TY - CHAP
T1 - TAMSAT
AU - Maidment, Ross
AU - Black, Emily
AU - Greatrex, Helen
AU - Young, Matthew
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85089065433&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85089065433&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-24568-9_22
DO - 10.1007/978-3-030-24568-9_22
M3 - Chapter
AN - SCOPUS:85089065433
T3 - Advances in Global Change Research
SP - 393
EP - 407
BT - Advances in Global Change Research
PB - Springer
ER -