Recent progress and review of issues related to Physics Dynamics Coupling in geophysical models

Geophysical models of the atmosphere and ocean invariably involve parameterizations. These represent two distinct areas: a) Subgrid processes which the model cannot (yet) resolve, due to its discrete resolution, and b) sources in the equation, due to radiation for example. Hence coupling between these physics parameterizations and the resolved fluid dynamics and also between the dynamics of the different fluids in the system (air and water) is necessary. This coupling is an important aspect of geophysical models. However, often model development is strictly segregated into either physics or dynamics. Hence, this area has many more unanswered questions than in-depth understanding. Furthermore, recent developments in the design of dynamical cores (e.g. significant increase of resolution, move to non-hydrostatic equation sets etc), extended process physics (e.g. prognostic micro physics, 3D turbulence, non-vertical radiation etc) and predicted future changes of the computational infrastructure (e.g. Exascale with its need for task parallelism, data locality and asynchronous time stepping for example) is adding even more complexity and new questions. This paper reviews the state-of-the-art of the physics-dynamics coupling in geophysical models, surveys the analysis techniques, and points out the open questions in this research field.

[1]  Mark A. Taylor,et al.  CAM-SE: A scalable spectral element dynamical core for the Community Atmosphere Model , 2012, Int. J. High Perform. Comput. Appl..

[2]  Todd D. Ringler,et al.  Observed Scaling in Clouds and Precipitation and Scale Incognizance in Regional to Global Atmospheric Models , 2013 .

[3]  Hui Wan,et al.  Short‐term time step convergence in a climate model , 2015, Journal of advances in modeling earth systems.

[4]  N. McFarlane,et al.  Sensitivity of Climate Simulations to the Parameterization of Cumulus Convection in the Canadian Climate Centre General Circulation Model , 1995, Data, Models and Analysis.

[5]  Sylvie Malardel,et al.  An alternative cell‐averaged departure point reconstruction for pointwise semi‐Lagrangian transport schemes , 2015 .

[6]  Francis X. Giraldo,et al.  A study of spectral element and discontinuous Galerkin methods for the Navier-Stokes equations in nonhydrostatic mesoscale atmospheric modeling: Equation sets and test cases , 2008, J. Comput. Phys..

[7]  A. P. Siebesma,et al.  A Combined Eddy-Diffusivity Mass-Flux Approach for the Convective Boundary Layer , 2007 .

[8]  H. Pitsch,et al.  Antialiasing Filters for Coupled Reynolds-Averaged/Large-Eddy Simulations , 2005 .

[9]  Christian Kühnlein,et al.  Modelling atmospheric flows with adaptive moving meshes , 2012, J. Comput. Phys..

[10]  D. Randall,et al.  A Semiempirical Cloudiness Parameterization for Use in Climate Models , 1996 .

[11]  M. J. P. Cullen,et al.  On the use of a predictor–corrector scheme to couple the dynamics with the physical parametrizations in the ECMWF model , 2003 .

[12]  Andreas Bott,et al.  Dynamics of the Atmosphere: A Course in Theoretical Meteorology , 2003 .

[13]  C. Kilsby.  Context and Aims , 2007 .

[14]  Nigel Wood,et al.  Some numerical properties of approaches to physics–dynamics coupling for NWP , 2006 .

[15]  James A. Hansen,et al.  The Impact of Noisy Physics on the Stability and Accuracy of Physics–Dynamics Coupling , 2013 .

[16]  Todd D. Ringler,et al.  A Multiscale Nonhydrostatic Atmospheric Model Using Centroidal Voronoi Tesselations and C-Grid Staggering , 2012 .

[17]  Sungsu Park,et al.  A Unified Convection Scheme (UNICON). Part I: Formulation , 2014 .

[18]  M. Taylor,et al.  Effects of localized grid refinement on the general circulation and climatology in the Community Atmosphere Model , 2015 .

[19]  Hui Wan,et al.  Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models , 2014 .

[20]  E. Hanert,et al.  On the mathematical stability of stratified flow models with local turbulence closure schemes , 2008 .

[21]  Benjamin Ganis,et al.  Stability of algorithms for a two domain natural convection problem and observed model uncertainty , 2011 .

[22]  Eric Blayo,et al.  Optimized global-in-time Schwarz algorithm for diffusion equations with discontinuous and spatially variable coefficients , 2008 .

[23]  L. Leung,et al.  Numerical Issues Associated with Compensating and Competing Processes in Climate Models: an Example from ECHAM-HAM , 2013 .

[24]  Mark A. Taylor,et al.  Petascale atmospheric models for the Community Climate System Model: new developments and evaluation of scalable dynamical cores , 2008 .

[25]  Nigel Wood,et al.  A Simple Comparison of Four Physics–Dynamics Coupling Schemes , 2002 .

[26]  R. Neale,et al.  The Impact of Convection on ENSO: From a Delayed Oscillator to a Series of Events , 2008 .

[27]  René Laprise,et al.  Consequences of Using the Splitting Method for Implementing Physical Forcings in a Semi-Implicit Semi-Lagrangian Model , 1998 .

[28]  Steven J. Woolnough,et al.  Precipitation distributions for explicit versus parametrized convection in a large‐domain high‐resolution tropical case study , 2012 .

[29]  Nils Wedi,et al.  How does subgrid‐scale parametrization influence nonlinear spectral energy fluxes in global NWP models? , 2016 .

[30]  D. Williamson.  The effect of time steps and time‐scales on parametrization suites , 2013 .

[31]  C. Zarzycki,et al.  Characterizing Sierra Nevada Snowpack Using Variable-Resolution CESM , 2016 .

[32]  Christiane Jablonowski,et al.  Aquaplanet Experiments Using CAM’s Variable-Resolution Dynamical Core , 2014 .

[33]  J. Morcrette,et al.  A fast, flexible, approximate technique for computing radiative transfer in inhomogeneous cloud fields , 2003 .

[34]  J. Deardorff,et al.  The Counter-Gradient Heat Flux in the Lower Atmosphere and in the Laboratory , 1966 .

[35]  P. Squires.  The Growth of Cloud Drops by Condensation. I. General Characteristics , 1952 .

[36]  Philip J. Rasch,et al.  Effects of Convective Momentum Transport on the Atmospheric Circulation in the Community Atmosphere Model, Version 3 , 2008 .

[37]  Ming Zhao,et al.  Some counterintuitive dependencies of tropical cyclone frequency on parameters in a GCM , 2012 .

[38]  C. W. Newton.  Atmospheric general circulation , 2014 .

[39]  M. Diamantakis,et al.  An inherently mass‐conserving semi‐implicit semi‐Lagrangian discretization of the deep‐atmosphere global non‐hydrostatic equations , 2014 .

[40]  U. Wacker,et al.  Continuity equations as expressions for local balances of masses in cloudy air , 2003 .

[41]  A. Molod.  Running GCM physics and dynamics on different grids: algorithm and tests , 2006 .

[42]  D. Williamson,et al.  Dependence of aqua‐planet simulations on time step , 2003 .

[43]  Blackwell Munksgaard.  Running GCM physics and dynamics on different grids: algorithm and tests , 2009 .

[44]  S. Mishra,et al.  Effects of time step size on the simulation of tropical climate in NCAR-CAM3 , 2011 .

[45]  Nigel Wood,et al.  Mixed Parallel–Sequential-Split Schemes for Time-Stepping Multiple Physical Parameterizations , 2005 .

[46]  Andrew Gettelman,et al.  Advanced Two-Moment Bulk Microphysics for Global Models. Part II: Global Model Solutions and Aerosol–Cloud Interactions* , 2015 .

[47]  Mark A. Taylor,et al.  A compatible and conservative spectral element method on unstructured grids , 2010, J. Comput. Phys..

[48]  Nigel Wood,et al.  A monotonically‐damping second‐order‐accurate unconditionally‐stable numerical scheme for diffusion , 2007 .

[49]  W. Collins,et al.  Impact of horizontal resolution on simulation of precipitation extremes in an aqua-planet version of Community Atmospheric Model (CAM3) , 2011 .

[50]  U. Lohmann,et al.  The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations , 2012 .

[51]  Nigel Wood,et al.  Analysis of Parallel versus Sequential Splittings for Time-Stepping Physical Parameterizations , 2004 .

[52]  Todd D. Ringler,et al.  Exploring a Multiresolution Modeling Approach within the Shallow-Water Equations , 2011 .

[53]  R. Nanjundiah,et al.  The Impact of the Time Step on the Intensity of ITCZ in an Aquaplanet GCM , 2008 .

[54]  P. Marquet,et al.  On a general definition of the squared Brunt–Väisälä frequency associated with the specific moist entropy potential temperature , 2014, 1401.2379.

[55]  D. Williamson.  Convergence of atmospheric simulations with increasing horizontal resolution and fixed forcing scales , 1999 .

[56]  M. Suárez,et al.  A Moist Benchmark Calculation for Atmospheric General Circulation Models , 2008 .

[57]  B. Hoskins,et al.  Believable scales and parameterizations in a spectral transform model , 1997 .

[58]  R. Smith.  A scheme for predicting layer clouds and their water content in a general circulation model , 1990 .

[59]  Vincent E. Larson,et al.  A PDF-Based Model for Boundary Layer Clouds. Part I: Method and Model Description , 2002 .

[60]  Eric Blayo,et al.  Analysis of Ocean-atmosphere Coupling Algorithms: Consistency and Stability , 2017, ICCS.

[61]  I. Kang,et al.  Impacts of cumulus convection parameterization on aqua-planet AGCM simulations of tropical intraseasonal variability , 2003 .

[62]  P. Rasch,et al.  The Separate Physics and Dynamics Experiment (SPADE) framework for determining resolution awareness: A case study of microphysics , 2013 .

[63]  J. Wyngaard.  Toward Numerical Modeling in the “Terra Incognita” , 2004 .

[64]  William B. Large,et al.  Surface fluxes for practitioners of global ocean data assimilation , 2006 .

[65]  A. Arakawa,et al.  A Unified Representation of Deep Moist Convection in Numerical Modeling of the Atmosphere. Part I , 2013 .

[66]  Vincent E. Larson,et al.  A PDF-Based Model for Boundary Layer Clouds. Part II: Model Results , 2002 .

[67]  S. Ghan,et al.  Assessing the CAM5 physics suite in the WRF-Chem model: implementation, resolution sensitivity, and a first evaluation for a regional case study , 2014 .

[68]  S. Manabe,et al.  Climate Calculations with a Combined Ocean-Atmosphere Model , 1969 .

[69]  Robert D. Gregg,et al.  A unified parameterization of human gait across ambulation modes , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[70]  Niels Bormann,et al.  Representing Equilibrium and Nonequilibrium Convection in Large-Scale Models , 2014 .

[71]  B. Möbis,et al.  Factors controlling the position of the Intertropical Convergence Zone on an aquaplanet , 2012 .

[72]  G. Martin,et al.  A New Boundary Layer Mixing Scheme. Part I: Scheme Description and Single-Column Model Tests , 2000 .

[73]  Eric Blayo,et al.  Sensitivity of Ocean-Atmosphere Coupled Models to the Coupling Method : Example of Tropical Cyclone Erica , 2014 .

[74]  Luis Kornblueh,et al.  Sensitivity of Simulated Climate to Horizontal and Vertical Resolution in the ECHAM5 Atmosphere Model , 2006 .

[75]  J. Geleyn,et al.  Cloud and Precipitation Parameterization in a Meso-Gamma-Scale Operational Weather Prediction Model , 2009 .

[76]  David B. Stephenson,et al.  The impact of changing the horizontal diffusion scheme on the northern winter climatology of a general circulation model , 1995 .

[77]  D. Lawrence,et al.  A new synoptic scale resolving global climate simulation using the Community Earth System Model , 2014 .

[78]  C. Hannay,et al.  Exploratory High-Resolution Climate Simulations using the Community Atmosphere Model (CAM) , 2014 .

[79]  David L. Williamson,et al.  Convergence of aqua-planet simulations with increasing resolution in the Community Atmospheric Model, Version 3 , 2008 .

[80]  David L. Williamson,et al.  Time-Split versus Process-Split Coupling of Parameterizations and Dynamical Core , 2002 .

[81]  A. Kitoh,et al.  Effect of SST Variation on ITCZ in APE Simulations , 2013 .

[82]  Shian‐Jiann Lin.  A “Vertically Lagrangian” Finite-Volume Dynamical Core for Global Models , 2004 .

[83]  P. Termonia,et al.  Multiscale Performance of the ALARO-0 Model for Simulating Extreme Summer Precipitation Climatology in Belgium , 2013 .

[84]  William C. Skamarock,et al.  Evaluation of Global Atmospheric Solvers Using Extensions of the Jablonowski and Williamson Baroclinic Wave Test Case , 2013 .