To deal with the adverse impacts of climate change, index-based or parametric insurance has been recognized as an adaptation technique to compensate farmers for economic losses from extreme weather events. The insurance can be either private or sovereign. African Risk Capacity Insurance (ARC Ltd) offers the latter to African countries against drought events through contingency planning, risk pooling and transfer facilities. While the ARC insurance initiative seems promising, the current approaches used to estimate risk and determine premiums do not consider the change in risk from anthropogenic climate change. As the frequency of extreme weather events changes, the price of insurance premiums is likely to rise. Representing a cutting-edge science from weather to impact attribution, this study links attribution modelling with parametric insurance modelling to quantify how the probability of drought events has changed due to human influence on the climate system and translates the impacts into actual costs. To quantify this change, global climate models consisting of both factual and counterfactual world (with and without human forcing of climate, respectively) experiments were post-processed and used as rainfall inputs into an insurance risk modelling software, Africa RiskView. Estimated response costs needed for drought assistance in a world with and without climate change were calculated in Malawi, Zimbabwe, Senegal and Mauritania for the last 30 years. The empirical cumulative distribution function plots show that the distributions of models that represent the counterfactual natural world estimate lesser drought-affected population and lower response costs for assistance than those of the factual world distributions. The results suggest that climate change is likely to increase the price of insurance premiums. Therefore, there is a need for blended financing models that integrate international climate funds generated on a responsibility-based approach to cater for the added cost brought in by climate change.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/32627 |
| Date | 21 January 2021 |
| Creators | Dorbor, Sylvia Saygbay Diamond |
| Contributors | New, Mark, Odoulami, Romaric C. |
| Publisher | Faculty of Science, Department of Environmental and Geographical Science |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MSc |
| Format | application/pdf |
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