scholarly journals Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling

2020 ◽  
Vol 12 (10) ◽  
Author(s):  
Hui Wan ◽  
Carol S. Woodward ◽  
Shixuan Zhang ◽  
Christopher J. Vogl ◽  
Panos Stinis ◽  
...  
Keyword(s):  
Time Step ◽  
Atmosphere Model ◽  
Process Coupling ◽  
Closure Assumption

scholarly journals The Role of Process Coupling in the Time Step Sensitivity of E3SM's Microphysics

2020 ◽  
Author(s):  
Sean Patrick Santos ◽  
Peter Caldwell ◽  
Christopher Bretherton
Keyword(s):  
Time Step ◽  
Process Coupling

scholarly journals WAVETRISK-2.1: an adaptive dynamical core for ocean modelling

2021 ◽  
Author(s):  
Nicholas Keville-Reynolds Kevlahan ◽  
Florian Lemarié
Keyword(s):  
Free Surface ◽  
Shallow Water ◽  
Time Integration ◽  
Ocean Model ◽  
Mesh Adaptivity ◽  
Time Step ◽  
Vertical Coordinate ◽  
Slip Boundary ◽  
Modelling Framework ◽  
Atmosphere Model

Abstract. This paper introduces WAVETRISK-2.1 (i.e. WAVETRISK-OCEAN), an incompressible version of the atmosphere model wavetrisk-1.x with free-surface. This new model is built on the same wavelet-based dynamically adaptive core as wavetrisk, which itself uses DYNANICO's mimetic vector-invariant multilayer rotating shallow water formulation. Both codes use a Lagrangian vertical coordinate with conservative remapping. The ocean variant solves the incompressible multilayer shallow water equations with inhomogeneous density layers. Time integration uses barotropic--baroclinic mode splitting via an semi-implicit free surface formulation, which is about 34–44 times faster than an unsplit explicit time-stepping. The barotropic and baroclinic estimates of the free surface are reconciled at each time step using layer dilation. No slip boundary conditions at coastlines are approximated using volume penalization. The vertical eddy viscosity and diffusivity coefficients are computed from a closure model based on turbulent kinetic energy (TKE). Results are presented for a standard set of ocean model test cases adapted to the sphere (seamount, upwelling and baroclinic turbulence). An innovative feature of wavetrisk-ocean is that it could be coupled easily to the wavetrisk atmosphere model, thus providing a first building block toward an integrated Earth-system model using a consistent modelling framework with dynamic mesh adaptivity and mimetic properties.

WAVETRISK-OCEAN: an adaptive dynamical core for ocean modelling

2021 ◽  
Author(s):  
Kevlahan Nicholas
Keyword(s):  
Free Surface ◽  
Shallow Water ◽  
Time Integration ◽  
Ocean Model ◽  
Time Step ◽  
Vertical Coordinate ◽  
Modelling Framework ◽  
Standard Set ◽  
Atmosphere Model ◽  
Multilayer Shallow Water Equations

<p>This talk introduces WAVETRISK-OCEAN, an incompressible version of the atmosphere model WAVETRISK.  This new model is built on the same wavelet-based dynamically adaptive core as WAVETRISK, which itself uses DYNAMICO's mimetic vector-invariant multilayer shallow water formulation. Both codes use a Lagrangian vertical coordinate with conservative remapping.  The ocean variant solves the incompressible multilayer shallow water equations with a Ripa type thermodynamic treatment of horizontal density gradients.  Time integration uses barotropic-baroclinic mode splitting via an implicit free surface formulation, which is about 15 times faster than explicit time stepping.  The barotropic and baroclinic estimates of the free surface are reconciled at each time step using layer dilation. No slip boundary conditions at coastlines are approximated using volume penalization.  Results are presented for a standard set of ocean model test cases adapted to the sphere (seamount,  upwelling and baroclinic jet) as well as  turbulent wind-driven gyre flow in simplified geometries.  An innovative feature of WAVETRISK-OCEAN is that it could be coupled easily to the WAVETRISK atmosphere model, providing a simple integrated Earth system model using a consistent modelling framework.</p>

scholarly journals Cloud Process Coupling and Time Integration in the E3SM Atmosphere Model

2021 ◽  
Author(s):  
Sean Patrick Santos ◽  
Christopher Bretherton ◽  
Peter Caldwell
Keyword(s):  
Time Integration ◽  
Atmosphere Model ◽  
Cloud Process ◽  
Process Coupling

scholarly journals Empirical Correction of a Coupled Land–Atmosphere Model

2008 ◽  
Vol 136 (11) ◽  
pp. 4063-4076 ◽  
Author(s):  
Timothy DelSole ◽  
Mei Zhao ◽  
Paul A. Dirmeyer ◽  
Ben P. Kirtman
Keyword(s):  
Forecast Error ◽  
Error Variance ◽  
Correction Method ◽  
Mean Value ◽  
Lead Times ◽  
Time Step ◽  
Relaxation Methods ◽  
Empirical Correction ◽  
Atmosphere Model

Abstract This paper investigates empirical strategies for correcting the bias of a coupled land–atmosphere model and tests the hypothesis that a bias correction can improve the skill of such models. The correction strategies investigated include 1) relaxation methods, 2) nudging based on long-term biases, and 3) nudging based on tendency errors. The last method involves estimating the tendency errors of prognostic variables based on short forecasts—say lead times of 24 h or less—and then subtracting the climatological mean value of the tendency errors at every time step. By almost any measure, the best correction strategy is found to be nudging based on tendency errors. This method significantly reduces biases in the long-term forecasts of temperature and soil moisture, and preserves the variance of the forecast field, unlike relaxation methods. Tendency errors estimated from ten 1-day forecasts produced just as effective corrections as tendency errors estimated from all days in a month, implying that the method is trivial to implement by modern standards. Disappointingly, none of the methods investigated consistently improved the random error variance of the model, although this finding may be model dependent. Nevertheless, the empirical correction method is argued to be worthwhile even if it improves only the bias, because the method has only marginal impacts on the numerical speed and represents forecast error in the form of a tendency error that can be compared directly to other terms in the tendency equations, which in turn provides clues as to the source of the forecast error.

The Formulation and Atmospheric Simulation of the Community Atmosphere Model Version 3 (CAM3)

2006 ◽  
Vol 19 (11) ◽  
pp. 2144-2161 ◽  
Author(s):  
William D. Collins ◽  
Philip J. Rasch ◽  
Byron A. Boville ◽  
James J. Hack ◽  
James R. McCaa ◽  
...  
Keyword(s):  
Finite Volume ◽  
Radiative Forcing ◽  
General Circulation ◽  
Circulation Model ◽  
Surface Radiation ◽  
Time Step ◽  
Community Land Model ◽  
Enso Events ◽  
Community Atmosphere Model ◽  
Atmosphere Model

Abstract A new version of the Community Atmosphere Model (CAM) has been developed and released to the climate community. CAM Version 3 (CAM3) is an atmospheric general circulation model that includes the Community Land Model (CLM3), an optional slab ocean model, and a thermodynamic sea ice model. The dynamics and physics in CAM3 have been changed substantially compared to implementations in previous versions. CAM3 includes options for Eulerian spectral, semi-Lagrangian, and finite-volume formulations of the dynamical equations. It supports coupled simulations using either finite-volume or Eulerian dynamics through an explicit set of adjustable parameters governing the model time step, cloud parameterizations, and condensation processes. The model includes major modifications to the parameterizations of moist processes, radiation processes, and aerosols. These changes have improved several aspects of the simulated climate, including more realistic tropical tropopause temperatures, boreal winter land surface temperatures, surface insolation, and clear-sky surface radiation in polar regions. The variation of cloud radiative forcing during ENSO events exhibits much better agreement with satellite observations. Despite these improvements, several systematic biases reduce the fidelity of the simulations. These biases include underestimation of tropical variability, errors in tropical oceanic surface fluxes, underestimation of implied ocean heat transport in the Southern Hemisphere, excessive surface stress in the storm tracks, and offsets in the 500-mb height field and the Aleutian low.

scholarly journals Cloud Process Coupling and Time Integration in the E3SM Atmosphere Model

2020 ◽  
Author(s):  
Sean Patrick Santos ◽  
Christopher Bretherton ◽  
Peter Caldwell
Keyword(s):  
Time Integration ◽  
Atmosphere Model ◽  
Cloud Process ◽  
Process Coupling

scholarly journals Diagnostic Computation of Moisture Budgets in the ERA-Interim Reanalysis with Reference to Analysis of CMIP-Archived Atmospheric Model Data*

2013 ◽  
Vol 26 (20) ◽  
pp. 7876-7901 ◽  
Author(s):  
Richard Seager ◽  
Naomi Henderson
Keyword(s):  
Data Availability ◽  
Diagnostic Evaluation ◽  
Vertical Resolution ◽  
Model Data ◽  
Time Step ◽  
Sources Of Error ◽  
Daily Data ◽  
Hourly Data ◽  
Moisture Fluxes ◽  
Atmosphere Model

Abstract The diagnostic evaluation of moisture budgets in archived atmosphere model data is examined. Sources of error in diagnostic computation can arise from the use of numerical methods different from those used in the atmosphere model, the time and vertical resolution of the archived data, and data availability. These sources of error are assessed using the climatological moisture balance in the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) that archives vertically integrated moisture fluxes and convergence. The largest single source of error arises from the diagnostic evaluation of divergence. The chosen second-order accurate centered finite difference scheme applied to the actual vertically integrated moisture fluxes leads to significant differences from the ERA-Interim reported moisture convergence. Using daily data, instead of 6-hourly data, leads to an underestimation of the patterns of moisture divergence and convergence by midlatitude transient eddies. A larger and more widespread error occurs when the vertical resolution of the model data is reduced to the 8 levels that is quite common for daily data archived for the Coupled Model Intercomparison Project (CMIP). Dividing moisture divergence into components due to the divergent flow and advection requires bringing the divergence operator inside the vertical integral, which introduces a surface term for which a means of accurate evaluation is developed. The analysis of errors is extended to the case of the spring 1993 Mississippi valley floods, the causes of which are discussed. For future archiving of data (e.g., by CMIP), it is recommended that monthly means of time-step-resolution flow–humidity covariances be archived at high vertical resolution.

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