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DART interface module for the *forced_lorenz_96* model. The 16 public interfaces
are standardized for all DART compliant models. These interfaces allow
DART to advance the model, get the model state and metadata describing
this state, find state variables that are close to a given location,
and do spatial interpolation for model state variables.

The *forced_lorenz_96* model implements the standard L96 equations except
that the forcing term, F, is added to the state vector and is
assigned an independent value at each gridpoint. The result is a
model that is twice as big as the standard L96 model. The forcing
can be allowed to vary in time or can be held fixed so that the
model looks like the standard L96 but with a state vector that
includes the constant forcing term. An option is also included to
add random noise to the forcing terms as part of the time
tendency computation which can help in assimilation performance.
If the random noise option is turned off (see namelist) the
time tendency of the forcing terms is 0.

DART state vector composition | |
---|---|

state variables indices 1 - 40 |
forcing terms indices 41 - 80 |

traditional Lorenz_96 state | "extended" state |

The DART tutorial Section 20 [pdf]
explores parameter estimation using the *forced_lorenz_96* model.

To become familiar with the model, try this quick experiment.

- compile everything in the
*model/forced_lorenz_96/work*directory.

cd models/forced_lorenz_96/work

./quickbuild.csh - make sure the
*input.nml*looks like the following (there is a lot that has been left out for clarity, these are the settings of interest for this example):

&perfect_model_obs_nml start_from_restart = .true., output_restart = .true., async = 0, restart_in_file_name = "perfect_ics", obs_seq_in_file_name = "obs_seq.in", obs_seq_out_file_name = "obs_seq.out", ... &filter_nml async = 0, ens_size = 80, start_from_restart = .true., output_restart = .true., obs_sequence_in_name = "obs_seq.out", obs_sequence_out_name = "obs_seq.final", restart_in_file_name = "filter_ics", restart_out_file_name = "filter_restart", num_output_state_members = 80, num_output_obs_members = 80, ... &model_nml num_state_vars = 40, forcing = 8.00, delta_t = 0.05, time_step_days = 0, time_step_seconds = 3600, reset_forcing = .false., random_forcing_amplitude = 0.10 /

- Run
*perfect_model_obs*to generate*true_state.nc*and*obs_seq.out*. The default*obs_seq.in*will cause the model to advance for 1000 time steps.

./perfect_model_obs - If you have
*ncview*, explore the*true_state.nc*. Notice that the State Variable indices from 1-40 are the dynamical part of the model and 41-80 are the Forcing variables.

ncview true_state.nc - Run
*filter*to generate*preassim.nc*,*analysis.nc*and*obs_seq.final*.

./filter - Launch Matlab and run
*plot_ens_time_series*.

>> plot_ens_time_series

Input name of prior or posterior diagnostics file:

for preassim.nc

*preassim.nc*

OPTIONAL: if you have the true state and want it superimposed, provide

: the name of the input file. If not, enter a dummy filename.

: Input name of True State file:

for true_state.nc

*true_state.nc*

Using state state variable IDs 1 13 27

If these are OK,;

If not, please enter array of state variable ID's

To choose from entire state enter A 25 50 75 (between 1 and 80)

To choose traditional model state enter S 1 23 40 (between 1 and 40)

To choose forcing estimates enter F 2 12 22 (between 1 and 40)

(no intervening syntax required)

*A 20 30 40 60 70 80*Indices 20, 30, and 40 will be from the dynamical part of the lorenz_96 attractor, indices 60, 70, and 80 will be the corresponding Forcing values. Here are some images for just indices 20 and 60. Click on each image for a high-res version.

Repeat the experiment with *reset_forcing = .true.* when creating the
true state and *reset_forcing = .false.* when assimilating. What happens?

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types_mod time_manager_mod oned/location_mod utilities_mod random_seq_mod

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A note about documentation style.
Optional arguments are enclosed in brackets
*[like this]*.

integer ::get_model_size

Returns the length of the model state vector. Required.

model_size |
The length of the model state vector. |

real(r8), dimension(:), intent(inout) ::xtype(time_type), intent(in) ::time

Advances this model for a single time step using a four-step Runga-Kutta. The time argument is not used.

x |
State vector of length model_size. |

time |
Specifies time of the initial model state. |

integer, intent(in) ::index_intype(location_type), intent(out) ::locationinteger, optional, intent(out) ::var_type

Returns metadata about a given element, indexed by index_in, in the model state vector. Returns location of the state variable at the given index. If present, var_type is set to 1 for the default variable type, and set to 2 if the forcing parameter is being assimilated.

index_in |
Index of state vector element about which information is requested. |

location |
The location of state variable element. |

var_type |
Returns the type of the indexed state variable as an optional argument. Valid types are 1 and 2. |

real(r8), dimension(:), intent(in) ::xtype(location_type), intent(in) ::locationinteger, intent(in) ::itypereal(r8), intent(out) ::obs_valinteger, intent(out) ::istatus

Given model state, returns the value of variable itype interpolated to a given location by a method of the model's choosing. At present, this is the only support for forward operators that is required from the model_mod.

x |
A model state vector. |

location |
Location to which to interpolate. |

itype |
Integer indexing which type of state variable is to be interpolated. Can be ignored for low order models with a single type of variable. |

obs_val |
The interpolated value from the model. |

istatus |
Quality control information about the observation of the model state. |

type(time_type) ::get_model_time_step

Returns the time step (forecast length) of the model; The time step defaults to 1 hour but is settable by namelist.

var |
Smallest time step of model. |

Used for runtime initialization of model; reads namelist, initializes model parameters, etc. This is the first call made to the model by any DART-compliant assimilation routine.

A stub routine in this model.

type(time_type), intent(out) ::time

Returns the time at which the model will start if no input initial conditions are to be used. This is used to spin-up the model from rest. Sets time to 0 in this model.

time |
Initial model time. |

real(r8), dimension(:), intent(out) ::x

Returns default initial conditions for model; generally used for spinning up initial model states. Sets the entire state variable to the value of the forcing and then slightly perturbs the first element.

x |
Initial conditions for state vector. |

integer ::nc_write_model_attsinteger, intent(in) ::ncFileID

Function to write model specific attributes to a netCDF file. At present, DART is using the NetCDF format to output diagnostic information. This is not a requirement, and models could choose to provide output in other formats. This function writes the metadata associated with the model to a NetCDF file opened to a file identified by ncFileID.

ncFileID |
Integer file descriptor to previously-opened netCDF file. |

ierr |
Returns a 0 for successful completion. |

integer ::nc_write_model_varsinteger, intent(in) ::ncFileIDreal(r8), dimension(:), intent(in) ::statevecinteger, intent(in) ::copyindexinteger, intent(in) ::timeindex

Writes a copy of the state variables to a netCDF file. Multiple copies of the state for a given time are supported, allowing, for instance, a single file to include multiple ensemble estimates of the state.

ncFileID |
file descriptor to previously-opened netCDF file. |

statevec |
A model state vector. |

copyindex |
Integer index of copy to be written. |

timeindex |
The timestep counter for the given state. |

ierr |
Returns 0 for normal completion. |

real(r8), dimension(:), intent(in) ::statereal(r8), dimension(:), intent(out) ::pert_statelogical, intent(out) ::interf_provided

Given a model state, produces a perturbed model state. This particular model does not implement an interface for this and so returns .false. for interf_provided.

state |
State vector to be perturbed. |

pert_state |
Perturbed state vector: NOT returned. |

interf_provided |
Returned false; interface is not implemented. |

type(get_close_type), intent(inout) ::gcreal(r8), intent(in) ::maxdist

Pass-through to the 1-D locations module. See get_close_maxdist_init() for the documentation of this subroutine.

type(get_close_type), intent(inout) ::gcinteger, intent(in) ::numtype(location_type), intent(in) ::obs(num)

Pass-through to the 1-D locations module. See get_close_obs_init() for the documentation of this subroutine.

type(get_close_type), intent(in) ::gctype(location_type), intent(in) ::base_obs_locinteger, intent(in) ::base_obs_kindtype(location_type), intent(in) ::obs(:)integer, intent(in) ::obs_kind(:)integer, intent(out) ::num_closeinteger, intent(out) ::close_ind(:)real(r8), optional, intent(out) ::dist(:)

Pass-through to the 1-D locations module. See get_close_obs() for the documentation of this subroutine.

real(r8), dimension(:), intent(in) ::ens_mean

A NULL INTERFACE in this model.

ens_mean |
State vector containing the ensemble mean. |

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This namelist is read from the file *input.nml*.
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.
The values shown here are the default values.

&model_nml num_state_vars = 40, forcing = 8.00, delta_t = 0.05, time_step_days = 0, time_step_seconds = 3600, reset_forcing = .false., random_forcing_amplitude = 0.10 /

Item | Type | Description |
---|---|---|

num_state_vars | integer | Number of variables in model. |

forcing | real(r8) | Forcing, F, for model. |

delta_t | real(r8) | Non-dimensional timestep. |

time_step_days | real(r8) | Base model time step maps to this much real time. |

time_step_seconds | real(r8) | Base model time step maps to this. |

reset_forcing | logical | If true, all forcing values are held fixed at the value specified for the forcing namelist. |

random_forcing_amplitude | real(r8) | Standard deviation of the gaussian noise with zero mean that is added to each forcing value's time step. |

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filename | purpose |
---|---|

input.nml |
to read the model_mod namelist |

true_state.nc |
the time-history of the single model state used to generate the synthetic observations |

preassim.nc |
the time-history of the model state before assimilation |

analysis.nc |
the time-history of the model state after assimilation |

advance_model.csh |
shell script to advance the model as a standalone executable. Each advance will then read the model's namelist. |

dart_log.out |
the run-time diagnostic output |

dart_log.nml |
the record of all the namelists actually USED - contains the default values |

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- none

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Routine | Message | Comment |
---|---|---|

nc_write_model_atts nc_write_model_vars |
Various netCDF-f90 interface error messages | From one of the netCDF calls in the named routine |

none at this time

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none at this time

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N/A

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DART software - Copyright UCAR. This open source software is provided by UCAR, "as is", without charge, subject to all terms of use at http://www.image.ucar.edu/DAReS/DART/DART_download

Contact: | DART core group |

Revision: | $Revision: 11626 $ |

Source: | $URL: https://svn-dares-dart.cgd.ucar.edu/DART/releases/Manhattan/models/forced_lorenz_96/model_mod.html $ |

Change Date: | $Date: 2017-05-11 11:27:50 -0600 (Thu, 11 May 2017) $ |

Change history: | try "svn log" or "svn diff" |