This adds the positive specific humidity limiter and a precipitation update to the reservoir stepper. It also adds the associated diagnostics for column net heating/moistening from the reservoir step.
The existing functions for these computations already existed for the ML stepper but took in tendency inputs only. To minimize changes to the existing code I added a conversion of the reservoir's state prediction to the equivalent tendencies, which are now returned by the reservoir stepper instead of an empty dict. The tendencies are used in the reservoir step of the loop file to compute diagnostics.
Significant internal changes:
added hydrostatic and mse_conserving_limiter optional fields in the reservoir config. These are used to compute diagnostics in the same way as in the ML stepper, where they are also config fields.
added model_timestep attribute to the reservoir stepper so it can compute the equivalent tendencies from the predicted and input state.
This adds the positive specific humidity limiter and a precipitation update to the reservoir stepper. It also adds the associated diagnostics for column net heating/moistening from the reservoir step.
The existing functions for these computations already existed for the ML stepper but took in tendency inputs only. To minimize changes to the existing code I added a conversion of the reservoir's state prediction to the equivalent tendencies, which are now returned by the reservoir stepper instead of an empty dict. The tendencies are used in the reservoir step of the loop file to compute diagnostics.
Significant internal changes:
added
hydrostaticandmse_conserving_limiteroptional fields in the reservoir config. These are used to compute diagnostics in the same way as in the ML stepper, where they are also config fields.added
model_timestepattribute to the reservoir stepper so it can compute the equivalent tendencies from the predicted and input state.[x ] Tests added
Resolves # [JIRA-TAG]
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