Multiscale

Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System

Research Highlights

Media

2015 Highlights

  1. Chowdhary, K., Salloum, B. Debusschere, V. E. Larson (2015). “Quadrature methods for the calculation of subgrid microphysics moments.” Mon. Wea. Rev. (accepted). doi:10.1175/MWR-D-14-00168.1 (early online release).
  2. Fan, J. Y.-C. Liu, K.-M. Xu, K. North, S. Collis, X. Dong, J. Zhang, Q. Chen, P. Kollias, S. Ghan (2015): “Improving representation of convective transport for scale-aware parameterization: 1. Convective and cloud properties simulated with spectral bin and bulk microphysics,” J. Geophys. Res. Atmos., 120, 3485 –3509, doi:10.1002/2014JD022142.
  3. Guba, O., A. Taylor, P. Ullrich, J.R. Overfelt, M.N. Levy (2014): “The spectral element method on variable resolution grids: Evaluating grid sensitivity and resolution-aware numerical viscosity”, Geosci. Model Dev., 7 No. 3: 4081–4117.doi:10.5194/gmdd-7-4081-2014.
  4. Guo, Z., Wang, Y. Qian, V. E. Larson, S. Ghan, M. Ovchinnikov, P. Bogenchutz, A. Gettelman, and T. Zhou (2015): “Parametric behaviors of CLUBB in simulation of low clouds in the Community Atmosphere Model CAM5.” J. Adv. Model. Earth Sys. doi:10.1002/2014MS000405.
  5. Langhans, W., K. Yeo, M. Romps (2015): “Lagrangian investigation of the precipitation efficiency of convective clouds.” Journal of the Atmospheric Sciences 72, no. 3 (2015): 1045-1062.
  6. Liu, Y.-C., J. Fan, G. J. Zhang, K.-M. Xu, Ghan (2015): “Improving representation of convective transport for scale-aware parameterization: 2. Analysis of cloud-resolving model simulations.” J. Geophys. Res. Atmos., 120, 3510-3532, doi:10.1002/2014JD022145.
  7. Romps, D.M. (2015): “MSE minus CAPE is the true conserved variable for an adiabatically lifted parcel,” Journal of the Atmospheric Sciences, in press. doi:10.1175/JAS-D-15-0054.1 (early online release).
  8. Saenz, J.A., Chen, T. Ringler, (2015): “Prognostic residual-mean flow in an ocean general circulation model and its relation to prognostic Eulerian-mean flow.” Journal of Physical Oceanography. (accepted).
  9. Storer, R., B. Griffin, J. Höft, J. Weber, E. Raut, Larson, M. Wang, P. Rasch (2015): “Parameterizing deep convection using the assumed probability density function method,” Geoscientific Model Development, 8, 1–19, 2015. doi:10.5194/gmd-8-1-2015.
  10. Suhas, E., J. Zhang (2015): “Evaluating convective parameterization closures using cloud-resolving model simulation of tropical deep convection,” J. Geophys. Res. Atmos., 120, doi:10.1002/2014JD022246.
  11. Thayer-Calder, K., A. Gettelman, C. Craig, S. Goldhaber, P.A. Bogenschutz, C.-C. Chen, H. Morrison, J. Höft, E. Raut, B.M. Griffin, J.K. Weber, E. Larson, M.C. Wyant, M. Wang, Z. Guo, S.J. Ghan (2015): “A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model,” Geosci. Model Dev. Discuss., 8, 5041-5088, doi:10.5194/gmdd-8-5041-2015.
  12. Ullrich, P.A., M.A. Taylor (2015): “Arbitrary-Order Conservative and Consistent Remapping and a Theory of Linear Maps, Part 1”, Wea. Rev. 143, 2419–2440. doi:10.1175/MWR-D-14-00343.1.
  13. Wan, H., P.J. Rasch, M.A. Taylor, C. Jablonowski (2015): “Short-term time step convergence in a climate model,” Adv. Model. Earth Syst., 7, 215–225, doi:10.1002/2014MS000368.
  14. Zarzycki, C.M., C. Jablonowski, D.R. Thatcher, A. Taylor (2015): “Effects of localized grid refinement on the general circulation and climatology in the Community Atmosphere Model”,
    J. Clim.28, No.7: 2777–2803. doi:10.1175/JCLI-D-14-00599.1.
  15. Zhang, G.J., J. Fan, K.-M. Xu (2015): Comments on “A unified representation of deep moist convection in numerical modeling of the atmosphere. Part I”. J. Atmos. Sci., 72, 2562-2565. doi:10.1175/JAS-D-14-0246.1

2014 Highlights

  1. Duarte, M., A.S. Almgren, K. Balakrishnan, J.B. Bell, and D.M. Romps (2014), A numerical study of methods for moist atmospheric flows: compressible equations, Monthly Weather Review, in press.
  2. Gettelman, A., H. Morrison, S. Santos, P. Bogenschutz and P. M. Caldwell (2014), Advanced Two-Moment Microphysics for Global Models. Part II: Global model solutions and Aerosol-Cloud Interactions. J. Climate, 2014, doi: 10.1175/JCLI-D-14-00103.1. In press.
  3. Guo, Z., M. Wang, Y. Qian, V. Larson, S. Ghan, M. Ovchinnikov, P. Bogenschutz, C. Zhao, G. Lin, and T. Zhou, 2014: A sensitivity study of cloud properties to CLUBB parameters in the single column Community Atmosphere Model (SCAM5), J. Adv. Model. Earth Sys., accepted. doi: 10.1002/2014MS000315.
  4. Lott, P.A., C.S. Woodward, K.J. Evans (2014). Algorithmically scalable block preconditioner for fully implicit shallow water equations in CAM-SE. Comp. Geosci. , accepted. doi: 10.1007/s10596-014-9447-6
  5. Salloum, M., K. Chowdhary, B. Debusschere, “ForQint v. 1.0”. Fortran library for quadrature integration released as open source under Lesser General Public License (LGPL), 7/31/2014.
  6. Romps, D.M., J.T. Seeley, Vollaro, J. Molinari (2014), “Projected increase in lightning strikes in the United States due to global warming,” Science, 346, no. 6211 (2014): 851-854.
  7. Romps, D.M. (2014), An analytical model for tropical relative humidity, Journal of Climate, vol. 27, no. 19, 7432–7449. doi: http://dx.doi.org/10.1175/JCLI-D-14-00255.1
  8. Suhas, E., and G. J. Zhang, 2014: “Evaluation of trigger functions for convective parameterization schemes using observations.” J. Climate, Volume 27, Issue 20 doi: http://dx.doi.org/10.1175/JCLI-D-13-00718.1, accepted.
  9. Wan, H., P. J. Rasch, K. Zhang, Y. Qian, H. Yan, and C. Zhao, 2014: An efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models, Geosci. Model Dev. Discuss., 7, 2173-2216, doi:10.5194/gmdd-7-2173-2014.
  10. Zhang, K., H. Wan, X. Liu, S. J. Ghan, G. J. Kooperman, P.-L. Ma, and P. J. Rasch, 2014: “On the use of nudging for aerosol-climate model intercomparison studies”, Atmos. Chem. Phys., 14, 8631-8645, doi:10.5194/acp-14-8631-2014.