More Accurate OMI Tropospheric NO2 Retrievals, Aided by NASA's A-Train High-Resolution Data

Emissions and concentrations of nitrogen oxides (NO_x=NO+NO₂) are regulated in several countries, as nitrogen dioxide (NO₂) is a toxic pollutant and NO_x leads to the formation of surface-level ozone, acid rain and particular matter. Space–based global measurements of NO₂ are among the main objectives of the NASA Aura Ozone Monitoring Instrument (OMI) mission, aimed at advancing our understanding of the NO_x sources and enabling the application of OMI data to inform public policy. We describe ongoing updates to the OMI standard NO₂ products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include: (1) an improved spectral fitting algorithm for retrieving slant column densities, (2) higher-resolution (1^o latitude x 1.25^o longitude) a priori NO₂ profiles from the Global Modeling Initiative chemistry-transport model with yearly varying emissions, (3) re-processed OMI monthly solar irradiances, and (4) the new (version 2) OMI cloud data product OMCLDO2. This year we plan to introduce major changes to the tropospheric NO₂ Air-Mass Factor (AMF) calculation, which we expect to lead to more accurate tropospheric NO₂ Vertical Column Density (VCD) retrievals. We plan to replace the use of the OMI Lambertian Equivalent surface reflectivity (LER) climatology in the retrieval with a conceptually new, geometry-dependent Lambertian equivalent reflectivity (GLER). GLER is calculated using a vector radiative transfer model with high–resolution bidirectional reflectance distribution (BRDF) information from NASA’s Aqua MODIS over land and the Cox–Munk slope distribution over ocean with a contribution from the water-leaving radiance. GLER and the corresponding retrieved cloud products will then be used as input to the AMF algorithm. We find that replacing the climatological OMI-based LERs with GLERs can increase NO₂ tropospheric VCDs by up to 50% in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. These updates will facilitate development (by the OMI core team) of coupled and consistent algorithms for NO₂ and cloud retrievals, accommodating the most important improvements proposed for the regional OMI NO₂ products by users of the data.