Identifying Precipitation and Reference Evapotranspiration Trends in West Africa to Support Drought Insurance

被引:11
作者
Blakeley, S. Lucille [1 ]
Sweeney, Stuart [1 ]
Husak, Gregory [1 ]
Harrison, Laura [1 ]
Funk, Chris [2 ]
Peterson, Pete [1 ]
Osgood, Daniel E. [3 ]
机构
[1] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA
[2] US Geol Survey, Earth Resources Observat & Sci Ctr, 47914 252nd St, Sioux Falls, SD 57198 USA
[3] Columbia Univ, Int Res Inst Climate & Soc, Palisades, NY 10964 USA
关键词
West Africa; climate variability; precipitation; evapotranspiration; index insurance; RISK-MANAGEMENT; INDEX INSURANCE; SAHEL RAINFALL; DEMAND; NDVI;
D O I
10.3390/rs12152432
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
West Africa represents a wide gradient of climates, extending from tropical conditions along the Guinea Coast to the dry deserts of the south Sahara, and it has some of the lowest income, most vulnerable populations on the planet, which increases catastrophic impacts of low and high frequency climate variability. This paper investigates low and high frequency climate variability in West African monthly and seasonal precipitation and reference evapotranspiration from the early 1980s to 2016. We examine the impact of those trends and how they interact with payouts from index insurance products. Understanding low and high frequency variability in precipitation and reference evapotranspiration at these scales can provide insight into trends during periods critical to agricultural performance across the region. For index insurance, it is important to identify low-frequency variability, which can result in radical departures between designed/planned and actual insurance payouts, especially in the later part of a 30-year period, a common climate analysis period. We find that evaporative demand and precipitation are not perfect substitutes for monitoring crop deficits and that there may be space to use both for index insurance design. We also show that low yields-aligned with the need for insurance payouts-can be predicted using classification trees that include both precipitation and reference evapotranspiration.
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页数:29
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