Open AccessRadiative forcing by well‐mixed greenhouse gases: Estimates from climate models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)
Author(s) -
Collins W. D.,
Ramaswamy V.,
Schwarzkopf M. D.,
Sun Y.,
Portmann R. W.,
Fu Q.,
Casanova S. E. B.,
Dufresne J.L.,
Fillmore D. W.,
Forster P. M. D.,
Galin V. Y.,
Gohar L. K.,
Ingram W. J.,
Kratz D. P.,
Lefebvre M.P.,
Li J.,
Marquet P.,
Oinas V.,
Tsushima Y.,
Uchiyama T.,
Zhong W. Y.
Publication year - 2006
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2005jd006713
Subject(s) - radiative forcing , greenhouse gas , forcing (mathematics) , climatology , radiative transfer , environmental science , climate change , climate model , atmospheric sciences , cloud forcing , meteorology , physics , ecology , biology , geology , quantum mechanics
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 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 CO 2 , CH 4 , N 2 O, CFC‐11, CFC‐12, and the increased H 2 O 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) Fourth 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 CH 4 and N 2 O, 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 multimodel ensemble of AOGCM simulations assembled for the IPCC AR4.