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.
In the DART/models/bgrid_solo/work
directory, an example “perfect model” experiment
can be run in which a bgrid_solo netcdf file is produced and then perturbed
to get an ensemble. 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.
The steps to run this example are as follows:
./quickbuild.sh
(orquickbuild.sh nompi
if you are not building with mpi)Builds all DART executables andperfect_input.nc
from the cdl fileperfect_input.cdl
./perfect_model_obs
Reads in an observation sequence file which has only observation definitions (obs_seq.in
) and generates synthetic observation values from a hindcast model (perfect_input.nc
). Results in output state vector file (perfect_output.nc
) and an output observation sequence file (obs_seq.out
) to be assimilated byfilter
cp perfect_output.nc filter_input.nc
Copies the output from theperfect_model_obs
program to the input file for thefilter
program- In
work/input.nml
, setperturb_from_single_instance = .true.
in the&filter_nml
This setting causes filter to perturb a single restart file to generate an ensemble ./filter
Runs the assimilation program, resulting in three main output files:preassim.nc
- the state of all ensemble members prior to the assimilation (i.e. the forecast with any prior inflation applied)analysis.nc
- the state of all ensemble members after the assimilationobs_seq.final
- the ensemble members’ estimate of the observations.
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 ofobservations (essentially synthetic radiosondes) that observe surface pressurealong with temperature and wind components at all model levels. - Program
id_set_def_stdin
generates an obs_sequence file that observes everystate variable with error variance of 10000 for surface pressure and 1.0 fortemperature and wind components. - Program
ps_id_stdin
generates an obs_sequence that observes every surfacepressure variable for the default model size (30x60) with an error variance of 100. - Program
ps_rand_local
generates a set of randomly located surface pressureobservations with an interactively specified error variance. It also allows theobservations to be confined to a rectangular subdomain.
Diagnostics
The best method to determine the performance of an experiment in which you
assimilate data from real-world sources is to compare the ensemble estimates of
the observation to your real-world data. You can estimate the bias and error of
the ensemble mean or gauge how many of the real-world observations are actually
being assimilated. These diagnostics are known as observation-space diagnostics.
DART provides the program obs_diag
and MATLAB observation space diagnostics
for you to use to quickly assess the performance of your experiment.
obs_diag
reads the obs_seq.final
files and calculates several quantities,
such as the root-mean-squared error, bias, and spread, for an arbitrary number of
regions and levels. obs_diag
outputs a netCDF file called obs_diag_output.nc
,
which can then be used in the DART MATLAB routines located in
DART/diagnostics/matlab/
.
For more detail on obs_diag and the MATLAB diagnostics, see PROGRAM obs_diag for the threed_sphere location module and MATLAB observation space diagnostics.
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, minute, and second. 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 |
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 |
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 |
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.