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Remote Sens. 2016, 8(4), 342; doi:10.3390/rs8040342

The Use of Remotely Sensed Rainfall for Managing Drought Risk: A Case Study of Weather Index Insurance in Zambia

1
Department of Meteorology, University of Reading, Reading RG6 6BB, UK
2
Climate Division of the National Centre for Atmospheric Science (NCAS-Climate), UK
3
National Centre for Earth Observation (NCEO), UK
4
International Research Institute for Climate and Society, Columbia University, Palisades, NY 10964-8000, USA
5
Independent Consulting Actuary, UK
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Ioannis Gitas and Prasad S. Thenkabail
Received: 7 January 2016 / Revised: 18 March 2016 / Accepted: 6 April 2016 / Published: 20 April 2016
View Full-Text   |   Download PDF [1810 KB, uploaded 20 April 2016]   |  

Abstract

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere. View Full-Text
Keywords: weather index insurance; drought; Africa; Satellite-based rainfall estimates; TAMSAT weather index insurance; drought; Africa; Satellite-based rainfall estimates; TAMSAT
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Black, E.; Tarnavsky, E.; Maidment, R.; Greatrex, H.; Mookerjee, A.; Quaife, T.; Brown, M. The Use of Remotely Sensed Rainfall for Managing Drought Risk: A Case Study of Weather Index Insurance in Zambia. Remote Sens. 2016, 8, 342.

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