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The rapid development of the economy and the implementation of environmental policies adapted in India has led to fast changes of regional SO2 emissions. We present a monthly SO2 emission inventory for India covering December 2018 to November 2023 based on the TROPOMI Level-2 COBRA SO2 dataset, by using an improved flux-divergence method and estimated local SO2 lifetime which includes both its chemical loss and dry deposition. We update the methodology to use the daily CAMS model output estimates of the hydroxyl-radical distribution as well as the measured dry deposition velocity to account for the variability in the tropospheric SO2 lifetime. The results show the application of the local SO2 lifetime improves the accuracy of SO2 emissions estimation when compared to calculations using a constant lifetime. Our improved flux-divergence method reduced the spreading of the point source emissions compared to the standard flux-divergence method. The averaged SO2 emissions covering the recent 5 years are about 5.2 Tg year-1, which is lower than the bottom-up emissions of 11.0 Tg year-1 from CAMS-GLOB-ANT v5.3. The total emissions from the 92 largest point source emissions are estimated to be 2.9 Tg year-1, lower than the estimation of 5.2 Tg year-1 from the global SO2 catalog MSAQSO2LV4. We argue that for other important regions that have high SO2 emissions, the variability in the SO2 lifetime becomes more important to account for estimating top-down SO2 emissions. [ABSTRACT FROM AUTHOR]

The Ozone Monitoring Instrument (OMI) was launched on 15 July 2004, with an expected mission lifetime of 5 years. After more than 17 years in orbit the instrument is still functioning satisfactorily and in principle can continue doing so until the expected decommissioning of its platform Aura in 2025. In order to continue the datasets acquired by OMI and the Microwave Limb Sounder, the mission was extended up to at least 2023. Actions have been taken to ensure the proper functioning of the OMI operations, the data processing, and the calibration monitoring system until the eventual end of the mission. For the data processing a new level-0 (L0) to level-1b (L1b) data processor was built based on the recent developments for the TROPOspheric Monitoring Instrument (TROPOMI). With corrections for the degradation of the instrument now included, it is feasible to generate a new data collection to supersede the current collection-3 data products and reprocess the data of the entire mission up to now. This paper describes the differences between the collection-3 and collection-4 data. It will be shown that the collection-4 L1b data comprise a clear improvement with respect to the previous collections. By correcting for the gentle optical and electronic aging that has occurred over the past 17 years, OMI's ability to make trend-quality ozone measurements has further improved. [ABSTRACT FROM AUTHOR]

The aim of this paper is to highlight how TROPOspheric Monitoring Instrument (TROPOMI) trace gas data can best be used and interpreted to understand event-based impacts on air quality from regional to city scales around the globe. For this study, we present the observed changes in the atmospheric column amounts of five trace gases (NO 2 , SO 2 , CO, HCHO, and CHOCHO) detected by the Sentinel-5P TROPOMI instrument and driven by reductions in anthropogenic emissions due to COVID-19 lockdown measures in 2020. We report clear COVID-19-related decreases in TROPOMI NO 2 column amounts on all continents. For megacities, reductions in column amounts of tropospheric NO 2 range between 14 % and 63 %. For China and India, supported by NO 2 observations, where the primary source of anthropogenic SO 2 is coal-fired power generation, we were able to detect sector-specific emission changes using the SO 2 data. For HCHO and CHOCHO, we consistently observe anthropogenic changes in 2-week-averaged column amounts over China and India during the early phases of the lockdown periods. That these variations over such a short timescale are detectable from space is due to the high resolution and improved sensitivity of the TROPOMI instrument. For CO, we observe a small reduction over China, which is in concert with the other trace gas reductions observed during lockdown; however, large interannual differences prevent firm conclusions from being drawn. The joint analysis of COVID-19-lockdown-driven reductions in satellite-observed trace gas column amounts using the latest operational and scientific retrieval techniques for five species concomitantly is unprecedented. However, the meteorologically and seasonally driven variability of the five trace gases does not allow for drawing fully quantitative conclusions on the reduction in anthropogenic emissions based on TROPOMI observations alone. We anticipate that in future the combined use of inverse modeling techniques with the high spatial resolution data from S5P/TROPOMI for all observed trace gases presented here will yield a significantly improved sector-specific, space-based analysis of the impact of COVID-19 lockdown measures as compared to other existing satellite observations. Such analyses will further enhance the scientific impact and societal relevance of the TROPOMI mission. [ABSTRACT FROM AUTHOR]

Measurements by the Dobson ozone spectrophotometer at the British Antarctic Survey's (BAS) Halley research station form a record of Antarctic total column ozone that dates back to 1956. Due to its location, length, and completeness, the record has been, and continues to be, uniquely important for studies of long-term changes in Antarctic ozone. However, a crack in the ice shelf on which it resides forced the station to abruptly close in February of 2017, leading to a gap of two ozone hole seasons in its historic record. We develop and test a method for filling in the record of Halley total ozone by combining and adjusting overpass data from a range of different satellite instruments. Comparisons to the Dobson suggest that our method reproduces monthly ground-based total ozone values with an average difference of 1.1 ± 6.2 DU for the satellites used to fill in the 2017–2018 gap. We show that our approach more closely reproduces the Dobson measurements than simply using the raw satellite average or data from a single satellite instrument. The method also provides a check on the consistency of the provisional data from the automated Dobson used at Halley after 2018 with earlier manual Dobson data and suggests that there were likely inconsistencies between the two. The filled Halley dataset provides further support that the Antarctic ozone hole is healing, not only during September but also in January. [ABSTRACT FROM AUTHOR]

The TROPOspheric Monitoring Instrument (TROPOMI) level-2 aerosol layer height (ALH) product has now been released to the general public. This product is retrieved using TROPOMI's measurements of the oxygen A-band, radiative transfer model (RTM) calculations augmented by neural networks and an iterative optimal estimation technique. The TROPOMI ALH product will deliver ALH estimates over cloud-free scenes over the ocean and land that contain aerosols above a certain threshold of the measured UV aerosol index (UVAI) in the ultraviolet region. This paper provides background for the ALH product and explores its quality by comparing ALH estimates to similar quantities derived from spaceborne lidars observing the same scene. The spaceborne lidar chosen for this study is the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission, which flies in formation with NASA's A-train constellation since 2006 and is a proven source of data for studying ALHs. The influence of the surface and clouds is discussed, and the aspects of the TROPOMI ALH algorithm that will require future development efforts are highlighted. A case-by-case analysis of the data from the four selected cases (mostly around the Saharan region with approximately 800 co-located TROPOMI pixels and CALIOP profiles in June and December 2018) shows that ALHs retrieved from TROPOMI using the operational Sentinel-5 Precursor Level-2 ALH algorithm is lower than CALIOP aerosol extinction heights by approximately 0.5 km. Looking at data beyond these cases, it is clear that there is a significant difference when it comes to retrievals over land, where these differences can easily go over 1 km on average. [ABSTRACT FROM AUTHOR]

Aerosol vertical distributions are important for aerosol radiative forcing assessments and atmospheric remote sensing research. From our perspective, the aerosol layer height (ALH) is one of the major concerns in quantifying aerosol absorption from the ultra-violet aerosol index (UVAI). The UVAI has a global daily record since 1978, whereas a corresponding ALH data set is still limited. In this paper, we attempted to construct such an ALH data set from aerosol extinction profiles provided by the MERRA-2 aerosol reanalysis, meanwhile we evaluated them, together with several satellite ALH products in terms of the UVAI sensitivity to ALH. In the first part of this paper, we derived ALHs from the MERRA-2 aerosol profiles by four definitions. Through the sensitivity studies, we found that the definition of top boundary aerosol layer height (Haert) is more robust to the changes in extinction profile properties than others. The spatial and temporal variation of Haert are also well associated with the major aerosol sources and the atmospheric dynamics. In the second part, we further evaluated the UVAI altitude dependence on the MERRA-2 ALH as well as several satellite ALH. Among all the satellite ALH products in this paper, the correlation between the TROPOMI oxygen (O2) A-band ALH and UVAI, and that between the GOME-2 absorbing aerosol layer height (AAH) and UVAI are in agreement with our a-priori knowledge that the altitude dependence of UVAI increases with aerosol loadings. The correlation between the MERRA-2 Haert and UVAI also matches well with what we found from observational data sets. This implies the top boundary of the aerosol layer derived from MERRA-2 can be an alternative in case there is no observational ALH data available for quantitively aerosol absorption from UVAI and other UVAI-related applications. [ABSTRACT FROM AUTHOR]

To retrieve aerosol properties from satellite measurements of the oxygen A-band in the near-infrared, a line-by-line radiative transfer model implementation requires a large number of calculations. These calculations severely restrict a retrieval algorithm's operational capability as it can take several minutes to retrieve the aerosol layer height for a single ground pixel. This paper proposes a forward modelling approach using artificial neural networks to speed up the retrieval algorithm. The forward model outputs are trained into a set of neural network models to completely replace line-by-line calculations in the operational processor. Results comparing the forward model to the neural network alternative show an encouraging outcome with good agreement between the two when they are applied to retrieval scenarios using both synthetic and real measured spectra from TROPOMI (TROPOspheric Monitoring Instrument) on board the European Space Agency (ESA) Sentinel-5 Precursor mission. With an enhancement of the computational speed by 3 orders of magnitude, TROPOMI's operational aerosol layer height processor is now able to retrieve aerosol layer heights well within operational capacity. [ABSTRACT FROM AUTHOR]

The Tropospheric Monitoring Instrument's (TROPOMI) level-2 aerosol layer height (ALH) product has now been released to the general public. This product is retrieved using TROPOMI's measurements of the oxygen A-band, radiative transfer model (RTM) calculations augmented by neural networks and an iterative optimal estimation technique. The TROPOMI ALH product will deliver aerosol layer height estimates over cloud-free scenes over the ocean and land that contain aerosols above a certain threshold of the measured UV absorbing index (UVAI) in the ultraviolet region. This paper provides background for the ALH product and explores its quality by comparing ALH estimates to similar quantities derived from spaceborne lidars observing the same scene. The spaceborne lidar chosen for this study is the Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, which flies in formation with NASA's A-train constellation since 2006 and is a proven source of data for studying aerosol layer heights. The influence of the surface and clouds are discussed and the aspects of the TROPOMI ALH algorithm that will require future development efforts are highlighted. [ABSTRACT FROM AUTHOR]

To retrieve aerosol properties from satellite measurements of the oxygen A-band in the near infrared, a line-by-line radiative transfer model implementation requires a large number of calculations. These calculations severely restrict a retrieval algorithm's operational capability as it can take several minutes to retrieve aerosol layer height for a single ground pixel. This paper proposes a forward modeling approach using artificial neural networks to speed up the retrieval algorithm. The forward model outputs are trained into a set of neural network models to completely replace line-by-line calculations in the operational processor. Results of comparing the forward model to the neural network alternative show encouraging results with good agreements between the two when applied to retrieval scenarios using both synthetic and real measured spectra from TROPOMI (TROPOspheric Monitoring Instrument) on board the ESA Sentinel-5 Precursor mission. With an enhancement of the computational speed by three orders of magnitude, TROPOMI's operational aerosol layer height processor is now able to retrieve aerosol layer heights well within operational capacity. [ABSTRACT FROM AUTHOR]

Global mapping of satellite tropospheric NO2 vertical column density (VCD), a key gas in air quality monitoring, requires accurate retrievals over complex urban and industrialized areas and under any atmospheric conditions. The high abundance of aerosol particles in regions dominated by anthropogenic fossil fuel combustion, e.g. megacities, and/or biomass-burning episodes, affects the space-borne spectral measurement. Minimizing the tropospheric NO2 VCD biases caused by aerosol scattering and absorption effects is one of the main retrieval challenges from air quality satellite instruments. In this study, the reference Ozone Monitoring Instrument (OMI) DOMINO-v2 product was reprocessed over cloud-free scenes, by applying new aerosol correction parameters retrieved from the 477 nm O2-O2 band, over eastern China and South America for 2 years (2006–2007). These new parameters are based on two different and separate algorithms developed during the last 2 years in view of an improved use of the OMI 477 nm O2-O2 band: the updated OMCLDO2 algorithm, which derives improved effective cloud parameters, the aerosol neural network (NN), which retrieves explicit aerosol parameters by assuming a more physical aerosol model. The OMI aerosol NN is a step ahead of OMCLDO2 because it primarily estimates an explicit aerosol layer height (ALH), and secondly an aerosol optical thickness τ for cloud-free observations. Overall, it was found that all the considered aerosol correction parameters reduce the biases identified in DOMINO-v2 over scenes in China with high aerosol abundance dominated by fine scattering and weakly absorbing particles, e.g. from [ -20%:-40% ] to [ 0%:20% ] in summertime. The use of the retrieved OMI aerosol parameters leads in general to a more explicit aerosol correction and higher tropospheric NO2 VCD values, in the range of [ 0%:40% ], than from the implicit correction with the updated OMCLDO2. This number overall represents an estimation of the aerosol correction strategy uncertainty nowadays for tropospheric NO2 VCD retrieval from space-borne visible measurements. The explicit aerosol correction theoretically includes a more realistic consideration of aerosol multiple scattering and absorption effects, especially over scenes dominated by strongly absorbing particles, where the correction based on OMCLDO2 seems to remain insufficient. However, the use of ALH and τ from the OMI NN aerosol algorithm is not a straightforward operation and future studies are required to identify the optimal methodology. For that purpose, several elements are recommended in this paper. Overall, we demonstrate the possibility of applying a more explicit aerosol correction by considering aerosol parameters directly derived from the 477 nm O2-O2 spectral band, measured by the same satellite instrument. Such an approach can, in theory, easily be transposed to the new-generation of space-borne instruments (e.g. TROPOMI on board Sentinel-5 Precursor), enabling a fast reprocessing of tropospheric NO2 data over cloud-free scenes (cloudy pixels need to be filtered out), as well as for other trace gas retrievals (e.g. SO2 , HCHO). [ABSTRACT FROM AUTHOR]

The Tropospheric Emission Spectrometer (TES) on the A-Train Aura satellite was designed to profile tropospheric ozone and its precursors, taking measurements from 2004 to 2018. Starting in 2008, TES global sampling of tropospheric ozone was gradually reduced in latitude, with global coverage stopping in 2011. To extend the record of TES, this work presents a multispectral approach that will provide O3 data products with vertical resolution and measurement error similar to TES by combining the single-footprint thermal infrared (TIR) hyperspectral radiances from the Aqua Atmospheric Infrared Sounder (AIRS) instrument and the ultraviolet (UV) channels from the Aura Ozone Monitoring Instrument (OMI). The joint AIRSCOMI O3 retrievals are processed through the MUlti- SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) retrieval algorithm. Comparisons of collocated joint AIRSCOMI and TES to ozonesonde measurements show that both systems have similar errors, with mean and standard deviation of the differences well within the estimated measurement error. AIRSCOMI and TES have slightly different biases (within 5 parts per billion) vs. the sondes. Both AIRS and OMI have wide swath widths (~ 1650 km for AIRS; ~ 2600 km for OMI) across satellite ground tracks. Consequently, the joint AIRSCOMI measurements have the potential to maintain TES vertical sensitivity while increasing coverage by 2 orders of magnitude, thus providing an unprecedented new data set with which to quantify the evolution of tropospheric ozone. [ABSTRACT FROM AUTHOR]

The absorbing aerosol index (AAI) is a qualitative parameter directly calculated from satellite-measured reflectance. Its sensitivity to absorbing aerosols in combination with a long-term data record since 1978 makes it an important parameter for climate research. In this study, we attempt to quantify aerosol absorption by retrieving the singlescattering albedo (ω0) at 550 nm from the satellite-measured AAI. In the first part of this study, AAI sensitivity studies are presented exclusively for biomass-burning aerosols. Later on, we employ a radiative transfer model (DISAMAR) to simulate the AAI measured by the Ozone Monitoring Instrument (OMI) in order to derive ω0 at 550 nm. Inputs for the radiative transfer calculations include satellite measurement geometry and surface conditions from OMI, aerosol optical thickness (τ) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and aerosol microphysical parameters from the AErosol RObotic NETwork (AERONET), respectively. This approach is applied to the Chile wildfires for the period from 26 to 30 January 2017, when the OMIobserved AAI of this event reached its peak. The Cloud- Aerosol Lidar with Orthogonal Polarization (CALIOP) overpasses missed the evolution of the smoke plume over the research region; therefore the aerosol profile is parameterized. The simulated plume is at an altitude of 4.5-4.9 km, which is in good agreement with available CALIOP backscatter coefficient measurements. The data may contain pixels outside the plume, so an outlier detection criterion is applied. The results show that the AAI simulated by DISAMAR is consistent with satellite observations. The correlation coefficients fall into the range between 0.85 and 0.95. The retrieved mean ω0 at 550 nm for the entire plume over the research period from 26 to 30 January 2017 varies from 0.81 to 0.87, whereas the nearest AERONET station reported ω0 between 0.89 and 0.92. The difference in geolocation between the AERONET site and the plume, the assumption of homogeneous plume properties, the lack of the aerosol profile information and the uncertainties in the inputs for radiative transfer calculation are primarily responsible for this discrepancy in ω0. [ABSTRACT FROM AUTHOR]

Global mapping of satellite tropospheric NO2 vertical column density (VCD), a key gas in air quality monitoring, requires accurate retrievals over complex urban and industrialized areas. The high abundance of aerosol particles in regions dominated by anthropogenic fossil fuel combustion, mega-cities and biomass burning affects the space-borne spectral measurement. Minimizing the tropospheric NO2 VCD biases under such conditions are one of the main challenges for the retrieval from air quality satellite instruments. In this study, reference Ozone Monitoring Instrument (OMI) DOMINO-v2 product was reprocessed over cloud-free scenes, by applying new aerosol correction parameters retrieved from the 477nm O2-O2 band, over east China and South America for 2 years (2006-2007). These new parameters are based on two different and separate algorithms developed during the last two years in view of an improved use of the 477nm O2-O2 band: (1) the updated OMCLDO2 algorithm which derives improved effective cloud parameters, (2) the aerosol neural network (NN) giving explicit aerosol parameters by assuming a more physical aerosol model. The OMI aerosol NN is a step ahead to OMCLDO2 by retrieving primarily an explicit aerosol layer height (ALH), and secondly an aerosol optical thickness τ for cloud-free observations. Overall, it was found that all the considered aerosol correction parameters reduce the biases identified in DOMINO-v2 over scenes in China with high aerosol abundance and scattering particles: e.g. from [-20:-40]% to [0:20]% in summertime. The use of the retrieved OMI aerosol parameters leads in general to a more explicit aerosol correction and higher tropospheric NO2 VCD values, in the range of [0:40]%, than from the implicit correction with the updated OMCLDO2. This number overall represents an estimation of the aerosol correction strategy uncertainty nowadays for tropospheric NO2 VCD retrieval from space-borne visible measurements. The explicit aerosol correction theoretically includes more realistic aerosol multiple scattering and absorption effects, especially over scenes dominated by strongly absorbing particles, where the correction based on OMCLDO2 seems to remain insufficient. However, the use of ALH and τ from the OMI NN aerosol algorithm is not a straightforward operation and future studies are required to identify the optimal methodology. Several elements to be considered are recommended in this paper. Overall, we demonstrate the possibility to apply a more explicit aerosol correction by considering aerosol parameters directly derived from the 477nm O2-O2 spectral band, measured by the same satellite instrument. Such an approach can, in theory, easily be transposed to the new-generation of space-borne instruments (e.g. TROPOMI on-board Sentinel-5 Precursor), enabling a fast reprocessing of tropospheric NO2 data over cloud-free scenes (cloudy pixels need to be filtered out), as well as for other trace gas retrievals (e.g. SO2, HCHO). [ABSTRACT FROM AUTHOR]

This paper presents a weighted least squares approach to retrieve aerosol layer height from top-ofatmosphere reflectance measurements in the oxygen A band (758-770 nm) over bright surfaces. A property of the measurement error covariance matrix is discussed, due to which photons travelling from the surface are given a higher preference over photons that scatter back from the aerosol layer. This is a potential source of biases in the estimation of aerosol properties over land, which can be mitigated by revisiting the design of the measurement error covariance matrix. The alternative proposed in this paper, which we call the dynamic scaling method, introduces a scene-dependent and wavelength-dependent modification in the measurement signal-to-noise ratio in order to influence this matrix. This method is generally applicable to other retrieval algorithms using weighted least squares. To test this method, synthetic experiments are done in addition to application to GOME-2A and GOME-2B measurements of the oxygen A band over the August 2010 Russian wildfires and the October 2017 Portugal wildfire plume over western Europe. [ABSTRACT FROM AUTHOR]

The Tropospheric Emission Spectrometer (TES) on the A-Train Aura satellite was designed to profile tropospheric ozone and its precursors, taking measurements from 2004 to 2018. Starting in 2008, TES global sampling of tropospheric ozone was gradually reduced in latitude with global coverage stopping in 2011. To extend the record of TES, this work presents a multispectral approach that will provide O3 data products with vertical resolution and measurement uncertainty similar to TES by combining the single-footprint thermal infrared (TIR) hyperspectral radiances from the Aqua Atmospheric Infrared Sounder (AIRS) instrument and the ultraviolet (UV) channels from the Aura Ozone Monitoring Instrument (OMI). The joint AIR+OMI O3 retrievals are processed through the MUlti-SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) retrieval algorithm. Comparisons of collocated joint AIRS+OMI and TES to ozonesonde measurements show that both systems have similar errors, with mean and standard deviation of the differences well within the estimated measurement uncertainty. AIRS+OMI and TES have slightly different biases (within 5 parts per billion) versus the sondes. Both AIRS and OMI have wide swath widths (~ 1,650 km for AIRS; ~ 2,600 km for OMI) across satellite ground tracks. Consequently, the joint AIRS+OMI measurements have the potential to maintain TES vertical sensitivity while increasing coverage by two orders of magnitude, thus providing an unprecedented new dataset to quantify the evolution of tropospheric ozone. [ABSTRACT FROM AUTHOR]

This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain. [ABSTRACT FROM AUTHOR]

A global picture of atmospheric aerosol vertical distribution with a high temporal resolution is of key importance not only for climate, cloud formation, and air quality research studies but also for correcting scattered radiation induced by aerosols in absorbing trace gas retrievals from passive satellite sensors. Aerosol layer height (ALH) was retrieved from the OMI 477 nm O2-O2 band and its spatial pattern evaluated over selected cloud-free scenes. Such retrievals benefit from a synergy with MODIS data to provide complementary information on aerosols and cloudy pixels. We used a neural network approach previously trained and developed. Comparison with CALIOP aerosol level 2 products over urban and industrial pollution in eastern China shows consistent spatial patterns with an uncertainty in the range of 462-648 m. In addition, we show the possibility to determine the height of thick aerosol layers released by intensive biomass burning events in South America and Russia from OMI visible measurements. A Saharan dust outbreak over sea is finally discussed. Complementary detailed analyses show that the assumed aerosol properties in the forward modelling are the key factors affecting the accuracy of the results, together with potential cloud residuals in the observation pixels. Furthermore, we demonstrate that the physical meaning of the retrieved ALH scalar corresponds to the weighted average of the vertical aerosol extinction profile. These encouraging findings strongly suggest the potential of the OMI ALH product, and in more general the use of the 477 nm O2-O2 band from present and future similar satellite sensors, for climate studies as well as for future aerosol correction in air quality trace gas retrievals. [ABSTRACT FROM AUTHOR]

A three-dimensional global ozone distribution has been derived from assimilation of ozone profiles that were observed by satellites. By simultaneous assimilation of ozone profiles retrieved from the nadir looking satellite instruments Global Ozone Monitoring Experiment 2 (GOME-2) and Ozone Monitoring Instrument (OMI), which measure the atmosphere at different times of the day, the quality of the derived atmospheric ozone field has been improved. The assimilation is using an extended Kalman filter in which chemical transport model TM5 has been used for the forecast. The combined assimilation of both GOME-2 and OMI improves upon the assimilation results of a single sensor. The new assimilation system has been demonstrated by processing 4 years of data from 2008 to 2011. Validation of the assimilation output by comparison with sondes shows that biases vary between -5 and +10% between the surface and 100 hPa. The biases for the combined assimilation vary between -3 and +3% in the region between 100 and 10 hPa where GOME-2 and OMI are most sensitive. This is a strong improvement compared to direct retrievals of ozone profiles from satellite observations. [ABSTRACT FROM AUTHOR]

The absorbing aerosol index (AAI) based on the near Ultra-Violet (near-UV) remote sensing techniques is a qualitative parameter that allows to retrieve aerosol optical properties with confidence. In the first part of this study, a series of AAI sensitivity analysis is presented exclusively on biomass burning aerosols. Later on, this study applies a radiative transfer model (DISAMAR) to simulate the AAI measured by the Ozone Monitoring Instrument (OMI) and to derive the aerosol single scattering albedo (ω0). The inputs for the radiative transfer calculations are satellite measurement geometry and surface conditions from OMI, aerosol optical thickness (τ) from the MODerate-resolution Imaging Spectroradiometer (MODIS), and aerosol micro-physical parameters from the AErosol RObotic NETwork (AERONET), respectively. This approach is applied to the Chile wildfires for the period from 26 to 30 January 2017, when the OMI observed AAI of this event reached its peak. The Cloud and Aerosol Lidar with Orthogonal Polarization (CALIOP) failed to capture the evolution of the smoke plume, therefore the aerosol profile is parameterized. The simulated plume ascends to an altitude of 4.5–4.9 km, which is in good agreement with measurements. Due to the relatively small data size of this case, an outlier detection criterion has to be applied. The results show that the AAI simulated by DISAMAR is consistent with observations. The correlation coefficients are over 0.85. The retrieved mean ω0 at 550 nm is approximately 0.84, slightly smaller than the value of 0.90 measured independently by the AERONET instrument. The relative distance between the AERONET site and the plume, the assumption of homogeneous and static plume properties, the lack of the aerosol profile information, and the uncertainties in observations are primarily responsible for this discrepancy. Except for the observational errors, the impact of remaining error sources on ω0 retrieval is difficult to quantify. [ABSTRACT FROM AUTHOR]

Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top-of-atmosphere reflectance spectrum in the oxygen A band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in the literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top-of-atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A band, and discusses its implications. The underlying physics are introduced by analysing the top-of-atmosphere reflectance spectrum as a sum of atmospheric path contribution and surface contribution, obtained using a radiative transfer model. Furthermore, error analysis of an aerosol layer height retrieval algorithm is conducted over dark and bright surfaces to show the dependence on surface reflectance. The analysis shows that the derivative with respect to aerosol layer height of the atmospheric path contribution to the top-of-atmosphere reflectance is opposite in sign to that of the surface contribution – an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these derivatives are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A band from the GOME-2 instrument on board the Metop-A satellite over the 2010 Russian wildfires incident. [ABSTRACT FROM AUTHOR]

A global picture of atmospheric aerosol vertical distribution with a high temporal resolution is of key importance not only for climate, cloud formation and air quality research studies, but also for correcting aerosol radiation effect in absorbing trace gas retrievals from passive satellite sensors. Aerosol layer height (ALH) was retrieved from the OMI 477 nm O2-O2 band and its spatial pattern evaluated over selected cloud-free scenes. Such retrievals benefit from a synergy with MODIS data to provide complementary information on aerosols and cloudy pixels. We used a neural network approach previously trained and developed. Comparison with CALIOP aerosol level 2 products over urban and industrial pollution in east China shows consistent spatial patterns with an uncertainty in the range of 462-648 m. In addition, we show the possibility to determine the height of thick aerosol layers released by intensive biomass burning events in South-America and Russia, and of a Saharan dust outbreak over sea from OMI visible measurements. Complementary detailed analyses show that the assumed aerosol properties in the modeling are the key factors affecting the accuracy of the results, together with potential cloud residuals in the observation pixels. Furthermore, we demonstrate that the physical meaning of the retrieved ALH scalar corresponds to the weighted average of the vertical aerosol extinction profile. These encouraging findings strongly suggest the potential of the OMI ALH product, and in more general the use of the 477 nm O2-O2 band from present and future similar satellite sensors, for climate studies as well as for future aerosol correction in air quality trace gas retrievals. [ABSTRACT FROM AUTHOR]

Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top of atmosphere reflectance spectrum in the oxygen A-band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top of atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A-band, and discusses its implications. The underlying physics are introduced by analysing top of atmosphere reflectance spectra obtained using a radiative transfer model. Furthermore, error analysis of the aerosol layer height retrieval algorithm are conducted over dark and bright surfaces to show the dependency on surface reflectance. The analysis shows that the information on aerosol layer height from atmospheric path contribution and the surface contribution to the top of atmosphere are opposite in sign - an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these contributions are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A-band from GOME-2A instrument on board the Metop-A satellite over the 2010 Russian wildfires incident. [ABSTRACT FROM AUTHOR]

This paper presents the retrieval method that was developed to derive tropospheric NO2 columns from UV/VIS spectral measurements obtained with the Spectrolite Breadboard Instrument during the AROMAPEX campaign in Berlin (April 2016). A typical DOAS retrieval approach is followed. For the calculation of air mass factors this study specifically focuses on the impact of the surface reflectance, which varies considerably from pixel to pixel over this urban region. Ground-based aerosol optical thickness measurements are used as prior information. It is shown that retrieved surface reflectance shows good agreement with those derived from Landsat 8 measurements performed on the same day. Furthermore we demonstrate that tropospheric NO2 columns retrieved for pairs of adjacent pixels are self-consistent in the sense that they do not show a substantial systematic dependence on surface reflectance, in contrast to differential slant column densities. Also some cases are identified to illustrate this on a pixel-by-pixel level. An error budget is provided to quantify the impact of various assumptions on the accuracy of the retrieval of surface reflectance and tropospheric NO2 columns. Both in the morning and afternoon flight a NO2 plume is observed stretching out over Berlin from West to East. Peak values between 15 × 1015 and 20 × 1015 molec/cm² are detected, whereas - at much lower spatial resolution - OMI detects peak values between 9 × 1015 (first overpass) and 4 × 1015 molec/cm² (second overpass). [ABSTRACT FROM AUTHOR]

The Dutch-Finnish Ozone Monitoring Instrument (OMI) is an imaging spectrograph flying on NASA's EOS Aura satellite since 15 July 2004. OMI is primarily used to map trace-gas concentrations in the Earth's atmosphere, obtaining mid-resolution (0.4-0.6 nm) ultraviolet-visible (UV- VIS; 264-504 nm) spectra at multiple (30-60) simultaneous fields of view. Assessed via various approaches that include monitoring of radiances from selected ocean, land ice and cloud areas, as well as measurements of line profiles in the solar spectra, the instrument shows low optical degradation and high wavelength stability over the mission lifetime. In the regions relatively free from the slowly unraveling "row anomaly" (RA) the OMI irradiances have degraded by 3-8%, while radiances have changed by 1-2%. The long-term wavelength calibration of the instrument remains stable to 0.005-0.020 nm. [ABSTRACT FROM AUTHOR]

The Dutch-Finnish Ozone Monitoring Instrument (OMI) is an imaging spectrograph flying on NASA's EOS Aura satellite since July 15, 2004. OMI is primarily used to map trace gas concentrations in the Earth's atmosphere, obtaining mid-resolution (0.4-0.6 nm) UV-VIS (264-504 nm) spectra at multiple (30-60) simultaneous fields of view. Assessed via various approaches that include monitoring of radiances from selected ocean, land, ice and cloud areas, as well as measurements of line profiles in the Solar spectra, the instrument shows low optical degradation and high wavelength stability over the mission lifetime. In the regions relatively free from the slowly unraveling 'row anomaly' the OMI irradiances have degraded by 3-8 %, while radiances have changed by 1-2 %. The long-term wavelength calibration of the instrument remains stable to 0.005-0.020 nm. [ABSTRACT FROM AUTHOR]

The OMI (Ozone Monitoring Instrument on board NASA's Earth Observing System (EOS) Aura satellite) OMCLDO2 cloud product supports trace gas retrievals of for example ozone and nitrogen dioxide. The OMCLDO2 algorithm derives the effective cloud fraction and effective cloud pressure using a DOAS (differential optical absorption spectroscopy) fit of the O2-O2 absorption feature around 477 nm. A new version of the OMI OMCLDO2 cloud product is presented that contains several improvements, of which the introduction of a temperature correction on the O2-O2 slant columns and the updated look-up tables have the largest impact. Whereas the differences in the effective cloud fraction are on average limited to 0.01, the differences of the effective cloud pressure can be up to 200 hPa, especially at cloud fractions below 0.3. As expected, the temperature correction depends on latitude and season. The updated look-up tables have a systematic effect on the cloud pressure at low cloud fractions. The improvements at low cloud fractions are very important for the retrieval of trace gases in the lower troposphere, for example for nitrogen dioxide and formaldehyde. The cloud pressure retrievals of the improved algorithm are compared with ground-based radar-lidar observations for three sites at mid-latitudes. For low clouds that have a limited vertical extent the comparison yields good agreement. For higher clouds, which are vertically extensive and often contain several layers, the satellite retrievals give a lower cloud height. For high clouds, mixed results are obtained. [ABSTRACT FROM AUTHOR]