Open surbhigoel77 opened 6 months ago
The co2
to ca
conversion is very straightforward, then kmm
, gammastar
and ns_star
are complex functions of tc
and patm
only. vpd
is passed straight through to the OptimalChiABC
subclasses. So using np.meshgrid
to get some inputs for combinations of tc
and patm
should do it. I think it's very likely that the random values of the forcing variables within bounds selected in the benchmarking data would fill that grid space pretty well, but this would be more explicit.
Does that sound right?
Fixed in #153
The PModel environment module takes in environmental forcing variables (
tc
,patm
,co2
,vpd
) and produce photosynthesis variables (ca
,kmm
,gammastar
,ns_star
). There are hard bounds on the forcing variables values that should ideally not generate anyphotosynthsis variables
that are out of bound within their own ranges.We need to check if there are any cases where the valid forcing variables produce any out-of-bound outputs.