1. Su Buda, subd@cma.gov.cn1 Weather Index-based Insurance in China: 1- Introduction 2- Data screening to determine a pilot area 3- Data collection 4- Data processing

2. 2 Introduction (1) Background: - Growing frequency and severity of extreme weather events in China have caused very high economic losses. But Lack of modern risk management mechanisms to cope with these perils. direct economic losses caused by weather disaster during 1990-2010 (173.2×109 RMB per year )

3. 3 Introduction (2) Developing a weather-index based insurance implies: Collecting and analyzing weather/climate and loss data to find a trigger (farmers will receive insurance payouts once a certain trigger,such as a certain precipitation or water levels for a flood insurance is reached.)

4. 4 Data screening to determine a pilot area (1) Identification of areas in China suitable for developing and launching weather index based insurance According to the following criteria: - Weather data available for at least 30 years - Significant number of weather stations - Existence of significant weather risks which cause losses for the local economy - The risk is independent - High population density/Large number of potential clients Result: Fujian province was chosen as a pilot area

5. Data screening to determine a pilot area (2) Percentage of losses in GDP : stemmed from heavy precipitation Percentage of population affected: stemmed from droughts

6. Data screening to determine a pilot area (3) Potential target area for study : (tropical) Cyclone: high number of population, losses, large market, station density, triggers ‘easy’ 614 national meteorological stations with at least 30-years observational record 582 national meteorological stations with at least 40-years observational record 435 national meteorological stations with at least 50-years observational record

7. 7 Data collection: Weather data (1) Daily wind and daily precipitation were collected for the period 1961-2009 for the 66 climate stations of CMA based in Fujian province Other sources providing weather data: Office of Flood Control and Drought Relief, Agricultural Bureau, Forestry Bureau, etc.

8. 8 In China, damage and loss data related to weather/climate- induced disasters are recorded by CMA on county-level The records of damages and losses are mainly based on official reports from county governments For Fujian province: record of past typhoon events over the last 50 years compiled by the Fujian Climate Center Types of economic losses (in 10,000 RMB)Data availability Direct economic losses91.8% Agricultural losses35.8% Livestock economic losses0.57% Economic losses related to water14% Industrial economic losses4.2% Economic losses related to forestry1.5% Economic losses related to fishery4.7% Economic losses related to traffic12.9% Economic losses related to electricity5.7% Economic losses related to communication1.1% Economic losses related to infrastructures2.3% Economic losses related to commerce0.2% Data collection: Losses data (2)

9. 9 Data processing (1) Trigger estimation Risks of heavy precipitation on tobacco in Longyan County Relationship of heavy precipitation index and losses rate

10. 10 Data processing (2) Challenges -Challenge in obtaining comprehensive, reliable and harmonized loss data -Change of climate station’s location or instrument might affect time-series -Density of climate station plays a crucial role

11. 11 Data processing (3) Solutions -Weather/climate data might have to be interpolated between stations of different altitude ； Interpolate the results and check the reliability in backup stations;The homogeneity of data has to be checked - Interaction with local stakeholders important to identify local needs for an insurance product ；（ Validation of triggers and thresholds ； Re-adjustment of thresholds based on insurer’s needs ） Lianjiang Station58844 5884 5 5884 7 589 41 daily precipitation 1984-2007 588 480.7760.8030.831 0.82 2 daily maximum wind 1984-2007 588 480.4240.5710.577 0.33 0 daily precipitation (typhoon) 588 480.6170.749 0.90 4 0.69 3 daily maximum wind (typhoon) 588 480.672 0.85 40.824 0.42 3 If a station fails, the trigger and threshold can be determined by back-up station

12. Thank you 谢谢