bgrid_solo

Overview

DART interface module for the dynamical core of the GFDL AM2 Bgrid model. This model is subroutine callable from DART and can be run in a similar fashion to low-order models that produce diagnostic output files with multiple assimilation times per file.

The Bgrid model was originally configured as a comprehensive atmospheric model as described in Anderson et al. (2004). [1]

All of that code remains in the directories under the DART/models/bgrid_solo directory, however, much of the capability has been disabled by code modification. What is left is a dry dynamical core for a model with no diurnal cycle at equinox with forcing described in Held and Suarez (1994). [2]

The default settings are for a model with a 60x30 horizontal grid and 5 vertical levels. This is close to the smallest version that has somewhat realistic baroclinic instability resulting in mid-latitude ‘storm tracks’. The model resolution can be changed with the entries in the bgrid_cold_start_nml namelist described in the Namelist section. It may be necessary to change the model time step to maintain stability for larger model grids. The model state variables are the gridded surface pressure, temperature, and u and v wind components.

The bgrid_solo directory has a work/workshop_setup.csh script that compiles and runs an example. This example is intended to demonstrate that the same process used for a low-order model may be used for a much more complex model and generates output for state-space or observation-space diagnostics.

Some examples of ways in which this model can be configured and modified to test DART assimilation capabilities are documented in Anderson et al. (2005). [3]

Several programs that generate interesting observation sequences are available in the DART/models/bgrid_solo directory. These programs take interactive user input and create a text file that can be piped into program create_obs_sequence to create obs_sequence files. These can serve as examples for users who are interested in designing their own custom obs_sequence files.

Program column_rand creates an obs_sequence with randomly located columns of observations (essentially synthetic radiosondes) that observe surface pressure along with temperature and wind components at all model levels.

Program id_set_def_stdin generates an obs_sequence file that observes every state variable with error variance of 10000 for surface pressure and 1.0 for temperature and wind components.

Program ps_id_stdin generates an obs_sequence that observes every surface pressure variable for the default model size (30x60) with an error variance of 100.

Program ps_rand_local generates a set of randomly located surface pressure observations with an interactively specified error variance. It also allows the observations to be confined to a rectangular subdomain.

Namelist

The &model_nml namelist is read from the input.nml file. Namelists start with an ampersand & and terminate with a slash /. Character strings that contain a / must be enclosed in quotes to prevent them from prematurely terminating the namelist.

&model_nml
   current_time =  0, 0, 0, 0
   override = .false.,
   dt_atmos = 3600,
   days     = 10,
   hours    = 0,
   minutes  = 0,
   seconds  = 0,
   noise_sd = 0.0,
   dt_bias  = -1,
   state_variables = 'ps', 'QTY_SURFACE_PRESSURE',
                     't',  'QTY_TEMPERATURE',
                     'u',  'QTY_U_WIND_COMPONENT',
                     'v',  'QTY_V_WIND_COMPONENT',
   template_file = 'perfect_input.nc'
/
# only used if initial conditions file not specified in run
&bgrid_cold_start_nml
   nlon = 60,
   nlat = 30,
   nlev = 5,
   equal_vert_spacing = .true.
/
# Values in hs_forcing_nml are described in Held and Suarez (1994)
&hs_forcing_nml
   delh      =  60.,
   t_zero    = 315.,
   t_strat   = 200.,
   delv      =  10.,
   eps       =   0.,
   ka        = -40.,
   ks        =  -4.,
   kf        =  -1.,
   sigma_b   =  .7,
   do_conserve_energy = .false.
/
&bgrid_core_driver_nml
   damp_coeff_wind   = 0.10,
   damp_coeff_temp   = 0.10,
   damp_coeff_tracer = 0.10,
   advec_order_wind   = 4,
       advec_order_temp   = 2,
       advec_order_tracer = 2,
       num_sponge_levels = 1,
       sponge_coeff_wind   = 1.00,
       sponge_coeff_temp   = 1.00,
       sponge_coeff_tracer = 1.00,
       num_fill_pass = 2,
       decomp = 0,0,
       num_adjust_dt = 3,
       num_advec_dt  = 3,
       halo = 1,
       do_conserve_energy = .false.
/
&bgrid_integrals_nml
   file_name  = 'dynam_integral.out',
   time_units = 'days',
   output_interval = 1.00
/

Description of each namelist entry

The following values are specified in model_nml.

Item	Type	Description
current_time(4)	integer	Specifies the initial time of the Bgrid model internal clock. The four integer values are the day, hour, minutes, and seconds. The default version of the Bgrid model has neither a diurnal or seasonal cycle, so these can all be set to 0, the default value.
override	logical	If true, then the initial model date is taken from namelist entry current_time, even if an atmos_model.res file is found in directory INPUT. For most DART applications, atmospheric restart values are coming from DART files and no INPUT directory is used.
dt_atmos	integer	Model timestep in seconds.
noise_sd	real(r8)	Standard deviation of random perturbations to the time tendency of temperature applied at each timestep. Each gridpoint value of the computed temperature tendency is multiplied by 1+N(0, noise_sd) before the updated values of temperature are computed.
dt_bias	integer	Allows a simple mechanism to simulate model error. If dt_bias is non-zero, the assimilation programs believe that each model advance changes the time by dt_bias. However, internally the bgrid model is moving things forward by dt_atmos. By running perfect_model_obs with one time step for the internal bgrid clock (for instance dt_atmos = 3600, dt_bias = 3600), and filter with another (dt_atmos = 3000, and dt_bias = 3600) model error is simulated.
state_variables(:,2)	character(len=129)	Strings that identify the bgrid_solo variables that should be part of the DART state vector. The first column is the netCDF variable name, the second column is the corresponding DART quantity.
template_file	character(len=256)	This is the name of the file that specifies the resolution of the variables DART uses to create the DART state vector. If template_file = “null” the &bgrid_cold_start_nml namelist variables are used to specify the resolution. The actual input filenames for filter and perfect_model_obs come from their respective namelists. The resolutions in the file specified in template_file must match the resolutions of the variables in the input filenames. To start an experiment with a new model resolution, set template_file to “null” and set the resolutions in bgrid_cold_start_nml.

The following values are specified in bgrid_cold_start_nml.

Item	Type	Description
nlon	integer	The number of longitudes on the model grid.
nlat	integer	The number of latitudes on the model grid.
nlev	integer	The number of model levels.
equal_vertical_spacing	logical	Model levels are equally spaced in pressure if true.

The Held-Suarez forcing details can be modified with the hs_forcing_nml namelist using the documentation in Held and Suarez (1994).

Model dynamics can be adjusted with the bgrid_core_driver_nml following the documentation in the references and internal documentation in the bgrid code.

References

[1]

Anderson, J. L. and Coauthors, 2004: The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations. Journal of Climate, 17, 4641-4673. doi:10.1175/JCLI-3223.1

[2]

Held, I. M., and M. J. Suarez, 1994: A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models, Bulletin of the American Meteorological Society, 75(10), 1825-1830. doi:10.1175/1520-0477(1994)075<1825:APFTIO>2.0.CO;2

[3]

Anderson, J. L., Wyman, B., Zhang, S. & Hoar, T., 2005: Assimilation of surface pressure observations using an ensemble filter in an idealized global atmospheric prediction system, Journal of the Atmospheric Sciences, 62, 2925-2938. doi:10.1175/JAS3510.1