Atmospheric forcing data that CLM receives at the grid level is downscaled to the column level. This is done in a multi-step process, first assigning the the grid scale value to the column, then applying corrections. The initial implementation of water isotopes in clm5 is only doing the first step. Science review is needed to determine if any additional downscaling is needed.
Example problem: The qs_ratio for forc_wtr_q (specific humidity) requires filtering over the 'downscale_filter', but using this filter results in uninitialized values that cause floating point exceptions elsewhere in the wiso code.
Summary of Issue:
Atmospheric forcing data that CLM receives at the grid level is downscaled to the column level. This is done in a multi-step process, first assigning the the grid scale value to the column, then applying corrections. The initial implementation of water isotopes in clm5 is only doing the first step. Science review is needed to determine if any additional downscaling is needed.
Example problem: The qs_ratio for forc_wtr_q (specific humidity) requires filtering over the 'downscale_filter', but using this filter results in uninitialized values that cause floating point exceptions elsewhere in the wiso code.