At JPL we are currently developing an accurate and flexible integrated retrieval code by combining two existing projects: Reusable Framework for Atmospheric Composition (ReFRACtor), an extensible multi-instrument atmospheric composition retrieval framework that supports and facilitates data fusion of radiance measurements from different instrument in the UV, Visible, and near- to thermal IR spectrum; and Multi-Spectral, Multi-Species, Multi-Sensors (MUSES), an atmospheric composition retrieval code based on optimal estimation, which has been applied successfully to joint AIRS/OMI observations. The ReFRACtor/MUSES code is designed to retrieve trace gas vertical profile concentrations and total column amounts in a consistent manner across spectral regions, by combining fast and accurate radiative transfer code with a non-linear optimal estimation solver. Inclusion of instrument-specific information (e.g., instrument transfer functions) for a variety of sensors allows the application of the same code base to different sensors for a consistent retrieval methodology across platforms, which facilitates the comparison of retrievals of the same species across platforms. The goal is to extend the currently single-instrument retrieval capabilities to joint multi-spectral retrievals of the kind AIRS/OMI and CrIS/OMPS.
We present latest results on the concentration and vertical distribution of O3, NO2, and CO, derived from the application of ReFRACtor/MUSES to AIRS, OMI, CrIS, OMPS, and TROPOMI observations during 2019 FIREX-AQ. We describe the building blocks of the retrieval code, including radiative transfer approach, a priori assumptions on the atmospheric state, and the non-linear solver, and we outline the roadmap of the future development of an Open Source code base. Results from ReFRACtor/MUSES will be compared with standard data products from the individual satellite sensors.