Consistent High-Quality Global SO2 and HCHO Datasets from EOS Aura/OMI and Suomi NPP/OMPS

Abstract:

We report on recent effort and progress at NASA Goddard Space Flight Center in developing consistent SO₂ and HCHO retrieval products from Aura/Ozone Monitoring Instrument (OMI) and Suomi National Polar-orbiting Partnership (S-NPP)/Ozone Mapping and Profiler Suite (OMPS) nadir mapper. Given the substantial differences between OMI and OMPS in several key aspects, such as spatial and spectral resolution and signal-to-noise ratio, a major challenge in ensuring data continuity between the two instruments is to properly account for different instrument characteristics as well as instruments’ degradation over time. To this end, we have developed an innovative approach based on principal component analysis (PCA) of measured Earthshine radiances. We utilize a PCA technique to extract a series of spectral features (principal components or PCs) explaining the variance of measured reflectance spectra, associated with both physical processes (e.g., ozone absorption, rotational Raman scattering) and measurement details (e.g., wavelength shift). By fitting these PCs along with pre-computed Jacobians for our target species (SO₂ or HCHO) to the measured radiance spectra, we can estimate the atmospheric loading of SO₂ or HCHO while minimizing the impacts of interfering processes and measurement imperfection on retrievals. Since no explicit instrument-specific radiance data correction scheme is required, the PCA method is easily implemented with both OMI and OMPS and maximizes data continuity. The PCA algorithm currently runs operationally in the production of the new generation NASA standard OMI planetary boundary layer (PBL) SO₂ data that have been shown to improve the detection limit of anthropogenic SO₂ emission sources by a factor of two, as compared with the previous generation product. In this presentation, we will demonstrate that the PCA algorithm can produce SO₂ and HCHO retrievals from OMPS that have comparable data quality with our OMI retrievals. We will also demonstrate the advantage of the PCA approach in mitigating the adverse effects of instrument degradation, and discuss its other features that make it a promising technique for extending the global SO₂ and HCHO datasets from EOS/Aura to S-NPP and follow-up JPSS satellites.