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Abstract. We present an overview of state-of-the-art chemistry-climate and chemistry transport models that are used within phase 1 of the Chemistry-Climate Model Initiative (CCMI-1). The CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models' projections of the stratospheric ozone layer, tropospheric composition, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to which CCMI-1 recommendations for simulations have been followed is necessary to understand model responses to anthropogenic and natural forcing and also to explain intermodel differences. This becomes even more important given the ongoing development and the ever-growing complexity of these models. This paper also provides an overview of the available CCMI-1 simulations with the aim of informing CCMI data users.

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A new global climate model, MRI-CGCM3, has been developed at the Meteorological Research Institute (MRI). This model is an overall upgrade of MRI's former climate model MRI-CGCM2 series. MRI-CGCM3 is composed of atmosphere-land, aerosol, and ocean-ice models, and is a subset of the MRI's earth system model MRI-ESM1. Atmospheric component MRI-AGCM3 is interactively coupled with aerosol model to represent direct and indirect e¤ects of aerosols with a new cloud microphysics scheme. Basic experiments for pre-industrial control, historical and climate sensitivity are performed with MRI-CGCM3. In the pre-industrial control experiment, the model exhibits very stable behavior without climatic drifts, at least in the radiation budget, the temperature near the surface and the major indices of ocean circulations. The sea surface temperature (SST) drift is sufficiently small, while there is a 1 W m À2 heating imbalance at the surface. The model's climate sensitivity is estimated to be 2.11 K with Gregory's method. The transient climate response (TCR) to 1 % yr À1 increase of carbon dioxide (CO 2 ) concentration is 1.6 K with doubling of CO 2 concentration and 4.1 K with quadrupling of CO 2 concentration. The simulated present-day mean climate in the historical experiment is evaluated by comparison with observations, including reanalysis. The model reproduces the overall mean climate, including seasonal variation in various aspects in the atmosphere and the oceans. Variability in the simulated climate is also evaluated and is found to be realistic, including El Niñ o and Southern Oscillation and the Arctic and Antarctic oscillations. However, some important issues are identified. The simulated SST indicates generally cold bias in the Northern Hemisphere (NH) and warm bias in the Southern Hemisphere (SH), and the simulated sea ice expands excessively in the North Atlantic in winter. A double ITCZ also appears in the tropical Pacific, particularly in the austral summer.

[1] A physically based snow albedo model (PBSAM), which can be used in a general circulation model, is developed. PBSAM calculates broadband albedos and the solar heating profile in snowpack as functions of snow grain size and concentrations of snow impurities, black carbon and mineral dust, in snow with any layer structure and under any solar illumination condition. The model calculates the visible and near-infrared (NIR) albedos by dividing each broadband spectrum into several spectral subbands to simulate the change in spectral distribution of solar radiation in the broadband spectra at the snow surface and in the snowpack. PBSAM uses (1) the look-up table method for calculations of albedo and transmittance in spectral subbands for a homogeneous snow layer, (2) an "adding" method for calculating the effect of an inhomogeneous snow structure on albedo and transmittance, and (3) spectral weighting of radiative parameters to obtain the broadband values from the subbands. We confirmed that PBSAM can calculate the broadband albedos of single-and two-layer snow models with good accuracy by comparing them with those calculated by a spectrally detailed radiative transfer model (RTM). In addition, we used radiation budget measurements and snow pit data obtained during the two winters from 2007 to 2009 at Sapporo, Hokkaido, Japan, for simulation of the broadband albedos by PBSAM and compared the results with the in situ measurements. A five-layer snow model with one visible subband and three NIR subbands were necessary for accurate simulation. Comparison of solar heating profiles calculated by PBSAM with those calculated by the spectrally detailed RTM showed that PBSAM calculated accurate solar heating profiles when at least three subbands were used in both the visible and NIR bands.Citation: Aoki, T., K. Kuchiki, M. Niwano, Y. Kodama, M. Hosaka, and T. Tanaka (2011), Physically based snow albedo model for calculating broadband albedos and the solar heating profile in snowpack for general circulation models, J. Geophys.