 9783030245672

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To link to this item DOI: 10.1007/978-3-030-24568-9_22

Abstract/Summary

Rainfall monitoring over Africa using satellite imagery is essential given the lack of land-based rainfall measurements and the dependency of economies largely based on climate-sensitive practices. Motivated by a need to monitor rainfall deficits and its impact on crop yield over the Sahel, the TAMSAT Group have, since the 1980s, helped pioneer the use of Meteosat thermal infrared (TIR) imagery for rainfall estimation using cold cloud duration (CCD). Unlike other TIR-based algorithms, the TAMSAT algorithm, which is calibrated using rain gauges, varies spatially and temporally to account for the strong spatial and seasonal changes in the rainfall climate across Africa. TAMSAT produce high-resolution (0.0375°), operational rainfall estimates from 1983 to the delayed present for all Africa, at the daily to seasonal time-step. Currently, TAMSAT is only one of a handful of datasets that provide long-term (+30 years) and sub-monthly rainfall estimates for Africa. The data, whose skill is comparable or better (depending on the metric) than other satellite products, are used by a variety of stakeholders in the commercial, humanitarian, agricultural and financial sectors. The temporal consistency and longevity of the TAMSAT record makes it a valuable dataset for climate monitoring and risk assessment.

Item Type:Book or Report Section
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:91181
Publisher:Springer

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