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Tropical cyclones in a warmer climate - a modeling study-

Tropical cyclones in a warmer climate - a modeling study-. Professor Lennart Bengtsson Max Planck Institute for Meteorology ESSC, University of Reading (Thanks to colleagues in UK, Germany and Japan). Tropical Cyclones in a warmer climate.

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Tropical cyclones in a warmer climate - a modeling study-

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  1. Tropical cyclones in a warmer climate- a modeling study- Professor Lennart Bengtsson Max Planck Institute for Meteorology ESSC, University of Reading (Thanks to colleagues in UK, Germany and Japan) MISU, Stockholm

  2. Tropical Cyclones in a warmer climate • Societal damages are to a large extent related to extreme weather mostly in association with tropical and extra-tropical cyclones • The cost for hurricane Katrina is estimated to some 200 G$ • There are many examples of great loss of life due to extreme tropical cyclones. • Damages are mostly related to high winds, flooding due to the high precipitation and in coastal areas to high sea-level and waves. • The question whether cyclones may intensify in a future climate is consequently an issue of primary importance for society. • This is further enhanced by the ongoing increased exposure to extreme weather independent of climate change. MISU, Stockholm

  3. Tropical cyclones in a future climatewhat could be expected? • Higher SST and higher atmospheric moisture would generally favor more intense storms ( e.g. Emanuel 1988, 1999) • This is supported by modeling results by Knutson and Tuleya (2004) driving an limited area model with CMIP2+ boundary data ( 9 different models). • Increasing vertical wind-shear and reduced relative humidity would counteract this tendency. Such influences occur in the tropical N. Atlantic during El Nino. • Some GCM indicate reduced number of cyclones in a warmer climate • How will the number of storms change? What are the general conditions controlling the number of tropical storms? • What are the critical conditions in modeling tropical storms? Are results from large scale models with limited resolution credible? MISU, Stockholm

  4. The Carnot cycle concept After Emanuel MISU, Stockholm

  5. Modeling approach • Direct simulation of tropical cyclones in a global GCM • Using limited area models at high resolution • Identifying climate predictors in a GCM (SST, vorticity, static stability, relative humidity, vertical wind-shear) MISU, Stockholm

  6. Simulation of tropical cyclones with a GCM • Typical criteria: • An identifiable vortex ( often at 850 hPa) • A minimum in the surface pressure • Surface wind speed above a given value (> 18m/s) • A warm core vortex ( reduced circulation with height) MISU, Stockholm

  7. Direct simulation of tropical cyclones in a global GCM • Disadvantage: Difficulties to resolve the intense features of a tropical storm • Examples of studies: Bengtsson et al. 1995, 1996, Tellus Sugi et al. 2002, JMS, Japan McDonald et al. 2005, Clim.Dyn. Chauvin et al. 2006, Clim Dyn. Oouchi et al. 2006, JMS, Japan Yoshimori et al. 2006, JMS, Japan MISU, Stockholm

  8. Effect of 2xCO2 From Bengtsson et al., 1996 (Tellus) ( number of cyclones /basin) MISU, Stockholm

  9. Using limited area models at high resolution • Disadvantages: Generation of storms, Large scale influences difficult to handle • Examples of studies: Knutson et al. 1998, Science Knutson and Tuleya, 1999, Clim. Dyn. Knutson and Tuleya, 2004, J Clim. MISU, Stockholm

  10. Impact of CO2-induced warming on simulated hurricane intensityKnutson and Tuleya (2004, J of Climate) • They used a high resolution limited area model driven by the SST and moisture of 9 CGCM from the CMIP 2+ project. • CMIP2 uses 1%yr-1 increase over an 80-year period implying an increase by a factor of 2.2. • Model calculations are undertaken in NW Pacific-, NE Pacific- and Atlantic basin • Four different convective schemes are tested (no significant differences) • RESULTS: • Max. surface wind speed increases by 6% • Min. central pressure by 14% • Max. precipitation by 24% • Hurricane increase by a factor of 1/2 in the Simpson-Saffir scale MISU, Stockholm

  11. Intensification of hurricanes at 2xCO2Knutson and Tuleya (2004) MISU, Stockholm

  12. Identifying climate predictors in a GCM • Disadvantage: Lack of proper understanding, ad hoc selection of predictors, overestimation of the effect of SST • Examples of studies Gray, 1979 Met. over the Tropical oceans, RMetSoc Royer et al. 1998, Clim. Change Chauvin et al. 2006, Clim. Dyn. MISU, Stockholm

  13. Objectives of the present studyTropical cyclones (TC) in ECHAM5 in the Northern Hemisphere(Using high global resolution) How do the TCs respond to anthropogenic climate change and how does this depend on resolution? What changes occur in intensity, life time and power dissipation index? What possible mechanisms control the change in TC? What are the dominant factors? MISU, Stockholm

  14. Tracking methods and vortex identification • Tracks are followed from its generation (6x10-6s-1) until it disappears as an extra-tropical cyclones north of 60N • We calculate the total life-time of the TCs • We are able to identify the transition from a tropical to an extra-tropical vortex • Alternatively we use the wind speed at 925 hPa as a selection criteria for intense storms • We have also calculated the potential dissipation index, PDI. See Emanuel, Nature, 2005 MISU, Stockholm

  15. Hurricane Katrina August 2005ECMWF operational analyses, 850 hPa vorticity MISU, Stockholm

  16. Katrina vorticity at different levels MISU, Stockholm

  17. Selection of TC indicators • We use criteria for minimum vorticity at 850 hPa (V), minimum vertical vorticity gradient (G) between 850 and 250 hPa, and number of time steps of 6 hrs (T) when these conditions are fulfilled. • (V, G, T) = (6, 6, 4) vorticity at 850 hPa = 6x10-5s-1 vorticity 850- 250 hPa = 6x10-5s-1 conditions fulfilled at least 24 hrs (6, 6, 4) is defined as a TC MISU, Stockholm

  18. All Tropical Storms Hurricanes, Typhoons, Cyclones >33ms-1 (6, 6, 4) (10, 6, 4) (12, 6, 4) 2003 75 33 71 48 39 2004 72 36 79 52 41 2005 80 38 83 62 48 Selection of criteria for selecting tropical storms (TC)(using ECMWF operational analyses) MISU, Stockholm

  19. Intensity v Speed (T213) MISU, Stockholm

  20. Objectives of the present studyTropical cyclones in ECHAM5 • We have used scenario A1B and studied the periods 1861-1890, 1961-1990 and 2071-2100 • We have explored the coupled T63 run (3 runs) for all periods and • T213 time - slice 1961-1990 and 2071-2100 • T319 time - slice 1971-1990, (2080-2100) • We have also used AMIP2 runs (20 years) with T63 and T159 as a validation study MISU, Stockholm

  21. Structure of modeled tropical cyclones This shows the averaged structure of the 100 most intense storms at the time when the reach their maximum intensity MISU, Stockholm

  22. Tangential (left) and Radial winds (right) for the T63 resolution. Negative values inflow. Average of 100 tropical cyclones. At the time of maximum wind. Radius 5 degrees. MISU, Stockholm South

  23. Tangential (left) and Radial winds (right) for the T213 resolution. Negative values inflow. Average of 100 tropical cyclones. Radius 5 degrees. The flow is predominantly inward to the rear and left of the storm and outward to the front and right (Frank 1977 MWR) Observations: MISU, Stockholm

  24. Tangential (left) and Radial winds (right) for the T319 resolution. Negative values inflow. Average of 100 tropical cyclones. Radius 5 degrees. MISU, Stockholm

  25. Hurricane Mitch, Oct -Nov. 1998Kepert 2006 JAS MISU, Stockholm

  26. Hurricane Mitch: Tangential winds (left) and Radial winds (right) at 500 m. Units: 5 m/sKepert 2006 JAS outflow West MISU, Stockholm

  27. Tangential wind cross section Temperature anomaly T63 resolution MISU, Stockholm

  28. Tangential wind cross section Temperature anomaly T213 resolution MISU, Stockholm

  29. Tangential wind cross section Temperature anomaly T319 resolution MISU, Stockholm

  30. Comparison with observations from the Tropical Warning Centers and with ERA-40 re-analyses MISU, Stockholm

  31. Super Typhoon 21 (1991) in ERA-40 (left)and selected similar storm in ECHAM5 (right)Intensity (vorticity at 850 hPa) MISU, Stockholm

  32. Lifetime of TCs in days MISU, Stockholm

  33. Hurricane genesis (a) observed, (b) ERA-40 and (c ) ECHAM5 T159 MISU, Stockholm

  34. Hurricane track density(a) observed, (b) ERA-40 and (c ) ECHAM5 T159 MISU, Stockholm

  35. Hurricane track density (Atlantic)(d) observed, (e) ERA-40 and (f ) ECHAM5 T159 MISU, Stockholm

  36. Are there observational evidence that tropical cyclones are becoming more intense? Why is it so difficult? • Longer term records are needed due to internal variability • There have been large changes in the observing systems making it easier to detect more tropical cyclones in later years. • Recent papers have used PDI ( time integral of max. wind cube) which is overly sensitive to observational accuracy • Model studies (e.g. Knutson and Tuleya, 2004) indicate small changes in intensity as of now which are hardly detectable MISU, Stockholm

  37. Are there observational evidence that tropical cyclones are becoming more intense? • YES • Webster et al. (2005), Science, Emanuel (2005), Nature, Sriver and Huber (2006), GRL • NO • Chan (2006), Science, Klotzbach ( 2006), GRL, Landsea et al. (2006), Science MISU, Stockholm

  38. There are recent claims that there is an increase in hurricane intensity ( e.g. Emanuel (2005), Webster et al. (2005) • Are these findings credible? • They are generally not supported by operational meteorologists • According to Knutson and Tuleya (2004) any changes are probably undetectable“for decades to come” • There are structural problems in the detection of trends • Changes in observing systems • Difficulties to separate a genuine change in storms from societal causes behind the huge increase in damages and damage cost MISU, Stockholm

  39. What may happen in a warmer climate?A modeling approach We have used the AIB scenario And the coupled MPI model at T63 resolution used in the IPCC 4th assessment Higher resolution experiments use the transient SST from T63 (time - window) We study C20 (1961- 1990) C21 ( 2071-2100) MISU, Stockholm

  40. What is A1B? • Middle of the line scenario • Carbon emission peaking in the 2050s (16 Gt/year) • CO2 reaching 450 ppm. in 2030 • CO2 reaching 700 ppm. in 2100 • SO2 peaking in 2020 then coming done to 20% thereof in 2100 MISU, Stockholm

  41. SST difference (C 21-C 20) MISU, Stockholm

  42. TCs at T63 resolution C19 (black), C20 (red) and C21(blue) MISU, Stockholm

  43. Hurricane genesis T213From top C21-C20, C21 and C20 MISU, Stockholm

  44. Hurricane track density, T213From top C21-C20, C21 and C20 MISU, Stockholm

  45. T213 T213 All (6, 6, 4) >18ms-1 >2x10-4 s-1 >33ms-1 >5x10-4 s-1 >50ms-1 >1x10-3 s-1 20C (1961-1990) 20C (1961-1990) 104 100 97 33 40 3.7 6.0 21C (2071-2100) 21C (2071-2100) 94 92 90 36 4.9 49 9.8 Number of TCs/year (T213) for C 20 and C21 for wind speed and vorticity MISU, Stockholm

  46. Changes of TCs in four NH regions (T213) MISU, Stockholm

  47. Change in TC lifetime (T213) MISU, Stockholm

  48. Change in min. surface pressure (T213) C21 C20 MISU, Stockholm

  49. Accumulated precipitation ( in mm and for an area with a radius of 5 degrees) along the track of the TCs for C20 and C21(T213)HTVs reaching >33ms-1 C20 C21 Total increase 30% MISU, Stockholm

  50. Climate change and the water cycle • Atmosphere appears to conserve relative humidity. This means that atmospheric water vapor follows Clausius- Clapeyron relation. (Held and Soden, 2006, J. Clim.) • We see an increase of 27% in atmospheric water vapor at C21 compared to C20 • Precipitation must be balanced by evaporation. Evaporation is driven by the surface energy balance which increases slower than atmospheric water vapor. In fact it can even diminish at a high aerosol concentration (ECHAM4). • Precipitation increases by 6% both globally and in the tropics • This means that the residence time of water in the atmosphere increases from 8.7 to 10.3 days or by 16%. MISU, Stockholm

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