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Using Physics to Assess Hurricane Risk

Using Physics to Assess Hurricane Risk. Kerry Emanuel Massachusetts Institute of Technology. Risk Assessment Methods. Methods based on hurricane history Numerical Simulations Downscaling Approaches. 3 Cat 3 Storms in New England. 3 Cat 5 Storms in U.S. History.

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Using Physics to Assess Hurricane Risk

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  1. Using Physics to Assess Hurricane Risk Kerry Emanuel Massachusetts Institute of Technology

  2. Risk Assessment Methods • Methods based on hurricane history • Numerical Simulations • Downscaling Approaches

  3. 3 Cat 3 Storms in New England

  4. 3 Cat 5 Storms in U.S. History

  5. U.S. Hurricane Damage, 1900-2004, Adjusted for Inflation, Wealth, and Population

  6. Some U.S. Hurricane Damage Statistics: • >50% of all normalized damage caused by top 8 events, all category 3, 4 and 5 • >90% of all damage caused by storms of category 3 and greater • Category 3,4 and 5 events are only 13% of total landfalling events; only 30 since 1870 • Landfalling storm statistics are grossly inadequate for assessing hurricane risk

  7. Issues with Historically Based Risk Assessment • Historical record too short to provide robust assessment of intense (damaging) events • Numerous quality problems with historical records • History may be a poor guide to the future, owing to natural and anthropogenic climate change

  8. Using Global and Regional Models to Simulate HurricanesThe Problem: • Global models are far too coarse to simulate high intensity tropical cyclones • Embedding regional models within global models introduces problems stemming from incompatibility of models, and even regional models are usually too coarse • Models to expensive to run many times.

  9. Histograms of Tropical Cyclone Intensity as Simulated by a Global Model with 50 km grid point spacing. (Courtesy Isaac Held, GFDL) Category 3

  10. To the extent that they simulate tropical cyclones at all, global models simulate storms that are largely irrelevant to society and to the climate system itself, given that ocean stirring effects are heavily weighted towards the most intense storms

  11. What are the true resolution requirements for simulating tropical cyclones?

  12. Numerical convergence in an axisymmetric, nonhydrostatic model (Rotunno and Emanuel, 1987)

  13. Another Major Problem with Using Global and/or Regional Models to Simulate Tropical Cyclones: Model TCs are not coupled to the ocean

  14. Comparing Fixed to Interactive SST:

  15. Our Solution: Drive a simple but very high resolution, coupled ocean-atmosphere TC model using boundary conditions supplied by the global model or reanalysis data set

  16. CHIPS: A Time-dependent, axisymmetric model phrased in R space • Hydrostatic and gradient balance above PBL • Moist adiabatic lapse rates on M surfaces above PBL • Boundary layer quasi-equilibrium • Deformation-based radial diffusion

  17. Detailed view of Entropy and Angular Momentum

  18. Ocean Component: ((Schade, L.R., 1997: A physical interpreatation of SST-feedback. Preprints of the 22nd Conf. on Hurr. Trop. Meteor., Amer. Meteor. Soc., Boston, pgs. 439-440.) • Mixing by bulk-Richardson number closure • Mixed-layer current driven by hurricane model surface wind

  19. Hindcast of Katrina

  20. Comparison to Skill of Other Models

  21. Application to Assessing Tropical Cyclone Risk in a Changing Climate

  22. Approach: Step 1: Seed each ocean basin with a very large number of weak, randomly located cyclones Step 2: Cyclones are assumed to move with the large scale atmospheric flow in which they are embedded, plus a correction for beta drift Step 3: Run the CHIPS model for each cyclone, and note how many achieve at least tropical storm strength Step 4: Using the small fraction of surviving events, determine storm statistics. Details: Emanuel et al., BAMS, 2008

  23. 200 Synthetic U.S. Landfalling tracks (color coded by Saffir-Simpson Scale)

  24. 6-hour zonal displacements in region bounded by 10o and 30o N latitude, and 80o and 30o W longitude, using only post-1970 hurricane data

  25. Calibration Absolute genesis frequency calibrated to North Atlantic during the period 1980-2005

  26. Genesis rates Western North Pacific Southern Hemisphere Eastern North Pacific North Indian Ocean Atlantic Calibrated to Atlantic

  27. Seasonal Cycles Atlantic

  28. Cumulative Distribution of Storm Lifetime Peak Wind Speed, with Sample of 1755Synthetic Tracks 95% confidence bounds

  29. 3000 Tracks within 100 km of Miami 95% confidence bounds

  30. Return Periods

  31. Sample Storm Wind Swath

  32. Captures effects of regional climate phenomena (e.g. ENSO, AMM)

  33. Year by Year Comparison with Best Track and with Knutson et al., 2007

  34. Couple to Storm Surge Model (SLOSH) Courtesy of Ning Lin, Princeton University

  35. Surge map for single event

  36. Histogram of the SLOSH-model simulated (primary) storm surge at the Battery for 7555 synthetic tracks that pass within 200 km of the Battery site.

  37. Surge Return Periods, New York City

  38. Now Use Daily Output from IPCC Models to Derive Wind Statistics, Thermodynamic State Needed by Synthetic Track Technique

  39. Compare two simulations each from 7 IPCC models: 1.Last 20 years of 20th century simulations2. Years 2180-2200 of IPCC Scenario A1b (CO2 stabilized at 720 ppm)

  40. IPCC Emissions Scenarios This study

  41. Projected Warming: This study

  42. Basin-Wide Percentage Change in Power Dissipation Different Climate Models

  43. 7 Model Consensus Change in Storm Frequency

  44. Economic Analysis of Impact of Climate Change on Tropical Cyclone Damages With Robert Mendelsohn Yale

  45. Assessing the Impact of Climate Change • Measure how climate change affects future extreme events • Reflect any underlying changes in vulnerability in future periods • Estimate damage functions for each type of extreme event • Estimate future extreme events caused by climate change

  46. Integrated Assessment Model Emissions Trajectory Climate Scenario Event Risks Vulnerability Projection Damage Function Damage Estimate

  47. Climate Models • CNRM (France) • ECHAM (Germany) • GFDL (U.S.) • MIROC (Japan; tropical cyclones only)

  48. Baseline Changes in Tropical Cyclone Damage (due to population and income, holding climate fixed) • Current Global Damages: $13.9 billion/yr • Future Global Damages: 30.6 billion/yr • Current Global Deaths: 18,918/yr • Future Global Deaths: 7,168/yr

  49. Examples of Modeling Output Current and Future Probability Density of U.S. Damages, MIROC Model Current and Future Damage Probability, MIROC Model

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