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Enhancing Hurricane Risk Prediction with Proxy Data Analysis

Learn how the Risk Prediction Initiative (RPI) utilizes proxies to improve hurricane landfall probabilities, aiding insurers in assessing risks. Discover the methods, results, and future directions of RPI activities. Proxy data analysis includes storm surges, lake cores, and climate diagnostic proxies.

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Enhancing Hurricane Risk Prediction with Proxy Data Analysis

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  1. Casualty Actuarial Society Hurricane Landfall Probabilities from Proxy Data David Malmquist Risk Prediction Initiative Bermuda Biological Station for Research, Inc.

  2. Preview • Risk Prediction Initiative • Need for Proxies • Proxy Methods and Results • Future Directions

  3. The Goal of the RPI To create links between the climate science and insurance communities so that the science of climate forecasting is available, understandable, and usable by insurers

  4. RPI Information Flow INSURERS Risk Prediction Initiative Government Academia Commercial RiskModelers

  5. X.L. Mid Ocean Re General Re Renaissance Re ACE Limited Centre Solutions Employers Re AIG/IPC Re RPI Corporate Sponsors

  6. RPI Activities • Facilitate working groups • Fund novel research • Develop and distribute research products

  7. Insured Loss terms of coverage Catastrophe Risk Model Hazard landfall probabilitymaximum sustained windspeak wind gustradius of maximum windsforward speed and directiondecay rate latitudelongitudeelevationtopographyconstruction typesurrounding structures Damage physical damagerepair costs

  8. RPI Activities • Facilitate working groups • Fund novel research • extend historical records via proxies • improve hurricane forecasts • climate variability • wind-field dynamics • develop public models • Develop and distribute research products

  9. 1 2 3 4 5 ≥ 28.94 28.5-28.9 27.9-28.4 27.2-27.8 < 27.17 74-95 96-110 111-130 131-155 > 155 4-5 6-8 9-12 13-18 > 18 Minimal Moderate Extensive Extreme Catastrophic Saffir/Simpson Scale Pressure(inches) Wind(mph) Surge(ft) Damage

  10. US Tropical Cyclone Damage(1925-1995) $ = Millions of 1995 US dollars Pielke & Landsea, 1997

  11. 1900 1950 1990 Tropical Cyclone Observation Land observations Ship logs Aircraft reconnaissance Satellites NOAA, 1993

  12. RPI Funded Research Extend Historical Records Via Proxies

  13. Ocean Lake Hurricane Proxies: Storm Surge Sand BarrierIsland Mud

  14. from K.-B. Liu

  15. Lake Core Analysis • Lake Shelby, Alabama • 3.2-3.0, 2.6, 2.2, 1.4, 0.8 ka • ~ 600 year return period • Category 4 or 5 sand layers 0 100 200 300 400 500 Depth (cm) data from K.-b. Liu

  16. H216O > 99.7% H218O ~ 0.2% A Climate Diagnostic Proxy:Oxygen Isotopes Mean Sea Water

  17. Texas Summer Precipitation 1985-92 Summer Rain Tropical Cyclones n = 208 Rainfall Events -15 -13 -11 -9 -7 -5 -3 -1 1 Oxygen Isotope Values Lawrence & Gedzelman, 1996

  18. Proxy Tape Recorder 10 8 6 4 2 18O 0 -2 - 2.93‰ -4 -6 -8 - 9.35‰ -10 Time

  19. Growth of Cave Deposits precipitation dissolution H2O + CO2 + CaCO3 <––> Ca++ + 2HCO3- stalactite column stalagmite

  20.  Stalagmite Cross-Section Fidelity Sampling Interval 18O

  21. Tree Growth

  22. Suppressed vs. Released Rings

  23. What are the Potential Proxy Signals? • Within-tree differences in ring width • Between-tree differences in ring width • local (cohort) • regional (intersite) • Isotopic Signals

  24. Hurricane Camille (1969) Mississippi Louisiana Slidell Pass Christian

  25. Single -Tree Analysis Hurricane Wind

  26. Single -Tree Analysis 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Hurricane Camille Standardized Ratio 1990 1950 1960 1970 1980 Doyle & Gorham, 1996

  27. Cohort Analysis Hurricane Wind A B B A

  28. 1950 1960 1970 1980 1990 Cohort Analysis 6 5 4 3 2 1 0 Hurricane Camille Growth Ratio Doyle & Gorham, 1996

  29. Inter-Site Analysis MS LA LA MS

  30. 1950 1960 1970 1980 1990 Inter-Site Analysis 7 6 5 4 3 2 1 0 Hurricane Camille Growth Ratio Doyle & Gorham, 1996

  31. Hurricane Proxies: U.S. Geography Lake cores Tree-rings Caves

  32. Facilitate working groups • Fund novel research • Develop and distribute research products • http://www.bbsr.edu/rpi/

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