Speaker
Description
The Electrojet Zeeman Imaging Explorer (EZIE) uses polarized microwave measurements of molecular oxygen emission to infer magnetic perturbations associated with ionospheric currents. This contribution describes PRIZM—Polarized Radiative Transfer and Inversion for Zeeman Magnetic Imaging—the scientific-processing software developed to support and validate the connected EZIE product chain from L0A through L3. PRIZM carries observation geometry, ancillary geophysical models, processing configuration, and provenance across product levels while producing structured NetCDF outputs at each stage.
Within this chain, L0A establishes the observation, spacecraft, and geometric context used by downstream processing. L0B represents the radiance and spectral-product layer, used for calibrating downlinked instrument data. L1 provides the calibrated science measurements used for inversion. L2 contains retrieved magnetic-field perturbations, associated uncertainties, and fit diagnostics, while L3 derives electrojet and current-related products from the retrieved magnetic information.
The software integrates polarized radiative-transfer calculations, magnetic-field inversion, spacecraft geometry, ancillary models, product generation, and metadata handling within an installable Python package. A central design objective is to make both individual components and interfaces between product levels testable. Validation includes unit tests, synthetic cases with known injected perturbations, canonical comparisons with an independent radiative-transfer implementation, and field-level comparisons between generated and reference NetCDF products. These product-level comparisons reveal discrepancies in retrieved quantities, uncertainty estimates, metadata, coordinate conventions, and data organization that may not be identified through isolated algorithm tests.
PRIZM also represents a transition from heritage observing-system simulation and research workflows toward reusable mission software. Key lessons include the need to validate interfaces as well as algorithms, preserve configuration and provenance across the full product chain, compare complete products rather than only numerical kernels, and retain executable reference cases during modernization. These practices provide a foundation for algorithm refinement, reprocessing, and scientific review, and may benefit other mission teams developing maintainable and traceable science-data systems.