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Every model that is DART compliant must provide an interface as documented
here. The file models/template/model_mod.f90
provides the fortran interfaces for a minimal implementation meeting
these requirements. When adding a new model to DART you can either
start by modifying a
model_mod.f90 file from a similar model already in
DART or start with the template file.
Either way, the supplied interface must match these descriptions exactly;
no details of the underlying model can impact the interface.
Several of the routines listed below are allowed
to be a NULL INTERFACE. This means the subroutine or function name
must exist in this file, but it is ok if it contains no executable code.
A few of the routines listed below are allowed
to be a PASS-THROUGH INTERFACE. This means the subroutine or function
name can be listed on the 'use' line from the location_mod,
and no subroutine or function with that name is supplied in this file.
Alternatively, this file can provide an implementation which calls
the underlying routines from the location_mod and
then alters or augments the results based on model-specific requirements.
The system comes with several types of location modules for computing
distances appropriately. Two of the
ones most commonly used are for data in a 1D system and for data in
a 3D spherical coordinate system. Make the selection by listing
the appropriate choice from location/*/location_mod.f90
in the corresponding path_names_* file at compilation time.
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.
&model_nml /
Models are free to include a model namelist which can be read when static_init_model is called. A good example can be found in the lorenz_96 model_mod.f90.
types_mod time_manager_mod location_mod (multiple choices here) utilities_mod POSSIBLY MANY OTHERS DEPENDING ON MODEL DETAILS
A namelist interface &model_nml may be defined by the module, in which case it will be read from file input.nml. The details of the namelist are always model-specific (there are no generic namelist values).
A note about documentation style. Optional arguments are enclosed in brackets [like this].
integer(i8) :: 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) :: x type(time_type), intent(in) :: time
Does a single timestep advance of the model. The input value of the vector x is the starting condition and x must be updated to reflect the changed state after a timestep. The time argument is intent in and is used for models that need to know the date/time to compute a timestep, for instance for radiation computations. This interface is only called if the namelist parameter async is set to 0 in perfect_model_obs or filter or if the program integrate_model is to be used to advance the model state as a separate executable. If one of these options is not going to be used (the model will only be advanced as a separate model-specific executable), this can be a NULL INTERFACE. (The subroutine name must still exist, but it can contain no code and it will not be called.)
x | State vector of length model_size. |
time | Current time of the model state. |
integer, intent(in) :: index_in type(location_type), intent(out) :: location integer, optional, intent(out) :: var_type
Given an integer index into the state vector, returns the associated location. An optional argument returns the generic quantity of this item, e.g. QTY_TEMPERATURE, QTY_DENSITY, QTY_SALINITY, QTY_U_WIND_COMPONENT. This interface is required to be functional for all applications.
index_in | Index of state vector element about which information is requested. |
location | The location of state variable element. |
var_type | The generic quantity of the state variable element. |
type(ensemble_type), intent(in) :: state_handle integer, intent(in) :: ens_size type(location_type), intent(in) :: location integer, intent(in) :: obs_quantity real(r8), intent(out) :: expected_obs(ens_size) integer, intent(out) :: istatus(ens_size)
Given a handle containing information for a state vector, an ensemble size, a location, and a model state variable quantity interpolates the state variable field to that location and returns an ensemble-sized array of values in expected_obs(:). The istatus(:) array should be 0 for successful ensemble members and a positive value for failures. The obs_quantity variable is one of the quantity (QTY) parameters defined in the obs_kind_mod.f90 file and defines the quantity to interpolate. In low-order models that have no notion of kinds of variables this argument may be ignored. For applications in which only perfect model experiments with identity observations (i.e. only the value of a particular state variable is observed), this can be a NULL INTERFACE. Otherwise it is required (which is the most common case).
state_handle | The handle to the state structure containing information about the state vector about which information is requested. |
ens_size | The ensemble size. |
location | Location to which to interpolate. |
obs_quantity | Quantity of state field to be interpolated. |
expected_obs | The interpolated values from the model. |
istatus | Integer values return 0 for success. Other positive values can be defined for various failures. |
type(time_type) :: shortest_time_between_assimilations
Returns the smallest increment in time that the model is capable of advancing the state in a given implementation. The actual value may be set by the model_mod namelist (depends on the model). This interface is required for all applications.
var | Smallest advance time of the model. |
Called to do one time initialization of the model. As examples, might define information about the model size or model timestep, read in grid information, read a namelist, set options, etc. In models that require pre-computed static data, for instance spherical harmonic weights, these would also be computed here. Can be a NULL INTERFACE for the simplest models.
type(time_type), intent(out) :: time
Companion interface to init_conditions. Returns a time that is somehow appropriate for starting up a long integration of the model. At present, this is only used if the perfect_model_obs namelist parameter read_input_state_from_file = .false. If this option should not be used in perfect_model_obs, calling this routine should issue a fatal error.
time | Initial model time. |
real(r8), dimension(:), intent(out) :: x
Returns a model state vector, x, that is some sort of appropriate initial condition for starting up a long integration of the model. At present, this is only used if the perfect_model_obs namelist parameter read_input_state_from_file = .false. If this option should not be used in perfect_model_obs, calling this routine should issue a fatal error.
x | Initial conditions for state vector. |
integer, intent(in) :: ncFileID integer, intent(in) :: domain_id
This routine writes the model-specific attributes to netCDF files
that DART creates. This includes coordinate variables and any
metadata, but NOT the actual model state vector.
models/template/model_mod.f90 contains code that
can be used for any model as-is.
The typical sequence for adding new dimensions, variables, attributes:
NF90_OPEN ! open existing netCDF dataset NF90_redef ! put into define mode NF90_def_dim ! define additional dimensions (if any) NF90_def_var ! define variables: from name, kind, and dims NF90_put_att ! assign attribute values NF90_ENDDEF ! end definitions: leave define mode NF90_put_var ! provide values for variable NF90_CLOSE ! close: save updated netCDF dataset
ncFileID | Integer file descriptor to previously-opened netCDF file. |
domain_id | integer describing the domain (which can be a nesting level, a component model ...) Models with nested grids are decomposed into 'domains' in DART. The concept is extended to refer to 'coupled' models where one model component may be the atmosphere, another component may be the ocean, or land, or ionosphere ... these would be referenced as different domains. |
integer, intent(in) :: ncFileID integer, intent(in) :: domain_id type(ensemble_type), intent(in) :: state_ens_handle integer, optional, intent(in) :: memberindex integer, optional, intent(in) :: timeindex
This routine may be used to write the model-specific state vector (data) to a
netCDF file. Only used if
model_mod_writes_state_variables = .true.
Typical sequence for adding new dimensions,variables,attributes:
NF90_OPEN ! open existing netCDF dataset NF90_redef ! put into define mode NF90_def_dim ! define additional dimensions (if any) NF90_def_var ! define variables: from name, kind, and dims NF90_put_att ! assign attribute values NF90_ENDDEF ! end definitions: leave define mode NF90_put_var ! provide values for variable NF90_CLOSE ! close: save updated netCDF dataset
ncFileID | file descriptor to previously-opened netCDF file. |
domain_id | integer describing the domain (which can be a nesting level, a component model ...) |
state_ens_handle | The handle to the state structure containing information about the state vector about which information is requested. |
memberindex | Integer index of ensemble member to be written. |
timeindex | The timestep counter for the given state. |
type(ensemble_type), intent(inout) :: state_ens_handle integer, intent(in) :: ens_size real(r8), intent(in) :: pert_amp logical, intent(out) :: interf_provided
Given an ensemble handle, the ensemble size, and a perturbation amplitude; perturb the ensemble. Used to generate initial conditions for spinning up ensembles. If the model_mod does not want to do this, instead allowing the default algorithms in filter to take effect, interf_provided =&nbps;.false. and the routine can be trivial. Otherwise, interf_provided must be returned as .true.
state_ens_handle | The handle containing an ensemble of state vectors to be perturbed. |
ens_size | The number of ensemble members to perturb. |
pert_amp | the amplitude of the perturbations. The interpretation is based on the model-specific implementation. |
interf_provided | Returns false if model_mod cannot do this, else true. |
type(get_close_type), intent(in) :: gc type(location_type), intent(in) :: base_loc integer, intent(in) :: base_type type(location_type), intent(in) :: locs(:) integer, intent(in) :: loc_qtys(:) integer, intent(in) :: loc_types(:) integer, intent(out) :: num_close integer, intent(out) :: close_ind(:) real(r8), optional, intent(out) :: dist(:) type(ensemble_type), optional, intent(in) :: state_handle
Given a location and quantity, compute the distances to all other locations
in the obs list. The return values are the number
of items which are within maxdist of the base, the index numbers in the
original obs list, and optionally the distances. The gc
contains precomputed information to speed the computations.
In general this is a PASS-THROUGH ROUTINE. It is listed on
the use line for the locations_mod, and in the public list
for this module, but has no subroutine declaration and
no other code in this module:
use location_mod, only: get_close_obs public :: get_close_obs
However, if the model needs to alter the values or wants to supply an alternative implementation it can intercept the call like so:
use location_mod, only: & lm_get_close_obs => get_close_obs public :: get_close_obs
In this case a local get_close_obs() routine must be supplied. To call the original code in the location module use:
call lm_get_close_obs(gc, base_loc, ...)
This subroutine will be called after get_close_maxdist_init
and get_close_obs_init.
In most cases the PASS-THROUGH ROUTINE will be used, but some models need
to alter the actual distances depending on the observation or state vector kind,
or based on the observation or state vector location.
It is reasonable in this case to leave
get_close_maxdist_init()
and get_close_obs_init() as pass-through routines and
intercept only get_close_obs(). The local
get_close_obs() can first call the location mod routine
and let it return a list of values, and then inspect the list and alter
or remove any entries as needed. See the CAM and WRF model_mod files
for examples of this use.
gc | The get_close_type which stores precomputed information about the locations to speed up searching |
base_loc | Reference location. The distances will be computed between this location and every other location in the obs list |
base_type | The DART quantity at the base_loc |
locs(:) | Compute the distance between the base_loc and each of the locations in this list |
loc_qtys(:) | The corresponding quantity of each item in the locs list |
loc_types(:) | The corresponding type of each item in the locs list. This is not available in the default implementation but may be used in custom implementations. |
num_close | The number of items from the locs list which are within maxdist of the base location |
close_ind(:) | The list of index numbers from the locs list which are within maxdist of the base location |
dist(:) | If present, return the distance between each entry in the close_ind list and the base location. If not present, all items in the obs list which are closer than maxdist will be added to the list but the overhead of computing the exact distances will be skipped. |
state_handle | The handle to the state structure containing information about the state vector about which information is requested. |
type(get_close_type), intent(in) :: gc type(location_type), intent(inout) :: base_loc integer, intent(in) :: base_type type(location_type), intent(inout) :: state_loc(:) integer, intent(in) :: state_qtys(:) integer(i8), intent(in) :: state_indx(:) integer, intent(out) :: num_close integer, intent(out) :: close_ind(:) real(r8), optional, intent(out) :: dist(:) type(ensemble_type), optional, intent(in) :: state_handle
Given a location and quantity, compute the distances to all other locations
in the state_loc list. The return values are the number
of items which are within maxdist of the base, the index numbers in the
original state_loc list, and optionally the distances. The gc
contains precomputed information to speed the computations.
In general this is a PASS-THROUGH ROUTINE. It is listed on
the use line for the locations_mod, and in the public list
for this module, but has no subroutine declaration and
no other code in this module:
use location_mod, only: get_close_state public :: get_close_state
However, if the model needs to alter the values or wants to supply an alternative implementation it can intercept the call like so:
use location_mod, only: & lm_get_close_state => get_close_state public :: get_close_state
In this case a local get_close_state() routine must be supplied. To call the original code in the location module use:
call loc_get_close_state(gc, base_loc, ...)
This subroutine will be called after get_close_maxdist_init
and get_close_state_init.
In most cases the PASS-THROUGH ROUTINE will be used, but some models need
to alter the actual distances depending on the observation or state vector kind,
or based on the observation or state vector location.
It is reasonable in this case to leave
get_close_maxdist_init()
and get_close_state_init() as pass-through routines and
intercept only get_close_state(). The local
get_close_state() can first call the location mod routine
and let it return a list of values, and then inspect the list and alter
or remove any entries as needed. See the CAM and WRF model_mod files
for examples of this use.
gc | The get_close_type which stores precomputed information about the locations to speed up searching |
base_loc | Reference location. The distances will be computed between this location and every other location in the list |
base_type | The DART quantity at the base_loc |
state_loc(:) | Compute the distance between the base_loc and each of the locations in this list |
state_qtys(:) | The corresponding quantity of each item in the state_loc list |
state_indx(:) | The corresponding DART index of each item in the state_loc list. This is not available in the default implementation but may be used in custom implementations. |
num_close | The number of items from the state_loc list which are within maxdist of the base location |
close_ind(:) | The list of index numbers from the state_loc list which are within maxdist of the base location |
dist(:) | If present, return the distance between each entry in the close_ind list and the base location. If not present, all items in the state_loc list which are closer than maxdist will be added to the list but the overhead of computing the exact distances will be skipped. |
state_handle | The handle to the state structure containing information about the state vector about which information is requested. |
type(ensemble_type), intent(in) :: state_handle integer, intent(in) :: num type(location_type), intent(in) :: locs(:) integer, intent(in) :: loc_qtys(:) integer, intent(in) :: loc_types(:) integer, intent(in) :: which_vert integer, intent(out) :: status(:)
Converts the observations to the desired vertical localization coordinate system. Some models (toy models with no 'real' observations) will not need this. Most (real) models have observations in one or more coordinate systems (pressure, height) and the model is generally represented in only one coordinate system. To be able to interpolate the model state to the observation location, or to compute the true distance between the state and the observation, it is necessary to convert everything to a single coodinate system.
state_handle | The handle to the state. |
num | the number of observation locations |
locs | the array of observation locations |
loc_qtys | the array of observation quantities. |
loc_types | the array of observation types. |
which_vert | the desired vertical coordinate system. There is a table in the location_mod.f90 that relates integers to vertical coordinate systems. |
status | Success or failure of the vertical conversion. If istatus = 0, the conversion was a success. Any other value is a failure. |
type(ensemble_type), intent(in) :: state_handle integer, intent(in) :: num type(location_type), intent(in) :: locs(:) integer, intent(in) :: loc_qtys(:) integer, intent(in) :: loc_types(:) integer, intent(in) :: which_vert integer, intent(out) :: status(:)
Converts the state to the desired vertical localization coordinate system. Some models (toy models with no 'real' observations) will not need this. To compute the true distance between the state and the observation, it is necessary to convert everything to a single coodinate system.
state_handle | The handle to the state. |
num | the number of state locations |
locs | the array of state locations |
loc_qtys | the array of state quantities. |
loc_types | the array of state types. |
which_vert | the desired vertical coordinate system. There is a table in the location_mod.f90 that relates integers to vertical coordinate systems. |
status | Success or failure of the vertical conversion. If istatus = 0, the conversion was a success. Any other value is a failure. |
character(len=*), intent(in) :: filename type(time_type) :: model_time
Reads the valid time of the model state in a netCDF file. There is a default routine in assimilation_code/modules/io/dart_time_io_mod.f90 that can be used as a pass-through. That routine will read the last timestep of a 'time' variable - which is the same strategy used for reading netCDF files that have multiple timesteps in them. If your model has some other representation of time (i.e. it does not use a netCDF variable named 'time') - you will have to write this routine.
ncid | handle to an open netCDF file |
dart_time | The current time of the model state. |
integer, intent(in) :: ncid type(time_type), intent(in) :: dart_time
Writes the assimilation time to a netCDF file. There is a default routine in assimilation_code/modules/io/dart_time_io_mod.f90 that can be used as a pass-through. If your model has some other representation of time (i.e. it does not use a netCDF variable named 'time') - you will have to write this routine.
ncid | handle to an open netCDF file |
dart_time | The current time of the model state. |
Does any shutdown and clean-up needed for model. Can be a NULL INTERFACE if the model has no need to clean up storage, etc.
none at this time
It is likely that a number of additional optional interfaces will be added to the model_mod structure. For instance, hints about how to divide the state vector into regions for parallel assimilation will need to be obtained from the model. It is planned that the interf_provided mechanism used in pert_model_copies will allow those who do not wish to support enhanced interfaces to add NULL interfaces by simply pasting in an interface block.
N/A
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