Evaluation and validation of TAMSAT-ALERT soil moisture and WRSI for use in drought anticipatory action

Boult, V. L. ORCID: https://orcid.org/0000-0001-7572-5469, Asfaw, D. T., Young, M., Maidment, R. ORCID: https://orcid.org/0000-0003-2054-3259, Mwangi, E., Ambani, M., Waruru, S., Otieno, G., Todd, M. C. and Black, E. ORCID: https://orcid.org/0000-0003-1344-6186 (2020) Evaluation and validation of TAMSAT-ALERT soil moisture and WRSI for use in drought anticipatory action. Meteorological Applications, 27 (5). e1959. ISSN 1469-8080 doi: 10.1002/met.1959

Abstract/Summary

Reliable information on the likelihood of drought is of crucial importance in agricultural planning and humanitarian decision-making. Acting based upon probabilistic forecasts of drought, rather than responding to prevailing drought conditions, has the potential to save lives, livelihoods and resources, but is accompanied by the risk of acting in vain. The suitability of a novel forecasting tool is assessed in the present paper in terms of its ability to provide skilful information of the likeli hood of drought impacts on crops and pasture within a timeframe that allows for anticipatory action. The Tropical Applications of Meteorology using SATellite data—AgriculturaL Early waRning sysTem (TAMSAT-ALERT) tool provides forecasts of seasonal mean soil moisture and the water requirement satisfaction index (WRSI). TAMSAT-ALERT metrics were found to be strongly correlated with pasture availability and maize yield in Kenya and provided skilful forecasts early in key seasons, allowing sufficient time for preparatory actions. Incorporating TAMSAT-ALERT forecasts in a layered approach, with actions triggered by spatiotemporally varying triggers and fundamentally informed by humanitarian actors, will provide reliable information on the likelihood of drought, ultimately mitigating food insecurity.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/94549
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Royal Meteorological Society
Download/View statistics	View download statistics for this item