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jacobcook1995
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LGTM, and can confirm that that change gives me more reasonable temperatures to work with
| leaf_area_index_sum = data["leaf_area_index"].sum(dim="layers") | ||
| leaf_area_index_sum = data["leaf_area_index"][ | ||
| layer_structure.index_filled_canopy | ||
| ].sum(dim="layers") |
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Only query would be whether it's worth adding a TODO to revisit this at some point when you are further along with the vegetation heat transfer model that you mentioned? (I'm not 100% on that though)
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1169-remove-understorey-vegetation-from-lai-sum-in-abiotic-simple
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The abiotic simple model is based on observations of temperatures at 1.5 m below a canopy. At the moment the model sums the LAI over all layers, including the understorey layer which has a very high LAI. That causes the soil to be freezing. Although the understorey vegetation takes some light from hitting the soil, the LAI is currently high and the cooling unrealistic.
I propose removing the understorey vegetation from the summing step. This does not solve the issue of a canopy being lower than 1.5m, but it gives a correct representation of the initial assumptions.
Fixes #1169
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pre-commitchecks:$ pre-commit run -a$ poetry run pytest