Model_mods which use their own structure to keep track of state variables #389
Labels
IO
IO refactoring notes and issues
missing_state
missing_r8 in the state
mpas
Model for Prediction Across Scales (MPAS)
POP
Parallel Ocean Program
Refactor
Working but needs cleanup
state_structure
notes on refactoring of state_structure_mod
wrf
Weather Research & Forecasting Model
progvar type:
* mpas_ocn (does not compile)
* mpas_atm
* NCOMMAS (does not compile)
* NAAPS (does not compile)
wrf has
type wrf_static_data_for_dart
wrf_hydro is making assumptions about the indexing.
clm has metadata arrays that are the same size as the state:
607 allocate(lonixy(model_size), latjxy(model_size), levels(model_size), landarea(model_size))
this you don't want to access with dart_index (i.e. assume the state structure), but instead
f(x,y,z,variable)
.Same for the small models have state-length metadata storage. Any model that adds a domain like this
dom_id = add_domain(model_size)
. 9-var hasunpack9var
.hot take: I don't think model_mods should have access to dart_index at all.
Some models have their own
get_varid_from_kind
POP - using offset
CICE
bgrid_solo
I think you can flush out if a non-toy model_mod is assuming the state order by reversing the order of the variables in the state_structure_mod.
i = num_vars, 1, -1
, run filter/model_mod_check/whatever and seeing if your results change.Who cares?
Possible reasons to care:
- same across the ensemble, e.g. POP
- different across the ensemble, e.g. CLM
I don't think ensemble manager can stop checking for missing_r8 because a missing_r8 result for a forward operator is valid.
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