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International audience; For more than three years now, the first atmospheric satellite of the Copernicus EO programme, Sentinel-5p (S5P) TROPOMI, has acquired spectral measurements of the Earth radiance in the visible range, from which near-real-time (NRTI) and offline (OFFL) processors retrieve the total, tropospheric and stratospheric column abundance of NO2. The S5P Mission Performance Centre performs continuous QA/QC of these data products enabling users to verify the fitness-for- purpose of the S5P data. Quality Indicators are derived from comparisons to ground-based reference data, both station-by-station in the S5P Automated Validation Server (AVS), and globally in more in-depth analyses. Complementary quality information is obtained from product intercomparisons (NRTI vs. OFFL) and from satellite-to-satellite comparisons. After three years of successful operation we present here a consolidated overview of the quality of the S5P TROPOMI NO2 data products, with particular attention paid to the impact of the various processor improvements, especially in the latest version (v1.4), activated on 2 December 2020, which introduces an updated cloud retrieval resulting in higher NO2 columns in polluted regions. Also the upcoming v2, due in April 2021 but already used to produce a Diagnostic Data Set, is discussed.S5P NO2 data are compared to ground-based measurements collected through either the ESA Validation Data Centre (EVDC) or network data archives (NDACC, PGN). Measurements from the Pandonia Global Network (PGN) serve as a reference for total NO2 validation, Multi-Axis DOAS data for tropospheric NO2 validation, and NDACC zenith-scattered-light DOAS data for stratospheric NO2 validation. Comparison methods are optimized to limit spatial and temporal mismatch errors (co-location strategy, photochemical adjustment to account for local time difference). Comparison results are analyzed to derive Quality Indicators and to conclude on the compliance w.r.t. the Powered by TCPDF (www.tcpdf.org)mission requirements. This include estimates of: (1) the bias, as proxy for systematic errors, (2) the dispersion of the differences, which combines random errors with seasonal and mismatch errors, and (3) the dependence of these on key influence quantities (surface albedo, cloud cover...)Overall, the MPC quality assessment of S5P NO2 data concludes to an excellent performance for the stratospheric data (bias

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically −23 % to −37 % in clean to slightly polluted conditions but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about −0.2 Pmolec cm−2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm−2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm−2) but exceed those for the tropospheric column data (0.7 Pmolec cm−2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm−2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values. This research has been supported by the ESA/ESRIN (grant no. 4000117151/16/I-LG) and the BELSPO/ESA ProDEx (TROVA-E2 (PEA grant no. 4000116692)). Part of the reported work was carried out in the framework of the Copernicus Sentinel-5 Precursor Mission Performance Centre (S5P MPC), contracted by the European Space Agency and supported by the Belgian Federal Science Policy Office (BELSPO), the Royal Belgian Institute for Space Aeronomy (BIRA-IASB), the Netherlands Space Office (NSO), and the German Aerospace Centre (DLR). Part of this work was carried out also in the framework of the S5P Validation Team (S5PVT) AO projects NIDFORVAL (ID no. 28607, PI Gaia Pinardi, BIRA-IASB) and CESAR (ID no. 28596, PI Arnoud Apituley, KNMI). The authors express special thanks to Ann Mari Fjæraa, José Granville, Sander Niemeijer, and Olivier Rasson for post-processing of the network and satellite data and for their dedication to the S5P operational validation. The LATMOS real-time processing facility is acknowledged for fast delivery of ZSL-DOAS SAOZ data. Fast delivery of MAX-DOAS data tailored to the S5P validation was organized through the S5PVT AO project NIDFORVAL. The authors are grateful to ESA/ESRIN for supporting the ESA Validation Data Centre (EVDC) established at NILU and for running the Fiducial Reference Measurements (FRM) programme and in particular the FRM4DOAS and Pandonia projects. The PGN is a bilateral project between NASA and ESA, and the NASA funding for the PGN is provided through the NASA Tropospheric Composition Program and Goddard Space Flight Center Pandora project. The MAX-DOAS, ZSL-DOAS, and PGN instrument PIs and staff at the stations are thanked warmly for their sustained effort on maintaining high-quality measurements and for valuable scientific discussions. Aleksandr Elokhov and Aleksandr Gruzdev acknowledge national funding from RFBR through the project 20-95-00274. IUP Bremen acknowledges DLR Bonn for funding received through project 50EE1709A. The SAOZ network acknowledges funding from the French Institut National des Sciences de l'Univers (INSU) of the Centre National de la Recherche Scientifique (CNRS), Centre National d'Etudes Spatiales (CNES), and Institut polaire français Paul Emile Victor (IPEV). Work done by Hitoshi Irie was supported by the Environment Research and Technology Development Fund (2-1901) of the Environmental Restoration and Conservation Agency of Japan, JSPS KAKENHI (grant nos. JP19H04235 and JP17K00529), the JAXA 2nd Research Announcement on the Earth Observations (grant no. 19RT000351), and JST CREST (grant no. JPMJCR15K4). The University of Toronto ZSL-DOAS measurements at Eureka were made at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC), with support from the Canadian Space Agency (AVATARS project), the Natural Sciences and Engineering Research Council (PAHA project), and Environment and Climate Change Canada. 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This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOspheric Monitoring Instrument (TROPOMI) on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite. Tropospheric, stratospheric, and total NO2 column data from S5P are compared to correlative measurements collected from, respectively, 19 Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS), 26 Network for the Detection of Atmospheric Composition Change (NDACC) Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 Pandonia Global Network (PGN)/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatiotemporal co-location of the satellite and correlative data, e.g. by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5P data show, on average, (i) a negative bias for the tropospheric column data, of typically-23 % to-37 % in clean to slightly polluted conditions but reaching values as high as-51 % over highly polluted areas; (ii) a slight negative median difference for the stratospheric column data, of about-0:2 Pmolec cm-2, i.e. approx.-2 % in summer to-15 % in winter; and (iii) a bias ranging from zero to-50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec cm-2 and negative values above. The dispersion between S5P and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec cm-2) but exceed those for the tropospheric column data (0.7 Pmolec cm-2). While a part of the biases and dispersion may be due to representativeness differences such as different area averaging and measurement times, it is known that errors in the S5P tropospheric columns exist due to shortcomings in the (horizontally coarse) a priori profile representation in the TM5-MP chemical transport model used in the S5P retrieval and, to a lesser extent, to the treatment of cloud effects and aerosols. Although considerable differences (up to 2 Pmolec cm-2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and offline (OFFL) versions of the S5P NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

International audience; This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values.

International audience; Tropospheric ozone is a pollutant that damages ecosystems and triggers human health problems. Ozone concentrations are highly variable over time and across the troposphere, which poses clear challenges to deepen our understanding of the processes involved in the production and transport of ozone. Further progress depends on the availability of instruments capable of measuring tropospheric ozone and its distribution at finer spatio-temporal scales. The TROPOMI instrument on the Sentinel-5p platform, launched into an early afternoon polar orbit in October 2017, combines a high spatial resolution, a large swath width and the spectral measurement characteristics required to deliver tropospheric ozone data records at unprecedented detail. The first of these products was released during Fall 2018. It consists in 0.5° (latitude) by 1° (longitude) resolved daily maps of 3-day moving mean values of the tropospheric ozone column between 20°S and 20°N, and it is computed using the convective-cloud method (CCD). A second data product consists in maps of tropical upper tropospheric ozone mixing ratio at a coarser spatial and temporal resolution. It is based on a cloud slicing algorithm (CSA), which is currently being fine-tuned for release in the very near future. A third data product, also under development at the time of this abstract, consists of the vertical profile of ozone concentration in the global troposphere and stratosphere, retrieved with the classical Optimal Estimation (OE) technique. We present here an assessment of the quality of the first year of the different tropospheric ozone column data sets retrieved from Sentinel-5p TROPOMI measurements, carried out within the context of ESA’s Sentinel-5p Mission Performance Center (MPC) and the S5PVT AO project CHEOPS-5p (Validation of Copernicus Height-resolved Ozone data Products from Sentinel-5p TROPOMI using global sonde and lidar networks, #28587). The first stage of this analysis consists of an inspection of the tropospheric ozone fields for structures which are potentially introduced in the measurement process. Sampling effects, in particular, are a possible source of uncertainty as the CCD product is derived from binned TROPOMI total ozone column data. Another structure introduced by retrieval assumptions would be the dependence of the quality of Sentinel-5p retrieved total column data to cloud parameters. In a second stage the satellite data are confronted to quality-assured ozonesonde and –tentatively– ground-based lidar measurements from the NDACC, SHADOZ and TOLNET networks. These well-characterized observational data records serve as a reference to evaluate the bias and uncertainty of the Sentinel-5p data, and their dependence on influence quantities. The study concludes with an assessment of the compliance of Sentinel-5p tropospheric ozone data with respect to mission and user requirements for key data applications.

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric ChartographY) aboard ESA's environmental satellite ENVISAT observed the Earth's atmosphere in limb, nadir, and solar/lunar occultation geometries covering the UV-Visible to NIR spectral range. It is a joint project of Germany, the Netherlands and Belgium and was launched in February 2002. SCIAMACHY doubled its originally planed in-orbit lifetime of five years before the communication to ENVISAT was severed in April 2012, and the mission entered its post-operational phase. In order to preserve the best quality of the outstanding data recorded obtained by SCIAMACHY, the data processors were updated in phase F and the whole mission was reprocessed. In addition to the usual updates, the following items were added to the processor 1. Tropospheric BrO, a new retrieval based on the scientific algorithm of (Theys et al., 2011). This algorithm had been originally developed for the GOME-2 sensor and later adapted for SCIAMACHY. 2. Improved cloud flagging using limb measurements. Limb cloud flags are already part of the SCIAMACHY L2 product. They are currently calculated based on the scientific algorithm by (Eichmann et al., 2015). Clouds are categorized into four types: water, ice, polar stratospheric and noctilucent clouds. 3. A new, future-proof file format for the level 2 product based on NetCDF. We will present results from the verification and the mission re-processing.

Using the convective clouds differential (CCD) method on total ozone and cloud data from three European satellite instruments GOME/ERS-2 (1995–2003), SCIAMACHY/Envisat (2002–2012), and GOME-2/MetOp-A (2007–2015) it is possible to retrieve tropical tropospheric columns of ozone (TTCO) which are in good agreement with in-situ measurements. Small differences in TTCO between the individual instruments are evident and therefore the individual datasets retrieved are harmonised into one consistent time-series starting from 1996 until 2015. Correction offsets (bias) between the instruments using SCIAMACHY as intermediate reference have been calculated and six different harmonisation scenarios have been tested. Finally, the datasets have been harmonised applying no correction to GOME data while GOME-2 has been corrected using for each grid-box the mean bias with respect SCIAMACHY for the years of common operation (2007–2012). Depending on the choice of harmonisation, the magnitude, pattern, and uncertainty of the trend can strongly vary. The harmonisation represents an additional source of uncertainty in the merged dataset and derived trend estimates. For the preferred harmonised dataset, the trend ranges between −4 and 4 DU decade-1. The trend of the tropically averaged tropospheric ozone is equal to 0 ± 0.64 DU decade-1 (2σ). Regionally, tropospheric ozone has a statistically significant increase by ~ 3 DU decade-1 over southern Africa (~ 1.5 % year-1), the southern tropical Atlantic (~ 1.5 % year-1), southeastern tropical Pacific Ocean (~ 1 % year-1), and central Oceania (~ 2 % year-1). Additionally, over central Africa (2–2.5 % year-1) and south India (~ 1.5 % year-1), tropospheric ozone increases by ~ 2 DU decade-1. These regional positive tropospheric ozone trends maybe linked to anthropogenic activities such as emissions in mega cities or biomass burning in combination with changes in meteorology or/and long range transport of precursor emissions. On the other hand, tropospheric O3 decreases by ~ −3 DU decade-1 over the Caribbean sea and parts of the North Pacific Ocean (~ −2 % year-1), and by less than −2 DU decade-1 over some regions of the southern Pacific and Indian Ocean (~ −0.5–−1 % year-1). Possible reasons for this decrease are changes in dynamical processes, convection, STE, and precipitation. The comparison of the calculated trends from the current study with tropospheric ozone trends from Heue et al. (2016) and Ebojie et al. (2016) in ten selected mega-cities showed that they agree within 2σ of the trend uncertainty.

The SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) aboard Envisat observed the Earth’s atmosphere in nadir, limb and solar/lunar occultation geometries covering the UV-Visible to NIR (240-2380 nm) spectral range with a moderate spectral resolution of 0.2-1.5nm. The instrument provided decade long coverage (2002-2012) of various atmospheric parameters from the troposphere up to the mesosphere. These decadal datasets are important building blocks for long term assessments of climate relevance. The SCIAMACHY Quality Working Group (SQWG), formed in 2007, aims at improving the quality of the operational data products. University of Bremen (IUP), BIRA, DLR-IMF, SRON and KNMI are the members providing expertise in this group. Since the establishment of SQWG, the ESA operational Level 2 processor was significantly improved w.r.t. data quality and the product list was substantially enhanced with new parameters. The current project builds on the heritage of previous SQWG projects and has the following objectives: update the Level 0-2 processing chain, deliver the processor baseline enabling the generation of a quality controlled Level 1b and Level 2 dataset for the whole mission and to ensure long-term usability of the data. The SQWG Level 2 team is working on the improvement and implementation of processor Version 6 and the future Version 7. Under the SQWG framework, the main focus is on the following products: in nadir mode, total columns of O3, NO2, CO, IO and the tropospheric columns of NO2, and O3 (from limb-nadir matching) and the tropospheric columns of BrO and HCHO and, in limb, the aerosol and water vapour profiles and cloud flagging improvement and implementation. Here we present the key results of SCIAMACHY Level 2 Version 6 and Version 7 implementation and verification activities.

Since the foundation of the SCIAMACHY Quality Working Group (SQWG) in a joint ESA-DLR-NIVR inter-agency effort in late 2006, the ESA operational Level 2 processor was significantly improved w.r.t. data quality and product range. During the last two years the product list was substantially enhanced by new (total columns of SO2, BrO, OClO, H2O, CO, Limb BrO profiles, Limb cloud flags) and improved products (total columns of O3, NO2, Absorbing Aerosol Index, Limb O3 profiles, Limb NO2 profiles). For example, important improvements were achieved in the O3 and NO2 profile calculation by implementing an upgraded retrieval scheme and using now Level 1b version 7.0 data with an improved pointing correction. Nadir products of total column O3 and Absorbing Aerosol Index were improved by applying a radiometric degradation correction (m-factors) in the Level 1 to 2 processing step.

Measurements of stratospheric ozone over the Northern hemisphere forthe winter/spring periods of 1997 to 2000 taken with the GOMEinstrument were used to derive the chemical ozone depletion inside thepolar vortex. GOME onboard the ERS-2 satellite measures radiationcoming from the Earth in the UV/vis spectral range.To discern the chemical depletion from dynamical influences, a modelwas developed to calculate vortex averaged diabatic descent ratesusing the radiative transfer model MIDRAD and the FURM ozoneprofiles. The permeability of the Arctic vortex was analysed by usingthe trajectory model TANGO in conjunction with a reverse domainfilling algorithm, developed within the framework of this thesis.The chemical ozone depletion at 475 K for the stratospheric coldwinter/spring period in 1997 was found to be 1.6 ppmv with a depletionrate of 22 ppbv/d for a strong, long lasting vortex until beginning ofMay. The chemical depletion of ozone in 1998, a comparingly warm year,was narrowed to a period at the end of February with 0.5 ppmv and arate of 8 ppbv/d. 1999 was quite warm and the vortex was veryinstable. A depletion of 0.3 ppmv was measured, but this is in partdue to intrusion of air from outside the vortex. 2000 was the coldestyear on record. The vortex was detected very early by GOME at the endof January. A chemical depletion of 1.8 ppmv (32 ppbv/d) until thebeginning of April was found, when the vortex broke down.

Ozone profile retrieval, ERS-2, GOME, FURM, ozone decline, Northern hemisphere. - Measurements of stratospheric ozone over the Northern hemisphere forthe winter/spring periods of 1997 to 2000 taken with the GOMEinstrument were used to derive the chemical ozone depletion inside thepolar vortex. GOME onboard the ERS-2 satellite measures radiationcoming from the Earth in the UV/vis spectral range.To discern the chemical depletion from dynamical influences, a modelwas developed to calculate vortex averaged diabatic descent ratesusing the radiative transfer model MIDRAD and the FURM ozoneprofiles. The permeability of the Arctic vortex was analysed by usingthe trajectory model TANGO in conjunction with a reverse domainfilling algorithm, developed within the framework of this thesis.The chemical ozone ..., thesis