• Chou, M-D., , and M. J. Suarez, 1999: A solar radiation parameterization for atmospheric studies. NASA Tech. Memo. 104606, Vol. 15, 40 pp.

    • Search Google Scholar
    • Export Citation
  • Chou, M-D., , M. J. Suarez, , X-Z. Liang, , and M-H. Yan, 2001: A thermal infrared radiation parameterization for atmospheric studies. NASA Tech. Memo. 104609, Vol. 19, 56 pp.

    • Search Google Scholar
    • Export Citation
  • Collins, W. D., and Coauthors, 2006: Radiative forcing by well-mixed greenhouse gases: Estimates from climate models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). J. Geophys. Res., 111 , D14317. doi:10.1029/2005JD006713.

    • Search Google Scholar
    • Export Citation
  • Edwards, J. M., , and A. Slingo, 1996: Studies with a flexible new shortwave radiation code. I, Choosing a configuration for a large-scale model. Quart. J. Roy. Meteor. Soc., 122 , 689719.

    • Search Google Scholar
    • Export Citation
  • Fomichev, V. I., , J-P. Blanchet, , and D. S. Turner, 1998: Matrix parameterization of the 15-μm CO2 band cooling in the middle and upper atmosphere for variable CO2 concentration. J. Geophys. Res., 103 , (D10). 1150511528.

    • Search Google Scholar
    • Export Citation
  • Fomichev, V. I., , V. P. Ogibalov, , and S. R. Beagley, 2004: Solar heating by the near-IR CO2 bands in the mesosphere. Geophys. Res. Lett., 31 , L21102. doi:10.1029/2004GL020324.

    • Search Google Scholar
    • Export Citation
  • Forster, P., and Coauthors, 2007: Changes in atmospheric constituents and in radiative forcing. Climate Change 2007: The Physical Science Basis. S. Solomon et al., Eds., Cambridge University Press, 130–234. [Available online at http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-chapter2.pdf].

    • Search Google Scholar
    • Export Citation
  • Fouquart, Y., , and B. Bonnel, 1980: Computation of solar heating of the Earth’s atmosphere: A new parameterization. Beitr. Phys. Atmos., 53 , 3562.

    • Search Google Scholar
    • Export Citation
  • Fu, Q., , and K. N. Liou, 1992: On the correlated k-distribution method for radiative transfer in nonhomogeneous atmospheres. J. Atmos. Sci., 49 , 21392156.

    • Search Google Scholar
    • Export Citation
  • Fueglistaler, S., , A. E. Dessler, , T. J. Dunkerton, , I. Folkins, , Q. Fu, , and P. W. Mote, 2009: Tropical tropopause layer. Rev. Geophys., 47 , RG1004. doi:10.1029/2008RG000267.

    • Search Google Scholar
    • Export Citation
  • Gettelman, A., and Coauthors, cited 2010: SPARC CCMVal Report. SPARC Rep. 5, WCRP-X, WMO/TD-No. X. [Available online at http://www.atmosp.physics.utoronto.ca/SPARC].

    • Search Google Scholar
    • Export Citation
  • Gleckler, P., 1996: AMIP-II guidelines. Atmospheric Model Intercomparison Project Newsletter 8, 24 pp. [Available online at http://www-pcmdi.llnl.gov/projects/amip/NEWS/amipnl8.pdf].

    • Search Google Scholar
    • Export Citation
  • Holling, H-D., 1993: A k distribution method considering centres and wings of atmospheric absorption lines. J. Geophys. Res., 98 , 27472756.

    • Search Google Scholar
    • Export Citation
  • Kato, S., , T. P. Ackerman, , J. H. Mather, , and E. E. Clothiaux, 1999: The k-distribution method and correlated-k approximation for a shortwave radiative transfer model. J. Quant. Spectrosc. Radiat. Transfer, 62 , 109121.

    • Search Google Scholar
    • Export Citation
  • Kratz, D. P., 1995: The correlated-k distribution technique as applied to the AVHRR channels. J. Quant. Spectrosc. Radiat. Transfer, 53 , 501517.

    • Search Google Scholar
    • Export Citation
  • Lacis, A. A., , and J. Hansen, 1971: A parameterization for the absorption of solar radiation in the earth’s atmosphere. J. Atmos. Sci., 31 , 118133.

    • Search Google Scholar
    • Export Citation
  • Lacis, A. A., , and V. Oinas, 1991: A description of the correlated k distribution method modeling nongray gaseous absorption, thermal emission, and multiple scattering in vertically inhomogeneous atmospheres. J. Geophys. Res., 96 , 90279063.

    • Search Google Scholar
    • Export Citation
  • Li, J., 2000: Gaussian quadrature and its application to infrared radiation. J. Atmos. Sci., 57 , 753765.

  • Li, J., 2002: Accounting for unresolved clouds in a 1D infrared radiative transfer model. Part I: Solution for radiative transfer, cloud scattering, and overlap. J. Atmos. Sci., 59 , 33023320.

    • Search Google Scholar
    • Export Citation
  • Li, J., , and H. W. Barker, 2005: A radiation algorithm with correlated-k distribution. Part I: Local thermal equilibrium. J. Atmos. Sci., 62 , 286309.

    • Search Google Scholar
    • Export Citation
  • Liou, K. N., 2002: An Introduction to Atmospheric Radiation. 2nd ed. Academic Press, 577 pp.

  • López-Puertas, M., , and F. W. Taylor, 2001: Non-LTE Radiative Transfer in the Atmosphere. World Scientific, 447 pp.

  • McClatchey, R. A., , R. W. Fenn, , J. E. A. Selby, , F. E. Volz, , and J. S. Garing, 1972: Optical properties of the atmosphere. 3rd ed. AFCRL-72-0497 (NTIS N7318412), 108 pp.

    • Search Google Scholar
    • Export Citation
  • McFarlane, N. A., , J. F. Scinocca, , M. Lazare, , R. Harvey, , D. Verseghy, , and J. Li, 2005: The CCCma third generation atmospheric general circulation model. CCCma Internal Rep., CCCma, 40 pp. [Available online at http://www.cccma.ec.gc.ca/papers/jscinocca/AGCM3_report.pdf].

    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., , S. J. Taubman, , P. D. Brown, , M. J. Iacono, , and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 , 1666316682.

    • Search Google Scholar
    • Export Citation
  • Randel, W. J., , F. Wu, , J. M. Russell, , A. Roche, , and J. W. Waters, 1998: Seasonal cycles and QBO variations in stratospheric CH4 and H2O observed in UARS HALOE data. J. Atmos. Sci., 55 , 163185.

    • Search Google Scholar
    • Export Citation
  • Scinocca, J. F., , N. A. McFarlane, , M. Lazare, , J. Li, , and D. Plummer, 2008: Technical note: The CCCma third generation AGCM and its extension into the middle atmosphere. Atmos. Chem. Phys., 8 , 70557074.

    • Search Google Scholar
    • Export Citation
  • Shi, G., , N. Xu, , B. Wang, , T. Dai, , and J. Zhao, 2009: An improved treatment of overlapping absorption bands based on the correlated k distribution model for thermal infrared radiative transfer calculations. J. Quant. Spectrosc. Radiat. Transfer, 110 , 435451. doi:10.1016/j.jqsrt.2009.01.008.

    • Search Google Scholar
    • Export Citation
  • Strobel, D. F., 1978: Parameterization of the atmospheric heating rate from 15 to 120 km due to O2 and O3 absorption of solar radiation. J. Geophys. Res., 83 , 62256230.

    • Search Google Scholar
    • Export Citation
  • Sun, Z., 2008: Development of the Sun–Edwards–Slingo radiation scheme (SES2). CAWCR Tech. Rep. 009, 73 pp.

  • Sun, Z., , and L. Rikus, 1999: Improved application of exponential sum fitting transmissions to inhomogeneous atmosphere. J. Geophys. Res., 104 , 62916303.

    • Search Google Scholar
    • Export Citation
  • Zhang, H., , T. Nakajima, , G. Shi, , T. Suzuki, , and R. Imasu, 2003: An optional approach to overlapping bands with correlated k distribution method and its application to radiative transfer calculations. J. Geophys. Res., 108 , 4641. doi:10.1029/2002JD003358.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 59 59 15
PDF Downloads 51 51 14

Overlap of Solar and Infrared Spectra and the Shortwave Radiative Effect of Methane

View More View Less
  • 1 Canadian Centre for Climate Modelling and Analysis, Science and Technology Branch, Environment Canada, University of Victoria, Victoria, British Columbia, Canada
  • | 2 Centre for Australian Weather and Climate Research, Australian Bureau of Meteorology, Melbourne, Victoria, Australia
  • | 3 Illinois State Water Survey, Department of Natural Resources, University of Illinois at Urbana—Champaign, Champaign, Illinois
© Get Permissions
Restricted access

Abstract

This paper focuses on two shortcomings of radiative transfer codes commonly used in climate models. The first aspect concerns the partitioning of solar versus infrared spectral energy. In most climate models, the solar spectrum comprises wavelengths less than 4 μm with all incoming solar energy deposited in that range. In reality, however, the solar spectrum extends into the infrared, with about 12 W m−2 in the 4–1000-μm range. In this paper a simple method is proposed wherein the longwave radiative transfer equation with solar energy input is solved. In comparison with the traditional method, the new solution results in more solar energy absorbed in the atmosphere and less at the surface.

As mentioned in a recent intercomparison of the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) and line-by-line (LBL) radiation models, most climate model radiation schemes neglect shortwave absorption by methane. However, the shortwave radiative forcing at the surface due to CH4 since the preindustrial period is estimated to exceed that due to CO2. The authors show that the CH4 shortwave effect can be included in a correlated k-distribution model, with the additional flux being accurately simulated in comparison with LBL models.

Ten-year GCM simulations are presented, showing the detailed climatic effect of these changes in radiation treatment. It is demonstrated that the inclusion of solar flux in the infrared range produces a significant amount of extra warming in the atmosphere, specifically (i) in the tropical stratosphere where the warming can exceed 1 K day−1, and (ii) near the tropical tropopause layer. Additional GCM simulations show that inclusion of CH4 in the shortwave calculations also produces a warming of the atmosphere and a consequent reduction of the upward flux at the top of the atmosphere.

Corresponding author address: Dr. Jiangnan Li, Canadian Center for Climate Modeling and Analysis, University of Victoria, P.O. Box 3065, Victoria, BC V8W 3V6, Canada. Email: jiangnan.li@ec.gc.ca

Abstract

This paper focuses on two shortcomings of radiative transfer codes commonly used in climate models. The first aspect concerns the partitioning of solar versus infrared spectral energy. In most climate models, the solar spectrum comprises wavelengths less than 4 μm with all incoming solar energy deposited in that range. In reality, however, the solar spectrum extends into the infrared, with about 12 W m−2 in the 4–1000-μm range. In this paper a simple method is proposed wherein the longwave radiative transfer equation with solar energy input is solved. In comparison with the traditional method, the new solution results in more solar energy absorbed in the atmosphere and less at the surface.

As mentioned in a recent intercomparison of the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) and line-by-line (LBL) radiation models, most climate model radiation schemes neglect shortwave absorption by methane. However, the shortwave radiative forcing at the surface due to CH4 since the preindustrial period is estimated to exceed that due to CO2. The authors show that the CH4 shortwave effect can be included in a correlated k-distribution model, with the additional flux being accurately simulated in comparison with LBL models.

Ten-year GCM simulations are presented, showing the detailed climatic effect of these changes in radiation treatment. It is demonstrated that the inclusion of solar flux in the infrared range produces a significant amount of extra warming in the atmosphere, specifically (i) in the tropical stratosphere where the warming can exceed 1 K day−1, and (ii) near the tropical tropopause layer. Additional GCM simulations show that inclusion of CH4 in the shortwave calculations also produces a warming of the atmosphere and a consequent reduction of the upward flux at the top of the atmosphere.

Corresponding author address: Dr. Jiangnan Li, Canadian Center for Climate Modeling and Analysis, University of Victoria, P.O. Box 3065, Victoria, BC V8W 3V6, Canada. Email: jiangnan.li@ec.gc.ca

Save