Integrated Threshold Development for Parametric Insurance Solutions for Guangdong Province China (INPAIS)

GSTDTAP

项目编号	NE/R014264/1
	Integrated Threshold Development for Parametric Insurance Solutions for Guangdong Province China (INPAIS)
	Gregor C Leckebusch
主持机构	University of Birmingham
项目开始年	2018
	2018
项目结束日期	2020-08-20
资助机构	UK-NERC
项目类别	Research Grant
项目经费	222312(GBP)
国家	英国
语种	英语
英文摘要	Meteorological extreme events affect China's economic development, society and welfare condition in an extra-ordinary way. The impact of strong tropical cyclones (TCs or Typhoons) is of crucial importance and leading to major losses in southern China, especially in Guangdong Province. One way of mitigating severe, negative impacts on different sectors of society is the development and application of financial instruments for risk transfer and adequate response. Beside classical (privately organised) (re-)insurance solutions, since recently, parametric insurance solutions have been developed for test cases in some areas, as e.g. by SwissRe Beijing Branch, our practitioner partner. The challenge SwissRe Beijing Branch is now facing, is to achieve a reliable structure for the parametric insurance programmes designed and underwritten for TC index triggers for Guangdong Government. The first major challenge is the regionalised effect of Typhoons, leading to difficulties in the robust estimate of losses per sub-region or prefecture level in Guangdong province, which will lead to under- or overcompensating for specific prefectures. The second major challenge is the very limited and instationary nature of meteorological information (as well as for past losses) available for extreme Typhoons. Consequently, the design of parametric insurance has shortcomings in the assessment of the real hazard frequency and intensity on one side and on the other side suffers from limited availability of historic loss (insured and economic loss) to calibrate the impact. INPAIS aims to improve the hazard risk assessment and thus to improve the response trigger points for Guangdong province. Ultimately, this will lead to increased rapid response and recovery after a Typhoon strikes. To address challenge one, the problem of missing regional assessment of losses in affected prefectures, INPAIS will apply and further develop the successful tool to objectively measure and quantify storm severity (Storm Severity Index, SSI) based on the WiTrack algorithm from University of Birmingham. This hazard assessment will allow for an integrated characterisation on event basis. Detailed information per Typhoon system (footprint, area affected in relation to damages; wind speed information relative to climatological background; track location; etc.) will be provided. Our co-investigator, Prof. Ye, will collect information of losses on prefecture level from archives of the Chinese Meteorological Agency, only available in local sites and in Chinese. To address challenge two, the problem of small samples of physically consistent meteorological data available and thus leading to less robust assessments of the real hazard risk and its uncertainty, the objective tool will be applied to the operational forecast archive TIGGE (THORPEX Interactive Grand Global Ensemble) in a climatological approach. The TIGGE dataset consists of multi-model ensemble forecast data from 10 global Numerical Weather Prediction centres, available for the last 10 years. This will allow to estimate return-levels of Typhoons out of a sample equivalent to some 40,000 to 50,000 years. The INPAIS outputs will be used: A) Scientifically: To inform about more realistic frequency-intensity distributions of the integrated hazard Typhoon (dry - wet) on a regional scale. This will lead to improved estimates of uncertainties of hazards on seasonal to decadal time scales necessary for output: B) Financial Instrument: to improve the trigger points of the existing parametric Typhoon insurance for Guangdong province. This will led to improved matching of damages/losses and cover existing. This will also tackle the problem of under- or overcompensating in specific regions and the potential development of improved distribution mechanisms, ultimately enabling increased rapid response and recovery.
来源学科分类	Natural Environment Research
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/86966
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	Gregor C Leckebusch.Integrated Threshold Development for Parametric Insurance Solutions for Guangdong Province China (INPAIS).2018.