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 US History ID: 1041968
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1. Using Physics to Assess Hurricane RiskKerry EmanuelMassachusetts Institute of Technology
2. Risk Assessment MethodsMethods based on hurricane historyNumerical SimulationsDownscaling 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 greaterCategory 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 AssessmentHistorical record too short to provide robust assessment of intense (damaging) eventsNumerous quality problems with historical recordsHistory 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 cyclonesEmbedding regional models within global models introduces problems stemming from incompatibility of models, and even regional models are usually too coarseModels 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 spaceHydrostatic and gradient balance above PBLMoist adiabatic lapse rates on M surfaces above PBLBoundary layer quasi-equilibriumDeformation-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 closureMixed-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 cyclonesStep 2: Cyclones are assumed to move with the large scale atmospheric flow in which they are embedded, plus a correction for beta driftStep 3: Run the CHIPS model for each cyclone, and note how many achieve at least tropical storm strengthStep 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. CalibrationAbsolute genesis frequency calibrated to North Atlantic during the period 1980-2005
26. Genesis ratesAtlanticEastern North PacificWestern North PacificNorth Indian OceanSouthern HemisphereCalibrated to Atlantic
27. Seasonal CyclesAtlantic
28. Cumulative Distribution of Storm Lifetime Peak Wind Speed, with Sample of 1755 Synthetic Tracks95% confidence bounds
29. 3000 Tracks within 100 km of Miami95% 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 for7555 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. 1. Last 20 years of 20th century simulations2. Years 2180-2200 of IPCC Scenario A1b (CO2 stabilized at 720 ppm)Compare two simulations each from 7 IPCC models:
40. IPCC Emissions ScenariosThis study
41. Projected Warming:This study
42. Basin-Wide Percentage Change in Power DissipationDifferent Climate Models
43. 7 Model Consensus Change in Storm Frequency
44. Economic Analysis of Impact of Climate Change on Tropical Cyclone DamagesWith Robert MendelsohnYale
45. Assessing the Impact of Climate ChangeMeasure how climate change affects future extreme eventsReflect any underlying changes in vulnerability in future periodsEstimate damage functions for each type of extreme event Estimate future extreme events caused by climate change
46. Emissions TrajectoryClimate ScenarioEvent RisksVulnerability ProjectionDamage FunctionDamage Estimate Integrated Assessment Model
47. Climate ModelsCNRM (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/yrFuture Global Damages: 30.6 billion/yrCurrent Global Deaths: 18,918/yrFuture Global Deaths: 7,168/yr
49. Examples of Modeling OutputCurrent and Future Probability Density of U.S. Damages, MIROC ModelCurrent and Future Damage Probability, MIROC Model
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57. Change in Landslide Risk
58. LimitationsAll steps of the integrated assessment are uncertain: emission path, climate response, tropical cyclone response, and damage functionSea level rise not yet taken into accountRelationship between storm intensity and fatalities is uncertainCountry level analysis is desirable (likely gains in accuracy from finer resolution analysis)
59. Summary:History to short and inaccurate to deduce real risk from tropical cyclonesGlobal (and most regional) models are far too coarse to simulate reasonably intense tropical cyclonesGlobally and regionally simulated tropical cyclones are not coupled to the ocean
60. We have developed a technique for downscaling global models or reanalysis data sets, using a very high resolution, coupled TC model phrased in angular momentum coordinatesModel shows high skill in capturing spatial and seasonal variability of TCs, has an excellent intensity spectrum, and captures well known climate phenomena such as ENSO and the effects of warming over the past few decades
61. Application to global models under warming scenarios shows great regional and model-to-model variability. As with many other climate variables, global models are not yet capable of simulating regional variability of TC metricsPredicted climate impacts from all extreme events (including tropical storms) range from $17 to $25 billion/yr global damages by 2100Equivalent to 0.003 to 0.004 percent of GWP by 2100Climate change also predicted to increase fatalities by 2200 to 2500 deaths/yr