Sergey Marchenko

Revising the slant column density retrieval of nitrogen dioxide observed by the Ozone Monitoring Instrument

Abstract Nitrogen dioxide retrievals from the Aura/Ozone Monitoring Instrument (OMI) have been used extensively over the past decade, particularly in the study of tropospheric air quality. Recent comparisons of OMI NO2 with independent data sets and models suggested that the OMI values of slant column density (SCD) and stratospheric vertical column density (VCD) in both the NASA OMNO2 and Royal Netherlands Meteorological Institute DOMINO products are too large, by around 10–40%. We describe a substantially revised spectral fitting algorithm, optimized for the OMI visible light spectrometer channel. The most important changes comprise a flexible adjustment of the instrumental wavelength shifts combined with iterative removal of the ring spectral features; the multistep removal of instrumental noise; iterative, sequential estimates of SCDs of the trace gases in the 402–465 nm range. These changes reduce OMI SCD(NO2) by 10–35%, bringing them much closer to SCDs retrieved from independent measurements and models. The revised SCDs, submitted to the stratosphere‐troposphere separation algorithm, give tropospheric VCDs ∼10–15% smaller in polluted regions, and up to ∼30% smaller in unpolluted areas. Although the revised algorithm has been optimized specifically for the OMI NO2 retrieval, our approach could be more broadly applicable.

A cloud algorithm based on the O 2 -O 2 477 nm absorption band featuring an advanced spectral fitting method and the use of surface geometry-dependent Lambertian-equivalent reflectivity

We discuss a new cloud algorithm that retrieves an effective cloud pressure, also known as cloud optical centroid pressure (OCP), from oxygen dimer (O2-O2) absorption at 477 nm after determining an effective cloud fraction (ECF) at 466 nm, a wavelength not significantly affected by trace-gas absorption and rotational Raman scattering. The retrieved cloud products are intended for use as inputs to the operational nitrogen dioxide (NO2) retrieval algorithm for the Ozone Monitoring Instrument (OMI) flying on the Aura satellite. The cloud algorithm uses temperature-dependent O2-O2 cross sections and incorporates flexible spectral fitting techniques that account for specifics of the surface reflectivity. The fitting procedure derives O2-O2 slant column densities (SCDs) from radiances after O3, NO2, and H2O absorption features have been removed based on estimates of the amounts of these species from independent OMI algorithms. The cloud algorithm is based on the frequently used mixed Lambertian-equivalent reflectivity (MLER) concept. A geometry-dependent Lambertian-equivalent reflectivity (GLER), which is a proxy of surface bidirectional reflectance, is used for the ground reflectivity in our implementation of the MLER approach. The OCP is derived from a match of the measured O2-O2 SCD to that calculated with the MLER method. Temperature profiles needed for computation of vertical column densities are taken from the Global Modeling Initiative (GMI) model. We investigate the effect of using GLER instead of climatological LER on the retrieved ECF and OCP. For evaluation purposes, the retrieved ECFs and OCPs are compared with those from the operational OMI cloud product, which is also based on the same O2-O2 absorption band. Impacts of the application of the newly developed cloud algorithm to the OMI NO2 retrieval are discussed.

Applying the OMI NO 2 Retrieval Algorithm to Estimate the Production Efficiency of Lightning NO x

The Ozone Monitoring Instrument (OMI) on board the NASA Aura satellite was launched into sun-synchronous low-earth orbit in 2004. Its hyperspectral measurements have been an invaluable tool in determining trace-gas concentrations in the troposphere and stratosphere. Nitrogen dioxide (NO2) has a particularly prominent absorption signature in the violet and near-UV regions of the OMI spectrum. This signature can be exploited in retrievals of column amounts of NO2 attributable to both natural and anthropogenic sources. We outline the OMI NO2 retrieval algorithm and demonstrate its utility for inferring NOx (NO + NO2) amounts due to lightning. Lightning is the dominant source of NOx in the free troposphere, and most estimates of the concentration of lightning NOx (LNOx) require knowledge of the amount of this species produced per lightning flash. We present the largest spatial- and temporal-scale investigation of LNOx to date that combines satellite-based NOx estimates and lightning flash data. The study comprises five northern-hemisphere (NH) summers, including much of the mid-latitude regions in North America and Asia and adjacent waters. NO2 measurements are converted to LNOx and compared with flashes preceding OMI overpass by 2 hours. The flash counts are derived from ground-based World Wide Lightning Location Network (WWLLN) data that are adjusted for detection efficiency. We find reasonable correlation between the number of lightning flashes and the amount of LNOx produced and estimate mean efficiencies for the production of LNOx in various NH regions. Overall results indicate mole/flash values near the low end of those reported in previous LNOx studies, as well as a possible dependence of production efficiency on flash rate. These findings have potential implications in the chemistry of upper tropospheric trace gases and the global NOx budget.