Incorporate proflr DA into JEDI for RRFS

[delippi]

Description

The UFO in JEDI is the component that not only computes model-simulated observations, but also houses filters and methods for observation QC, ob errors, and bias correction. The GSI observer is the equivalent. Many forward operators for various observations have been developed for the UFO. These operators can be utilized in RDAS. However these operators still must be tested for RDAS. The steps for transition by observation platform are as follows:

1. Establish IODA processing
2. Establish operator in UFO
3. Establish YAML input file
4. Validate with test assimilation experiments
5. Create ctest, if necessary
6. proflr data is bufr obtype=227

Requirements

To create yaml configurations for assimilating profiler data.

Acceptance Criteria (Definition of Done)

• Phase 1 validation (hofx validation using GSI-IODA and GSI-geovals as necessary; GSI vs FV3-JEDI)

• Phase 2 validation (QC validation; no reliance on GSI except to be used as the baseline; GSI vs FV3-JEDI)

• Phase 3 validation (FV3-JEDI and GSI vs MPAS-JEDI)

• Link any relevant pull requests here:

Dependencies

None

[delippi]

Phase 1 update:
These results were created using GSI for IODA, geovals, QC, and final ob error which passes the standard for phase 1 testing.

Here are the results after using only GSI-IODA and allowing JEDI to handle the rest (geovals, QC, and oberror inflation). This results also used ObsErrorFactorConventional (OEFC) which seems to play a role in the differences we are seeing here in final ob errors. I think the differences in hofx are simply due to differences in geovals calculations since in the previous plot we saw an exact one-to-one match using GSI-IODA and GSI-geovals.