Workshop on Climate Sensitivity - Index of

IPCC <strong>Workshop</strong> on Climate Sensitivity
Paris, France, July 26–29, 2004
Pre-Conference Volume
A Comparison of Climate Sensitivity Among the Japanese Models
Akio Kitoh 1 , Akira Noda 1 , Seiji Yukimoto 1 , Seita Emori 2 , Toru Nozawa 2 , Tomoo Ogura 2 , Masahide
Kimoto 3 , Ayako Abe-Ouchi 3 , and Akimasa Sumi 3
1 Meteorological Research Institute, Tsukuba, Japan
2 National Institute for Environmental Studies, Tsukuba, Japan
3 Center for Climate System Research, University of Tokyo, Tokyo, Japan
1. Introduction
Two Japanese models (MRI and CCSR/NIES models)
showed the smallest and the largest climate sensitivity
at the time of the IPCC TAR in 2001. Here we report
recent changes in their models’ climate sensitivity.
2. MRI model
The MRI-CGCM2 (Yukimoto et al. 2001; Yukimoto and
Noda 2002) has several versions depending on cloudradiation
tuning. In its radiation scheme, CO , H O, 2 2
O , CH and N O are treated as the greenhouse effect
3 4 2
gases directly, and the direct effect of sulfate aerosol is
explicitly treated, but the indirect effect is not included.
For the AR4 scenario experiments, atmospheric
concentration of sulfate aerosols has been calculated
for all SRES emission scenarios of sulfur dioxide by
a chemical transport model MASINGER developed at
MRI (Tanaka et al. 2003). The global mean surface air
temperature rises about 2.4K, 2.7K and 2.0K at the end
of the 21st century compared to the 1961-1990 value in
A1B, A2 and B2 scenarios, respectively (Uchiyama et
al. 2004).
IPCC <strong>Workshop</strong> on Climate Sensitivity – 51
The global and annual mean surface air temperature
change at 2xCO 2 of the MRI-CGCM2.0 in the IPCC
TAR was very small, that is, 1.1K, with effective
climate sensitivity of 1.4K. In this simulation, the
energy budget was not balanced between the top and
the bottom of atmosphere, and the global mean and
meridional distribution of radiative flux at the top of
atmosphere had a large difference from the observation.
The revised MRI-CGCM2.3 is improved in reproducing
mean climate of global-mean and meridional
distribution of energy budget by mainly adjusting clouds
representation. With the improved version of the model,
the effective climate sensitivity increased more than 1K.
The decrease of negative feedback due to cloud forcing
can explain most of the changes in climate sensitivity.
The major difference of cloud feedback can be explained
by the change in tropical low-level clouds for shortwave
forcing and in tropical middle level clouds for longwave
forcing. Associated with the tropical low-level clouds,
the stratus and stratocumulus clouds over the eastern
part of the oceans (especially over the eastern Pacific)
have large impact on shortwave forcing. The change in
the tropical middle level clouds is associated with the
change in deep convective clouds.
Figure 1. Zonally averaged annual mean cloud amount change normalized by global-mean surface air temperature change for (left)
MRI-CGCM2.0 and (right) MRI-CGCM2.3.