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Modifications to generalize the way ensemble forecast members are num…
…bered and named. Details below. Direct modifications: * Introduce the new app configuration parameters `ENSMEM_BASENAME` and `NDIGITS_IN_ENSMEM_NAMES`. * Remove the variable `VX_NDIGITS_ENSMEM_NAMES` since the role of this variable is now filled by `NDIGITS_IN_ENSMEM_NAMES`. * Use `ENSMEM_BASENAME` and `NDIGITS_IN_ENSMEM_NAMES` in `setup.py` to generate the names of the ensemble members during the experiment generation step and saving the lists containing these names (and indices) in `var_defns.yaml` and `rocoto_defns.yaml`. * Use the new lists defined in `rocoto_defns.yaml` in the various workflow config files to set values of ensemble member names in the rocoto XML (instead of including code in the config files to re-generate the names for each metatask). * Make sure generation of ensemble member names for all vx tasks is done in `setup.py` and passed to the ex-scripts instead of in the ex-scripts themselves. Other modifications: * Remove unused environment variables (e.g. `SLASH_ENSMEM_SUBDIR_OR_NULL`) in various workflow config files. * For consistency with the way the (meta)tasks are named, rename some tags in the workflow config files (e.g change `envars_GenEnsProd_CCPA` to `envars_GenEnsProd_APCP`).
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