The Yin and Yang of Best Track Data: User "needs" and Producer "wants"

1. The Yin and Yang of Best Track Data:User "needs" and Producer "wants" Richard J. Murnane RPI/BIOS and Baseline Management Company, Inc. 7 May, 2009 IBTrACS Workshop Asheville, NC

2. Overview • Motivation: A (re)insurer’s view of hurricane science • RPI, (re)insurance, and extreme events • Examples of RPI-funded research related to best-track data • Another example: offshore risk • Previous workshop on western North Pacific best-track data

3. 2001 West Pacific Tracks And Typhoon Lingling

4. Lingling Wind Speed Estimates Agency Speed (kts) Category Maximum wind speed (satellite obs) China 115 Cat 4 JTWC 115 Cat 4 Hong Kong 109 Cat 3 JMA 97 Cat 3 Just before landfall (satellite obs) China 91 Cat 2 JTWC 95 Cat 2 Hong Kong 75 Cat 1 JMA 57 TS Measured wind Vietnam 71(?) Cat 1

5. Sea Surface Temperature Power Dissipation Index Year Changes In Hurricane Power? “… future warming may lead to an upward trend in tropical cyclone destructive potential, and – taking into account an increasing coastal population – a substantial increase in hurricane-related losses in the twenty-first century.” K. Emanuel, Nature, 2005.

6. Changes In Intense Hurricanes? “… global data indicate a 30-year trend toward more frequent and intense hurricanes, …” Webster et al., Science, 2005.

7. Or, No Change? “Subjective measurements and variable procedures make existing tropical cyclone databases insufficiently reliable to detect trends in the frequency of extreme cyclones.” Landsea et al., Science, 2006.

8. Future Unfavorable Conditions? “… the increase of [vertical wind shear] has been historically associated with diminished hurricane activity and intensity. A suite of state-of-the-art global climate model[s] project… [s]ubstantial increases in tropical Atlantic and East Pacific shear …” Vecchi and Soden, GRL, 2007.

9. Upward Trend In Strongest Storms? “... possible trends … are less obvious, owing to the unreliability and incompleteness of the observational record... Here we overcome these two limitations by examining trends … from homogeneous data derived from … satellite records. We find significant upward trends for wind speed quantiles above the 70th percentile…” Elsner et al., Nature, 2008

10. Climate Signal Yes or No? Yin and Yang

11. State Of Knowledge Intergovernmental Panel on Climate Change

12. Attribution And Projection CCSP, 2008

13. Catastrophe Risk Model Hazard Exposure LocationConstructionAgeBuilding Code ProbabilityLocationIntensity, Wave HeightDuration Damage physical damagerepair costs Insured Loss terms of coverage

14. Science Can delay decisions for further study Should be better than previous attempts 95% certainty Private Sector Must make a decision (now) Good enough is sufficient 51% certainty will drive a decision Yin and Yang

15. Overview • Motivation: A (re)insurer’s view of hurricane science • RPI, (re)insurance, and extreme events • Examples of RPI-funded research related to best-track data • Another example: offshore risk • Previous workshop on western North Pacific best-track data

16. XL Re Ltd. PartnerRe Amlin Underwriting Renaissance Reinsurance Corporation Axis Specialty Nephila Capital RPI Corporate Sponsors • State Farm • Aspen Insurance • Risk Management Solutions • FlagstoneRe

17. Onshore Katrina/Rita Losses Offshore Top 40 Property Cat Losses 1970-2007 Losses total$308 billion in2007 dollars Swiss Re Sigma, 1/2008

18. Top 30 For Victims (1970-2006) Swiss Re Sigma, 2/2007

19. 2007 Non-life Premium Volume The US and Europe account for ~80% of global premium: ~$1.7 trillion Swiss Re, Sigma 3/2008

20. Top 30 For Victims (1970-2006) Swiss Re Sigma, 2/2007

21. Science Information from any basin is valuable, Pacific of potentially greater interest than Atlantic because of sample size ENSO or climate a major driver Focus on over-ocean behavior More responsive (concerned?) to human or environmental factors Private Sector Mainly interested in the Atlantic (but Pacific is of growing import) ENSO of interest, but a single storm in any year drives losses Focus on over-land characteristics More concerned with monetary factors Yin and Yang

22. Overview • Motivation: A (re)insurer’s view of hurricane science • RPI, (re)insurance, and why they’re not interested in all extreme events • Examples of RPI-funded research related to best-track data • Another example: offshore risk • Previous workshop on western North Pacific best-track data

23. 2004 Hurricane Ivan 2005 Hurricane Dennis Analyzed Vmax 95kts20 nm from center Insured loss of$7.1 Billion Analyzed Vmax 100kts7 nm from center Insured loss of$1.1 Billion Impact Of Storm Size • Satellite data: • Available on a global basis • Records back to 1970s • Untapped potential information H*Wind analyses from HRD

24. Extended Best-Track Data • 1997 RPI workshop: “Wind Field Dynamics of Landfalling Tropical Cyclones” • Mark DeMaria said there were boxes of observations sitting in hallway • RPI funded effort to digitize data: Extended Best Track data set

25. Wind Radii From Satellite Observations Lower latitude Higher latitude Kossin, 2005

26. UW/NCDC Reanalysis For PDI Atlantic NE Pacific NW Pacific Global Kossin et al., 2007

27. Formation and Tracks of 1970-2003 European Impacts Evans and Hart, 2005

28. Overview • Motivation: A (re)insurer’s view of hurricane science • RPI, (re)insurance, and why they’re not interested in all extreme events • Examples of RPI-funded research related to best-track data • Another example: offshore risk • Previous workshop on western North Pacific best-track data

29. Offshore Industry In Gulf Of Mexico Offshore structures: >4000 Length of pipeline: >56,000 km Property Value: ~$150 Billion Oil and gas pipelines with diameters ≥ 20 inches MMS, 2008

30. Cat Model Date Onshore Losses Offshore Losses (Billions $) (Billions $) AIR Sept. 13 8 - 12 0.6 - 1.3 December 10 - 15 1 - 2 EQECAT Sept. 13 8 - 18 Sept. 19 8 - 12 4 - 6 RMS Sept. 14 6 - 16 Sept. 17 7 - 12 Oct. 24 13 - 21 1 - 3 Hurricane Ike (2008) To a great extent, offshore losses driven by storm wind field, motion, and track because of wave damage Losses from : http://www.gccapitalideas.com/2009/01/21/synopses-of-significant-tropical-cyclones-in-2008/

31. Environmental issues covered (in 3.5 pages) are: Deep-sea currents Deepwater shipwrecks (finding them is a benefit) Environmental impacts, mainly on biology The word: “hurricane” occurs 5 times, mainly in conjunction with an explanation of a drop in production “weather” occurs 2 times (in a single paragraph) “climate” does not rate a single mention… Minerals Management Service Report U.S. Department of the Interior, Minerals Management Service,Gulf of Mexico OCS Region, 102 pages, New Orleans, May 2008

32. Overview • Motivation: A (re)insurer’s view of hurricane science • RPI, (re)insurance, and why they’re not interested in all extreme events • Examples of RPI-funded research related to best-track data • Another example: offshore risk • Previous workshop on western North Pacific best-track data

33. 2001 RPI Workshop • Potential Development of a Unified Northwestern Pacific (NWPAC) Tropical Cyclone Best-Track Data Set • http://w3.bios.edu/rpi/public/meetings/2001/nov01/agenda.htm • Chris Landsea, Colin McAdie, Mark DeMaria, Chip Guard, Tatsuo Ueno, Chris Cantrell, Shangyao Nong

34. Reinsurer’s Perspective:Areas Or Countries Of Most Interest • In general, all countries exposed to tropical cyclones, but a rough order of importance is: • Japan • South Korea • Taiwan, Philippines • Hong Kong • Mainland China

35. Reinsurer’s Perspective:Type Of Desired Information • Two levels of information • Level 1: Mainly basic information for calculating gradient winds • Location on 3-hour basis • Central pressure • Radius of maximum winds • Maximum wind • Forward Movement

36. Reinsurer’s Perspective:Type Of Desired Information • Two levels of information • Level 2: Full wind field and precipitation data, e.g., • Radii of 34 and 50 knot winds • Sustained winds versus peak gusts • Rainfall rate

37. Reinsurer’s Perspective:Data Format And Availability • Data format relatively unimportant, as long as it is standardized • Comma-delimited ASCII probably most practical • On-line access preferred

38. http://w3.bios.edu/rpi/public/meetings/2001/nov01/agenda.htm

39. Reinsurer’s Perspective:Use Of “Real-Time” Wind Data • With initial storm landfall try to overlap wind field data to “exposure” information to estimate expected losses • At other times use proprietary models that have a version of integrated wind fields

40. WMO Report Data • CI and T numbers • Confidence in center position • Max gust and quality code • Rmax • Wind radii: gale force and optional wind speed in 4 quadrants