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Is your feature request related to a problem? Please describe.
In #675, we switched canopy temperature to be stepped implicitly. There is some behavior that suggests the jacobian approximation used could be improved - specifically these two points described in that PR:
There are two things I dont understand about this change:
there seem to be some times during the simultation where the error is always large, and a smaller dt doesnt help. For example, the 99th percentile error curve dips below the mean error for small dt, which indicates there are outliers that are very large in the top 1% error
update 9/18: it's possible this may happen during times in the simulation where temperature is changing a lot, e.g. shortly after a driver update, as opposed to when the temperature is in equilibrium. See plots in comments for more information
the derivative of SHF with respect to temperature is correct to a few percent, but the derivative of LHF with respect to temeperature is ~30% wrong. This is partly due to d_qsat/d_T errors (but Ive double checked that I entered the formula correct), but seems like it is also due to d_LHF/d_qsat. I think I have followed CLM exactly. Not sure why the error is large.
We should look into this more and see if we can use a better jacobian approximation that alleviates these issues.
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe.
In #675, we switched canopy temperature to be stepped implicitly. There is some behavior that suggests the jacobian approximation used could be improved - specifically these two points described in that PR:
We should look into this more and see if we can use a better jacobian approximation that alleviates these issues.
The text was updated successfully, but these errors were encountered: