AMIP Simulation with the CAM4 Spectral Element Dynamical Core

K. J. Evans Oak Ridge National Laboratory, Oak Ridge, Tennessee

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P. H. Lauritzen National Center for Atmospheric Research, Boulder, Colorado

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S. K. Mishra National Center for Atmospheric Research, Boulder, Colorado

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R. B. Neale National Center for Atmospheric Research, Boulder, Colorado

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M. A. Taylor Sandia National Laboratories, Albuquerque, New Mexico

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J. J. Tribbia National Center for Atmospheric Research, Boulder, Colorado

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Abstract

The authors evaluate the climate produced by the Community Climate System Model, version 4, running with the new spectral element atmospheric dynamical core option. The spectral element method is configured to use a cubed-sphere grid, providing quasi-uniform resolution over the sphere and increased parallel scalability and removing the need for polar filters. It uses a fourth-order accurate spatial discretization that locally conserves mass and total energy. Using the Atmosphere Model Intercomparison Project protocol, the results from the spectral element dynamical core are compared with those produced by the default finite-volume dynamical core and with observations. Even though the two dynamical cores are quite different, their simulated climates are remarkably similar. When compared with observations, both models have strengths and weaknesses but have nearly identical root-mean-square errors and the largest biases show little sensitivity to the dynamical core. The spectral element core does an excellent job reproducing the atmospheric kinetic energy spectra, including fully capturing the observed Nastrom–Gage transition when running at 0.125° resolution.

Current affiliation: Indian Institute of Technology Delhi, New Delhi, India.

Corresponding author address: M. A. Taylor, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-0370. E-mail: mataylo@sandia.gov

This article is included in the CCSM4 Special Collection.

Abstract

The authors evaluate the climate produced by the Community Climate System Model, version 4, running with the new spectral element atmospheric dynamical core option. The spectral element method is configured to use a cubed-sphere grid, providing quasi-uniform resolution over the sphere and increased parallel scalability and removing the need for polar filters. It uses a fourth-order accurate spatial discretization that locally conserves mass and total energy. Using the Atmosphere Model Intercomparison Project protocol, the results from the spectral element dynamical core are compared with those produced by the default finite-volume dynamical core and with observations. Even though the two dynamical cores are quite different, their simulated climates are remarkably similar. When compared with observations, both models have strengths and weaknesses but have nearly identical root-mean-square errors and the largest biases show little sensitivity to the dynamical core. The spectral element core does an excellent job reproducing the atmospheric kinetic energy spectra, including fully capturing the observed Nastrom–Gage transition when running at 0.125° resolution.

Current affiliation: Indian Institute of Technology Delhi, New Delhi, India.

Corresponding author address: M. A. Taylor, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-0370. E-mail: mataylo@sandia.gov

This article is included in the CCSM4 Special Collection.

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  • Adams, J. C., and P. N. Swarztrauber, 1997: Spherepack 2.0: A model development facility. NCAR Tech. Note NCAR-TN-436-STR, 58 pp.

  • Adler, R. F., and Coauthors, 2003: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167.

    • Search Google Scholar
    • Export Citation
  • Carpenter, I., R. Archibald, K. Evans, J. Larkin, P. Micikevicius, J. Rosinski, J. Schwarzmeier, and M. A. Taylor, 2012: Progress towards accelerating HOMME on hybrid multi-core systems. Int. J. High Perform. Comput. Appl., doi:10.1177/1094342012462751, in press.

    • Search Google Scholar
    • Export Citation
  • Collins, W. D., and Coauthors, 2006: The Community Climate System Model version 3 (CCSM3). J. Climate, 19, 21222143.

  • Craig, A., M. Vertenstein, and R. Jacob, 2012: A new flexible coupler for earth system modeling developed for CCSM4 and CESM1. Int. J. High Perform. Comput. Appl., 26, 3142.

    • Search Google Scholar
    • Export Citation
  • Dennis, J. M., 2003: Partitioning with space-filling curves on the cubed-sphere. Proc. of the Workshop on Massively Parallel Processing at IPDPS’03, Nice, France, doi:10.1109/IPDPS.2003.1213486.

  • Dennis, J. M., A. Fournier, W. F. Spotz, A. St-Cyr, M. A. Taylor, S. J. Thomas, and H. Tufo, 2005: High resolution mesh convergence properties and parallel efficiency of a spectral element atmospheric dynamical core. Int. J. High Perform. Comput. Appl., 19, 225235.

    • Search Google Scholar
    • Export Citation
  • Dennis, J. M., and Coauthors, 2012: CAM-SE: A scalable spectral element dynamical core for the Community Atmosphere Model. Int. J. High Perform. Comput. Appl., 26, 7489.

    • Search Google Scholar
    • Export Citation
  • Donner, L. J., and Coauthors, 2011: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. J. Climate, 24, 34843519.

    • Search Google Scholar
    • Export Citation
  • Evans, K. J., M. A. Taylor, and J. B. Drake, 2010: Accuracy analysis of a spectral element atmospheric model using a fully implicit solution framework. Mon. Wea. Rev., 138, 33333341.

    • Search Google Scholar
    • Export Citation
  • Fournier, A., M. Taylor, and J. Tribbia, 2004: The spectral element atmosphere model (SEAM): High-resolution parallel computation and localized resolution of regional dynamics. Mon. Wea. Rev., 132, 726748.

    • Search Google Scholar
    • Export Citation
  • Gates, W. L., and Coauthors, 1999: An overview of the results of the Atmospheric Model Intercomparison Project (AMIP I). Bull. Amer. Meteor. Soc., 80, 2955.

    • Search Google Scholar
    • Export Citation
  • Gent, P. R., and Coauthors, 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991.

  • Giraldo, F. X., 2005: Semi-implicit time-integrators for a scalable spectral element atmospheric model. Quart. J. Roy. Meteor. Soc., 131, 24312454.

    • Search Google Scholar
    • Export Citation
  • Giraldo, F. X., and T. E. Rosmond, 2004: A scalable spectral element Eulerian atmospheric model (SEE-AM) for NWP: Dynamical core tests. Mon. Wea. Rev., 132, 133153.

    • Search Google Scholar
    • Export Citation
  • Gleckler, P., Ed., 2004: The Second Phase of the Atmospheric Model Intercomparison Project (AMIP2): Toward Innovative Model Diagnostics. Météo-France, 253 pp.

  • Hack, J. J., J. T. Kiehl, and J. W. Hurrell, 1998: The hydrologic and thermodynamic characteristics of the NCAR CCM3. J. Climate, 11, 11791206.

    • Search Google Scholar
    • Export Citation
  • Hamilton, K., Y. O. Takahashi, and W. Ohfuchi, 2008: Mesoscale spectrum of atmospheric motions investigated in a very fine resolution global general circulation model. J. Geophys. Res., 113, D18110, doi:10.1029/2008JD009785.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J. W., J. J. Hack, A. S. Phillips, J. Caron, and J. Yin, 2006: The dynamical simulation of the Community Atmosphere Model version 3 (CAM3). J. Climate, 19, 21622183.

    • Search Google Scholar
    • Export Citation
  • Jablonowski, C., and D. Williamson, 2011: The pros and cons of diffusion, filters and fixers in atmospheric general circulation models. Numerical Techniques for Global Atmospheric Models, P. H. Lauritzen et al., Eds., Lecture Notes in Computational Science and Engineering, Vol. 80, Springer, 381–493.

  • Jackson, C. S., M. K. Sen, G. Huerta, Y. Deng, and K. Bowman, 2008: Error reduction and convergence in climate prediction. J. Climate, 21, 66986709.

    • Search Google Scholar
    • Export Citation
  • Jones, P., 1999: First- and second-order conservative remapping schemes for grids in spherical coordinates. Mon. Wea. Rev., 127, 22042210.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471.

  • Khouider, B., A. St-Cyr, A. J. Majda, and J. Tribbia, 2011: MJO and convectively coupled waves in a coarse-resolution GCM with a simple multicloud parameterization. J. Atmos. Sci., 68, 240264.

    • Search Google Scholar
    • Export Citation
  • Kim, Y.-J., F. Giraldo, M. Flatau, C.-S. Liou, and M. Peng, 2008: A sensitivity study of the Kelvin wave and the Madden–Julian oscillation in aquaplanet simulations by the Naval Research Laboratory Spectral Element Atmospheric Model. J. Geophys. Res., 113, D20102, doi:10.1029/2008JD009887.

    • Search Google Scholar
    • Export Citation
  • Kistler, R., and Coauthors, 2001: The NCEP-NCAR 50-Year Reanalysis: Monthly means CD-ROM and documentation. Bull. Amer. Meteor. Soc., 82, 247268.

    • Search Google Scholar
    • Export Citation
  • Lauritzen, P., C. Jablonowski, M. Taylor, and R. Nair, 2010: Rotated versions of the Jablonowski steady-state and baroclinic wave test cases: A dynamical core intercomparison. J. Adv. Model. Earth Syst., 2 (15), doi:10.3894/JAMES.2010.2.15.

    • Search Google Scholar
    • Export Citation
  • Lauritzen, P., A. Mirin, J. Truesdale, K. Raeder, J. Anderson, J. Bacmeister, and R. Neale, 2012: Implementation of new diffusion/filtering operators in the CAM-FV dynamical core. Int. J. High Perform. Comput. Appl., 26, 6373.

    • Search Google Scholar
    • Export Citation
  • Liebmann, B., and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 12751277.

    • Search Google Scholar
    • Export Citation
  • Lin, J.-L., and Coauthors, 2006: Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: Convective signals. J. Climate, 19, 26652690.

    • Search Google Scholar
    • Export Citation
  • Lin, S.-J., 2004: A “vertically Lagrangian” finite-volume dynamical core for global models. Mon. Wea. Rev., 132, 22932307.

  • Lindborg, E., 1999: Can the atmospheric kinetic energy spectrum be explained by two-dimensional turbulence? Fluid Mech., 388, 259288.

    • Search Google Scholar
    • Export Citation
  • Loeb, N. G., B. A. Wielicki, D. R. Doelling, G. Smith, D. Keyes, S. Kato, N. Manalo-Smith, and T. Wong, 2009: Towards optimal closure of the earth’s top-of-atmosphere radiation budget. J. Climate, 22, 748766, doi:10.1175/2008JCLI2637.1.

    • Search Google Scholar
    • Export Citation
  • Loft, R., S. Thomas, and J. Dennis, 2001: Terascale spectral element dynamical core for atmospheric general circulation models. Proc. ACM/IEEE Supercomputing SC’2001 Conf., Denver, CO, IEEE, doi:10.1109/SC.2001.10044.

  • Mishra, S. K., M. A. Taylor, R. D. Nair, P. Lauritzen, H. M. Tufo, and J. J. Tribbia, 2011a: Evaluation of the HOMME dynamical core in the aquaplanet configuration of NCAR CAM4: Rainfall. J. Climate, 24, 40374055.

    • Search Google Scholar
    • Export Citation
  • Mishra, S. K., M. A. Taylor, R. D. Nair, H. M. Tufo, and J. J. Tribbia, 2011b: Performance of the HOMME dynamical core in the aqua-planet configuration of NCAR CAM4: Equatorial waves. Ann. Geophys., 29, 221227, doi:10.5194/angeo-29-221-2011.

    • Search Google Scholar
    • Export Citation
  • Murphy, D., S. Solomon, R. Portman, K. Rosenlof, P. Forster, and T. Wong, 2009: An observationally based energy balance for the earth since 1950. J. Geophys. Res., 114, D17107, doi:10.1029/2009JD012105.

    • Search Google Scholar
    • Export Citation
  • Nair, R. D., 2009: Diffusion experiments with a global discontinuous Galerkin shallow-water model. Mon. Wea. Rev., 137, 33393350.

  • Nastrom, G., and K. S. Gage, 1985: A climatology of atmospheric wavenumber spectra of wind and temperature observed by commercial aircraft. J. Atmos. Sci., 42, 950960.

    • Search Google Scholar
    • Export Citation
  • Neale, R. B., and B. J. Hoskins, 2000a: A standard test case for AGCMs including their physical parametrizations. I: The proposal. Atmos. Sci. Lett., 1, 101107, doi:10.1006/asle.2000.0022.

    • Search Google Scholar
    • Export Citation
  • Neale, R. B., and B. J. Hoskins, 2000b: A standard test case for AGCMs including their physical parametrizations. II: Results for the Met Office Model. Atmos. Sci. Lett., 1, 108114, doi:10.1006/asle.2000.0024.

    • Search Google Scholar
    • Export Citation
  • Neale, R. B., and Coauthors, 2010: Description of the NCAR Community Atmosphere Model (CAM 4.0). NCAR Tech. Note NCAR/TN-485+STR, 212 pp.

  • Putman, W., and S.-J. Lin, 2007: Finite-volume transport on various cubed-sphere grids. J. Comput. Phys., 227, 5578, doi:10.1016/j.jcp.2007.07.022.

    • Search Google Scholar
    • Export Citation
  • Putman, W., and S.-J. Lin, 2009: A finite-volume dynamical core on the cubed-sphere grid. Numerical Modeling of Space Plasma Flows: Astronum-2008, Astronomical Society of the Pacific Conference Series, Vol. 406, ASP, 268–276.

  • Rančić, M., R. Purser, and F. Mesinger, 1996: A global shallow-water model using an expanded spherical cube: Gnomonic versus conformal coordinates. Quart. J. Roy. Meteor. Soc., 122, 959982.

    • Search Google Scholar
    • Export Citation
  • Rayner, N., P. Brohan, D. Parker, C. Folland, J. Kennedy, M. Vanicek, T. Ansell, and S. F. B. Tett, 2005: Improved analyses of changes and uncertainties in sea surface temperature measured in situ since the mid-nineteenth century: The HadSST2 dataset. J. Climate, 19, 446469.

    • Search Google Scholar
    • Export Citation
  • Ringler, T. D., D. Jacobsen, M. Gunzburger, L. Ju, M. Duda, and W. Skamarock, 2011: Exploring a multi-resolution modeling approach within the shallow-water equations. Mon. Wea. Rev., 139, 33483368.

    • Search Google Scholar
    • Export Citation
  • Rossow, W., and R. Schiffer, 1999: Advances in understanding clouds from ISCCP. Bull. Amer. Meteor. Soc., 80, 22612287.

  • Sadourny, R., 1972: Conservative finite-difference approximations of the primitive equations on quasi-uniform spherical grids. Mon. Wea. Rev., 100, 136144.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W., 2004: Evaluating mesoscale NWP models using kinetic energy spectra. Mon. Wea. Rev., 132, 30193032.

  • Skamarock, W., 2011: Kinetic energy spectra and model filters. Numerical Techniques for Global Atmospheric Models, P. H. Lauritzen et al., Eds., Lecture Notes in Computational Science and Engineering, Vol. 80, Springer, 495–512.

  • Srinivasan, J., and G. L. Smith, 1996: Meridional migration of tropical convergence zones. J. Appl. Meteor., 35, 11891202.

  • St-Cyr, A., C. Jablonowski, J. M. Dennis, H. M. Tufo, and S. J. Thomas, 2008: A comparison of two shallow water models with non-conforming adaptive grids. Mon. Wea. Rev., 136, 18981922.

    • Search Google Scholar
    • Export Citation
  • Stoffelen, A., and D. Anderson, 1997a: Scatterometer data interpretation: Estimation and validation of the transfer function CMOD4. J. Geophys. Res., 102 (C3), 57675780.

    • Search Google Scholar
    • Export Citation
  • Stoffelen, A., and D. Anderson, 1997b: Scatterometer data interpretation: Measurement space and inversion. J. Atmos. Oceanic Technol., 14, 12981313.

    • Search Google Scholar
    • Export Citation
  • Stratton, R. A., 1999: A high resolution AMIP integration using the Hadley Centre model HadAM2b. Climate Dyn., 15, 928.

  • Taylor, K., 2001: Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res., 106 (D7), 71837192.

  • Taylor, M. A., 2011: Conservation of mass and energy for the moist atmospheric primitive equations on unstructured grids. Numerical Techniques for Global Atmospheric Models, P. H. Lauritzen et al., Eds., Lecture Notes in Computational Science and Engineering, Vol. 80, Springer, 357–380.

  • Taylor, M. A., and A. Fournier, 2010: A compatible and conservative spectral element method on unstructured grids. J. Comput. Phys., 229, 58795895, doi:10.1016/j.jcp.2010.04.008.

    • Search Google Scholar
    • Export Citation
  • Taylor, M. A., J. Tribbia, and M. Iskandarani, 1997: The spectral element method for the shallow water equations on the sphere. J. Comput. Phys., 130, 92108.

    • Search Google Scholar
    • Export Citation
  • Taylor, M. A., R. Loft, and J. Tribbia, 1998: Performance of a spectral element atmospheric model (SEAM) on the HP Exemplar SPP2000. NCAR Tech. Rep. TN-439+EDD, 16 pp.

  • Taylor, M. A., J. Edwards, S. Thomas, and R. Nair, 2007: A mass and energy conserving spectral element atmospheric dynamical core on the cubed-sphere grid. J. Phys. Conf. Ser., 78, 012074, doi:10.1088/1742-6596/78/1/012074.

    • Search Google Scholar
    • Export Citation
  • Taylor, M. A., J. Edwards, and A. St-Cyr, 2008: Petascale atmospheric models for the community climate system model: New developments and evaluation of scalable dynamical cores. J. Phys. Conf. Ser., 125, 012023, doi:10.1088/1742-6596/125/1/012023.

    • Search Google Scholar
    • Export Citation
  • Thomas, S., and R. Loft, 2002: Semi-implicit spectral element atmosphere model. J. Sci. Comput., 17, 339350.

  • Thomas, S., and R. Loft, 2005: The NCAR spectral element climate dynamical core: Semi-implicit Eulerian formulation. J. Sci. Comput., 25, 307322.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K., and J. M. Caron, 2001: Estimates of meridional atmosphere and ocean heat transports. J. Climate, 14, 34333443.

  • Wang, H., J. J. Tribbia, F. Baer, A. Fournier, and M. A. Taylor, 2007: A spectral element version of CAM2. Mon. Wea. Rev., 135, 38253840.

    • Search Google Scholar
    • Export Citation
  • Wheeler, M., and G. N. Kiladis, 1999: Convectively coupled equatorial waves: Analysis of clouds and temperature in the wavenumber–frequency domain. J. Atmos. Sci., 56, 374399.

    • Search Google Scholar
    • Export Citation
  • Williamson, D. L., 2002: Time-split versus process-split coupling of parameterizations and dynamical core. Mon. Wea. Rev., 130, 20242041.

    • Search Google Scholar
    • Export Citation
  • Williamson, D. L., 2008a: Convergence of aqua-planet simulations with increasing resolution in the Community Atmospheric Model, version 3. Tellus, 60, 848862.

    • Search Google Scholar
    • Export Citation
  • Williamson, D. L., 2008b: Equivalent finite volume and Eulerian spectral transform horizontal resolutions established for aqua-planet simulations. Tellus, 60, 839847.

    • Search Google Scholar
    • Export Citation
  • Williamson, D. L., J. Kiehl, and J. Hack, 1995: Climate sensitivity of the NCAR Community Climate Model (CCSM2) to horizontal resolution. Climate Dyn., 11, 377397.

    • Search Google Scholar
    • Export Citation
  • Worley, P. H., and J. B. Drake, 2005: Performance portability in the physical parameterizations of the community atmospheric model. Int. J. High Perform. Comput. Appl., 19, 187201.

    • Search Google Scholar
    • Export Citation
  • Worley, P. H., A. P. Craig, J. M. Dennis, A. A. Mirin, M. A. Taylor, and M. Vertenstein, 2011: Performance and performance engineering of the Community Earth System Model. Proc. ACM/IEEE Supercomputing SC’2011 Conf., Seattle, WA, IEEE, Article 54, doi:10.1145/2063384.2063457.

  • Wu, X., X.-Z. Liang, and G. J. Zhang, 2003: Seasonal migration of ITCZ precipitation across the equator: Why can’t GCMs simulate it? Geophys. Res. Lett., 30, 1824, doi:10.1029/2003GL017198.

    • Search Google Scholar
    • Export Citation
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