Model History

The System for Atmospheric Modeling, or SAM, evolved from the Large-Eddy Simulation (LES) model, coded by Dr. Marat Khairoutdinov while a Ph.D. student at the University of Oklahoma. Coupled with the explicit or bin microphysics of Yefim Kogan, his Ph.D. advisor, the model has become a useful tool to study detailed cloud processes in the stratocumulus-topped boundary layers (Khairoutdinov and Kogan 1999). The model was used to develop a bulk microphysics scheme for drizzling PBL clouds (Khairoutdinov and Kogan 2000).

In January 1998, Dr. Khairoutdinov started at the Department of Atmospheric Science, Colorado State University in David Randall’s research group. At CSU, the model code and physics were overhauled. The explicit warm-cloud microphysics has been replaced with the bulk microphysics that included the ice-microphysics processes. The thermodynamic prognostic variables have also been changed. The model has become suitable to run on massively parallel computers by using horizontal domain decomposition and employing the MPI communication protocol. The model’s details can be found in Khairoutdinov and Randall (2003). In 2003, the model received its official name – SAM – with the version count starting from 6.0, reflecting the fact that SAM represents the sixth cloud-model design since 1987 when Dr. Khairoutdinov started his cloud modeling career at the Central Aerological Observatory (CAO) in Russia.

Today, SAM is used by more than a dozen cloud modelers in the US and in Canada.  A partial list of publications of the scientific results obtained using SAM can be found at the end of this page.

Model Highlights

  • Anelastic dynamical core;
  • Prognostic liquid/ice water static energy, total non-precipitating (cloud water/ice) and total precipitating water(rain/snow/graupel);
  • Diagnostic cloud water, cloud ice, rain, snow, and graupel;
  • 1.5-order sub-grid scale closure (prognostic SGS TKE) or Smagorinsky-type closure;
  • Radiation from CCM3, CAM3, or CSU BUGS;
  • Periodical domain with the option of solid lateral walls (for beta-plane runs);
  • Surface fluxes based on Monin-Obukhov similarity;
  • ISCCP cloud simulator;
  • CAM3 physical parameterizations as an option for low-resolution runs;
  • Simple mixed-layer ocean;
  • Parallel (MPI).

Examples

Snapshot of a cloud scene at full model resolution (180x180 km2)

Snapshot of a cloud scene at full model resolution (180x180 km2)

Idealized GATE Simulation of Convection over Tropical Atlantic (“GigaLES”)

    • Based on average forcing and sounding from GATE Phase III observations (30 August – 19 September 1074, Tropical Atlantic);
    • Forcing: SST, horizontal advective tendencies of s and q; mean wind nudged to observed; radiative heating prescribed; surface fluxes – interactive.
    • Domain: 2048x2048x256 grid points, or 205x205x27 km3 (horizontal grid spacing 100m);
    • Vertical grid spacing: 50m below 1km, 50-100m @1-5km; 100m @5-18km; 100-300m above;
    • Time step: 2 sec, duration: 1 day;
    • Initialization: random small-amplitude noise in temperature near the surface;
    • run done over 6 days wall-clock time on 2048 processors of IBM BlueGene BG/L of NYCCS;
    • Animations of mock-up cloud albedo as would be seen from a satellite orbit (15 simulated minutes per movie second);
    • One day evolution whole domain, Zoom-in into a quarter of a domain (100x100 km2) for 13.5 hours and Zoom-in into a 50x50 km2 subdomain for 2h40m:

KWAJEX Simulation

  • 23 July – 15 September 1999: 52 days, Kwajalein Atoll, Marshall Islands.
  • Forcing: SST, horizontal advective tendencies of s and q; large-scale vertical velocity; mean wind nudged to observed.
    Radiation and surface fluxes – interactive.
    Domain: 256x256x64 grid points, or 256x256x27 km3, time step: 10 sec, duration: 52 days
  • Snapshots of various cloud regimes:
  • Animations of a 4-hour period of active deep convection and the whole 52-day period as if viewed from a satellite

YouTube Video Playlist

 

TRMM-LBA High-Resolution Simulation

      • Based on  TRMM-LBA Case 3 of the GCSS WG4;
      • Domain: 1536 x 1536 x 256 grid points, or 154 x 154 x 25 km3
      • Horizontal resolution: 100 m, vertical resolution: 50 m in PBL, 100 m in troposphere, 150-200 m in stratosphere
      • Time step: 2 sec; duration 6 hours.
      • Forcing: Prescribed surface fluxes and radiative cooling.
      • Case description: Starts early morning when no clouds present. About 2 hours into simulation, shallow convection develops gradually growing into mid-level convection with the transition to deep convection by the simulation end.
      • Snapshot of the cloud field at the end of simulation: pdf (1.5 Mb), jpg (80 kb). Note that the clouds tops are as high as 12 km.
      • Snapshot of a view from a satellite: pdf (620 kb), jpg (104 kb), and zoom into one quarter of the domain: pdf (540 kb), jpg (96 kb).
      • Zooming-in into the shallow cloud field: full (7.3 Mb), small (2.3 Mb). Note that even at the maximum zoom there is still plenty of resolution left.
      • Rotating cloud field at the end of simulation: full (35 Mb), small (10.4 Mb)

Download

Latest version of SAM (Contact Dr. Marat Khairoutdinov for access)

SAM Related Publications

If you use SAM in your research and don’t see your publication with SAM results in the list below, please shoot me an email with the reference.

    • Khairoutdinov, M. F., and C.-E. Yang, 2013: Cloud-Resolving Modeling of Aerosol Indirect Effects in Idealized Radiative-Convective Equilibrium with Interactive and Fixed Sea Surface Temperature. Atmos. Chem. Phys., in press.
    • Muller, C. J, 2013: Impact of convective organization on the response of tropical precipitation extremes to warming, J. Climate, in press
    • Kogan, Y. L., D. B. Mechem, and K. Choi, 2012: Effects of sea-salt aerosols on precipitation in simulations of shallow cumulus. J. Atmos. Sci., 69, 463-483.
    • Mechem, D. B., S. E. Yuter, and S. P. de Szoeke, 2012: Thermodynamic and aerosol controls in southeast Pacific stratocumulus. J. Atmos. Sci., 69, 1250-1266.
    • Muller, C. J., I. M. Held, 2012: Detailed Investigation of the Self-Aggregation of Convection in Cloud-Resolving Simulations. J. Atmos. Sci., 69, 2551–2565.
    • Stevens, R. G., Pierce, J. R., Brock, C. A., Reed, M. K., Crawford, J. H., Holloway, J. S., Ryerson, T. B., Huey, L. G., and Nowak, J. B., 2012: Nucleation and growth of sulfate aerosol in coal-fired power plant plumes: sensitivity to background aerosol and meteorology, Atmos. Chem. Phys., 12, 189-206, doi:10.5194/acp-12-189-2012
    • Berner, A. H., Bretherton, C. S., and Wood, R., 2011: Large-eddy simulation of mesoscale dynamics and entrainment around a pocket of open cells observed in VOCALS-REx RF06, Atmos. Chem. Phys., 11, 10525-10540
    • Fan, J., T. Yuan, J. M. Comstock, S. Ghan, A. Khain, L. R. Leung, Z. Li, V. J. Martins, and M. Ovchinnikov (2009): Dominant role by vertical wind shear in regulating aerosol effects on deep convective clouds, J. Geophys. Res., 114, D22206, doi:10.1029/2009JD012352.
    • Fan, J., S. Ghan, M. Ovchinnikov, X. Liu, P. Rasch, and A. Korolev, 2011:  Representation of arctic mixed-phase clouds and Wegener-Bergeron-Findeisen process in climate models – perspectives from cloud-resolving study. J. Geophys. Res., 116, D00T07, doi:10.1029/2010JD015375.
    • Wang, M; S. J. Ghan, R. C. Easter, M. Ovchinnikov, X. Liu, E. Kassianov, Y.  Qian, W. Gustafson, V. E. Larson, D.  Schanen, M. Khairoutdinov, and H. Morrison, 2011: The multi-scale aerosol-climate model PNNL-MMF: model description and evaluation. Geoscientific Model Development, 4, 137–168.
    • Wang, M., S. Ghan, M. Ovchinnikov, X. Liu, R. Easter, E. Kassianov, Y. Qian, R. Marchand, and H. Morrison, 2011: Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF, Atmos. Chem. & Phys., 11, 5431-5455, doi:10.5194/acp-11-5431-2011.
    • Larson, V. E., B. J. Nielsen, J. Fan, and M. Ovchinnikov (2011), Parameterizing correlations between hydrometeor species in mixed-phase Arctic clouds, J. Geophys. Res., 116, D00T02, doi:10.1029/2010JD015570.
    • Muller, Caroline J., Paul A. O’Gorman, Larissa E. Back, 2011: Intensification of Precipitation Extremes with Warming in a Cloud-Resolving Model. J. Climate, 24, 2784–2800.
    • Ovchinnikov, M., A. Korolev, and J. Fan (2011), Effects of ice number concentration on dynamics of a shallow mixed-phase stratiform cloud, J. Geophys. Res., 116, D00T06, doi:10.1029/2011JD015888.
    • Morrison, H., et al. (2011), Intercomparison of cloud model simulations of Arctic mixed-phase boundary layer clouds observed during SHEBA, J. Adv. Model. Earth Syst., 3, M06003, doi:10.1029/2011MS000066.
    • Kuang, Z., 2011: The Wavelength Dependence of the Gross Moist Stability and the Scale Selection in the Instability of Column-Integrated Moist Static Energy. J. Atmos. Sci., 68, 61-74.
    • Boos, W. R., and Z. Kuang, 2010: Mechanisms of Poleward Propagating, Intraseasonal Convective Anomalies in Cloud System–Resolving Models. J . Atmos. Sci., 67, 3673-3691.
    • Mechem, D. B., Y.  L. Kogan, D.  M. Schultz, 2010:  Large-Eddy Simulation of Post-Cold-Frontal Continental Stratocumulus. J. Atmos. Sci., 67, 3835-3853.
    • Fan, J., J. M. Comstock, M. Ovchinnikov, S. A. McFarlane, G. McFarquhar, and G. Allen (2010), Tropical anvil characteristics and water vapor of the tropical tropopause layer: Impact of heterogeneous and homogeneous freezing parameterizations, J. Geophys. Res., 115, D12201, doi:10.1029/2009JD012696.
    • Fan, J., J. M. Comstock, M. Ovchinnikov (2010), The cloud condensation nuclei and ice nuclei effects on tropical anvil characteristics and water vapor of the tropical tropopause layer, Environ. Res. Lett., 5, 044005.
    • Pakula, L., and G. L. Stephens, 2009: The Role of Radiation in Influencing Tropical Cloud Distributions in a Radiative–Convective Equilibrium Cloud-Resolving Model. J. Atmos. Sci., 66, 62-76.
    • Qian, Y., D. Gong, J. Fan, L. R. Leung, R. Bennartz, D. Chen, and W. Wang, 2009: Heavy pollution suppresses light rain in China: Observations and modeling, J. Geophys. Res., 114, D00K02, doi:10.1029/2008JD011575.
    • Khairoutdinov M. F., S. K. Krueger, C.-H. Moeng, P. A. Bogenschutz, and D. A Randall, 2009: Large-eddy simulation of maritime deep tropical convection, J. Adv. Model. Earth Syst., Vol. 1, Art. #15, 13 pp., doi:10.3894/JAMES.2009.1.15
    • Moeng C. H., M. A. LeMone, M. F. Khairoutdinov, S. K. Krueger, P. A. Bogenschutz, and D. A. Randall, 2009: The tropical marine boundary layer under a deep convection system: a large-eddy simulation study, J. Adv. Model. Earth Syst., Vol. 1, Art. #16, 13 pp., doi:10.3894/JAMES.2009.1.16
    • Fan, J., M. Ovtchinnikov, J. Comstock, S. A. McFarlane, and A. Khain (2009), Ice Formation in Arctic Mixed-Phase Clouds – Insights from a 3-D Cloud-Resolving Model with Size-Resolved Aerosol and Cloud Microphysics, J. Geophys. Res., 114, D04205, doi:10.1029/2008JD010782.
    • Lopez, M. A, D. L. Hartmann, P. N. Blossey, R. Wood, C. S. Bretherton, T. L. Kubar, 2009: A Test of the Simulation of Tropical Convective Cloudiness by a Cloud-Resolving Model. J. Climate, 22, 2834-2849
    • Caldwell, P., and C. S. Bretherton, 2009: Large Eddy Simulation of the Diurnal Cycle in Southeast Pacific Stratocumulus. J. Atmos. Sci., 66, 432-449.
    • Henderson, P. W., and R. Pincus, 2009: Multiyear Evaluations of a Cloud Model Using ARM Data. J. Atmos. Sci., 66, 2925-2936.
    • Kuang, Z, 2008: Modeling the interaction between cumulusc convection and linear gravity waves using a limited-domain cloud system–resolving model. J. Atmos. Sci., 65, 576-591
    • Tulich, S. N., and B. E. Mapes, 2008: Multiscale Convective Wave Disturbances in the Tropics: Insights from a Two-Dimensional Cloud-Resolving Model. J. Atmos. Sci., 65, 140-155.
    • Yamaguchi, T., and D. A. Randall, 2008: Large-Eddy Simulation of Evaporatively Driven Entrainment in Cloud-Topped Mixed Layers. J. Atmos. Sci., 65, 1481-1504.
    • Kuang, Z., D. L. Hartmann, 2007: Testing the Fixed Anvil Temperature Hypothesis in a Cloud-Resolving Model. J. Climate, 20, 2051-2057
    • Tulich, S. N., D. A. Randall, B. E. Mapes, 2007: Vertical-Mode and Cloud Decomposition of Large-Scale Convectively Coupled Gravity Waves in a Two-Dimensional Cloud-Resolving Model. 64, 1210-1229.
    • Kuang, Z., and C. S. Bretherton, 2006: A Mass-Flux Scheme View of a High-Resolution Simulation of a Transition from Shallow to Deep Cumulus Convection. J. Atmos. Sci., 63, 1895-1909.
    • Khairoutdinov, M. F., and D. A. Randall, 2006: High-resolution simulation of shallow-to-deep convection transition over land. J. Atmos. Sci., 63,  3421–3436.
    • Blossey, P. N., C. S. Bretherton, J. Cetrone, and M. Khairoutdinov, 2005: Cloud-resolving model simulations of KWAJEX: Model sensitivities and comparisons with satellite and radar observations.  J. Atmos. Sci., 64, 1488-1508.
    • Bretherton, C. S., P. N. Blossey, and M. Khairoutdinov, 2005: An energy-balance analysis of deep convective self-aggregation above uniform SST. J. Atmos. Sci., in press.
    • M. Zhao and P. H. Austin, 2005:  Life cycle of numerically simulated shallow cumulus clouds. Part I: Transport, J. Atmos. Sci., 62, 1269-1290.
    • M. Zhao and P. H. Austin, 2005:  Life cycle of numerically simulated shallow cumulus clouds. Part II: Mixing dynamics,  J. Atmos. Sci., 62, 1291-1310.
    • Kuang, Z., P. N. Blossey, and C. S. Bretherton, 2005: A new approach for 3D cloud resolving simulations of large scale atmospheric circulation. Geophys. Res. Lett., 32, L02809, doi: 10.1029/2004GL021024.
    • Kuang, Z., and C. S. Bretherton, 2004: Convective influence of the heat balance of the tropical tropopause layer: A cloud-resolving model study. J. Atmos. Sci., 61, 2919-2927.
    • Khairoutdinov, M. F., and D.A. Randall, 2003: Cloud-resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties and sensitivities. J. Atmos. Sci., 60, 607-625.
    • Oreopoulos L., and M. Khairoutdinov, 2003: Overlap properties of clouds generated by a cloud-resolving model. J. Geoph. Res., 108(D15), 4479-
    • Khairoutdinov, M. F., and D.A. Randall, 2002: Similarity of deep continental cumulus convection as revealed by a three-dimensional cloud resolving model. J. Atmos. Sci., 59, 2550-2566.

Examples

Idealized GATE Simulation of Convection over Tropical Atlantic (“GigaLES”)

    • Based on average forcing and sounding from GATE Phase III observations (30 August – 19 September 1074, Tropical Atlantic);
    • Forcing: SST, horizontal advective tendencies of s and q; mean wind nudged to observed; radiative heating prescribed; surface fluxes – interactive.
    • Domain: 2048x2048x256 grid points, or 205x205x27 km3 (horizontal grid spacing 100m);
    • Vertical grid spacing: 50m below 1km, 50-100m @1-5km; 100m @5-18km; 100-300m above;
    • Time step: 2 sec, duration: 1 day;
    • Initialization: random small-amplitude noise in temperature near the surface;
    • run done over 6 days wall-clock time on 2048 processors of IBM BlueGene BG/L of NYCCS;
    • Animations of mock-up cloud albedo as would be seen from a satellite orbit (15 simulated minutes per movie second);
    • One day evolution whole domain, Zoom-in into a quarter of a domain (100x100 km2) for 13.5 hours and Zoom-in into a 50x50 km2 subdomain for 2h40m:
Snapshot of a cloud scene at full model resolution (180x180 km2)

Snapshot of a cloud scene at full model resolution (180x180 km2)

KWAJEX Simulation

  • 23 July – 15 September 1999: 52 days, Kwajalein Atoll, Marshall Islands.
  • Forcing: SST, horizontal advective tendencies of s and q; large-scale vertical velocity; mean wind nudged to observed.
    Radiation and surface fluxes – interactive.
    Domain: 256x256x64 grid points, or 256x256x27 km3, time step: 10 sec, duration: 52 days
  • Snapshots of various cloud regimes: