How Well Do Multi-Decadal Global Climate Models Represent The Radiative Effect of Well-Mixed Greenhouse Gases? Part I

In a constructive exchange of views with Gavin Schmidt (see our comments on this posting), he alerted me to a Journal of Geophysical Research paper on a model intercomparison of the radiative transfer paramterizations used in a number of Atmosphere-Ocean General Circulation Models (AOGCMs). The paper is Collins, W. D., et al. (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.

I have read the excellent Collins et al 2006 paper, and since its implications to multi-decadal global modeling is so important, I have decided to post as a weblog.

Its experimental design is summarized as follows,

“In order to establish a common baseline, the background atmospheric state for all the calculations is a climatological midlatitude summer (MLS) atmospheric profile [Anderson et al., 1986]. Therefore all the calculations are performed using the same vertical profiles of temperature and the mixing ratio of O3. The profile of specific humidity is also held fixed except for calculation 4a (Table 1). The concentrations of WMGHGs are set to a constant mixing ratio with respect to dry air throughout the column. The standard MLS profile has been interpolated to 40 levels for the AOGCM groups and 459 levels for the LBL groups. As shown in Table 3, the comparison of forcings from AOGCM and LBL codes is not affected by the difference in resolution. Increasing resolution from 40 to 459 levels changes the longwave forcings at TOM and surface by less than approximately 0.01 W m−2. Changing the methods of temperature interpolation within each layer in the LBL calculations changes the longwave forcings by less than 0.02 W m−2. The input profiles are available from the RTMIP Web site atâ€?

Even with this standardization between AOGCMS, however, significant biases were found. A conclusion of the Collins et al study is that,

“The biases in the AOGCM forcings are generally largest at the surface level. For five out of seven surface shortwave forcings and four out of seven surface longwave forcings, differences between the mean AOGCM and LBL calculations are statistically significant. In addition, the largest biases in the shortwave and longwave forcings from all seven experiments occur at the surface layer.The reasonable accuracy of AOGCM forcings at TOM and the significant biases at the surface together imply that the effects of increased WMGHGs on the radiative convergence of the atmosphere are not accurately simulated.â€? [TOM=Top of the model].

This is a remarkable conclusion, as how can we accurately quantify the relative role of the radiative effect of CO2 when the radiation codes have such an uncertainty? Also, how can the multi-decadal global climate models be claimed as having skill when such uncertainty in radiative forcing, even in clear skies remain?

The link to “ucarâ€? listed in their paper, unfortunately, does not work. However, a search on the CGD web site found a relevant powerpoint presentation [].

A Conclusion listed on that talk is that

“Current AOGCM (radiation) codes exhibit unacceptably large differences relative to LBL benchmarksâ€?

[AOGCM = Atmospheric-Ocean General Circulation Models; LBL = line-by-line radiation codes]

The powerpoint also indicated a similarity in the formulation of most of the radiation codes used in the AOGCMs. The purpose of the powerpoint presentation is to present the rationale to develop a new radiation code. The new parameterization is called the Community Radiative Transfer Model (CouRT).

An important message from the Collins et al paper is that the existing AOGCM codes appear to be inadequate for the radiation physics that they are tasked to represent in the AOGCMs.

Part II of this discussion will be posted tomorrow.

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