The Global Ozone Monitoring Experiment (GOME) is a new instrument aboard the European Space Agency’s (ESA) Second European Remote Sensing Satellite (ERS-2), which was launched in April 1995. The main scientific objective of the GOME mission is to determine the global distribution of ozone and several other trace gases, which play an important role in the ozone chemistry of the earth’s stratosphere and troposphere. GOME measures the sunlight scattered from the earth’s atmosphere and/or reflected by the surface in nadir viewing mode in the spectral region 240–790 nm at a moderate spectral resolution of between 0.2 and 0.4 nm. Using the maximum 960-km across-track swath width, the spatial resolution of a GOME ground pixel is 40 × 320 km2 for the majority of the orbit and global coverage is achieved in three days after 43 orbits. Operational data products of GOME as generated by DLR-DFD, the German Data Processing and Archiving Facility (D-PAF) for GOME, comprise absolute radiometrically calibrated e... Abstract The Global Ozone Monitoring Experiment (GOME) is a new instrument aboard the European Space Agency’s (ESA) Second European Remote Sensing Satellite (ERS-2), which was launched in April 1995. The main scientific objective of the GOME mission is to determine the global distribution of ozone and several other trace gases, which play an important role in the ozone chemistry of the earth’s stratosphere and troposphere. GOME measures the sunlight scattered from the earth’s atmosphere and/or reflected by the surface in nadir viewing mode in the spectral region 240–790 nm at a moderate spectral resolution of between 0.2 and 0.4 nm. Using the maximum 960-km across-track swath width, the spatial resolution of a GOME ground pixel is 40 × 320 km2 for the majority of the orbit and global coverage is achieved in three days after 43 orbits. Operational data products of GOME as generated by DLR-DFD, the German Data Processing and Archiving Facility (D-PAF) for GOME, comprise absolute radiometrically calibrated e...

We present an improved tropospheric nitrogen dioxide column retrieval algorithm (DOMINO v2.0) for OMI based on better air mass factors (AMFs) and a correction for across-track stripes resulting from calibration errors in the OMI backscattered reflectances. Since October 2004, NO₂ retrievals from the Ozone Monitoring Instrument (OMI), a UV/Vis nadir spectrometer onboard NASA's EOS-Aura satellite, have been used with success in several scientific studies focusing on air quality monitoring, detection of trends, and NO_x emission estimates. Dedicated evaluations of previous DOMINO tropospheric NO₂ retrievals indicated their good quality, but also suggested that the tropospheric columns were susceptible to high biases (by 0–40%), probably because of errors in the air mass factor calculations. Here we update the DOMINO air mass factor approach. We calculate a new look-up table (LUT) for altitude-dependent AMFs based on more realistic atmospheric profile parameters, and include more surface albedo and surface pressure reference points than before. We improve the sampling of the TM4 model, resulting in a priori NO₂ profiles that are better mixed throughout the boundary layer. We evaluate the NO₂ profiles simulated with the improved TM4 sampling as used in the AMF calculations and show that they are highly consistent with in situ NO₂ measurements from aircraft during the INTEX-A and INTEX-B campaigns in 2004 and 2006. Our air mass factor calculations are further updated by the implementation of a high-resolution terrain height and a high-resolution surface albedo climatology based on OMI measurements. Together with a correction for across-track stripes, the overall impact of the improved terrain height and albedo descriptions is modest (<5%) on average over large polluted areas, but still causes significant changes locally. The main changes in the DOMINO v2.0 algorithm follow from the new LUT and the improved TM4 sampling that results in more NO₂ simulated aloft, where sensitivity to NO₂ is higher, and amount to reductions in tropospheric NO₂ columns of up to 20% in winter, and 10% in summer over extended polluted areas. We investigate the impact of aerosols on the NO₂ retrieval, and based on a comparison of concurrent retrievals of clouds from OMI and aerosols from MODIS Aqua, we find empirical evidence that OMI cloud retrievals are sensitive to the presence of scattering aerosols. It follows that an implicit correction for the effects of aerosols occurs through the aerosol-induced cloud parameters in DOMINO, and we show that such an empirical correction amounts to a 20 %AMF reduction in summer and ±10% changes in winter over the eastern United States.

During springtime in the polar regions, unique photochemistry converts inert halide salt ions (e.g. Br⁻) into reactive halogen species (e.g. Br atoms and BrO) that deplete ozone in the boundary layer to near zero levels. Since their discovery in the late 1980s, research on ozone depletion events (ODEs) has made great advances; however many key processes remain poorly understood. In this article we review the history, chemistry, dependence on environmental conditions, and impacts of ODEs. This research has shown the central role of bromine photochemistry, but how salts are transported from the ocean and are oxidized to become reactive halogen species in the air is still not fully understood. Halogens other than bromine (chlorine and iodine) are also activated through incompletely understood mechanisms that are probably coupled to bromine chemistry. The main consequence of halogen activation is chemical destruction of ozone, which removes the primary precursor of atmospheric oxidation, and generation of reactive halogen atoms/oxides that become the primary oxidizing species. The different reactivity of halogens as compared to OH and ozone has broad impacts on atmospheric chemistry, including near complete removal and deposition of mercury, alteration of oxidation fates for organic gases, and export of bromine into the free troposphere. Recent changes in the climate of the Arctic and state of the Arctic sea ice cover are likely to have strong effects on halogen activation and ODEs; however, more research is needed to make meaningful predictions of these changes.

An eight-year long reanalysis of atmospheric composition data covering the period 2003–2010 was constructed as part of the FP7-funded Monitoring Atmospheric Composition and Climate project by assimilating satellite data into a global model and data assimilation system. This reanalysis provides fields of chemically reactive gases, namely carbon monoxide, ozone, nitrogen oxides, and formaldehyde, as well as aerosols and greenhouse gases globally at a horizontal resolution of about 80 km for both the troposphere and the stratosphere. This paper describes the assimilation system for the reactive gases and presents validation results for the reactive gas analysis fields to document the data set and to give a first indication of its quality. Tropospheric CO values from the MACC reanalysis are on average 10–20% lower than routine observations from commercial aircrafts over airports through most of the troposphere, and have larger negative biases in the boundary layer at urban sites affected by air pollution, possibly due to an underestimation of CO or precursor emissions. Stratospheric ozone fields from the MACC reanalysis agree with ozonesondes and ACE-FTS data to within ±10% in most seasons and regions. In the troposphere the reanalysis shows biases of −5% to +10% with respect to ozonesondes and aircraft data in the extratropics, but has larger negative biases in the tropics. Area-averaged total column ozone agrees with ozone fields from a multi-sensor reanalysis data set to within a few percent. NO₂ fields from the reanalysis show the right seasonality over polluted urban areas of the NH and over tropical biomass burning areas, but underestimate wintertime NO₂ maxima over anthropogenic pollution regions and overestimate NO₂ in northern and southern Africa during the tropical biomass burning seasons. Tropospheric HCHO is well simulated in the MACC reanalysis even though no satellite data are assimilated. It shows good agreement with independent SCIAMACHY retrievals over regions dominated by biogenic emissions with some anthropogenic input, such as the eastern US and China, and also over African regions influenced by biogenic sources and biomass burning.