1. Tropical Cyclones and Climate: Some New Findings Kerry Emanuel Program in Atmospheres, Oceans, and Climate MIT

2. Some Issues What processes control rates of genesis of tropical cyclones? What processes control rates of genesis of tropical cyclones? What processes control the actual and potential intensity of TCs? What processes control the actual and potential intensity of TCs? Do TCs have important feedbacks on climate? Do TCs have important feedbacks on climate?

3. Atlantic Sea Surface Temperatures and Storm Max Power Dissipation (Smoothed with a 1-3-4-3-1 filter) Scaled Temperature Power Dissipation Index (PDI) Years included: 1870-2006 Data Sources: NOAA/TPC, UKMO/HADSST1

4. Theoretical Upper Bound on Hurricane Maximum Wind Speed: Air-sea enthalpy disequilibrium Surface temperature Outflow temperature Ratio of exchange coefficients of enthalpy and momentum s 0 * = saturation entropy of sea surface s b = actual entropy of subcloud layer

5. Condition of convective neutrality: s b = s* of free troposphere Also, s* of free troposphere is approximately spatially uniform (WTG approximation) approximately constant What matters, apparently, is the SST (s 0 *) relative to the tropospheric temperature (s*)

6. Can SST Vary Independently of s*? Ocean Surface Energy Balance:

7. Answer: On time scales long enough for the ocean mixed layer to be in thermal equilibrium (>~ 1 year) Potential intensity is determined by local radiative balance, local convergence of ocean heat flux, local surface wind speed, and local outflow temperature only Remote influences limited to remote effects on surface wind surface radiation ocean heat flux and, in marginal zones, on outflow temperature SST cannot vary independently of free atmospheric temperature

8. Interpretation of Recent Trends in Potential Intensity Based on NCAR/NCEP Reanalysis

9. Importance of Trends in Outflow Temperature

11. Very High Resolution Modeling of the Response of Tropical Cyclones to Climate Change

12. The Problem: Global models are far too coarse to simulate high intensity tropical cyclones 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 Embedding regional models within global models introduces problems stemming from incompatibility of models, and even regional models are usually too coarse

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

14. Probability Density of TC Damage, U.S. East Coast Damage Multiplied by Probability Density of TC Damage, U.S. East Coast

15. 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

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

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

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

19. Comparing Fixed to Interactive SST:

20. 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

21. 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

22. Detailed view of Entropy and Angular Momentum

23. Ocean Component: ((Schade, L.R., 1997: A physical interpreatation of SST-feedback. Preprints of the 22 nd 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

24. Ocean columns integrated only Along predicted storm track. Predicted storm center SST anomaly used for input to ALL atmospheric points.

25. Comparison with same atmospheric model coupled to 3-D ocean model; idealized runs: Full model (black), string model (red)

26. Hindcast of Katrina

27. Comparison to Skill of Other Models

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

29. 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

30. 200 Synthetic U.S. Landfalling tracks (color coded by Saffir-Simpson Scale)

31. 6-hour zonal displacements in region bounded by 10 o and 30 o N latitude, and 80 o and 30 o W longitude, using only post-1970 hurricane data

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

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

34. Seasonal Cycles

35. Cumulative Distribution of Storm Lifetime Peak Wind Speed, with Sample of 2946Synthetic Tracks Cumulative Distribution of Storm Lifetime Peak Wind Speed, with Sample of 2946 Synthetic Tracks

36. 3000 Tracks within 100 km of Miami 95% confidence bounds

37. Return Periods

38. Sample Storm Wind Swath

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

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

41. Couple Hurricane Model to Storm Surge Model (ADCIRC) Results for the Battery, New York City

42. Importance of Potential Intensity in Controlling Tropical Cyclone Activity

43. Decomposition of Frequency Trends

44. Decomposition of PDI Trends

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

46. Last 20 years of 20 th century simulations 2. Years 2180-2200 of IPCC Scenario A1b (CO 2 stabilized at 720 ppm) 1. Last 20 years of 20 th century simulations 2. Years 2180-2200 of IPCC Scenario A1b (CO 2 stabilized at 720 ppm) Compare two simulations each from 7 IPCC models:

47. U.S. Coastal Damage Potential

48. Northeast U.S. Damage Function

49. Application to the Climate of the Pliocene Application to the Climate of the Pliocene with Alexey Federov and Chris Brierley, Yale

50. 50 Pacific ocean SSTs

51. 51 ; Indo-Pacific ; Atlantic Mg/Ca – solid boxes Alkenone – open Pacific ocean SSTs Brierley, Fedorov, Liu, Herbert, Lawrence, LaRiviere 2009, Science 4Ma

52. 52 Pacific ocean SSTs 4Ma ; Indo-Pacific ; Atlantic Mg/Ca – solid boxes Alkenone – open Brierley, Fedorov, Liu, Herbert, Lawrence, LaRiviere 2009, Science

53. 53 Tropical warm pool (observations) Hypothetical warm pool in the early Pliocene (~4Ma) oCoC oCoC

58. Summary Potential intensity is an important (but not the only!) control on tropical cyclone activity On time scales long enough for the ocean mixed layer to be in thermal equilibrium, potential intensity is controlled largely by surface radiation, surface wind speed, ocean heat fluxes, and outflow temperature

59. Simple but high resolution coupled TC model can be used to ‘downscale” TC activity from global climate data sets Studies based on this downscaling suggest large sensitivity of TCs to climate state, and possibly important role for TC-induced ocean mixing in regulating climate