fastscape-lem / orographic-precipitation Goto Github PK

Hello @benbovy. I made a modification to the orographic_precipitation FastScape extension such that flowacc is properly scaled. For this I introduced a rainfall_frequency input parameter that is the number of storm of 1 hour duration per day. Note that the flow accumulation routine multiplies the runoff (in mm/hr) by the cell area (in m^2) such that the resulting flowacc is in mm m^2/hr (and not in mm^3/hr as specified in the current version). Therefore in order to get the flowacc in m^3/yr as expected in the SPL, one needs to scale it by:
self.flowacc *= 8.76*self.rainfall_frequency
I have also modified the test by adding a parameter rainfall_frequency in the file fixture_orographic_precipitation.py that contains the input parameters.
Unfortunately I forgot to create a new branch and I think I have overwritten the master branch on the GitHub repo. Sorry...
Jean.

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TODO:

• simplify the structure (no need of fixtures if it's just for the input parameters of a single test).
• test the actual logic implemented in compute_orographic_precip. Is there any ideal topography where we can compare the result against an analytical solution (e.g., with a gaussian pulse like shown in README)? Probably worth checking the paper.
• add tests for the two process classes in fastscape_ext. Testing OrographicPrecipitation could be very similar than the test for compute_orographic_precip. No need to test the whole logic of OrographicDrainageDischarge (its base class will be tested upstream in fastscape), just ensure that values are converted as expected.

We've discussed with @hannahsophiadavies the possibility to use a field of spatially variable precipitation rate as input. Technically, I think it should just work using the compute_orographic_precip function. However, this is currently not supported in the fastscape extension as OrographicPrecipitation.precip_base only accepts a scalar value:

All it needs is the precip_base variable to accept both a scalar and a 2D field using dims=[(), ('y', 'x')].

Other variables might be concerned too:

• rainfall_frequency could also accept a 2D field? (note: it should be moved to the OrographicDrainageDischarge process - #4 (comment))
• What about wind_speed and wind_dir? It looks like it would work with 2d arrays instead of scalars just like for precip_base. I've no idea whether or not this makes any sense regarding the theory (model assumptions), though.

Someone interested in putting together a pull-request?

cc @EstebanAce