The new lake_cell_tile_xwalkcreated in lake-temperature-model-prep contains two fields for both cell_no and tile_no -- a spatial_X and data_X field for each. The fields prefixed by spatial_ indicate the cell and tile into which each lake falls spatially. The fields prefixed by data_ indicate which cell and tile should be use for driver data for each lake. The data_cell_no will only differ from the spatial_cell_no for those lakes that fall within gcm cells that are missing data. The data_tile_no will only differ from the spatial_tile_no for those lakes that a) fall within gcm cells that are missing data, and b) are matched to a non-NaN cell in a different tile by our matching code.
In this repo, we now use the data_cell_no instead of just cell_no to determine which meteo file to use for each lake model.
And for our temporary solution of zipping the output feathers by tile number, we now use spatial_tile_no instead of just tile_no, since we are grouping the output spatially and providing a map to guide users:
The new
lake_cell_tile_xwalkcreated inlake-temperature-model-prepcontains two fields for bothcell_noandtile_no-- aspatial_Xanddata_Xfield for each. The fields prefixed byspatial_indicate the cell and tile into which each lake falls spatially. The fields prefixed bydata_indicate which cell and tile should be use for driver data for each lake. Thedata_cell_nowill only differ from thespatial_cell_nofor those lakes that fall within gcm cells that are missing data. Thedata_tile_nowill only differ from thespatial_tile_nofor those lakes that a) fall within gcm cells that are missing data, and b) are matched to a non-NaN cell in a different tile by our matching code.In this repo, we now use the
data_cell_noinstead of justcell_noto determine which meteo file to use for each lake model.And for our temporary solution of zipping the output feathers by tile number, we now use
spatial_tile_noinstead of justtile_no, since we are grouping the output spatially and providing a map to guide users: