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An Assessment of Low Frequency Variability in Tropical Cyclones in the North Atlantic Basin.

Philip J. Pegion GMAO Goddard Space Flight Center, SAIC Siegfried D. Schubert, Max Suarez GMAO Goddard Space Flight Center Julio Bacmeister GEST,GMAO Kerry Emanuel Department of Earth, Atmospheric, and Planetary Sciences, MIT, Cambridge, MA.

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An Assessment of Low Frequency Variability in Tropical Cyclones in the North Atlantic Basin.

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  1. Philip J. Pegion GMAO Goddard Space Flight Center, SAIC Siegfried D. Schubert, Max Suarez GMAO Goddard Space Flight Center Julio Bacmeister GEST,GMAO Kerry Emanuel Department of Earth, Atmospheric, and Planetary Sciences, MIT, Cambridge, MA An Assessment of Low Frequency Variability in Tropical Cyclones in the North Atlantic Basin.

  2. The hurricane Best Track Dataset shows an increase in the number of storms over the 20th Century as well as an increase in the intensity of these storms. The questions we have are: How much of the variability is due to decadal changes in Tropical Atlantic SSTs? How much of the variability is due to a Global Warming 'trend' or to differences in the observing system? Does an AGCM forced with observed SSTs capture this variability? Motivation

  3. Black Dots: Annual values Red-line: decadal filter Atlantic Basin ACE ∑ Vmax2/104 PDI ∫Vmax3 dt / 1010

  4. Atlantic Tropical Cyclones: Normalized Annual Means Annual Means Filtered to remove timescales less then 14 years. Year

  5. Atlantic Tropical Cyclones: Normalized Annual Means Entire Basin Main Development Region 20 - 80W 10-20N Rest of Basin Year

  6. Seasonal Genesis Parameter (Gray 1979) SGP=Vorticity*Coriolis*Shear*Thermal energy*Moist stability *RH Genesis Potential Index (Emanuel and Nolan 2004) GPI=Absolute vorticity*RH * Potential Intensity * Shear Does a AGCM represent this variability? Model: NASA NSIPP AGCM, 22 member ensemble run from 1902-2006. Since simulations are run at 3x3.5 degrees. Model is not explicitly able to represent tropical cyclones, so we used an index to represent tropical cyclones.

  7. Low Pass of the Data (timescales > 13 years) Year

  8. Low Pass of the Data (timescales > 13 years) Largest difference in recent period. Year

  9. Contribution of each term Vorticity Terms Relative Humidity SGP GPI Potential Intensity/ Heat Content+Stability Wind Shear

  10. Data:IPCC 4th Net Assessment Climate of the 20th Century Simulations NCAR ccm3 (6 ensemble members) ECHAM4 (4 ensemble members) GFDL cm2_0 and cm2_1 (3-members each) Are the fluctuations natural variability, or a response to global warming?

  11. Results from IPCC runs SGP GPI Year Year Model's show a general increase in SGP over the century, GPI is flat. Lack multi-decadal variability (individual member's don't show it either)

  12. Potential Intensity/ Heat Content+Stability Year Year

  13. Why is potential Intensity Decreasing even though SSTs are increasing? Correlations with SST Named Storms SGP PDI GPI

  14. Correlation of GPI and SST. Strong anti correlation with Indian Ocean SST. Global Mean SST removed

  15. SST over Main Development Region

  16. Atlantic MDR SST from IPCC model’s IPCC Models show a general warming of the Atlantic SST, but lack the Decadal variability indicated by the observations.

  17. Atlantic MDR SST from IPCC model’s (ensemble mean)

  18. Less Stable More Stable Air Temperature over Main Development Region Wildly different answers from the different reanalyses. Only JRA-25 agrees with the models. Warming of the upper troposphere is increasing stability over the Atlantic

  19. The changes of number of tropical cyclones matches the variability of SST over the Atlantic Main Development Region, but the same is not true for power dissipation, which only shows decadal variability. Atmospheric model derived indices show similar decadal variability, but differences arise in the long term trend. The SGP, which defines heat content referenced to 26oC, shows a trend, but the GPI, which calculates stability, shows only decadal variability from the AGCM, and no change from the IPCC runs. Looking forward to new reanalyses such as MERRA, CFSRR to get more confidence on the nature of the changes in the modern period, and am very interested in getting data from the “The 20th Century Reanalysis Project” Summary

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