Need some kind of way to allow for multiple observation types for the same field

[mkavulich]

Description

Currently the workflow is defined in a way that a given field (e.g. accumulated precipitation, reflectivity, ) can only be verified using a single observation type (e.g. CCPA, MRMS respectively)

However, there is a need to make this more flexible. For example, there are multiple different accumulated precipitation datasets that we might want to verify against in addition to the current CCPA (IMERG, MRMS, etc.). We actually already have an example of this: NDAS vs GDAS for conventional observations, but it is handled in a somewhat hacky way, where "NDAS" data is overwritten with GDAS variables in the test file.

Solution

We need a more elegant solution that allows the user to specify from the config file not only the field they would like to verify, but also the observation type to use for verifying that field.

Requirements

Capability to define both the field type and the observational dataset for a given verification experiment

Dependencies

• Python-ize the remaining bash run scripts, parallelize more tasks, fix some bugs #33 Need all run scripts to be in python to allow for more complicated config file structures

Alternative Solutions

None, this is a requirement for work such as IMERG precipitation verification