19.2 Coupling to datasets

In Section 19.1, the general case of two way coupling to an atmospheric GCM was considered. It is also useful to drive mom with atmospheric datasets representing simpler idealized atmospheres. One problem with doing this is that datasets act as infinite reservoirs of heat capable of masking shortcomings in parameterizations which only become apparent when two way coupling is allowed. Nevertheless, driving ocean models with derived from datasets is useful.

These datasets can be thought of as simple atmospheres prepared a priori such that data is defined at grid locations expected by mom for surface boundary conditions. All spatial interpolations are done beforehand, as described in Section 3.2. In this case, subroutines gasbc and goabc are bypassed because spatial interpolation to the mom grid is not needed. Also, the length of a time segment reduces to the length of one ocean time step. In general, the datasets contain either time mean conditions or time varying conditions and there are three options which configure these types of for mom:

•  simple_sbc allows for the simplest of atmospheric datasets. All are a function only of latitude. No time dependence here although it could easily be incorporated. The test case prototype is described in Sections 3.2 and 3.3 as CASE=0. In this case, there is no dataset on disk and is not needed since all are generated internally. This is an appropriate option for building forcing functions for idealized .

•  time_mean_sbc_data uses an atmosphere dataset defined in SBC/TIME_MEAN. The test case prototype is described in Sections 3.2 and 3.3 as CASE=1. The dataset resides on disk and each surface boundary condition is a function of latitude and longitude. The dataset should be prepared for the grid in MOM using scripts in PREP_DATA as described in Section 3.2. The surface boundary condition data is read into the surface boundary condition array  once in atmos for all latitude rows where m gives the ordering of the boundary conditions as described in Section 19.3. On every time step, data from is loaded into the surface tracer flux array stf_i,j,n and the surface momentum flux array smf_i,j,n. This is done in subroutine setvbc for rows j=2,jmw-1 in the memory window^19.22.

•  time_varying_sbc_data uses an atmosphere dataset defined in SBC/MONTHLY. The test case prototype is described in Sections 3.2 and 3.3 as CASE=2. The dataset resides on disk as a series of records. Each record is a climatological monthly mean surface boundary condition as a function of latitude and longitude. This dataset should be prepared for the grid in mom using scripts in PREP_DATA as described in Section 3.2. The complication is one of interpolating the monthly values to the model time in mom for each time step. Basically, the model time must be mapped into the dataset to find which two months (data records) straddle the current model time^19.23. For the purpose of interpolation, months are defined at the center of their averaging periods. Both months are read into additional boundary condition arrays in atmos and used to interpolate to array for the current model time. When the model time crosses the midpoint of a month, the next month is read into a boundary condition array^19.24 and the process continues indefinitely assuming the dataset is specified as periodic. If it is not, mom will stop when the ocean integration time reaches the end of the dataset. Although data is read into the additional boundary condition arrays only when ocean model time crosses the mid month boundary, data is interpolated into on every timestep. There are four allowable methods for interpolating these datasets in time:

  Method=0 is for no interpolation; the average value is used for all times within the averaging period. This is the simplest interpolation. It preserves the integral over averaging periods, but is discontinuous at period boundaries.

  Method=1 is for linear interpolation between the middles of two adjacent averaging periods. It is continuous but does not preserve integrals for unequal averaging periods.

  Method=2 is for equal linear interpolation. It assumes that the value on the boundary between two adjacent averaging periods is the unweighted average of the two average values. Linearly interpolates between the midperiod and period boundary. It is continuous but does not preserve integral for unequal periods.

  Method=3 is for equal area (midperiod to midperiod) interpolation. It chooses a value for the boundary between two adjacent periods such that linear interpolation between the two midperiods and this value will preserve the integral midperiod to midperiod.

  To explore how time interpolation works in a very simple environment, one can execute script run_timeinterp which exercises timeinterp^19.25 as a stand alone program.

  As mentioned above, two additional boundary condition arrays are needed for each surface boundary condition. The memory increase may get excessive with large resolution models. In that case, option minimize_sbc_memory reduces these arrays from being dimensioned as (imt,jmt) to being dimensioned as (imt,jmw). The trade off is increased disk access which may be prohibitive if using rotating disk. If efficiency is an issue, asynchronous reads with look ahead capability would be worth trying. This look ahead feature has not been implemented.