Determining Longwave Forcing and Feedback Using Infrared Spectra and GNSS Radio Occultation

Yi Huang Department of Earth and Planetary Sciences and the School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts

Search for other papers by Yi Huang in
Current site
Google Scholar
PubMed
Close
,
Stephen S. Leroy Department of Earth and Planetary Sciences and the School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts

Search for other papers by Stephen S. Leroy in
Current site
Google Scholar
PubMed
Close
, and
James G. Anderson Department of Earth and Planetary Sciences and the School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts

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

Abstract

The authors investigate whether combining a data type derived from radio occultation (RO) with the infrared spectral data in an optimal detection method improves the quantification of longwave radiative forcing and feedback. Signals derived from a doubled-CO2 experiment in a theoretical study are used. When the uncertainties in both data types are conservatively estimated, jointly detecting the feedbacks of tropospheric temperature and water vapor, stratospheric temperature, and high-level cloud from the two data types should reduce the mean errors by more than 50%. This improvement is achieved because the RO measurement helps disentangle the radiance signals that are ambiguous in the infrared spectrum. The result signifies the complementary information content in infrared spectral and radio occultation data types, which can be effectively combined in optimal detection to accurately quantify the longwave radiative forcing and feedback. The results herein show that the radiative forcing of CO2 and the longwave radiative feedbacks of tropospheric temperature, tropospheric water vapor, and stratospheric temperature can be accurately quantified from the combined data types, with relative errors in their global mean values being less than 4%, 10%, 15%, and 20%, respectively.

Corresponding author address: Yi Huang, 12 Oxford St., Link 284, Cambridge, MA 02138. Email: yihuang@huarp.harvard.edu

Abstract

The authors investigate whether combining a data type derived from radio occultation (RO) with the infrared spectral data in an optimal detection method improves the quantification of longwave radiative forcing and feedback. Signals derived from a doubled-CO2 experiment in a theoretical study are used. When the uncertainties in both data types are conservatively estimated, jointly detecting the feedbacks of tropospheric temperature and water vapor, stratospheric temperature, and high-level cloud from the two data types should reduce the mean errors by more than 50%. This improvement is achieved because the RO measurement helps disentangle the radiance signals that are ambiguous in the infrared spectrum. The result signifies the complementary information content in infrared spectral and radio occultation data types, which can be effectively combined in optimal detection to accurately quantify the longwave radiative forcing and feedback. The results herein show that the radiative forcing of CO2 and the longwave radiative feedbacks of tropospheric temperature, tropospheric water vapor, and stratospheric temperature can be accurately quantified from the combined data types, with relative errors in their global mean values being less than 4%, 10%, 15%, and 20%, respectively.

Corresponding author address: Yi Huang, 12 Oxford St., Link 284, Cambridge, MA 02138. Email: yihuang@huarp.harvard.edu

Save
  • Bell, T., 1986: Theory of optimal weighting of data to detect climate change. J. Atmos. Sci., 43 , 16941710.

  • Bernstein, L., A. Berk, P. Acharya, D. Robertson, G. Anderson, J. Chetwynd, and L. Kimball, 1996: Very narrow band model calculations of atmospheric fluxes and cooling rate. J. Atmos. Sci., 53 , 28872904.

    • Search Google Scholar
    • Export Citation
  • Bony, S. Coauthors 2006: How well do we understand and evaluate climate change feedback processes? J. Climate, 19 , 34453482.

  • Goody, R., J. Anderson, and G. North, 1998: Testing climate models: An approach. Bull. Amer. Meteor. Soc., 79 , 25412549.

  • Haskins, R., R. Goody, and L. Chen, 1999: Radiance covariance and climate models. J. Climate, 12 , 14091422.

  • Hasselmann, K., 1997: Multi-pattern fingerprint method for detection and attribution of climate change. Climate Dyn., 13 , 601611.

  • Huang, Y., and V. Ramaswamy, 2009: Evolution and trend of outgoing longwave radiation spectrum. J. Climate, 22 , 46374651.

  • Huang, Y., V. Ramaswamy, X. Huang, Q. Fu, and C. Bardeen, 2007a: A strict test in climate modeling with spectrally resolved radiances: GCM simulation versus AIRS observations. Geophys. Res. Lett., 34 , L24707. doi:10.1029/2007GL031409.

    • Search Google Scholar
    • Export Citation
  • Huang, Y., V. Ramaswamy, and B. Soden, 2007b: An investigation of the sensitivity of the clear-sky outgoing longwave radiation to atmospheric temperature and water vapor. J. Geophys. Res., 112 , D05104. doi:10.1029/2005JD006906.

    • Search Google Scholar
    • Export Citation
  • Huang, Y., S. Leroy, P. Gero, J. Dykema, and J. Anderson, 2010: Separation of longwave climate feedbacks from spectral observations. J. Geophys. Res., 115 , D07104. doi:10.1029/2009JD012766.

    • Search Google Scholar
    • Export Citation
  • Kiehl, J., 1983: Satellite detection of effects due to increased atmospheric carbon dioxide. Science, 222 , 504506.

  • Kursinski, E., G. Hajj, J. Schofield, R. Linfield, and K. Hardy, 1997: Observing Earth’s atmosphere with radio occultation measurements using the Global Positioning System. J. Geophys. Res., 102 , (D19). 2342923465.

    • Search Google Scholar
    • Export Citation
  • Leroy, S., 1997: Measurement of geopotential heights by GPS radio occultation. J. Geophys. Res., 102 , (D6). 69716986.

  • Leroy, S., and G. North, 2000: The application of COSMIC data to global change research. Terr. Atmos. Ocean. Sci., 11 , 187210.

  • Leroy, S., and J. Anderson, 2010: Optimal detection of regional trends using global data. J. Climate, 23 , 44384446.

  • Leroy, S., J. Anderson, and J. Dykema, 2006: Testing climate models using GPS radio occultation: A sensitivity analysis. J. Geophys. Res., 111 , D17105. doi:10.1029/2005JD006145.

    • Search Google Scholar
    • Export Citation
  • Leroy, S., J. Anderson, J. Dykema, and R. Goody, 2008: Testing climate models using thermal infrared spectra. J. Climate, 21 , 18631875.

    • Search Google Scholar
    • Export Citation
  • McClatchey, R., R. Fenn, J. Selby, R. Voltz, and J. Garing, 1972: Optical Properties of the Atmosphere. Air Force Cambridge Research Laboratories, 108 pp.

    • Search Google Scholar
    • Export Citation
  • North, G., K. Kim, S. Shen, and J. Hardin, 1995: Detection of forced climate signals. I: Filter theory. J. Climate, 8 , 401408.

  • Rodgers, C., 2000: Inverse Methods for Atmospheric Sounding: Theory and Practice. World Scientific, 238 pp.

  • Slingo, A., and M. Webb, 1997: The spectral signature of global warming. Quart. J. Roy. Meteor. Soc., 123 , 293307.

  • Smith, E., and S. Weintraub, 1953: The constants in the equation for atmospheric refractive index at radio frequencies. Proc. IEEE, 41 , 10351037.

    • Search Google Scholar
    • Export Citation
  • Solomon, S., D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. Tignor, H. L. Miller Jr., and Z. Chen, Eds. 2007: Climate Chance 2007: The Physical Science Basis. Cambridge University Press, 996 pp.

    • Search Google Scholar
    • Export Citation
  • Wetherald, R., and S. Manabe, 1988: Cloud feedback processes in a general circulation model. J. Atmos. Sci., 45 , 13971415.

  • Williams, K., and M. Webb, 2009: A quantitative performance assessment of cloud regimes in climate models. Climate Dyn., 33 , 141157.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 386 153 27
PDF Downloads 142 45 1