IPSL-CM4, IPSL

The IPSL-CM4-LOOP (ICM4) model combines four major dynamical components of the climate system: atmosphere, continental surface, ocean and sea-ice. The Atmosphere consists of the Laboratoire de Météorologie Dynamique atmospheric model (LMDZ-4) with a horizontal resolution of about 3°×3° and 19 vertical levers (Hourdin et al., 2006). The radiation scheme is the one introduced several years ago in the model of European Centre for Medium-Range Weather Forecast (ECMWF) by Morcrette et al. (1986). The ocean component of ICM4 consists of OPA-8 with a horizontal resolution of 2°×2° cos(lat) and 31 vertical levels and the LIM sea ice model (Madec et al., 1998; Marti et al. 2005). The parametrization of the vertical physics is based on a prognostic equation of the turbulent kinetic energy (Blanke and Delecluse, 1993), which computes the vertical eddy and viscosity coefficients using a 1.5 turbulent closure scheme. The sea-ice model LIM (Fichefet and Morales-Maqueda, 1997) consists of a prognostic resolution of the three layers (one layer for snow and two layers for ice) determining sea-ice dynamics.

The marine carbon cycle is represented by the PISCES model (Aumont et al., 2003). PISCES simulates the cycling of carbon, oxygen, and the major nutrients determining phytoplancton growth (PO4-, NO3-, NH4+, DSi, DFe). Phytoplankton growth is limited by the external availability of nutrients, temperature, and light. The model has two phytoplankton size classes (small and large), representing microzooplankton and mesozooplankton. For all species the C:N:P ratios are assumed Chl:C, and Si:C of phytoplankton are predicted by the model. There are three non-living components of organic carbon in the model: semi-labile dissolved organic carbon (DOC), with a lifetime of several weeks to years, large and small particles. Mortality, aggregation, fecal pellet production and grazing fuel the pool of detrital particles. While a constant sinking speed of 3m day-1 is assumed for small particles, depth of the mixed layer, increasing to a maximum sinking speed of 425m day -1 at 5000m. For a fore detailed description of the PISCES model see Aumont and Bopp (2006) and Gehlen et al. (2006).

Both models have been spun up for 3000 years in off-line mode forced by a preindustrial climatological ocean circulation derived from the respective coupled physical climate models. This long spin-up allows for the equilibration of biogeochemical tracers, but does not account for interannual variability. In a second step and in order to add interannual variability, both models were run on-line (fully coupled climate C cycle) still under pre-industrial conditions for 100 years in the case of ICM4, respectively 50 years for ICM5.

Transient simulations followed the protocol by Taylor et al. (2008). ICM4 was forced by antthropogenic CO2 emissions due to fossil fuel burning and land-sea changes (Houghton et al., 2001). Emissions over the historical period (1860-1999) were based on Marland and Andres (2005). Atmospheric forcing for ICM4 included both the historical development of anthropogenic green house gases (GHG) and aerosols distributions over the period 1860-2005 (REF).

References

Aumont, O and L. Bopp, 2006: Globaliwing results from ocean in situ iron fertilization studies. Global Biogechemical Cycles, 20.

Aumont, O. E. Maier-Reimer, S. Blain, and P. Monfray, 2003: An ecosystem model of the glopbal ocean including Fe, Si, P colimitations. Global biogeochemical Cycles, 17.

Blanke, B., and P. Delecluse, 1993: Low-frequency variability of the tropical Atlantic Ocean simulated by a general circulation with mixed layer physics. J. Phys. Oceanogr., 23, 1363-1388.

Fichefet, T. and Maqueda, M. A. M, 1997: Sensitivity of a global sea ice model to the treatment of ice thermodynamics and dynamics. Journal of Geophysical Research-Oceans, 102 )C6), 12609-12646.

Gehlen, M., L. Bopp, N. Enrprin, O. Aumont, C. Heinze, and O. Raguencau, 2006: Reconciling surface ocean productivity, export fluxes and sediment composition in a global biogeochemical ocean model. Biogeosciences, 3, 521-537.

Hourdin, F., I. Musat, S. Bony, P. Braconnot, F. Codron, J. L. Dufresne, L. Fairhead, M. A. Filiberti, P. Friedlingstein, J. Y. Grandpeix, G. Krinner, P. Levan, Z. X. Li, and F. Lott, 2006: The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection, Climate Dynamics, 27, 787-813.

Madec, G. P. Delecluse, M. Imbard, and M. Lévy, 1998: OPA 8.1 Ocean General Circulation Model Reference Manual. Notes du Pôle de Modélisation 11. IPSL, 91 pp.

Marland, G. and T. B. R. J. Andres, 2005: Global, regional, and national CO2 emissions. Trends: A comprendium of Data on Global Change, Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy.

Marti, O., P. Braconnot, J. L. Dufresne, J. Bellier, R. Benshila, S. Bony, P. Brockman, P. Cadule, A. Caubel, F. Codron, N. de Noblet, S. Denvil, L. Fairhead, T. Fichefet, M. A. Foujols, P. Friedlingstein, H. Goose, J. Y. Grandpeix, E. Guilyardi, F. Hourdin, A. Idelkadi, M. Kageyama, G. Krinner, C. Levy, G. Madec, J. Mignot, I. Musat, D. Swingedouw, and C. Talandier, 2009: Key features of the IPSL ocean atmosphere model and its sensitivity to atmospheric resolution. Climate Dynamics, 34, 1-26.

Mocrette, J.-J, Smith, L. Fouquart, Y. 1986: Pressure and temperature dependence of the absorption in longwave radiation parameterizations. Contributions to Atmospheric Physics, 59(4), 455-469.