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Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Black, E., Tarnavsky, E., Greatrex, H., Maidment, R., Mookerjee, A., Quaife, T. and Price, J. (2015) Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation. In: First International electronic conference on Remote Sensing, 22 Jun - 5 Jul 2015. (Vol 1: f002)

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To link to this item DOI: 10.3390/ecrs-1-f002

Abstract/Summary

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical, Physical and Computational Sciences > NCAS
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:60217

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