Details of Award
NERC Reference : NE/H017836/1
INSURANCE and WATER: Estimating uncertainty in future flood risk analysis for insurance and re-insurance markets
Training Grant Award
- Lead Supervisor:
- Professor PD Bates, University of Bristol, Geographical Sciences
- Grant held at:
- University of Bristol, Geographical Sciences
- Science Area:
- Freshwater
- Atmospheric
- Overall Classification:
- Freshwater
- ENRIs:
- Global Change
- Environmental Risks and Hazards
- Science Topics:
- Hydrological Processes
- Geohazards
- Climate & Climate Change
- Abstract:
- A forward view of likely future changes in flood risk resulting from predicted climate change is critically required by the insurance industry in order to take long term strategic decisions on risk management, allow future financial planning and improve business resilience to any increased frequency of large events. Typically, flood insurance losses are regarded as attritional events that impact on profit margins but which are unlikely to result in company bankruptcies and an inability to meet both insurance and reinsurance policy obligations. However, changes to the frequency of large flood events and event clustering may alter this situation and increase the potential for severe disruption to insurance markets. The re-prioritization of insurance portfolios and negotiation of new re-insurance contracts to deal with such threats must proceed on the basis of available evidence and requires a long term view as such changes take considerable time to implement and may incur substantial additional costs. A robust scientific understanding of the impact of climate change on future flood risk is, however, currently lacking because the impact of uncertainty in Global and Regional Climate Model output variables (rainfall, temperature and evapotranspiration) has yet to be cascaded all the way through to flood inundation models. In particular, such analyses have yet to be attempted for urban settings where the majority of at-risk assets are located because of the computational cost of the fine scale hydraulic simulations that are here required. Moreover. whilst methods have been developed to assign likelihoods to uncertain RCM and GCM outputs (e.g. Rougier, 2007) these require extension to cascade likelihoods through to hydraulic predictions such that likelihood-weighted inundation maps can be produced. For this reason University of Bristol and King's College London were approached by Willis Re, a leading global re-insurance firm based in London, to consider ways to research this issue. Such work is ideally suited to CASE studentship funding as it builds on existing research which has confirmed feasibility. It also requires both the substantial period of focussed individual research and close collaboration between industry and academics that a CASE award facilitates. The next steps for such research are therefore to: 1. Undertake further analysis of GCM and RCM output to better understand the strengths and limitations of such models for simulating current and future extreme rainfalls and determine best possible methods to assign likelihoods to these. 2. To test whether bias correction can reduce systematic spatio-temporal errors in climate model predicted rainfalls and increase confidence in these outputs. 3. To cascade uncertain rainfall estimates through catchment hydrology and hydraulic models for urban settings and at regional scales, and test the use of likelihood weighted methods to produce uncertain future flood risk maps. 4. To work closely with the insurance industry to ensure that such complex analyses are communicated in the most appropriate form and analyse the potential impact of such maps on long term strategic decision making. The outputs from the studentship will be: (1) new tools for assessing future flood risk with applicability to a wide range of problems including, primarily, the insurance sector; (2) new scientific understanding of likely future changes in flood risk and their associated uncertainty; and (3) a focus on visualization and communication of complex model outputs to determine how the developed understanding can be most effectively transferred to industry users. This represents high quality science in its own right, with potentially significant impact for UK industry. The student will be supervised by Professor Paul Bates and Dr. Jim Freer of University of Bristol, Dr. Hannah Cloke of King's College London and Matt Foote of Willis Re.
- NERC Reference:
- NE/H017836/1
- Grant Stage:
- Completed
- Scheme:
- DTG - directed
- Grant Status:
- Closed
- Programme:
- Open CASE
This training grant award has a total value of £67,825
FDAB - Financial Details (Award breakdown by headings)
| Total - Other Costs |
|---|
| £67,825 |
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