PCMDI

CAPT

Cloud Feedbacks

CMIP5

CMIP3

Other MIPs

Software

Publications

Google Calendar

Lab Calendar


Site Map

UCRL-WEB-152471

Privacy & Legal Notice

Thanks to Our Sponsors:

PCMDI > WCRP CMIP3 Model Output > Diagnostic Subprojects Printer Friendly Version
 
<< Back to WCRP CMIP3 Subprojects

  • Collins, W.D., V. Ramaswamy, M.D. Schwarzkopf, Y. Sun, R. Portmann, Q. Fu, S. Casanova, J.L. Dufresne, D. Fillmore, P. Forster, V. Galin, L. Gohar, W. Ingram, D. Kratz, M.-P. Lefebvre, J. Li, P. Marquet, V. Oinas, Y. Tsushima, T. Uchiyama, and W. Zhong, Radiative forcing by well-mixed greenhouse gases: Estimates from climate models in the IPCC AR4. J. Geophys. Res.. Accepted.

The radiative effects from increased concentrations of well-mixed greenhouse gases (WMGHGs) represent the most significant and best understood anthropogenic forcing of the climate system. The most comprehensive tools for simulating past and future climates influenced by WMGHGs are fully coupled atmosphere-ocean general circulation models (AOGCMs). Because of the importance of WMGHGs as forcing agents, it is essential that AOGCMs compute the radiative forcing by these gases as accurately as possible. We present the results of a Radiative-Transfer Model Intercomparison (RTMIP) between the forcings computed by the radiative parameterizations of AOGCMs and by benchmark line-by-line (LBL) codes. The comparison is focused on forcing by CO2, CH4, N2O, CFC-11, CFC-12, and the increased H2O expected in warmer climates. The models included in the intercomparison include several LBL codes and most of the global models submitted to the Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report (AR4). In general, the LBL models are in excellent agreement with each other. However, in many cases, there are substantial discrepancies among the AOGCMs and between the AOGCMs and LBL codes. In some cases this is because the AOGCMs neglect particular absorbers, in particular the near-infrared effects of CH4 and N2O, while in others it is due to the methods for modeling the radiative processes. The biases in the AOGCM forcings are generally largest at the surface level. We quantify these differences and discuss the implications for interpreting variations in forcing and response across the multi-model ensemble of AOGCM simulations assembled for the IPCC AR4.


Full Article: http://www.cgd.ucar.edu/cms/wcollins/papers/rtmip.pdf

Last Updated: 2006-03-02

<< Back to WCRP CMIP3 Subprojects
 
For questions or comments regarding this website, please contact the Webmaster.
 
Lawrence Livermore National Laboratory  |  Physical & Life Sciences Directorate