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Coupled atmosphere-ocean model SLAV-INMIO: implementation and first results. (English) Zbl 1382.86002
Summary: Coupled atmosphere-ocean models are widely used for climate change modelling. However, there is now more and more evidence on necessity to use such models in numerical weather prediction at different time scales. A coupled model is developed at the Institute of Numerical Mathematics, Shirshov Institute of Oceanology (Russian Academy of Sciences), and Hydrometeorological Research Centre of Russia. Particularities of program implementation for this model are discussed. The atmosphere model SLAV and the World Ocean model INMIO are coupled using the original program for models coupling. The results of numerical experiments with the coupled model demonstrate an agreement with observation data and show a possibility to use this model for probabilistic weather forecasts at time scales from weeks to year.

86-08 Computational methods for problems pertaining to geophysics
86A05 Hydrology, hydrography, oceanography
86A10 Meteorology and atmospheric physics
65Y05 Parallel numerical computation
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[1] AMIP II Sea Surface Temperature and Sea Ice Concentration Observations. URL: .
[2] K. Bryan, A numerical method for the study of the circulation of the World Ocean. J. Comp. Phys. 4 (1969), No. 3, 347-376. · Zbl 0195.55504
[3] B. Catry, J.-F. Geleyn, M. Tudor, P. Bernard, and A. Trojakova, Flux-conservative thermodynamic equations in a mass-weighted framework. Tellus A59 (2007), No. 1, 71-79.
[4] M.-D. Chou and M. J. Suarez, A solar radiation parameterization (CLIRAD-SW) for atmospheric studies-1999. NASA Tech. Memo. 10460, V. 15, NASA Goddard Space Flight Center, Greenbelt, MD, 48 pp.
[5] A. Craig, R. Jacob, and B. Kauffman, CPL6: The new extensible, high performance parallel coupler for the Community Climate System Model. IJHPCA 2005; 19: 309-327.
[6] R. De Troch, R. Hamdi, H. van de Vyver, J.-P. Geleyn, and P. Termonia, Multiscale performance of the ALARO-0 model for simulating extreme summer precipitation climatology in Belgium. J. Climate26 (2013), 8895-8915.
[7] J.-P. Geleyn, E. Bazile, P. Bougeault, M. Deque, V. Ivanovici, A. Joly, L. Labbe, J.-P. Piedelievre, J.-M. Piriou, and J.-F. Royer, Atmospheric parameterization schemes in Meteo-France’s, ARPEGE N.W.P. model. Parameterization of subgrid-scale physical processes, ECMWF Seminar proceedings. Reading, UK: 1994, pp. 385-402.
[8] L. Gerard, J.-M. Piriou, R. BroZkova, J.-F. Geleyn, and D. Banciu, Cloud and precipitation parameterization in a meso-gamma-scale operational weather prediction model. Mon. Weather Rev. 137 (2009), 3960-3977.
[9] R. A. Ibrayev, K. V. Ushakov, and R. N. Khabeev, Eddy-resolving 1/10° model of the World Ocean. Izv. Atmos. Ocean. Phys. 48 (2012), No. 1, 37-46.
[10] IPCC Fifth Assessment Report (AR5). Climate Change 2013: The Physical Science Basis. URL: .
[11] P. Jones, A User’s guide for SCRIP: A Spherical Coordinate Remapping and Interpolation Package. Los Alamos National Laboratory, 1998.
[12] P. Kallberg, P. Berrisford, B. Hoskins, A. Simmons, S. Uppala, S. Lamy-Thepaut, and R. Hine, 2005: ERA-40 Atlas. Reading, UK, ECMWF Re-Analysis Project.
[13] V. V. Kalmykov and R. A. Ibrayev, A framework for the ocean-ice-atmosphere-land coupled modelling on massively-parallel architectures. Numer. Meth. Programming (2013), No. 14, 88-95.
[14] V. V. Kalmykov and R. A. Ibrayev, The overlapping algorithm for solving shallow water equations on massively-parallel architectures with distributed memory. Vestnik UGATU17 (2013), No. 5 (58), 252-259 (in Russian).
[15] E. Kalnay M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, A. Leetmaa, R. Reynolds, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, Roy Jenne, and Dennis Joseph, The NCEP/NCAR 40-year Reanalyses Project. Bull. Amer. Meteorol. Soc. 77 (1996), 437-471.
[16] P. D. Killworth, D. Stainforth, D. J. Webb, and S. Paterson, The development of a free surface Bryan-Cox-Semtner model. J. Phys. Oceanogr. 21 (1991), 1333-1348.
[17] C. MacLachlan, A. Arribas, K. A. Peterson, A. Maidens, D. Fereday, A. A. Scaife, M. Gordon, M. Vellinga, A. Williams, R. E. Comer, J. Camp, P. Xavier, and G. Madec, Global seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Q. J. Roy. Meteorol. Soc. 141 (2015), 1072-1084.
[18] S. Manabe and K. Bryan, Climate and the ocean circulation. Mon. Weather Rev. 97 (1969), 739-827.
[19] G. I. Marchuk, V. P. Dymnikov, V. B. Zalesny, and V. N. Lykossov, Mathematical Simulation General Circulation of the Atmosphere and Ocean. Saint-Petersburg, Gidrometeoizdat, 1984 (in Russian).
[20] E. J. Mlawer, S. J. Taubman, P. D. Brown, M. J. lacono, and S. A. Clough, RRTM, a validated correlated-k model for the longwave. J. Geophys. Res. 102 1997, No. 16, 663-682.
[21] R. J. Murray, Explicit generation of orthogonal grids for ocean models. J. Comp. Phys. 1261996, No. 2, 251-273. · Zbl 0858.76067
[22] P. Pellerin, H. Ritchie, F. J. Saucier, F. Roy, S. Desjardins, M. Valin, and V. Lee, Impact of a two-way coupling between an atmospheric and an ocean-ice model over the Gulf of St. Lawrence. Mon. Weather Rev. 132, 1379-1398.
[23] C. Schrum and J. Backhaus, Sensitivity of atmosphere-ocean heat exchange and heat content in North Sea and Baltic Sea. A comparative Assessment. Tellus, 51A, 1999.
[24] T. Tarasova and B. Fomin, The use of new parameterizations for gaseous absorption in the CLIRAD-SW solar radiation code for models. J. Atmos. Oceanic Tech. 24 (2007), No. 6,1157-1162.
[25] The HDF Group. Hierarchical Data Format, version 5, 1997-2016. URL: .
[26] M. A. Tolstykh, Global semi-Lagrangian numerical weather prediction model. Moscow, Obninsk, OAO FOP, 2010 (in Russian).
[27] Unidata, (2015): Network Common Data Form (netCDF) version (software). Boulder, CO: UCAR/Unidata. URL: .
[28] S. Valcke, The OASIS3 coupler: a European climate modelling community software. Geosci. Model Dev. Discuss. 5 (2012), 2139-2178.
[29] E. M. Volodin, E. V. Mortikov, S. V. Kostrykin, V. Ya. Galin, V. N. Lykossov, A. S. Gritsoun, N. A. Diansky, A. V. Gusev, and N. G. Iakovlev, Simulation of contemporary climate in Earth system model INMCM5.0. Izv. Atmos. Ocean. Phys. 2016 (accepted).
[30] E. M. Volodin, N. A. Dianskii, and A. V. Gusev, Simulating present day climate with the INMCM4.0 coupled model of the atmospheric and oceanic general circulations. Izv. Atmos. Ocean. Phys. 40 (2010), No. 4, 414-431.
[31] E. M. Volodin and V. N. Lykossov, Parameterization of heat and moisture transfer in the soil-vegetation system for use in atmospheric general circulation models: 1. Formulation and simulations based on local observational data. Izv. Atmos. Ocean. Phys. 34 (1998). No. 4. 405-416.
[32] WCRP131. The World Modelling Summit for Climate Prediction, Reading 2008. URL .
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