Required model_mod routines

There are 18 Fortran subroutines necessary to implement in order to successfully integrate a model in DART. You will place these routines in your model_mod.f90 in a subdirectory with the name of your model in DART/models. There is often a sensible default implementation that can be used for each of these routines. For example, in the case of a model that starts at a time of “0”, for the required routine init_time() the following code will use this default implementation:

use default_model_mod,     only : init_time

As in all Fortran programs, a comma-separated list of routines can be listed after the colon.

The following table lists each of the 18 routines, their default modules relative to DART, and the default behavior. If the default behavior is not desired, see the section Suggestions for a “simple” model for a model that DART can advance, or Suggestions for a “complex” model for a model that is advanced externally from DART.

Routine # / name	Purpose	Default module / directory	Default behavior
init_time()	Set the initial time if not read from the restart file.	default_model_mod / models/utilities	Sets the initial time to 0 days, 0 seconds
init_conditions()	For a “cold start” fill in an empty state vector with initial conditions. Many models cannot just make up values from thin air and thus choose to fail when this is requested.	default_model_mod / models/utilities	Sets the initial state to 0. To fail use init_conditions => fail_init_conditions.
get_model_size()	Return the number of items in the state vector.	default_model_mod / models/utilities	Returns 1; i.e. there is only one item in the state.
static_init_model()	Initialize DART with information about the model that will be used by the remaining model_mod routines. The procedure for doing this will depend on how complex the model is; see below for suggestions for implementation.	default_model_mod / models/utilities	Does nothing.
get_state_meta_data()	Takes an index into the state vector and returns the location corresponding to that value and optionally the variable type. See below for suggestions on implementation.	default_model_mod / models/utilities	Sets a missing location and the default variable type.
end_model()	Deallocate any arrays allocated in static_init_model().	default_model_mod / models/utilities	Does nothing.
adv_1step()	If possible, advance the model state from one time to another. Complex models will be unable to implement this method and should fail.	default_model_mod / models/utilities	Call the error handler with the message “unable to advance model”.
shortest_time_between_assimilations()	Return a namelist or a fixed value for the minimum model advance time between assimilations. Note that complex models will handle advancing the time externally.	default_model_mod / models/utilities	Returns a time period of 1 day.
model_interpolate()	Interpolate a requested quantity to the given location to get an array of expected values for all ensemble members. NOTE: this is often the most time consuming method to implement.	default_model_mod / models/utilities	Fail and set the expected observation to “missing.”
nc_write_model_atts()	Add any additional information to the netCDF output diagnostic files. NOTE: the state will already be output by other routines, so this method should not create or write the state variables.	default_model_mod / models/utilities	Does nothing.
read_model_time()	Read the model time from a state vector netCDF file.	dart_time_io / assimilation_code/io/utilities	Attempt to read the “time” variable from a state file in an intelligent way.
write_model_time()	Write the model time to a state vector netCDF file.	dart_time_io / assimilation_code/io/utilities	Write the “time” variable from the file according to the DART calendar.
pert_model_copies()	Perturb a state vector in order to create an ensemble.	default_model_mod / models/utilities	Add Gaussian noise with a specified amplitude to all parts of the state vector.
convert_vertical_obs()	Some 3D models have multiple vertical coordinates (e.g. pressure, height, or model level); this method converts observations between different vertical coordinate systems.	location_mod/ assimilation_code/ location/XXX	Do no conversion.
convert_vertical_state()	Some 3D models have multiple vertical coordinates (e.g. pressure, height, or model level); this method converts state between different vertical coordinate systems.	location_mod/ assimilation_code/ location/XXX	Do no conversion.
get_close_obs()	Calculate which observations are “close” to a given location and, optionally, the distance. This is used for localization to reduce sampling error.	location_mod/ assimilation_code/ location/XXX	Uses the default behavior for determining distance.
get_close_state()	Calculate which state points are “close” to a given location and, optionally, the distance. This is used for localization to reduce sampling error.	location_mod/ assimilation_code/ location/XXX	Uses the default behavior for determining distance.
nc_write_model_vars()	This method is not currently called, so just use the default routine for now. This method will be used in a future implementation.	default_model_mod / models/utilities	Does nothing.