Tuesday, 9 January 2018: 11:00 AM
Room 18CD (ACC) (Austin, Texas)
Emissions and concentrations of nitrogen oxides (NOx=NO+NO2) are regulated in several countries, as nitrogen dioxide (NO2) is a toxic pollutant and NOx 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 NOx 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 (1o latitude x 1.25o 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.
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