Validating Atmospheric Reanalysis Data using Tropical Cyclones as Thermometers

James P. Kossin NOAA/National Climatic Data Center, Asheville, North Carolina

Search for other papers by James P. Kossin in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

Temperatures in the upper troposphere of the atmosphere, near the tropopause, play a key role in the evolution of tropical cyclones (TC) by controlling their potential intensity (PI), which describes the thermodynamically based maximum TC intensity that the environment will support. Accurately identifying past trends in PI is critical for understanding the causes of observed changes in TC intensity, but calculations of PI trends using different atmospheric reanalysis products can give very different results, largely due to differences in their representation of upper-tropospheric temperatures. Without a means to verify the fidelity of the upper-tropospheric temperatures, PI trends calculated from these products are very uncertain.

Here, a method is introduced to validate the upper-tropospheric temperatures in the reanalysis products by using the TCs themselves as thermometers. Using a 30-yr global dataset of TC cloud-top temperatures and three widely utilized atmospheric reanalysis products—Modern-Era Retrospective Analysis for Research and Applications (MERRA), ECMWF interim reanalysis (ERA-Interim), and NCEP–NCAR Global Reanalysis 1—it is shown that storm-local upper-level temperatures in the MERRA and ERA-Interim data vary similarly to the TC cloud-top temperatures on both interannual and decadal time scales, but the NCEP–NCAR data have substantial biases that introduce an increasing trend in storm-local PI not found in the other two products. The lack of global storm-local PI trends is due to a balance between temporal increases in the mean state and the poleward migration of TCs into lower climatological PI, and it has significant implications for the detection and attribution of mean TC intensity trends.

CORRESPONDING AUTHOR: James Kossin, NOAA/Cooperative Institute for Meteorological Satellite Studies, 1225 West Dayton Street, Madison, WI 53706, E-mail: james.kossin@noaa.gov

Abstract

Temperatures in the upper troposphere of the atmosphere, near the tropopause, play a key role in the evolution of tropical cyclones (TC) by controlling their potential intensity (PI), which describes the thermodynamically based maximum TC intensity that the environment will support. Accurately identifying past trends in PI is critical for understanding the causes of observed changes in TC intensity, but calculations of PI trends using different atmospheric reanalysis products can give very different results, largely due to differences in their representation of upper-tropospheric temperatures. Without a means to verify the fidelity of the upper-tropospheric temperatures, PI trends calculated from these products are very uncertain.

Here, a method is introduced to validate the upper-tropospheric temperatures in the reanalysis products by using the TCs themselves as thermometers. Using a 30-yr global dataset of TC cloud-top temperatures and three widely utilized atmospheric reanalysis products—Modern-Era Retrospective Analysis for Research and Applications (MERRA), ECMWF interim reanalysis (ERA-Interim), and NCEP–NCAR Global Reanalysis 1—it is shown that storm-local upper-level temperatures in the MERRA and ERA-Interim data vary similarly to the TC cloud-top temperatures on both interannual and decadal time scales, but the NCEP–NCAR data have substantial biases that introduce an increasing trend in storm-local PI not found in the other two products. The lack of global storm-local PI trends is due to a balance between temporal increases in the mean state and the poleward migration of TCs into lower climatological PI, and it has significant implications for the detection and attribution of mean TC intensity trends.

CORRESPONDING AUTHOR: James Kossin, NOAA/Cooperative Institute for Meteorological Satellite Studies, 1225 West Dayton Street, Madison, WI 53706, E-mail: james.kossin@noaa.gov
Save
  • Bister, M., and K. A. Emanuel, 1998: Dissipative heating and hurricane intensity. Meteor. Atmos. Phys., 65, 233240, doi:10.1007/BF01030791.

    • Search Google Scholar
    • Export Citation
  • Christensen, J. H., and Coauthors, 2013: Climate phenomena and their relevance for future regional climate change. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 1217–1308.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation
  • Elsner, J. B., J. P. Kossin, and T. H. Jagger, 2008: The increasing intensity of the strongest tropical cyclones. Nature, 455, 9295, doi:10.1038/nature07234.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1999: Thermodynamic control of hurricane intensity. Nature, 401, 665669, doi:10.1038/44326.

  • Emanuel, K. A., 2000: A statistical analysis of hurricane intensity. Mon. Wea. Rev., 128, 11391152, doi:10.1175/1520-0493(2000)128<1139:ASAOTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., S. Solomon, D. Folini, S. Davis, and C. Cagnazzo, 2013: Influence of tropical tropopause layer cooling on Atlantic hurricane activity. J. Climate, 26, 22882301, doi:10.1175/JCLI-D-12-00242.1.

    • Search Google Scholar
    • Export Citation
  • Holz, R. E., S. Ackerman, P. Antonelli, F. Nagle, and R. O. Knuteson, 2006: An improvement to the high-spectral-resolution CO2-slicing cloud-top altitude retrieval. J. Atmos. Oceanic Technol., 23, 653670, doi:10.1175/JTECH1877.1.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83, 16311643, doi:10.1175/BAMS-83-11-1631.

    • Search Google Scholar
    • Export Citation
  • Knapp, K. R., and J. P. Kossin, 2007: New global tropical cyclone data set from ISCCP B1 geostationary satellite observations. J. Appl. Remote Sens., 1, 013505, doi:10.1117/1.2712816.

    • Search Google Scholar
    • Export Citation
  • Knapp, K. R., M. C. Kruk, D. H. Levinson, H. J. Diamond, and C. J. Neumann, 2010: The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying tropical cyclone data. Bull. Amer. Meteor. Soc., 91, 363376, doi:10.1175/2009BAMS2755.1.

    • Search Google Scholar
    • Export Citation
  • Knutson, T. R., and Coauthors, 2010: Tropical cyclones and climate change. Nat. Geosci., 3, 157163, doi:10.1038/ngeo779.

  • Kossin, J. P., and S. J. Camargo, 2009: Hurricane track variability and secular potential intensity trends. Climatic Change, 97, 329337, doi:10.1007/s10584-009-9748-2.

    • Search Google Scholar
    • Export Citation
  • Kossin, J. P., T. L. Olander, and K. R. Knapp, 2013: Trend analysis with a new global record of tropical cyclone intensity. J. Climate, 26, 99609976, doi:10.1175/JCLI-D-13-00262.1.

    • Search Google Scholar
    • Export Citation
  • Kossin, J. P., K. A. Emanuel, and G. A. Vecchi, 2014: The poleward migration of the location of tropical cyclone maximum intensity. Nature, 509, 349352, doi:10.1038/nature13278.

    • Search Google Scholar
    • Export Citation
  • Rienecker, M., and Coauthors, 2011: MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 36243648, doi:10.1175/JCLI-D-11-00015.1.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., and Coauthors, 2012: Changes in climate extremes and their impacts on the natural physical environment. Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, C. B. Field et al., Eds., Cambridge University Press, 109–230.

    • Search Google Scholar
    • Export Citation
  • Vecchi, G. A., S. Fueglistaler, I. M. Held, T. R. Knutson, and M. Zhao, 2013: Impacts of atmospheric temperature trends on tropical cyclone activity. J. Climate, 26, 38773891, doi:10.1175/JCLI-D-12-00503.1.

    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. 2nd ed. International Geophysics Series, Vol. 91, Academic Press, 627 pp.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1338 544 269
PDF Downloads 508 116 13