Deriving a variable#

The variable derivation preprocessor module allows to derive variables which are not in the CMIP standard data request using standard variables as input. This is a special type of preprocessor function. All derivation scripts are located in esmvalcore/preprocessor/_derive/. A typical example looks like this:

"""Derivation of variable `dummy`."""
from ._baseclass import DerivedVariableBase

class DerivedVariable(DerivedVariableBase):
    """Derivation of variable `dummy`."""

    def required(project):
        """Declare the variables needed for derivation."""
        mip = 'fx'
        if project == 'CMIP6':
            mip = 'Ofx'
        required = [
            {'short_name': 'var_a'},
            {'short_name': 'var_b', 'mip': mip, 'optional': True},
        return required

    def calculate(cubes):
        """Compute `dummy`."""

        # `cubes` is a CubeList containing all required variables.
        cube = do_something_with(cubes)

        # Return single cube at the end
        return cube

The static function required(project) returns a list of dict containing all required variables for deriving the derived variable. Its only argument is the project of the specific dataset. In this particular example script, the derived variable dummy is derived from var_a and var_b. It is possible to specify arbitrary attributes for each required variable, e.g. var_b uses the mip fx (or Ofx in the case of CMIP6) instead of the original one of dummy. Note that you can also declare a required variable as optional=True, which allows the skipping of this particular variable during data extraction. For example, this is useful for fx variables which are often not available for observational datasets. Otherwise, the tool will fail if not all required variables are available for all datasets.

The actual derivation takes place in the static function calculate(cubes) which returns a single cube containing the derived variable. Its only argument cubes is a CubeList containing all required variables.