Poster Session

Anthropogenic CO₂ emissions from fossil fuel combustion have large impacts on climate. In order to monitor the increasing CO₂ concentrations in the atmosphere, accurate spaceborne observations—as available from the Orbiting Carbon Observatory-2 (OCO-2)—are needed. In our recent work [Hakkarainen et al., 2016] we provided a new approach to study anthropogenic CO₂ emission areas by deseasonalizing and detrending OCO-2 XCO₂ observations for deriving XCO₂ anomalies. The spatial distribution of the XCO₂ anomaly matches the features observed in the maps of the Ozone Monitoring Instrument NO₂ tropospheric columns, used as an indicator of atmospheric pollution, as well as the features observed in the ODIAC emission dataset. In addition, the results of a cluster analysis confirmed the correlation between CO₂ and NO₂ spatial patterns.

In this work, we study this idea further and provide the global XCO₂ anomalies for three full years 2015, 2016 and 2017. The patterns observed in these maps are compared with inventory-based estimates given by the Lagrangian particle dispersion model FLEXPART driven by the high-resolution ODIAC emission dataset.  We also use data from the TROPOspheric Monitoring Instrument (TROPOMI), launched on October 13th, 2017 on board of the Copernicus Sentinel-5 Precursor satellite. TROPOMI provides daily global coverage with a spatial resolution of 7 km × 7 km in nadir direction, and observes NO₂, SO₂ and CO, among other atmospheric parameters. We analyze these data in synergy to better detect anthropogenic CO₂ sources and plumes.

References 

Hakkarainen, J., I. Ialongo, and J. Tamminen (2016), Direct space-based observations of anthropogenic CO₂ emission areas from OCO-2, Geophys. Res. Lett., 43, 11,400–11,406, doi:10.1002/2016GL070885.

The OSIRIS instrument has measured vertical profiles of nitrogen dioxide number density within the stratosphere since its launch in early 2001. The OSIRIS measurements of limb scattered sunlight have been demonstrated to produce high quality vertical nitrogen dioxide profiles that have been used in many studies of stratospheric chemistry. Recently, there has been significant activity associated with limb-nadir matching and progress has been made in the development of techniques that involve using results inferred from both limb scattered sunlight and surface reflected sunlight to improve the accuracy of tropospheric nitrogen dioxide column density measurements. This paper will present results from a new data record of the column density of nitrogen dioxide derived from OMI and OSIRIS measurements. It will also present preliminary results from additional studies that are designed to show the improvements to air quality forecasts that are expected from this improved tropospheric nitrogen dioxide product.

The Sea and Land Surface Temperature Radiometer (SLSTR) instrument aboard Sentinel-3 is used for detection of volcanic ash plumes in atmosphere and for estimating the plume top height. Ash detection is based on the reverse absorption technique using SLSTR channels 8 (10.85 µm) and 9 (12 µm). The height estimates are based on the stereo-viewing capability of SLSTR and on an area-based correlation method approach. The algorithm determines the parallax between the nadir and backward views of SLSTR for an elevated feature, and calculates the corresponding height. It provides height estimates for each satellite pixel with nominal vertical resolution of 0.5 km for the visible channels and 1 km for the thermal infrared channels. The height estimate can be limited to ash-flagged pixels or run for a full scene. The algorithm is capable of retrieving the height of any elevated features with sufficient contrast to the background, such as clouds, ash and dust plumes, thick smoke plumes, or ground surface (for validation). Different wavelengths can be used in the correlation method to obtain complementary information on the feature heights. The SLSTR instrument, orbiting aboard Sentinel-3A since 2016 and on Sentinel-3B since April 2018, provides a unique combination of dual-view capability and a wavelength range from visible to thermal infrared which makes it an ideal instrument for this work. The method has been applied to volcanic eruptions and desert dust plume episodes in 2017 and 2018. The current research is being carried out as part of the H2020 project EUNADICS-AV (European Natural Disaster Coordination and Information System for Aviation).

Many remote sensing observations of vertical profiles of atmospheric variables are obtained with instruments operating on space-borne and airborne platforms, as well as from ground-based stations. When the same portion (or nearby portions) of atmosphere is observed more times by the same instrument or by different instruments the measurements can be combined in order to obtain a single vertical profile of improved quality with respect to that of the profiles retrieved from the single measurements. Recently, a new method of data fusion, referred to as Complete Data Fusion (CDF), was proposed for use in the combination of independent measurements of the same profile. This is an a posteriori method that uses standard retrieval products and with simple implementation requirements provides products equivalent to those of the simultaneous retrieval, which is considered to be the most comprehensive way of exploiting different observations of the same quantity.

As part of the AURORA project, we have applied the CDF method to ozone profiles obtained from simulated measurements in the ultraviolet and in the thermal infrared in the framework of the Sentinel 4 mission of the Copernicus programme.

We observe that the quality of the fused products is very good when we fuse consistent profiles, instead the quality is degraded when we fuse profiles that are either retrieved on different vertical grids or referred to different true profiles.

In order to address this shortcoming, a generalization of the CDF method, which takes into account interpolation and coincidence errors, was developed. We determine the expressions of these errors and show how they enter in the CDF formula. This upgrade overcomes the encountered problems and provides products of good quality also when the fusing profiles are both retrieved on different vertical grids and referred to different true profiles. The approach developed to account for the interpolation and coincidence errors can also be followed to include other error components, such as forward model errors.

The Emerging SPARC Activity "Towards Unified Error Reporting (TUNER)" aims at unification and harmonization of error analysis and reporting of satellite measurements of atmospheric state variables. Its goal is to make error estimates of existing satellite observations of atmospheric temperature and constituent profiles intercomparable. The main tasks within this project are (a) to develop a coherent terminology and formalism adequate to represent all existing retrieval schemes; (b) to assess the completeness of error budgets provided by the instrument teams of the relevant space missions; (c) to find ways to provide estimates of error components not considered so far and diagnostic data not provided so far, and (d) to develop recommendations how retrieval errors and other diagnostic data can be communicated to the user without generating unnecessary data traffic. In this talk the progress made will be reported, difficulties encountered will be discussed, and future plans will be presented.

Observations of the Earth’s atmosphere for the vertical profiling of atmospheric variables are provided by many space-borne missions, airborne and ground-based campaigns, aiming at global and continuous measurements which can highlight trends in the atmospheric species and provide the input to the physical and chemical models that are used to predict the evolution of the atmospheric status. In the last two decades, there has been a strong focus on the development of innovative techniques to exploit all the available information from measurements of the same portion of the atmosphere to retrieve the best vertical profile estimate. In this framework, a new method of data fusion, referred to as Complete Data Fusion (CDF), was proposed as a-posteriori algorithm to combine independent measurements of the same profile into a single estimate for a comprehensive and concise description of the atmospheric state. This method uses standard retrieval products and requires a simple implementation.

Multi-target retrievals are frequently applied to the analysis of remote sensing observations to determine simultaneously atmospheric constituents reducing the systematic error caused by interfering species. It is thus crucial to adapt the CDF algorithm to fuse profiles obtained from multi-target retrievals, in order to extend its application to a greater number of remote sensing data.

In this work we present the results of the first application of the complete data fusion to multi-target retrieval products showing how the inputs of the CDF have to be modified to take into account that state vectors of the fusing measurements may contain only the same atmospheric variables or include different variables as well. We applied the method to simulated measurements in the thermal infrared and in the far infrared spectral ranges, considering the instrumental specifications and performances of IASI-NG and FORUM instruments, respectively.

The results obtained demonstrate that the CDF can deal with state vectors from multi-target retrievals both when they contain the same variables and when they have only a subset of variables in common, providing outputs of improved quality with respect to the input data.

Phytoplankton form important parameters as far as the climate and the life in the oceans are concerned, firstly by affecting the global carbon cycle and the planetary heat budget and additionally by forming the base of the marine food chain. The proposed study addresses the determination of patterns in chlorophyll-a concentrations, as an index of the phytoplankton biomass, and the underlying correlation to distinct physical-chemical variables in different areas of the ocean.

Satellite sea surface chlorophyll-a monthly observations are derived from the ESA Ocean Colour Climate Change Initiative (OC-CCI) with a spatial resolution of 4 km for a 14-year period (2003 - 2016) and for four different areas, which are later separated in sub-regions according to the chlorophyll-a variability patterns. The four different areas are situated in the Mediterranean Sea (Adriatic Sea, Levantine Sea and West Mediterranean Sea) and in the Atlantic Ocean (the Gulf of Biscay). For the same areas satellite and model data are processed. The satellite data acquired are the Sea Surface Temperature (SST) and the Photosynthetically Active Radiation (PAR) measured by the MODIS instrument. The model derived data used are the nitrate and phosphate concentrations obtained by models from the Copernicus Marine Environmental Monitoring Service and dust deposition for the area of the Levantine Sea acquired by the NASA atmospheric reanalysis, MERRA-2. 

Higher concentrations of chlorophyll-a are found in the coastal sub-regions of the four previously mentioned areas, and mostly in waters affected by river discharges that contain nutrients that vary in response with the amount of the precipitation and the anthropogenic factor (i.e. industry, agriculture, different lifestyles). Great discrepancies, mostly in the chlorophyll-a and the nutrients variability, are shown between the sub-regions and different trends are calculated throughout the period of study. The correlations between the chlorophyll-a and the other variables demonstrate a great variation between the sub-regions. Maps, plots, correlations and trends will be presented.

Lower tropospheric ozone retrievals from nadir sounders is challenging due to the lack of vertical sensitivity of the measurements and towards the lowest layers. If improvements have been made during the last decade, it is still important to explore possibilities to improve the retrieval algorithms themselves. Ozone retrieval from nadir satellite observations is an ill-conditioned problem, which requires regularization using constraint matrices. Up to now, most of the retrieval algorithms rely on a fixed constraint. The constraint is determined and fixed beforehand, on the basis of sensitivity tests. This does not allow ones to take advantage of the entire capabilities of the satellite measurements, which vary with the thermal conditions of the observed scenes. To overcome this limitation, we developed a self-adapting and altitude-dependent regularization scheme. A crucial step is the choice of the strength of the constraint. This choice is done during an iterative process and depends on the measurement errors and on the sensitivity of the measurements to the target parameters at the different altitudes. The challenge is to limit the use of a priori constraints to the minimal amount needed to perform the inversion.

The algorithm has been tested on synthetic observations matching the future IASI-NG satellite instrument. IASI-NG measurements are simulated on the basis of ozone concentrations taken from an atmospheric model and retrieved using two retrieval schemes (the standard and self-adapting ones). Comparison of the results shows that the sensitivity of the observations to the ozone amount in the lowest layers (given by the degrees of freedom for the solution) is increased, which allows a better description of the ozone distribution, especially in the case of large ozone plumes. Biases are reduced and the spatial correlation is improved. Tentative of application to real observations from IASI, currently onboard the Metop satellite will also be presented.  

The main aim of this study is the improvement of comparisons between satellite and ground-based total ozone column, TOC, measurements in the cases where the collocation criteria result in the observations being affected by the location of the polar vortex. European Space Agency Ozone_CCIGODFIT (GOME-type direct fitting) v4 algorithm retrievals from GOME-2/Metop-A, GOME-2/Metop-B and OMI/Aura TOCs were validated against observations by spectrophotometer instruments (Brewer and Dobson) from the World Ozone and Ultraviolet Radiation Data Centre repository. For the determination of the edge and surface area of the polar vortex, the potential vorticity at 475 K potential temperature surface provided by ERA-Interim reanalysis datasets from the European Centre for Medium-Range Weather Forecasts was used as an indicator.

Ozone observations from 2007 to 2017 were examined for all Brewer and Dobson stations in the North and South Hemisphere with latitude greater than 30^o, the regions that are most affected by the position of polar vortex. The analysis was applied for three spatial criteria depending on each satellite’s spatial coverage. The main premise was that the collocations between ground and satellite were separated depending on whether both satellite and ground-based measurements are inside the polar vortex (matched) or one measurement is inside whereas the other one is outside the polar vortex (mismatched).

The results show that the mean difference between mismatched collocations is larger than the mean difference between matched collocations. When allowing for 50 km as radius of collocation, in Vindeln, Sweden (latitude=64.25^o N) the mean difference for the mismatched cases is 2.06 ± 0.75 %, 4.18 ± 0.99 % and 1.31 ± 0.28 % for GOME2-A, GOME2-B and OMI respectively, while the mean difference for the matched cases is 1.09 ± 0.03 %, 2.22 ± 0.04 % and 1.5 ± 0.01 % respectively. The number of mismatched collocations that were found to be 11, 3 and 58 for GOME2-A, GOME2-B and OMI respectively, while, the matched collocations are 14874, 5426 and 76216 for GOME2-A, GOME2-B and OMI respectively. Also, by applying a linear regression in the measurements, for the mismatched the slope is 0.97, 0.97 and 0.92 and the intercept is 17.98, 19.84 and 33.74 D.U. for GOME2-A, GOME2-B and OMI respectively, while, for the matched the slope is 1.02, 1.01 and 1.01 and the intercept is -1.43, 3.01 and 1.53 D.U. for GOME2-A, GOME2-B and OMI respectively.

New remote sensing satellite sensors for the measurements of atmospheric radiation offer the advantage of very high spectral resolution and spectral and/or spatial and temporal coverage. The analysis of these measurements often requires a forward model (FM) for the simulation of the radiation collected by the sensor. The FM should model all the processes affecting the radiance, such as absorption and scattering by molecules and particles. 

Despite the advancement in sensor technology, the radiative transfer solvers are almost the same since several decades. Among these, the DISORT solver is still one of the most widely used. The DISORT code was developed 30 years ago, and while the code is maintained and updated regularly, the improvements are more geared towards new features than to a revision of the original setup. While the implementation was the best possible at the time, the memory constrains and language limitations of the time are nowadays considerably changed. On the other hand there is still the need of NRT retrievals, and the computing time of the multiple scattering needed in cloudy sky conditions is still the bottleneck of the FM calculation. Thus, we needed an improvement of the execution time of the DISORT algorithm. We modified the DISORT algorithm in three directions:

Language improvements. In particular, making use of dynamical assignment and modularity of modern fortran reduces execution time. 

Algorithm improvements. For instance, by approaching the delta-m transformation on a per-layer basis, many computations can be saved, expecially when the cloud pattern does not cover all the atmospheric range.

Numerical analysis improvements. While these improvements do not shorten the computational time, they improve the precision of the solution of the eigenvalue sub-problems that arises in the multiple scattering calculations.

The modifications in the DISORT solver produce an improvement in calculation performances of a factor 3 with respect to the original version. 

The FORUM instrument, selected for phase A of ESA Earth Explorer 9, samples the Earth atmosphere between 70 and 1600 cm-1 to investigate the Long Wave energy flux in FIR spectral region. The new version of DISORT solver has been used to model FORUM spectra, as well as limb sounding measurements in presence of clouds. Here we report the comparison of limb and FORUM spectra obtained with the two DISORT versions.

Almost one year ago, in October 2017, the Sentinel 5 Precursor (S5P) mission was launched, carrying the Tropospheric Monitoring Instrument, TROPOMI. The new instrument provides a daily global coverage, has a swath width of 2600 km and covers bands in ultraviolet and visible (270–495 nm), near infrared (675–775 nm) and shortwave infrared (2305–2385 nm) at a spatial resolution as high as 7 km x 3.5 km. As such, TROPOMI extends the atmospheric composition record initiated with GOME/ERS-2 in 1996 and continued with the SCIAMACHY/ENVISAT, OMI/AURA and the two GOME-2/MetOp missions, until at least 2024, measuring atmospheric constituents including ozone, NO₂, SO₂, CO, CH₄, HCHO and aerosol properties. The S5P mission is expected to bring up significant new components to the scientific knowledge of atmospheric processes, and it will have a significantly positive impact on the monitoring of the global atmospheric composition and the related sources and sinks.

Due to the ongoing need to understand and monitor the recovery of the ozone layer, as well as the evolution of the tropospheric pollution, total ozone will remain one of the leading species of interest during this mission as well. The Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki, Greece, is the co-ordinator of the TROPOMI’s Total Ozone Column Validation (VALTOZ) team and in this work we present the validation results of almost one year of TROPOMI NRT and offline data against ground-based quality-assured Brewer and Dobson total ozone column (TOC) measurements deposited in the World Ozone and Ultraviolet Radiation Data Center (WOUDC) and the European Brewer Network (EUBREWNET). Additionally, comparisons to Brewer measurements from the Canadian Network are performed, as well as to twilight zenith-sky measurements obtained with ZSL-DOAS (Zenith Scattered Light Differential Optical Absorption Spectroscopy) instruments, that form part of the SAOZ network (Système d'Analyse par Observation Zénitale) of the Network for the Detection of Atmospheric Composition Change (NDACC). Through the comparison of the TROPOMI measurements to the total ozone ground-based measurements from stations that are distributed globally, as the background truth, the dependence of the new instrument on latitude, cloud properties, solar zenith and viewing angles, among others, is examined and the results are presented and commented. Preliminary validation results show that the mean and the standard deviation of the percentage difference between TROPOMI and QA ground TOC is within 3.5 – 5% and 1.6 – 2.5 %, respectively, which are the limits set in the ESA’s official “Sentinel-5P Level 2 Product Requirements”.

About 60% of the total NOx emission into the atmosphere is estimated to be due to fossil fuel combustion and other anthropogenic activities. Rest days induce therefore a weekly cycle in NO₂ concentrations, with low week-end values observed both by ground-based measurements, and by spaceborne NO₂ data (Beirle et al. 2003).

Here we use tropospheric NO₂ column observations from the OMI sensor over 2005-2017 provided by the recently released QA4ECV product (Boersma et al. 2017). This retrieval incorporates recent advances in differential optical absorption spectroscopy, and leads to smaller slant column uncertainties than previous retrievals, although systematic fitting errors are not completely removed (Zara et al 2018). Tropospheric NO₂ columns are calculated by using data assimilation and TM5-MP model profiles at 1^ox1^o so that hotspot gradients are better resolved. The OMI columns are averaged for each day of the week and each year between 2005 and 2017 for every city of more than 700,000 inhabitants according to the GeoNames database, using data lying within a 40 km radius of the city. The calculation is performed per season, for summer (June, July and August) and winter (December, January and February) months. Scenes with cloud fraction higher that 20% and surface albedo higher than 30% are excluded from the analysis.

Evidence of a rest day in the weekly cycle, i.e. a day with significantly lower NO₂ column, is found in 131 cities in summertime, of which 22 are in the US, 21 in Europe, 16 in Japan, 11 in South Korea, and 10 in the Middle East. In line with previous studies which considered a more limited number of cities, we find a marked Sunday minimum in many (North and South) American, European, Australian and Japanese cities, with NO₂ columns being between 10% and 50% lower on Sunday compared to weekdays. The analysis indicates a Friday minimum of the NO₂ columns by 10-20% in Muslim cities in the Middle East and a Saturday minimum of 20% in Jerusalem. In Africa, Russia, India and China, no significant weekly cycle is observed. Similar results are found in winter, but the number of cities exhibiting a significant minimum is much lower (69). Based on  these observations, we will further evaluate the weekly cycle variation assumed in models by performing sensitivity simulations with the MAGRITTE model over North America and different hypotheses for the weekly cycle of anthropogenic NOx emissions.   

The TROPspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (Sentinel-5P) is the first of the Atmospheric Composition Sentinels by the European Space Agency (ESA) that provides measurements of ozone, NO₂, SO₂, CH₄, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions. The early afternoon orbit of Sentinel-5P mission provides a strong synergy with the U.S. Suomi National Polar-orbiting Partnership (S-NPP) satellite, especially in that the S-NPP Ozone Monitoring and Profiling Suite (OMPS) facilitates high vertically resolved stratospheric and lower mesospheric ozone profiles.

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) supports over a thousand data collections in the Focus Areas of Atmospheric Composition, Water & Energy Cycles, and Climate Variability and it is the Distributed Active Archive Center (DAAC) that is curating both offline Sentinel-5P TROPOMI and S-NPP OMPS Level-1B (L1B) and Level-2 (L2) products. Through its convenient and enhanced tools/services such as OPeNDAP and L2 Subsetting, GES DISC offers air quality remote sensing user communities facile solutions for complex Earth science data and applications.

This presentation will demonstrate TROPOMI and OMPS products including earthview radiance, solar irradiance, and currently available L2 datasets, as well as easy ways to access, visualize and subset data. The implementation of the End User License Agreement (EULA) between NASA GES DISC and all data users accessing data at GES DISC will be emphasized as well.

The preservation and valorisation of Earth Observation (EO) data assets has gained importance in Space Agencies’ programs, alongside the development of new and innovative research missions. The Fundamental Data Record for Atmospheric Composition (FDR4ATMOS) project is part of the ESA Long Term Data Preservation (LTDP+) Programme aimed at the generation of long-term records of calibrated and quality-controlled EO data. Following the successful ERS-2 and ENVISAT mission operations and data exploitation, the FDR4ATMOS project shall revisit the long-standing series of historical satellite observations from the atmospheric composition sensors GOME, MIPAS and SCIAMACHY, and build long-term data records (Level 1) applying recalibration for the individual systems, but also inter-satellite calibration. The resulting decadal-scale EO-based data records will contribute improving the performance of the ESA historical data series and ensure continuity towards current and future missions. Fundamental Earth System Data Records enhance the potential of building the necessary base for reliable science applications, even climate monitoring, extending beyond the limits of the individual datasets and allowing the generation of products of augmented accuracy and length where a quantified evidence of the environmental variability over long periods of time, including climatic trends, can be detected. This paper aims at presenting the objectives of the ESA FDR4ATMOS project, expected to be issued as an ESA Invitation To Tender (ITT) at the end of 2018.

BIRA-IASB has the responsibility of developing the SO₂ retrieval algorithm for the Sentinel 5 (S5) UVN prototype processor. While the retrieval of SO₂ vertical columns is similar as for TROPOMI/S5P (Theys et al., 2017), the S5 SO2 algorithm also includes an additional module to derive an effective SO₂ layer height (LH) which is activated for enhanced SO₂ vertical columns (typically >25 DU).

In this paper, we introduce the algorithm, which is based on an iterative SO₂ optical depth fitting procedure. Although it makes use of a large look-up-table (of SO₂ optical depth spectra), the scheme is adequately fast for an operational environment. We demonstrate the technique based on synthetic spectra and apply the algorithm to OMI and TROPOMI for a number of volcanic eruptions. Results are compared to other satellite datasets, such as CALIOP attenuated backscattered profiles and SO₂ height estimates from MLS and IASI. In general, we find an excellent agreement with differences on the retrieved height of less than 1-2 km. The results for TROPOMI are discussed in more details because SO₂ plume height data derived at high spatial resolution can provide added-value information on the eruption chronology. Plans for future work, including the possible implementation of a near-real-time SO₂ plume height algorithm in the Support to Aviation Control Service (SACS), are addressed.

N. Theys, I. De Smedt, H. Yu, T. Danckaert, J. van Gent,C. Hörmann, T. Wagner, P. Hedelt, H. Bauer, F. Romahn, M. Pedergnana, D. Loyola, M. Van Roozendael :Sulfur dioxide operational retrievals from TROPOMI onboard Sentinel-5 Precursor: Algorithm Theoretical Basis, Atmos. Meas. Tech., 10, 119-153, doi:10.5194/amt-10-119-2017, 2017.

MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), a limb-viewing infrared interferometer, operated on-board the ENVISAT satellite from 2002 to 2012. In the past years a huge effort was performed in correcting the time dependent non-linear response of its detectors, in order to produce calibrated measurements stable in time. The new calibration strategy has been implemented into the latest version (V8) of the Level 1 processor. Also the Level 2 (L2) processor has been upgraded, the main improvements being the handling of horizontal gradients and the use of an upgraded spectroscopic database. Both new processors have been used to generate three Diagnostic Datasets. The new L2 datasets contain the vertical distributions of Temperature and the VMR of H₂O, O₃, HNO₃, CH₄, N₂O, NO₂, CFC-11, CFC-12, N₂O₅, ClONO₂, HCFC-22, COF₂, CF₄, HCN, CCl₄, OCS, CH₃Cl, HDO, C₂H₂, C₂H₆, and COCl₂.

For each month of MIPAS lifetime, the data have been averaged in latitudinal bins at fixed pressure levels, and for each level, trends have been estimated using the same method described in Valeri et al. (2017). In this paper we will show some examples of the estimated trends, concentrating on reactive molecules like phosgene.

Valeri, M., Barbara, F., Boone, C., Ceccherini, S., Gai, M., Maucher, G., Raspollini, P., Ridolfi, M., Sgheri, L., Wetzel, G., and Zoppetti, N.: CCl₄ distribution derived from MIPAS ESA v7 data: intercomparisons, trend, and lifetime estimation, Atmos. Chem. Phys., 17, 10143-10162, https://doi.org/10.5194/acp-17-10143-2017, 2017

Within the S5P Validation Team, the NIDFORVal project (S5P NItrogen Dioxide and FORmaldehyde VALidation using NDACC and complementary FTIR and UV-Vis DOAS ground-based remote sensing data) aims at assessing the quality of nitrogen dioxide (NO₂) and formaldehyde (HCHO) operational S5P products. Both Fourier Transform Infrared (FTIR) and UV-Visible Differential Optical Absorption Spectroscopy (UV-Vis DOAS) are recognized as independent techniques which can routinely provide total NO₂ (DirectSun DOAS), tropospheric NO₂ (Multi-AXis (MAX-) DOAS), and HCHO total column (FTIR and MAXDOAS) reference data sets for the long-term validation of satellite observations.

High-quality measurements from over 60 ground-based stations and 80 instruments will be gathered over the whole S5P mission timeline (10/2017-2023) from NDACC and other complementary networks, covering a large range of observation conditions including high, mid, and low latitudes, as well as remote, sub-urban, and urban polluted sites. About 50 stations were operational with data submission in rapid delivery mode during the commissioning and pre-operational phase and about 25 UV-vis DOAS stations were involved in the validation of the first TROPOMI total and tropospheric NO₂ column operational products released last June_. Data from 16 FTIR sites and 13 UV-vis stations were also used for the preliminary validation of the HCHO S5P vertical columns. The level of agreement varies from station to station, but globally and for both products, comparison results show negative biases (i.e. TROPOMI smaller than ground-based) which are within the accuracy requirements (50% for NO₂ and 40-80% for HCHO).

Updates of NO₂ and HCHO comparison results will be reported in this presentation, as well as the validation plan for the routine operations phase during which large TROPOMI data records will be accumulated.

We present our first results in the Level1-2 processing of carbon monoxide (CO) total columns from Sentinel-5P (S5P) Short-Wave Infrared (SWIR) observations. The retrievals will be performed using the Beer Infrared Retrieval (BIRRA). BIRRA performs a least squares fit of Earth’s radiance (essentially transmission) to retrieve the molecular column densities (essentially density scaling factors) along with some auxiliary parameters (reflectivity etc.) [Gimeno Garcia et al., AMT 2011]. It has been developed at DLR since about 2005 and its computational core modules have been integrated in the operational SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) L1b-2 processor to retrieve CO from channel 8 (2.3 microns) and methane from channel 6 (1.6 microns) nadir observations. In the framework of DLR's SCIAMACHY activities BIRRA CO columns have been thoroughly examined in several intercomparisons [e.g. Hochstaffl et al., Remote Sens.\ 2018]. The forward model of BIRRA is essentially based on the GARLIC (Generic Atmospheric Radiation Line-by-line Infrared Code, Schreier et al. 2014) which has also been thoroughly verified and validated in numerous studies [Schreier et al., JQSRT 2018; Schreier et al., Molec. Astrophysics 2018].

In this study we will use the latest version of the BIRRA prototype featuring new enhancements  such as advanced line shapes accounting for line mixing and speed dependence. An updated  framework is providing appropriate auxiliary information (e.g. latest molecular spectroscopy data, a priori atmospheric profiles of pressure, temperature, and concentrations of interfering species,  topography, ...).  
Finally, for diagnostic analysis we will consider the residual norms, residual spectra, the distribution of errors of the state vector elements, and comparisons with other data products. More specifically, we intend to estimate the quality of the product in view of the accuracy requirements defined in the mission preparation phase (i.e. 15% for CO) using NDACC (Network for the Detection of Atmospheric Composition Change) or TCCON (Total Carbon Column Observing Network) ground-based observations.

During the last four years the ESA Sensor Performance, Products and Algorithms (SPPA) section
invested significant resources in setting-up an atmospheric probing super-site in the area of Rome, named "Boundary-layer Air Quality-analysis Using Network of Instruments" (BAQUNIN) infrastructure. Atmospheric physics and remote sensing experts of Sapienza University, CNR-IIA and CNR-ISAC, who are in charge of hosting and operating the instrumentations at their premises,
are supported and coordinated by SERCO team for what concerns instrument maintenance, data analysis, and specific satellite Cal/Val needs.
In BAQUNIN, the ground based active and passive remote sensing instruments are operating in synergy, in both a urban context (University of Rome Sapienza), and in rural (CNR-IIA) and semi-rural (CNR-ISAC) environments. This instrumental set-up allows for the acquisition of qualitative and quantitative information for a wide range of atmospheric parameters such as trace gases and aerosols. The list of the BAQUNIN instrumentation comprises:
- LIDAR Raman+elastic+depolarisation (aerosols, H2O, clouds),
- SODAR (wind profiles in PBL)
- MFRSR radiometer (aerosols, O3 ,H2O),
- POM 01 L Prede sun-sky radiometer (aerosols, H2O, http://www.euroskyrad.net/)
- Brewer spectrophotometer (O3, SO2, NO2, http://www.eubrewnet.org/cost1207/)
- Pandora Spectrometers (O3, NO2, H2O, HCOH, SO2, aerosols, http://pandonia.net/)
- CIMEL photometer (aerosols, H2O, https://aeronet.gsfc.nasa.gov/new_web/index.html)
- YES broad-band UV radiometer
- Pyranometer
- All-sky camera (clouds, potentially aerosols)
- EM 27 FTIR Spectrometer (greenhouse gases)
- Meteo-station (air pressure, temperature and relative humidity)

The passive instruments are operated continuously, with the exception of the FTIR spectrometer,
only activated for short term campaigns, and of the LIDAR, which is operated on demand, typically
in correspondence of satellite overpasses (when close to nadir looking),
or in occurrence of particularly significant phenomena, such as Saharan dust events.
Geophysical products from all instruments are harmonised in terms of content (naming conventions, units), underpass a quality screening and are stored in NetCDF-CF format.
To complement the instrumental suite, the Weather Research and Forecasting (WRF) Model,
installed and running at ESRIN, is operated on a daily basis at very high spatial resolution (1km),
providing atmospheric dynamic forecasts for trajectory calculations and allowing
a more thorough analysis of the acquired BAQUNIN data.
The products acquired during BAQUNIN lifetime will be made available to the scientific community,
and will actively contribute to the validation of the aerosol and tropospheric trace gases satellite estimates produced by the Copernicus Sentinel-5p, Sentinel-4 and Sentinel-5, by EarthCare and Aeolus, and by the ESA Third Party Missions (TPM), such as the Ozone Monitoring Experiment (OMI).
In this contribution we describe in details the BAQUNIN set-up and data production/flow, along with recent S5p validation results.

The TROPOspheric Monitoring Instrument (TROPOMI) has been launched on October 13, 2017, aboard the polar orbiting platform Sentinel-5 Precursor (S5p). TROPOMI measures the Earth's radiance in the ultraviolet, visible, near and short-wave infrared spectral ranges with an unprecedented spatial resolution of 7x3.5km², providing important information on natural and anthropogenic emissions of trace gases and aerosols. Although currently not part of the suite of operational products, glyoxal tropospheric columns can be retrieved from TROPOMI measurements in the visible spectral range. Such retrievals remain challenging owing to the low glyoxal optical depths but offer the potential to provide additional quantitative information on VOC emissions.

The BIRA-IASB glyoxal algorithm, successfully applied in the past to GOME-2A/B and OMI, has been transferred to TROPOMI and we present here results of its application to one year of measurements. Based on comparisons with OMI retrievals, we illustrate the benefit of the excellent TROPOMI spatial resolution and signal-to-noise ratio to better identify and characterize the sources of this tropospheric trace gas. As part of the Sentinel-5 level-2 prototype processor development, we revisit the impact of uncertainties on water vapor absorption, a major interfering species for glyoxal retrieval. Verification activities involving the independent scientific algorithm developed at University of Bremen are finally presented using both synthetic and real S5p spectra.

Observation of the chemical composition of the atmosphere is an important study area of atmospheric research that has led to the development of various instruments that provide as precise information as possible about the concentration of pollutants in the atmosphere. In this paper, an intercomparison of different instruments for measurement of CO, CH4 and NO2 concentration was carried out. Continuous measurements of these pollutants were recorded during in situ campaign in Magurele town, in July 2017. The CO and CH4 concentrations measurements were accomplished using an analyzer based on the cavity ring-down spectroscopy (CRDS) technique and were compared to those measured by the ambient carbon monoxide (CO) monitor using the non-dispersive infrared analysis method as its operating principle, respectively, the ambient hydrocarbon (HC) monitor based on the selective combustion method and hydrogen flame ionization method. For the NO2 concentrations, the measurements from Optical absorption CAPS  (Cavity attenuated phase-shift spectroscopy technique) NO2 analyzer and an ambient nitrogen oxide monitor using the chemiluminescence (CLD) method as its operating principle were inter-compared. The results obtained  using these techniques are comparable, strong correlation coefficient were obtained.

ACE-FTS, the Atmospheric Chemistry Experiment - Fourier Transform Spectrometer onboard the Canadian Earth observation satellite "SciSat" is recording solar occultation spectra for about fifteen years. Five infrared atmospheric atlases for arctic summer and winter, midlatitude summer and winter, and the tropics and 31 limb rays (6 - 128 km) have been created by co-adding hundreds of cloud-free infrared spectra (2.2 - 13.3 mue) (Hughes et al., JQSRT 2014). These spectra provide a unique opportunity for model validation and to study the impact of individual molecules, spectral resolution, molecular spectroscopy data (HITRAN, GEISA, continua, etc.), and auxiliary data. Here we use GARLIC - Generic Atmospheric Radiative Transfer Line-by-Line Infrared Code (Schreier et al., JQSRT 2014) and compare observed and modeled "effective height spectra" obtained by integrating (summming) the entire limb sequence. This kind of spectra are typically used for remote sensing of (exo-)planetary atmospheres by transit spectroscopy, where only disk-averaged observations are possible.

The Earth effective height spectrum varies between a few kilometers (in atmospheric window regions) and about 50 km in the CO2 v2 and v3 bands with small variations due to season and latitude. The largest impact on the transit spectra is due to water, carbon dioxide, ozone, methane, nitrous oxide, nitrogen, nitric acid, oxygen, and some chlorofluorocarbons (CFC11 and CFC12). The effect of further molecules considered in the modeling is either marginal or absent. The impact of spectroscopic input data on the model spectra is small. The best matching model with 17 molecules absorbing has a mean residuum of 0.4 km and a maximum difference of 2 km to the measured effective height.

The ESA Atmospheric Validation Data Centre (EVDC) serves as a central, long-term repository for archiving and exchange of correlative data for validation of atmospheric composition products from satellite platforms.  The EVDC builds on the previous ENVISAT Cal/Val database system in operation at NILU since the early 2000s and provides tools for extraction, conversion and archival. The objective of the current ESA funded project lead by Skytek [1] with the partnership of NILU [2] and ICHEC [3], is to provide an online information system that supports users in managing and exploiting campaign datasets for Earth Observation missions and applications.

Through the web portal https://evdc.esa.int users can access to a large variety of data from campaigns, in-situ ground-based measurements, aircraft, balloons and, in general, from a wide range of stations and measurements principles for validation of the satellite atmospheric composition products. An important aspect for the Cal/Val data is the standardization of the format to enhance the usability of correlative data and ensure an extensive quality control. With this aim the portal offers numerous conversion tools and specific support for conversion to the GEOMS format [4].

EVDC provides, moreover, access to satellite Level-2 products for specific missions in particular Sentinel-5P and ADM-AEOLUS. Some new features and tools are available online via the EVDC portal e.g: the Orbit Predictor Overpass Tool (OPOT) and the Sub-Setting tool. The OPOT is based on the  TLEs (Two-Line Element set) [5] and uses the Simplified General Perturbation Model (SGP4) [6] to predict and store their future orbits. Given a location or a region of interest (defined as a polygon) the OPOT produces a list of overpasses for that region and satellite for a future time range. The Sub-Setting facility uses the HARP toolkit [7] as its backbone. Users searching for Sentinel-5P data, can choose to perform a sub-setting operation on the file instead of downloading the entire file, moreover the data extraction can be scheduled specifying location(s), temporal window, distance from spatial reference through a systematic service which make the data package available once the service job is completed.

References

[1] Skytek http://www.skytek.com/; info@skytek.com

[2] NILU Norwegian Institute for Air Research. http://www.nilu.no/; nadirteam@nilu.no.

[3] ICHEC  Irish Centre for High-End Computing. https://www.ichec.ie/

[4] GEOMS documentation: http://evdc.esa.int/documentation/geoms/

[5] Two Line Element set format: https://www.celestrak.com/NORAD/documentation/tle-fmt.php

[6] Models for Propagation of NORAD Element Sets. F. R. Hoots R. L. Roehrich 1980. https://www.celestrak.com/NORAD/documentation/spacetrk.pdf

[7] HARP documentation: https://cdn.rawgit.com/stcorp/harp/master/doc/html/index.html

Carbon dioxide (CO₂) and methane (CH₄) are important atmospheric greenhouse gases (GHG) and, therefore, classified as Essential Climate Variables (ECVs). Previously, satellite-derived atmospheric CO₂ and CH₄ ECV data sets have been generated and made available via the GHG-CCI project of the European Space Agency’s (ESA) Climate Change Initiative (CCI, http://www.esa-ghg-cci.org/). The latest GHG-CCI data set, Climate Research Data Package No. 4 (CRDP 4), covers the time period 2003-2015 and was made available in February 2017. Currently, the production and provision of these data sets is being continued operationally via the Copernicus Climate Change Service (C3S, https://climate.copernicus.eu/), which is implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission. The C3S satellite greenhouse gas (GHG) sub-project (C3S_312a_Lot6) is led by University of Bremen supported by University of Leicester (UK), SRON (The Netherlands) and CNRS-LMD (France). The first Climate Data Record (CDR) data set produced and delivered within the C3S framework covers the period 2003-2016 and consists of column-average dry-air mole fraction CO₂ and CH₄ products, i.e., XCO₂ and XCH₄, from SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT.  In addition, mid-tropospheric CO₂ and CH₄ mixing ratios from IASI Metop-A and Metop-B are part of this data set and mid-tropospheric CO₂ from AIRS. These data products have been made publicly available in mid 2018 via the C3S Climate Data Store (CDS, https://cds.climate.copernicus.eu/) and the data products are regularly updated. This new Earth Observation data set will reviewed in the presentation.

Outdoor air pollution is a major environmental health risk, particularly in urban areas. Nitrogen dioxide (NO₂) is one of the primary air pollutants and is harmful to human health and ecosystems. NO₂ monitoring is crucial for tackling the problem of air pollution and enforcing compliance with air quality regulations. This is done at a global scale using satellite instruments, which traditionally use the well-established Differential Optical Absorption Spectroscopy (DOAS) technique.

DOAS retrievals of NO₂ are commonly done using high-resolution spectral information – usually hundreds of channels. This requires the use of complex hardware and provides limited spatial and temporal resolutions. Even recent developments struggle to resolve NO₂ features at sub-urban scales and provide only one measurement per day at any given location.

In the work presented here a novel approach for NO₂ retrievals in the visible range of the spectrum is evaluated for the advancement of the High-resolution Anthropogenic Pollution Imager (HAPI) instrument concept. One of the ways to reduce data volumes and increase spatial resolution is to reduce the amount of spectral information used in the retrieval (< 20 channels). Moreover, the use of fewer channels allows for simpler, cheaper instrument designs that could be deployed in constellations of small satellites, which in turn would allow for lower revisit times. The HAPI instrument concept, developed by the Air Quality group at the University of Leicester (UK), is based on these premises and thus has the potential to retrieve NO₂ from space at unprecedented spatial and temporal resolution.

Discrete-wavelength DOAS retrievals are challenging due to NO₂ being a weak absorber and the limited spectral information available. However, previous work using synthetic data suggests that they are possible provided there is a good signal-to-noise ratio. In the work presented here discrete-wavelength DOAS-like retrievals of NO₂ are further evaluated using new synthetic data and real data from existing hyperspectral satellite instruments. Different instrumental and retrieval parameters and algorithms are considered. A sensitivity analysis of the retrieval results is conducted with the aim of finding the optimal configuration for the HAPI instrument concept.

   Precise knowledge of the location and height of the volcanic sulfur dioxide (SO₂) plume is essential for accurate determination of SO₂ emitted by volcanic eruptions. Current UV based SO2 plume height retrieval algorithms are very time-consuming and therefore not suitable for near-real-time applications. Here we present a novel method called the Full-Physics Inverse Learning Machine (FP-ILM) algorithm for extremely fast and accurate retrieval of the SO₂ plume and apply it to the pre-operational Sentinel-5 Precursor (S5P). S5P was launched on October 13, 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI), which has a spatial resolution of 7x3.5 km², hence providing an unprecedented level of details.
    In this presentation, we introduce the FP-ILM algorithm, which is based on dimensionality reduction techniques and machine learning. We show the first results obtained with the FP-ILM algorithm applied to a selection of volcanic SO₂ eruptions detected by TROPOMI and compare them to other plume height datasets available. The sensitivity of the plume height retrieval to various parameters is analyzed as well.

Tropical and subtropical ecosystems play an important role in the global carbon cycle. The African tropics and subtropics is the most dynamic region of the world with respect to terrestrial carbon flux variability and population growth, which imposes direct carbon emissions and perturbations to the natural ecosystems. The underlying mechanisms such as photosynthesis, respiration, natural and man-made biomass burning, as well as fossil fuel related emissions vary on sub-daily timescales. The forcing by meteorological and climatic factors imposes a fingerprint being variable on the seasonal and inter-annual time-scale. Event-wise emissions such as caused by agricultural burning blend with episodic change in land-use practices and permanent ecosystem degradation. Thus, gaining insights into the functioning of African tropical and subtropical carbon cycling and into its sensitivity to environmental variability and perturbations needs observations from the sub-daily to the seasonal to the year-to-year time-scale. However, the African continent is poorly sampled by current and planned atmospheric observation systems. Establishing a dense and robust ground-based network is logistically challenging. Satellite observations from low-Earth-orbit (LEO) are limited to a single local overpass time per day and, they are frequently cloudy.

The Middle East and Europe are major global players in fossil fuel extraction and usage, respectively. Leakage of carbon gases has been reported throughout the extracting-processing-transportation-consumption chain. Satellite observations from LEO will become progressively available as part of envisioned surveillance concepts. These LEO sensors, however, do not capture characteristic diurnal variations of fluxes, potentially resulting in biased emission estimates and lacking the ability to discriminate between man-made and biospheric flux signals.

The AbsoRption spectRometric patHfindEr for carboN regIonal flUx dynamicS (ARRHENIUS) is a proposed mission concept that will overcome the sampling gaps in the tropics and subtropics and on the sub-daily time scale by adopting a process-focused sampling strategy from geostationary orbit (GEO). For selectable focus regions, ARRHENIUS will deliver quasi-contiguous maps of atmospheric carbon species concentrations (carbon dioxide (CO₂), methane (CH₄), and carbon monoxide (CO)) and a photosynthesis process marker (solar induced plant fluorescence (SIF)) with sub-daily, seasonal, and year-to-year coverage. These observations will be used by top-down inverse atmospheric models and by bottom-up biosphere and land-surface models to inform on regional carbon cycle processes. Being process focused instead of surveillance driven, ARRHENIUS will pioneer a flexible and intelligent sampling approach with short lead times for pointing adjustments. Sampling will be flexible with regard to focus region selection, region extent (typically 1300x2400 km²), dwell times (typically 1h) and the number of revisits per day (up to 5 times per day), per season and per year. Sampling will be intelligent by actively avoiding regions which are expected cloudy based on observations of meteorological sounders (such as Meteosat Third Generation) from adjacent orbits. Small footprint sizes (2x2 km² at sub-satellite) and flexible day-time observation hours will further support cloud avoidance.

Infrared observations of the Earth’s limb by the MIPAS instrument on Envisat have contributed a unique data record to study physical and chemical processes in the atmosphere between 2002 and 2012. MIPAS spectra contain the information to infer accurate vertical profiles of air pressure, temperature and volume mixing ratio of more than 20 trace gases from cloud top well into the mesosphere. Over the past few years the chain of ESA's operational Level-1b and Level-2 processors was further developed and it now entered a phase of comprehensive testing and validation by the MIPAS Quality Working Group. This upgraded MIPAS chain is labelled V8 and it includes, e.g., (a) updated spectroscopic data, (b) revised non-linearity coefficients and an improved pointing correction model (Level-1b), and, (c) the handling of horizontal inhomogeneities in the retrieval of geophysical quantities (Level-2). Such changes potentially have an important impact on the quality of the Level-2 data products: their bias, precision or long-term stability, and their dependence on geophysical parameters.

Here, we present the results of a delta-validation study of the altitude registration and of five primary MIPAS Level-2 data products (temperature, O3, HNO3, CH4 and N2O). Our analyses are based on comparisons of ~10% of the MIPAS data record to co-located ground-based observations by ozonesonde, temperature and ozone lidar, microwave radiometer and FTIR instruments operating within monitoring networks contributing to WMO's Global Atmospheric Watch (GAW), such as the Network for the Detection of Atmospheric Composition Change (NDACC) and the Southern Hemisphere ADditional OZonesonde programme (SHADOZ). We performed comprehensive studies of the structure of MIPAS bias and short-term variability in the spatial (vertical, latitudinal) and in the temporal domain at various scales. Estimates of these quality indicators on the partial data record have proven in the past to be reliable and they reflect what is later on obtained once the entire mission is reprocessed. These first results for the upcoming V8 reprocessing are then compared to those obtained for earlier MIPAS processor chains in order to verify whether the Level-2 data quality evolves according to expectations.

Carbon monoxide (CO) is an important atmospheric constituent affecting air quality and methane (CH₄) is the second most important greenhouse gas contributing to human-induced climate change. Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution.

The TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5P, which was successfully launched in October 2017, is a spaceborne nadir viewing imaging spectrometer covering wavelength bands between the ultraviolet (UV) and the shortwave infrared (SWIR). It combines daily global coverage with a high spatial resolution of 7×7 km² .

Abundances of atmospheric CO and CH₄ can be retrieved from TROPOMI’s radiance measurements in the 2.3 μm spectral range of the shortwave infrared part of the solar spectrum. Here we present first results for both trace gases obtained using the scientific retrieval algorithm WFM-DOAS.

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.

Understanding the micro-physical processes that take place in clouds requires the knowledge of improved size distribution of the cloud droplets. To this purpose, in situ measurements using the Cloud Aerosol Spectrometers (CAS) prove to be very useful tools if some procedural clarifications are made. This paper proposes to fix some problems of size estimation from CAS outputs. The measuring principle of the instrument is based on analysing the forward single scattering of light by cloud particles. The estimation of size droplet is possible through conversion of the scattering cross section by droplet in particle diameter through the Mie formalism. Any droplet between 0.5-50 µm, which is the size range of the instrument, will have a scattering cross section that is a function of diameter. The Mie theory is used to estimate the theoretical curve used to correlate the droplet size with scattering cross section. An important hurdle is that the computed diagram is not smooth and for many values of scattering cross section can correspond 2 or 3 diameters. In this situation, the size range (0.5-50 µm) of the CAS will be divided in smaller size intervals, called bins in the literature. To generate these bins, an important issue is the number of diameters used to evaluate the scattering cross section (N_d). As this number increases, the curve that makes the conversion between scattering cross section and diameter becomes noisier and severely affects (usually decreases) the number of bins that can be generated.  The method was applied on a data set of a CAS instrument, recorded during a flight with a Beechcraft C90 GTx in a water cloud in the southern part of Romania. We expect that the method can be extended to other particle types like ice crystals and aerosol. 

The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO₂ which are needed for the retrieval of tropospheric columns from satellite observations. STREAM does not require input from chemical transport models, but is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. It was developed as verification algorithm for TROPOMI, as complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artefacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO₂, e.g. related to the polar vortex, and reduces interpolation errors over continents.

Upcoming geostationary measurements do not cover remote oceans, which so far were a significant contributor to the stratospheric estimate. Instead, the stratospheric estimate has to rely on measurements in remote continental regions as well as over cloudy scenes. As geostationary satellites will provide multiple measurements per day, the number of suitable clouded measurements will be far higher than for the instruments used so far on low orbit.

Here we investigate how far STREAM can be applied to the upcoming geostationary Sentinel-4 mission, and which modifications of the algorithm are necessary. The analysis is based on synthetic NO₂ slant column densities, which have been calculated within the Sentinel-4 verification project, using the chemical transport models TM5 and Lotos-Euros and the radiative transfer model SCIATRAN.

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) is a scanning nadir and limb spectrometer covering the wavelength range from 212 nm to 2386 nm in 8 channels. It is a joint project of Germany, the Netherlands and Belgium and was launched in February 2002 on the ENVISAT platform. After the platform failure in April 2012, SCIAMACHY is now in the postprocessing phase F. Its originally specified in-orbit lifetime was double the planned lifetime. SCIAMACHY was designed to measure column densities and vertical profiles of trace gas species in the mesosphere, in the stratosphere and in the troposphere (Bovensmann et al., 1999). It can detect a large amount of atmospheric gases (e.g. O3 , H2CO, CHOCHO, SO2 , BrO, OClO, NO2 , H2O, CO, CH4 ,  among others ) and can provide information about aerosols and clouds.
The operational processing of SCIAMACHY  is split into Level 0-1 processing (essentially providing calibrated radiances) and Level 1-2 processing providing geophysical products.
The operational Level 0-1 processor has been completely re-coded and embedded in a newly developed framework that speeds up processing considerably. In the frame of the SCIAMACHY Quality Working Group activities, ESA is continuing the improvement of the archived data sets. Version 9 of the Level 0-1 processor includes

An updated degradation correction

Improvements to the polarisation correction algorithm

Improvements to the geolocation by a better pointing characterisation

Several improvements in  the SWIR spectral range like a better dark correction, an improved dead & bad pixel characterisation and an improved spectral calibration

The new format for the Level 1b and Level 1c will be netCDF V4. We will present the verification results and the results of the mission re-processing.

The Sentinel-4 (S4) mission focuses on monitoring of trace gas column densities and aerosols over Europe at high spatial resolution with an hourly revisit time, thereby covering the diurnal variation of atmospheric constituents.

In this article we present the Level 2 (L2) products being developed in the framework of the ESA S4-L2 project: O₃ total and tropospheric column, NO₂ total and tropospheric column, SO₂, HCHO, CHOCHO columns, aerosol and cloud properties as well as surface reflectance.

The S4-L2 work comprises the development of bread-boarding algorithms, independent verification algorithms, prototype processors and ultimately the operational S4-L2 processors for the generation of state-of-science operational data products.

Tropospheric NO₂ is an anthropogenic pollutant characterized by a variety of important roles in atmospheric chemistry. It is mainly emitted by combustion processes associated to traffic, industrial activity and domestic heating. NO₂ is generally seen as a proxy of air pollution, as it is one of the most significant precursors of photochemical ozone production (O₃) and nitric acid (HNO₃). For this reason, its continuous monitoring is of major importance. One technique, which has been widely used, is the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) technique in order to extract simultaneous measurements of atmospheric trace gases and their vertical distribution in the troposphere. Using this technique, many species can be measured and one among them is the nitrogen dioxide.

In the present study, MAX-DOAS measurements from the BIRA-IASB research grade spectrometer operated in Uccle (Brussels, Belgium) are used to develop and demonstrate new approaches for investigating the vertical and horizontal spatial distributions of NO₂ under moderate to high pollution conditions, such as encountered in Brussels and its suburban area. More precisely, the BIRA-IASB MAX-DOAS was set to operate two different modes: a vertical scan composed by 11 elevation angles in a fixed azimuth angle and an azimuthal scan (15 azimuth angles) at a constant elevation angle. The new measurement schedule allows us the retrieval of 3-D NO₂ distributions.

A four-step retrieval has been used at two different wavelengths (based on Sinreich et al., 2013; Ortega et al., 2015) in order to describe the spatial and temporal concentration gradients of NO₂ and to identify the most important emission source areas in and around  Brussels. This will be complemented by car-DOAS measurements with the BIRA AEROMOBIL, and in-situ observations from the air quality telemetric network of Brussels that will be jointly exploited to study the horizontal and vertical distribution of tropospheric NO₂. Finally, the retrieved NO₂  is being compared with the TROPOMI satellite observations in order to support the validation of the satellite.

Chlorophyll fluorescence is the re-emittance of solar radiation at higher wavelengths by vegetation. It originates from the internal processes in leaves during photosynthesis. Since a few years, it has been shown by several researchers that sun-induced fluorescence (SIF) can be retrieved from satellite spectrometers measuring in the near-infrared, from about 640-780 nm. This fluorescence information is useful to constrain the actual photosynthesis rate of the global vegetation. Since there is a close connection between photosynthesis and gross primary production (GPP) of vegetation, SIF measurements may help to better quantify and understand the uptake of CO2 by the terrestrial biosphere.

The SIF retrieval algorithm that we use at KNMI for GOME-2 is based on the work by Joiner et al. (AMT, 2013) was adapted by Sanders et al. (AMT, 2016). The GOME-2 instrument has a good spectral coverage and resolution but a relatively large pixel size of 40x80 km2. Based on simulated top-of-atmosphere spectra with a known fluorescence signal we have performed sensitivity studies of SIF retrievals. This led to several algorithm improvements. Recent results of application of our SIF algorithm to GOME-2 data shows a better correlation with other space-born vegetation products. Especially the fluorescence signals of tropical forests are better captured. Also the improved retrieval algorithm is able to pick up regional reductions in fluorescence which coincide with severe drought events. Currently, in the EUMETSAT Satellite Application Facility on Atmospheric Composition Monitoring we are working towards operationalizing this SIF retrieval for GOME-2 on the MetOp-A/B/C satellite series.

The new TROPOMI instrument on the Sentinel-5P satellite, launched in October 2017, also has a near-infrared channel capable of measuring SIF. Because of its daily global coverage and high spatial resolution of 3.5x7 km2, i.e. more than two orders of magnitude better than GOME-2, a TROPOMI SIF product would be very useful for the global carbon modeling community and would provide insight in local carbon fluxes . TROPOMI would be bridging the gap in spatial resolution between GOME-2 and the FLEX mission, which is the ESA Earth Explorer mission planned for 2022, having a resolution of 300 m. Here we will present our plans for adapting the SIF algorithm for TROPOMI and first experiments.

The retrieval of vertical columns of trace gases such as NO₂ and SO₂ from satellites, aircraft or high-altitude platform stations (HAPS) requires air mass factors (AMF) to convert the fitted slant columns to vertical columns. AMFs can be calculated from vertically resolved AMFs (box-AMFs) with a radiative transfer model assuming horizontal homogeneity of surface reflectance, aerosols and trace gases.

However, the assumption of horizontal homogeneity is not necessarily valid where surface reflectance, aerosols and trace gases have a high spatial variability, for example, over cities. To study the effects of horizontal inhomogeneity on the AMFs and the retrieved trace gases, we implemented three-dimensional (3D) box-AMFs in the Mystic solver of the libRadtran radiative transfer model. The model output also provides the photon path-lengths in each box which is an intermediate result to calculate the box-AMFs and can be used for different scientific purposes (e.g. studies of impacts of aerosols on the incoming radiation). The implementation was tested by computing 3D box-AMFs for a spectrometer on an aircraft (6 km above surface), a high-altitude platform (20 km) and a satellite (700 km). We compared the size and shape of the effective footprint by varying instrument viewing direction, solar zenith angle, surface albedo and aerosol optical depth.

The preliminary results of 3D box-AMFs simulations show reasonable values. The new aspect of 3D box-AMFs compared to 1D box-AMFs is the possibility of observing the 3D structure of the box-AMFs and so to say the photons 3D path. This gives a much better appreciation of the possible influence of horizontal inhomogeneous input parameters. The photon paths can be investigated with input parameters variations. Preliminary results show a larger scattering of the photons with higher aerosol optical thickness or slant viewing direction of the instrument. Therewith, the boxes on the photons path from Sun to the instrument, after being reflected on the ground, have low AMFs values. Setting low albedo (<0.1) also seems to lower the AMFs values of these boxes and therefore suggests more important scattering.

In conclusion, 3D Box-AMFs implementation in Mystic allowed us to study the effects of changing input parameters on box-AMFs, in particular on their 3D shape and therefore to get sensitive to the possible influence of horizontal inhomogeneity on these box-AMFs.

We present the GOME-type Ozone Profile Essential Climate Variable (GOP-ECV) data record that has been compiled from five ultra-violet nadir-viewing satellite sensors GOME/ERS-2, SCIAMACHY/ENVISAT, GOME-2/MetOp-A, GOME-2/MetOp-B, and OMI/AURA. It consists of monthly mean profiles provided on a 5°x10° (latitude x longitude) grid and covers the 22-year period from 1995 to 2017. Level-2 ozone profiles are derived from the individual sensors using the Rutherford Appleton Laboratory (RAL) optimal estimation retrieval scheme, which is a three-step sequential approach. At first, a fit to the sun-normalized radiance in the wavelength region 266-307nm (Hartley band) is performed which yields information on the mid-to-upper stratosphere ozone profile. The second step is the retrieval of an effective surface albedo at 366nm. Both the ozone profile from step one and the albedo from step two contribute to the prior information for the last step, which is a fit in the ozone Huggins bands (323-335nm) in order to obtain accurate information on tropospheric ozone. Before merging the individual time series into one cohesive long-term data record, they are carefully adjusted to match total ozone column amounts from the well-established GOME-type Total Ozone Essential Climate Variable (GTO-ECV) data record generated in the framework of the European Space Agency's Climate Change Initiative (ESA-CCI) ozone project. This procedure leads to reduced inter-sensor biases and drifts. The altitude-dependent scaling of the RAL ozone profiles according to the GTO-ECV total ozone columns is performed using novel machine learning techniques. We compare the new ozone profile data record with other correspondent satellite-based products and discuss perspectives for the estimation of height- and spatially-resolved long-term ozone trends.

The Sentinel-4 mission will be the first geostationary mission using an instrument with a large spectral coverage and moderate spectral resolution in UV-VIS-NIR spectral range for atmospheric composition monitoring on an hourly basis. While the algorithms for the L2 retrievals can build on heritage from previous missions (GOME-1/2, SCIAMACHY, OMI, and Sentinel-5P), the simulation and interpretation of the atmospheric radiative transfer is different compared to previous (polar orbiting) missions in many aspects. The challenges include e.g. limited spatial coverage, varying solar illumination during the day, effects of the BRF, varying stratospheric ozone absorption during the day, and varying cloud and aerosol scattering properties.

Herein we present the test data set (TDS) generated for the verification of the Sentinel-4 level-2 atmospheric monitoring products. In contrast to the previous missions (e.g. Sentinel-5P) that can use real data from similar polar-orbiting missions, the test data sets (TDS) for Sentinel-4 is obtained by synthetic radiative transfer simulations. In particular, RTM SCIATRAN is utilized, variability in atmospheric absorbers is prescribed by CTMs LOTOS-EUROS and TM5, and variable cloud and aerosol scenes are considered. In this way we comprehensively cover the new and specific observation geometries of Sentinel-4.

We present the L1 > L2 prototype algorithms for formaldehyde (HCHO) and sulphur dioxide (SO2) total column density that have been developed in the framework of the ESA S4-L2 project in preparation of the Sentinel-4 mission. Sentinel-4 is an operational satellite foreseen for launch in the early 2020’s. It will be the first mission to monitor trace gas column densities and aerosol over Europe from a geostationary perspective.

For HCHO the mission is of high interest as the hourly revisit time will allow to better study the diurnal variation of HCHO columns, which is for the moment poorly known.
For SO2,  it is expected that Sentinel-4 measurements will be able to detect low levels of anthropogenic SO2 and improve on the existing satellite data sets due to the combination of high spatial resolution (8x8 km²) and high temporal sampling (1 hour). These aspects are also of value in the monitoring of volcanic plumes.
In this paper, we will address the specific challenges posed to the algorithms for both trace gases when observing in a geostationary geometry and discuss the new developments and performance with respect to existing algorithms for polar orbiters.

A spectrally and spatially high-resolution nadir viewing UV instrument (UVN) will be on board Sentinel-5 (S5) to be launched in 2021. In preparation for the Sentinel-5 satellite mission, the operational (baseline) UVN ozone profile retrieval will be verified using our (IUP) retrieval algorithm.  The vertical ozone distribution in the stratosphere and troposphere is determined from the backscatter spectrum in the ultraviolet spectral range (270 nm - 335nm).  The IUP retrieval combines  optimal estimation and Tikhonov regularisation and consists of 2 steps: First, the use of the full spectral range to study the entire atmosphere and secondly a consecutive retrieval using only Huggins ozone band ( 322-335 nm) to further improve the tropospheric content similar to the operational algorithm.

For a first application, our adapted ozone profile retrieval has been applied to synthetic data sets using S5 instrument characteristics (spectral resolution, instrument noise). The quality of the IUP algorithm has been tested (uncertainty budget, vertical resolution) and are compared with previously developed algorithms and the operational algorithm. The retrieval error in the stratosphere is about 2% and can increase up to 10% in the troposphere depending on the selected scenario. To test the IUP algorithm, selected orbits from OMI (on AURA) were processed. The evaluation of two exemplary orbits demonstrate the applicability of the retrieval for particularly polluted scenarios and under ozone hole conditions. If feasible, ozone profiles from TROPOMI (on Sentinel-5P) for selected orbits are to be presented as well.

Ozone (O₃) is one of the most important trace gases in the air, mostly present in the stratosphere, where it is produced naturally, O₃ is vital for life on Earth because it protects life from the Sun’s UV radiation. On the other hand, anthropogenic emissions lead to the production of O₃ in the lower atmosphere. Around 10% of the total amount of O₃ is in the troposphere, where it acts also as a greenhouse gas. Overexposure to this pollutant can cause health problems and damage on vegetation. As an essential climate variable their global concentration and evolution is needed and can only be provided by satellite measurements. Global tropospheric ozone distribution can be derived using the limb-nadir matching technique (LNM), which subtracts the stratospheric column (derived from limb observations) from collocated total column (derived from nadir observations) to obtain the tropospheric column amount up to the tropopause.

SCIAMACHY (2002-2012) was the first instrument that combined both limb and nadir observations in a single instrument. OMPS/NPP (2012-present) has the same capability, which allows us to extend the LNM tropospheric ozone data timeseries. Here we present initial results on the total ozone column from OMPS nadir observations retrieved using the Weighting Function–DOAS (WFDOAS) approach. These data are intended to be combined with the IUP limb ozone data to obtain tropospheric ozone.

Surface-level ozone (O₃) is secondary air pollutant that is formed via UV-radiation driven chemical reactions from precursor gases such as nitrogen oxides (NOx) and volatile organic compounds (VOCs). High concentrations of surface-level O₃ impact detrimentally human health, agriculture, and ecosystems. Recently published Tropospheric Ozone Assessment Report (Schultz et al., 2017) revealed that e.g. in many parts of southern Europe, US and Asia unhealthy levels of ground-level ozone is observed regularly.

 In continental regions the formation of surface O₃ concentration depends highly on the availability of the two precursor gases, NOx and VOCs.  The production of O₃ can be either NOx or VOC limited. In the NOx-limited (or VOC -saturated) regime the O₃ formation is almost entirely controlled by NOx concentrations. In this regime the reduction of NOx emissions reduce the photolysis of NO₂ and thus the formation of O₃. On the other hand, in the VOC-limited (or NOx- saturated) regime reduced VOC emissions lead in turn to lower concentrations of ambient O₃.

To effectively mitigate the surface level O₃ pollution requires knowledge on which precursor, or both, is/are contributing most to the surface O₃ formation. The O3-NOx-VOC sensitivity can be analyzed by defining a VOC- to- NOx ratio, which indicates whether the O₃ formation process is NOx-or VOC-limited. From satellite observations the ratio can be obtained by using formaldehyde (HCHO) as a proxy for VOCs, and tropospheric NO₂ columns to characterize NOx (e.g. Jin et al. (2017) and Jin and Holloway (2015)). In this work we will study the spatial and temporal variations in O₃ sensitivity by using HCHO and NO₂ data from GOME-2 and OMI satellite instruments.  We will also analyze the variations in the O₃ production rate in NOx-limited regions by using the GOME-2 NO₂ photolysis product developed at the Finnish Meteorological Institute (Kujanpää and Kalakoski, 2015). Potential improvements of using high-resolution TROPOMI observations in this kind of application will be also discussed.

Jin, X., and T. Holloway (2015): Spatial and temporal variability of ozone sensitivity over China observed from the Ozone Monitoring Instrument, J. Geophys. Res. Atmos., 120, 7229–7246.

 Jin,X. et al. (2017): Evaluating a space-based indicator of surface ozone-NOx-VOC sensitivity over midlatitude source regions and application to decadal trends. Journal of Geophysical Research: Atmospheres, 122, 10,439–10,461.

 Kujanpää and Kalakoski (2015): Operational surface UV radiation product from GOME-2 and AVHRR/3 data, Atmos. Meas. Tech, 8, 4399–4414.

Schultz, M.G. et al. (2017): Tropospheric Ozone Assessment Report: Database and Metrics Data of Global Surface Ozone Observations, Elementa Sci. Anthrop, 244.

Accurate knowledge of solar variability on longer timescales is important for improving our understanding of their contribution to climate variability. SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY) on-board Envisat performed daily Sun observations for nearly a decade from 2002-2012 covering the UV-vis-NIR spectral range (212-1760 nm and two narrow bands from 1930-2040 nm and 2260-2380 nm).

Recent developments in the SCIAMACHY calibration (e.g. a physical model of the scanner unit including degradation effects and an on-ground to in-flight correction using the on-board white light source) are used to provide a new SCIAMACHY solar reference spectrum. Detailed comparisons with several other established solar reference spectra show good agreement to within 3 % for most parts of the visible and NIR spectral range from about 350 to 1500 nm.

Special emphasis was placed on the spectral region above 1500 nm. In the NIR the various SSI reference data do not agree within their confidence interval and this led to a controversial debate (e.g. Bolsee et al., 2014; Thuillier et al., 2015; Weber, 2015; Bolsee et al., 2016; Elsey et al., 2017; Gröbner et al., 2017). The re-calibration of SCIAMACHY SSI shows a deficit of 4-8 % with respect to the ATLAS-3 composite (Thuillier et al., 2004) and WHI (SORCE/SIM) reference spectrum (Woods et al., 2009). In contrast, SCIAMACHY matches very well (above 400 nm) the SOLAR-ISS (Meftah et al., 2018) and new ground-based measurements from Mauna Loa (Pereira et al., 2018). There is now increasing evidence that the ATLAS-3 composite seems to be high biased in the NIR.

The new SCIAMACHY solar reference spectrum is the first step towards a 10 years time series of solar spectral irradiance data. This presentation will also summarise the revised degradation correction scheme that is necessary to study SSI trends and variability on different time scales.

The operational XCO2 retrieval algorithm of NASA’s Orbiting Carbon Observatory 2 (OCO-2) satellite is based on an optimisation algorithm in which it is assumed that the posterior distribution of the retrieval problem is close to linear near the Maximum a Posteriri (MAP) estimate point, and hence the related uncertainty quantification is made using a multivariate normal distribution. It is, however, well known that the underlying problem is not Gaussian and the uncertainty quantification may be missleading. In this work we investigate the non-linearity and  identifiability of the model parameters in the OCO-2 retrieval. This is done using Markov Chain Monte Carlo (MCMC) methods to sample the full multidimensional posterior distribution. We focus on a surrogate forward model, which fits a state vector that consists of CO2 density profile, surface pressure, surface albedo and aerosol moment parameters. We implement a Likelihood Informed Subspace (LIS) dimension reduction scheme to the MCMC sampler in order to reduce the dimension of the problem and speed up convergence of the chain. The sampled MCMC chain represents the multidimensional posterior distribution, which is analysed in detail.

Air quality mapping plays an important role in informing the public about air pollution levels as well as in the assesment of air quality in areas not covered by measuring stations. For this purpose various data sources can be utilized, in particular in-situ measurements, air quality models and satellite data. Within the scope of the ESA funded project SAMIRA (SAtellite based Monitoring Initiative for Regional Air quality) we have been testing data fusion techiques that combine these data sources to provide more accurate information within air quality mapping.

Here we present results obtained with the newly available Sentinel-5P/TROPOMI satellite data. We have applied the developed data fusion techniques (multiple linear regression followed by interpolation of residuals) to create NO₂ air quality maps over the region of the Czech Republic. Apart from the Sentinel-5P/TROPOMI data, we have used in-situ measurements from the air quality database of the Czech Hydrometeorological Institute and the chemical transport model CAMx.

The preliminary results show that the Sentinel-5P/TROPOMI can improve the bias of the maps as compared to mapping done using in-situ and model data only. We will also evaluate the results against maps created with OMI data to assess the the different impacts of the two instruments.

The atmospheric concentration of CO₂ and CH₄ have been defined as Essential Climate Variables (ECV) by the WMO, meaning that they are crucial to our understanding of the Earth’s climate. Satellite observations have provided global coverage which are essential to constraining surface flux estimates and forecasting long-term emission trends. The goal of the ESA GHG-CCI and EU Copernicus C3S programmes is the retrieval, validation, and provision of these datasets to the wider scientific and non-scientific community. As part of these projects, the University of Leicester (UoL) Earth Observation Science group have applied the UoL retrieval algorithms to retrieve the dry-air CO₂ (XCO₂) and CH₄ (XCH₄) column mole fractions from near-infrared spectra measured by the JAXA Greenhouse Gases Observing Satellite (GOSAT) to generate global, long-term (2009-2017) datasets..

The UoL ‘full-physics’ retrieval algorithm is a state-of-the-art retrieval based on the Optimal Estimation method. One key feature of the algorithm is that a priori information for aerosols is sourced from data from near real-time forecasts from the ECMWF MACC (now CAMS) aerosol model.

To evaluate the quality of the retrieved products, we validate them against reference data from the terrestrial Total Carbon Column Observing Network (TCCON).

In this presentation, we will give an overview of recent retrieval algorithm developments and the generated CO₂ and CH₄ ECV datasets. We will discuss their assessment against TCCON observations and comparisons with model calculations, and present plans to expand our algorithm to process data from the new generation of high spatial resolution satellite missions, such as Sentinel 5-P and OCO-2.

Water vapour is an essential climate variable. Thus it is important to generate consistent long term records of the atmospheric water vapour content for the ongoing monitoring and analysis of climate change on earth. We present first results from a DOAS retrieval of total column water vapour (TCWV) in the blue wavelength region (420-470 nm). While the optical depth of water vapour in this retrieval window is much lower than that in other frequently used retrieval windows, the blue window offers a few distinct advantages. The most important reason to choose this window, is that it is covered by many recent and upcoming satellite instruments including GOME, SCIAMACHY, GOME-2, OMI, TROPOMI and the upcoming Sentinel-4 and Sentinel-5 missions. Thus the blue retrieval window is very well suited to create long term records tailored for climate research, because the same algorithm can be used for a variety of instruments. This approach reduces the probability for algorithm dependent bias in the product derived for one mission. We present first results obtained with the DOAS approach in the blue wavelength region using TROPOMI data. The results of selected datasets are validated against reference data acquired by radiosondes. Furthermore a comparison to ECMWF model data will be performed. Additionally we show a comparison of results obtained with the proposed retrieval in the blue wavelength region with results from the operational GOME-2 TCWV product derived in the red region of the visible spectrum (610- 690 nm) within the scope of our AC-SAF work.  

In this presentation, we discuss the inversion algorithm for retrievals of high vertical resolution temperature profiles using bi-chromatic stellar scintillation measurements in the occultation geometry. This retrieval algorithm has been improved and applied to the measurements by Global Ozone Monitoring by Occultation of Stars (GOMOS) operated on board Envisat in 2002-2012. The retrieval method exploits the chromatic refraction in the Earth atmosphere. The bi-chromatic scintillations allow the determination of refractive angle, which is proportional to the time delay between the photometer signals. The paper discusses the basic principle and detailed inversion algorithm for reconstruction of high resolution density, pressure and temperature profiles (HRTP) in the stratosphere from scintillation measurements. The HRTP profiles are retrieved with very good vertical resolution ~200 m and high accuracy ~1-3 K for altitudes 15-32 km and a global coverage. The best accuracy is achieved in vertical (in orbital plane) occultations, and the accuracy weakly depends on star brightness. The whole GOMOS dataset has been processed with the improved HRTP inversion algorithm using the FMI’s Scientific Processor; and the dataset (HRTP FSP v1) is in open access.

              The validation of small-scale fluctuations in the retrieved HRTP profiles is performed via comparison of vertical wavenumber spectra of temperature fluctuations in HRTP and in collocated radiosonde data. We found that the spectral features of temperature fluctuations are very similar in HRTP and collocated radiosonde temperature profiles.

HRTP can be assimilated into atmospheric models, used in studies of stratospheric clouds and in analysis of internal gravity waves activity. As an example of geophysical applications, gravity wave potential energy has been estimated using the HRTP dataset. The obtained spatio-temporal distributions of gravity wave energy are in good agreement with the previous analyses using other measurements.

Active volcanoes are characterized by emitting gas and ash in atmosphere and during eruption the rate increase and can be detectable by satellite sensors. Depending on the size of eruption the volcanic emission can reach the stratosphere and in the troposphere they affect population leaving around volcanic area. In the case of the large Kilauea eruption in Hawaiian Big Inland starting in May 2018 a contextually eruption by 24 lateral fissures and by the summit occurred. In this work we shows the capability in Sentinel 2 and Sentinel 3 to follow the complex Kilauea eruption, detecting the gas and ash plume at the summit and in the ocean entry and mapping the active lava flow. We also retrieve the lava flow field by using Landsat 8 data and to compare it with the Sentinel 2 retrieved one.

Surface solar radiation products derived from polar orbiting satellite measurements
provide a global mapping of solar radiation at the Earth’s surface. These products
are very useful for solar resource assessments because of its global coverage and
consistency. We have developed an operational surface solar irradiance product for
SCIAMACHY and OMI satellite spectrometers. The SCIAMACHY overpass time was in the
morning at about 10.00 LT (2002-2012), while the OMI overpass time is in the afternoon
close to 13:30 LT (2004-). Recently we combined the SCIAMACHY and OMI solar radiation
products and made the daily mean monthly mean surface solar radiation
products at 0.25 degree x 0.25 degree (latitude x longitude) grid. The daily mean
monthly mean surface solar radiation is often used in solar energy models.
The SCIAMACHY and OMI daily orbit SSI products have been evaluated using the
Baseline Surface Radiation Network (BSRN) measurements. The daily mean month mean
surface solar radiation data have been compared with CERES monthly mean product and
validated using the BSRN measurements. The algorithm can also be applied to
GOME-2 (morning orbit) and OMI/TROPOMI (afternoon orbit). In this presentation we
will explain the algorithm and show some examples of the products.

An algorithm for the retrieval of the aerosol optical depth over land (ADL) using radiances at the top of the atmosphere (TOA) measured by the Advanced Very High Resolution Radiometer (AVHRR) is proposed. AVHRR is the only satellite sensor providing nearly continuous global coverage since June 1979, which could generate the longest aerosol climate data records currently available from operational satellites. In the implementation of the ADL algorithm, an analytical model is used which couples an atmospheric radiative transfer model and a land surface reflectance parameterization. The radiation field can be separated into three parts: direct radiance, single-scattered radiance, and multiple-scattered. Each of these parts is individually parameterized. To obtain the surface reflectance in an automatic retrieval procedure over land for AVHRR, the aerosol scattering effect at 3.75 μm was assumed to be negligible and relationships between the surface reflectances at 0.64 μm and 3.75 μm were evaluated for different surface types and the authors propose to use these to obtain the surface reflectance at the shorter wavelength. The 0.64 μm surface reflectance was then used in a radiative transfer model to compute AOD at that wavelength using six different aerosol types, where optimal estimation (OE) theory is applied to minimize the difference between modeled and measured radiances. The ADL algorithm is applied to re-calibrated Level 1B radiances from the AVHRRs on-board the TIROS-N and the Metop-B satellites to retrieve the AOD over North China and Central Europe. The results show that the AOD retrieved from these two instruments are in agreement with co-located AOD values from ground-based reference networks. Over North China, using AERONET sites, 58% of the ADL AOD values are within an expected error (EE) range of ±(0.05 + 20%) and 53% are within the EE range of ±(0.05 + 15%). For GAW-PFR (World Meteorological Organization, WMO, Global Atmosphere Watch, GAW) sites, part of the European ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure) sites, 79% of the ADL AOD values are within the EE range of ±(0.05 + 20%) and 75% are within the EE range of ±(0.05 + 15%). Not surprisingly, the agreement is better over Europe with generally lower AOD values. An additional cross comparison of the AOD results with MODIS (MODerate-resolution Imaging Spectroradiometer) DeepBlue aerosol products shows that the spatial distributions of the two AOD datasets are similar, but with generally lower values for ADL and lower coverage. The temporal variation of the annual mean AOD over selected AERONET sites shows that ADL values are generally between 0.2 and 0.5 over North-Eastern China and trace the MODIS and AERONET data for the overlapping years quite well.

The simultaneous retrieval of aerosol and trace gases from satellite instruments may suffer from the fact that multiple species are scattering and/or absorbing in the same spectral range. It is especially the case with the Global Ozone Monitoring by Occultation of Stars (GOMOS) mission, where the use of stellar occultation implies a reduced signal-to-noise ratio which makes even more difficult the distinction between the contributions of the different species.

In the framework of EXPANSION, an ESA Living Planet Fellowship project, we explored the performance of the AerGOM retrieval algorithm for the observation of several species (O₃, NO₂, NO₃ and aerosols, and preliminary work for O₂ and H₂O) from the upper troposphere to the mesosphere using the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument. AerGOM was initially developed to improve the aerosol extinction coefficient retrieval from GOMOS, more particularly its spectral dependence, but can also be used for the simultaneous retrieval of these gas species, and it is the purpose of EXPANSION to contribute to a better understanding of the way the different gases and aerosols interfere in, and contribute to the retrieval, and to use this knowledge to improve the retrieval for all species.

This presentation will show some of the results obtained in the EXPANSION project, more specifically how various retrieval parameters affect the trace gas inversion. We shall show how trace gases retrievals have been improved through, among other things, a refinement of the absorption cross-sections. A study of the mean residuals also highlight the need for the inclusion of more species to correctly model the GOMOS transmittance and as a result, preliminary work on O₂ forward will be presented.

Abstract: One of the most studied topics with respect to atmospheric pollution is the emission of trace gases. Recent developments in air borne remote sensing determinations of atmospheric constituents are based on UV/visible absorption measurements of scattered light at different elevation angles in addition to the traditional zenith-sky pointing. Thus, a newly instrument SWING (Small Whiskbroom Imager for atmospheric compositioN monitorinG), that employs on airborne MAX-DOAS (Multi AXis Differential Optical Absorption Spectroscopy) configuration, is used for data retrieval from an Unmanned Aerial Vehicle. Spectra recorded are being analyzed with the Differential Optical Absorption Spectroscopy (DOAS) method. This paper aims to determine the slant column densities (SCDs) and vertical column density (VCDs) of NO₂ (Nitrogen Dioxide) and H₂CO (Formaldehyde) during five days of measurements (10-14 September 2018) in a sub-urban area (Strejnicu, Romania). For this data spectra were recorded from a static position (at ground level with SWING mounted on a tripod) and at different altitudes with the instrument mounted on a UAV), the flights being performed in the morning and in the afternoon. These measurements contribute to the development of validation tools and expertise for air quality satellites in Romania.

Keywords: SWING, DOAS, atmospheric constituents, UAV platform.

ESA’s Envisat satellite has provided an important contribution to the global atmospheric composition monitoring from 2002 to 2012. The SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument is one of the three on-board passive remote sensing spectrometers that enabled measuring the abundance of a variety of trace gases and parameters, including reactive and greenhouse gases. Envisat operations currently reside in post-flight Phase F, and the product evolution cycle implemented by ESA with the support of the SCIAMACHY Quality Working Group has reached the stage of data reprocessing and validation. In the independent data quality assessment and validation, the uncertainties and geophysical consistency of the data must be assessed for the wider range of atmospheric states and over the relevant spatial domain, vertical range, and mission lifetime. Every upgrade of the data products and associated data processors must moreover be verified through delta-validation studies of the expected improvement. The outcome of these delta-validation studies provides valuable feedback to the respective data retrieval teams.

This work reports on the quality assessment of the evolution of operational SCIAMACHY L2 data products that include the nadir-observed vertical column of O₃, NO₂, BrO, CO, CH₄, and H₂O, and the limb profile measurement of O₃ and BrO. Validation analyses are based on comparisons to co-located ground-based observations by ozonesonde, lidar, DOAS spectrometers, FTIR instruments, and microwave radiometers operating within the Network for the Detection of Atmospheric Composition Change (NDACC), WMO's Global Atmospheric Watch (GAW) and the Southern Hemisphere ADditional OZonesonde programme (SHADOZ). These networks provide well-characterized data records of different atmospheric constituents with appropriate accuracy and spatio-temporal sampling and resolution properties. Correlative studies yield estimates of the SCIAMACHY bias, spread, long-term stability, and their dependence on geophysical parameters.

The focus of this validation exercise is on the latest SGP V7 processor full mission data and its improvement with respect to previous operational products. It is verified whether the quality of the V7 data is similar to that of the previous SGP V6.01 and V5.02 processors for all studied products, as suggested by a delta-validation study on a diagnostic dataset of selected orbits. The delta-validation pointed to vertical oscillations (order of a few percent) in the V7-V6 difference limb ozone profiles, and a 20-40 % decrease in the V7 nadir methane columns with respect to V6, related to the changes in the V9 Level-1 processor. In this work these results are being reconsidered by validation of the complete SGP V7 reprocessing. For other products and quality indicators no degradation is expected, but not a substantial improvement either.

Ships emit large quantities of nitrogen oxides  (NOx) into the marine boundary layer, and with ship bound international transport volume strongly  increasing over the last two decades, the relevance of these emissions has as well. The signature of ship emissions has been picked up in tropospheric NO2 maps derived from measurements of the GOME, SCIAMACHY, GOME2, and OMI instruments. However, detection of shipping NOx in these data sets is mostly limited to the main shipping routes and to averages over months and even years. The TROPOMI instrument, recently launched on the Sentinel-5 precursor satellite, has the potential to improve on this situation owing to its better spatial resolution and excellent signal to noise ratio. In this study, a first qualitative assessment is given of the shipping signals detected in the first months of S5p data, using both the operational and the University of Bremen S5p NO2 data.

The presence of clouds strongly affects the retrieval of trace gas columns and concentrations from S5P TROPOMI spectral measurements. The near-simultaneous observation of cloud properties by S5P TROPOMI and NPP-VIIRS allows trace gas product providers to properly take these clouds into account.

The Validation Data Analysis Facility (VDAF) of the Sentinel-5p Mission Performance Centre (MPC) aims at providing a routine TROPOMI validation service to ESA, Level-2 data developers, Copernicus services and other data users. It builds upon the heritage of two decades of geophysical validation applications for UV-Vis nadir-viewing instruments (GOME, SCIAMACHY, OMI, GOME-2) and on recent advances in Cal/Val practices and operational validation systems. The VDAF ingests Fiducial Reference Measurements (FRM) archived at ESA’s Validation Data Centre (EVDC) and collected from high-quality ground-based monitoring networks (GAW GO3OS, EARLINET, NDACC, TCCON...), and it compares them to TROPOMI data following community-endorsed protocols. After 9 months of commissioning, the system is now in the routine operations phase.

The S5P-TROPOMI L2_CLOUD product was first released in July 2018, with TROPOMI cloud products starting in November 2017. In this contribution, we present operational validation results of two L2_CLOUD geophysical variables: (i) the cloud top height (CTH), obtained by the S5P OCRA/ROCINN-CAL algorithm, and (ii) cloud height (CH), obtained by the S5P OCRA/ROCINN-CRB algorithm. Both NRTI and OFFL data streams (v1.0.0 and higher), are considered. As it is used in the retrieval of several trace gas data products, the unofficial S5P cloud product L2_FRESCO (v1.0.1 and higher) is also considered in the analysis.

The S5P CLOUD CTH and CH are compared with cloud top height and cloud middle height obtained/derived from the cloud target classification product from the CLOUDNET ground-based network (http://www.cloud-net.org/), itself based on a combination of lidar and radar measurements. The criteria for co-location are motivated, and comparison results are presented, including an analysis of dependences on influence quantities such as cloud fraction, cloud optical thickness, ice/liquid classification, etc. These studies show that S5P ROCINN-CAL CTH and ROCINN-CRB CH values are mostly below the CLOUDNET CTH and CH observations.  We find strong correlations (R>0.8) between S5P products and CLOUDNET measurements. Finally, the agreement with the mission requirements for cloud height (systematic error < 20%, random error < 0.5 km or 30 hPa) is verified, taking into consideration that the measured quantities of S5P cloud product on one hand and CLOUDNET on the other hand have not exactly the same meaning. We conclude that the degree of agreement does differ for low clouds vs. high clouds.

Atmospheric nitrogen dioxide (NO₂), formaldehyde (HCHO) and carbon monoxide (CO) play a key role as precursors to several Essential Climate Variables (ECVs) as well as in air quality. In the framework of the European Commission EO programme Copernicus, Climate Data Records (CDRs), established from satellite measurements, are collected and distributed among a wide set of users through the Copernicus Climate Change Service (C3S) coordinated by ECMWF. Here we report on a comprehensive quality assessment of three ECV-precursor CDRs generated in the H2020 QA4ECV project by KNMI, BIRA-IASB and ULB, respectively: QA4ECV NO₂ from OMI, QA4ECV HCHO from OMI, and IASI-A FORLI CO. First results from S5P TROPOMI are also considered.

The quality assessment of the satellite CDRs is performed with the Multi-TASTE versatile validation system developed at BIRA-IASB, recently enhanced with updates from the FP7 QA4ECV and H2020 GAIA-CLIM projects. Its backbone is a generic validation protocol, virtually applicable to all atmospheric ECVs, that builds on the heritage of several BELSPO/PRODEX, EC, ESA and EUMETSAT projects. This protocol outputs a wide range of quality indicators enabling potential users to verify the fitness of the data records for their own purpose. The QA/validation protocol is currently implemented in two validation servers, both accessible online: (i) the QA4ECV-AVS (the QA4ECV Atmospheric ECV Validation Server), and (ii) the MPC-VDAF-AVS (the automated Validation Data Analysis Facility in charge of Sentinel-5p Mission Performance Centre routine validation).

The study relies on reference measurements acquired by ground-based DOAS and FTIR instruments at several sites of the Network for the Detection of Atmospheric Composition Change (NDACC). Interpretation of the data comparisons is not straightforward due to the interference of satellite data errors, reference measurement errors, and comparison errors caused by differences in temporal/spatial/vertical sampling and smoothing of natural variability. Therefore, a comprehensive uncertainty budget is established, coupling the detailed ex-ante uncertainty components provided with the satellite and ground-based data products to estimates of the co-location mismatch errors. The latter are assessed using the model-based OSSSMOSE observation system simulator, and also with empirical data-driven methods.

Significant negative biases and occasionally high comparison spreads are found in the direct comparison of OMI QA4ECV tropospheric NO2 columns with MAXDOAS data, the amplitude of which depends on season and on measurement site. Using the uncertainty budgeting approach described above, we try to attribute the observed discrepancies to a combination of comparison errors (co-location and resolution mismatch) and errors in satellite and/or reference measurement. For the so-derived measurement errors, we verify whether these are compatible with the reported ex-ante uncertainties.

The paper presents an overview of the design study and current developments for an airborne multi-wavelength HSRL system, to be installed on board of a Hawker Beechcraft King Air C90-GTx aircraft under the second phase of project implementation. The system is meant to deliver the aerosol extinction, backscatter and depolarization profile distributions in IR, VIS and UV spectral range for the ESA Cal/Val activities. Interferometer based filtering technique is identified to be a feasible approach for UV and IR range, while for VIS, the Iodine cell approach was concluded to be most reliable. The work is carried out and financed by the ESA project Multiply, 4000112373/14/NL/CT

Recent years have seen strong activity on determining stratospheric ozone trends in order to find signs of recovery. Some weak positive signs have been detected, but also signs of continuing ozone loss. Satellites are needed to make sound judgments about global trends but trend analysis is still hampered by the short time coverage of measurements. Therefore, new combined and harmonised time series have been constructed that provide better basis for analysis.  The analysis of trends is largely based on the use of classical regression approach. The regressors most often used are annual and semi-annual harmonics and proxies for solar UV-radiation, Quasi-Biennial Oscillation and El Nino Southern Oscillation. Trends are retrieved assuming a linear or a piecewise linear trend model. 

One alternative to the linear regression is the so-called Dynamic Linear Model (DLM). This model allows the contributions of regressors and trend change at each time step. For ozone trend analysis, this approach was first used by Laine et al. (2014). In this work, we continue this analysis by using the new merged SAGE II, Ozone_cci and OMPS ozone profile dataset (Sofieva et al., 2017). We will provide ozone trends with several time resolutions and study how the prior assumptions of the proxy variables affect the ozone trends.

Atmospheric satellite observations from missions such as Aeolus and Sentinel-5 Precursor are ideally suited to provide information on global and regional scales. However, due the spatial resolution of the instruments and the orbit characteristics of the satellite itself, they have only limited capability to provide long-term diurnal information on urban and local scale. This information, however, is essential for the understanding of important atmospheric processes, for example related to atmospheric composition or small-scale dynamics, as well as to enhance services, such as for urban air quality or GHG emission monitoring.

A new class of observation platforms, High-Altitude Pseudo-Satellites (HAPS), is currently emerging, bridging the gab between ground based, aircraft or balloon measurements and space-borne systems. HAPS are unmanned airborne platforms in the lower stratosphere at 20 km altitude or higher allowing station keeping above a fixed location or area for extended periods of up to several months. A number of industrial HAPS developments for both airplanes (heavier-than-air) and airships (lighter-than-air) are on-going and first promising results have been achieved, such as the 25 days flight of the Airbus Zephyr HAPS system in summer 2018, the longest duration flight ever. HAPS payload capacities are diverse depending on the technology chosen and range from 5 kg to 250 kg. Miniaturized Earth observation instruments, e.g., for microsatellites, have been proposed and partially demonstrated for various applications comply with the weight and power requirements of HAPS. 

In the frame of ESA’s HAPS4ESA symposium in October 2017 and other consultations, the atmospheric science and application domain has shown great interest in exploiting this emerging technology. In addition to the potential long-term atmospheric observation of a specific target area, HAPS are ideally suited to support the development of new space-borne instruments by flying technology demonstrations in conditions similar to space and for targeted calibration and validation activities of new and established satellite missions. A wide range of atmospheric remote sensing instruments has been proposed for HAPS with some already existing. In addition, the science community was already active in proposing specific case studies, ranging from meteorological applications to Air Quality and GHG activities. In response, ESA has issued an open call for project proposals that aim to identify HAPS mission concepts in support of Air Quality and GHG monitoring complementing the space-borne and ground based observation capabilities in Spring 2018. 

The paper will provide an overview on HAPS technologies, their relation to ESA’s atmospheric satellite mission and how HAPS can generally support the atmospheric science community as a whole.

Bora is cold and gusty downslope wind with variable gust frequency and duration, appearing on the lee side of Dinaric Alps. Its flow characteristics are unique and theoretically still not fully described, especially for modeling purposes. We present an analysis of the wind speed vertical profiles at Razdrto, which lies in a gap between the Nanos and Javorniki plateau in southwest Slovenia and is strongly exposed to Bora. An analysis of the vertical wind speed profiles during Bora episodes is based on experimental wind data, provided by Helikopter energija, for six Bora events of different duration, appearing between April 2010 and May 2011. Average wind speed in 10-minute intervals was collected at four different heights (20, 31, 40 and 41.7 m above the ground)at the wind turbine site in Razdrto using cup anemometers. Wind direction data with same temporal resolution was obtained from a single wind vane placed at 40.9 m above the ground. Based on the collected data, the applicability of the empirical power-law and the logarithmic law profiles, commonly used for the description of neutrally stratified atmosphere, was investigated for the case of Bora. The parameters for the power-law and logarithmic law were obtained by fitting the wind speed data using linear regression method and are compared to standard values for that particular type of terrain. The quality of fits was very good with r² above 0.9, indicating that both power-law and logarithmic law adequately describe mean horizontal Bora wind. The median value of the power-law coefficient was found to be 0.16±0.03, which is consistent with standard value for neutral atmosphere (0.143). The aerodynamic roughness varied from 0.003 m to 0.22 m with the median value of 0.09±0.07, which describes open level country terrain with some trees. The event in November 2010 with large roughness is expected to be due to specific wind direction and surface conditions.

Atmospheric ozone plays a key role in the radiation budget of the Earth, both directly and through its chemical influence on other trace gases.  Its corresponding importance in the context of climate change has led ESA and the European Commission to organize dedicated support for the development and provision of state-of-the-art ozone Climate Data Records (CDRs), more specifically in the context of the Climate Change Initiative (CCI) and of the Copernicus Climate Change Service (C3S) operated by ECMWF, respectively.

In view of the recent closure of Phase 2 of ESA’s Ozone_cci  and the successful start of operational provision of the corresponding O₃ CDRs to the Copernicus Climate Change Service (C3S 312a Lot 4), this contribution summarizes the ground-based validation of the O₃ CDRs produced hitherto. These include CDRs of total column and vertical profile data (in nadir and limb mode) at level 2, level 3 and level 4, from a multitude of satellite platforms, retrieval systems, and merging schemes.

The validation of these climate-oriented data records is based on multi-decade time series of reference measurements collected from monitoring networks contributing to WMO’s Global Atmosphere Watch, such as GO3OS, NDACC and NASA’s SHADOZ. Acquired following Standard Operation Procedures (SOPs), the reference measurements are quality controlled and harmonized, and compared to the various satellite CDRs in BIRA-IASB’s Multi-TASTE validation system following the latest state-of-the-art protocols and tools. Our studies focus in particular on the long-term stability of the satellite data series, which may exhibit drifts and other long term patterns reflecting, e.g., instrumental drift and degradation, residual biases between different instruments, and changes in sampling of atmospheric variability and patterns.

The comparison results document the achieved quality of the CDR’s developed in Ozone_cci and provided to the C3S, in particular in terms of temporal stability. For instance, the level-3 and level-4 merged total O₃ column products, covering up to four decades, are found to be stable w.r.t. the reference measurements at the 0.1%/decade level. Similarly, most nadir and limb profile CDRs achieve a level of stability consistent with that expected from instrument specifications. However, the requirements by climate users can be more stringent. More demanding targets may be reached with longer time series, the addition of new sensors and continued improvements in the data merging and trending schemes.

Several of these CDRs are therefore extended on a regular basis with additional observations (by e.g., GOME-2, IASI, OMI, OSIRIS, ACE-FTS and OMPS-LP). We describe how these operational streams of CDRs are validated accordingly in the context of the Copernicus Climate Change Service.

Total and tropospheric columns of ozone are two key observables for the recently launched Sentinel-5 Precursor TROPOMI , which enhances to high resolution the long-term monitoring of ozone as a tropospheric pollutant, a dynamical tracer, a UV radiation shield and a climate forcing agent. The total column is derived from the radiance spectra both with a DOAS approach (the NRT product), and a direct fitting method (GODFIT algorithm, the OFFL product). Tropospheric column and upper tropospheric partial column data are derived from total column data at equatorial latitudes using, respectively, a convective cloud differential algorithm and a cloud slicing scheme.

The Validation Data Analysis Facility (VDAF) of the Sentinel-5p Mission Performance Centre (MPC) aims at providing a routine TROPOMI validation service to ESA, Level-2 data developers, Copernicus services and other data users.  Supported jointly by ESA and Belspo/BIRA-IASB, it builds upon the heritage of two decades of geophysical validation applications for UV-Vis nadir-viewing instruments (GOME, SCIAMACHY, OMI, GOME-2) and on recent advances in Cal/Val practices and operational validation systems.  The VDAF ingests correlative ground-based measurements,  archived at ESA’s Validation Data Centre (EVDC) and collected from high-quality ground-based monitoring networks (GAW GO3OS, EARLINET, NDACC, TCCON...), and it compares them to TROPOMI data following community-endorsed protocols.  After 9 months of commissioning, the VDAF system has now started routine operation.

In this contribution, we look in detail at the operational validation of the total and tropospheric O₃ column products, covering both the near-real time (NRT) and offline (OFFL) data streams. The different sources of ground-based reference data are described, the criteria for co-location are motivated, and comparison results are presented for the different networks, including an analysis of dependences on key influence quantities and parameters such as latitude, solar zenith angle, cloud fraction, pixel size etc. These analyses reveal that the total O₃ column products (both NRT and OFFL) satisfy the mission requirements, in systematic (<5%) as well as random (<2.5%) errors, with no apparent dependences on influence quantities. First results of the validation of the recently released tropospheric column products are also presented and assessed against mission requirements. Lessons learnt from this first phase of routine VDAF operation are discussed and potential improvements and extensions of the VDAF system are proposed.

The scientific and industrial communities are being confronted with a strong increase of Earth Observation (EO) satellite missions and related data. This is in particular the case for the Atmospheric Sciences communities, with the already launched Copernicus Sentinel-5 Precursor and the upcoming Sentinel-4, -5 and -3B, and ESA’s Earth Explorers scientific satellites ADM-Aeolus and EarthCARE. The challenge is not only to manage the large volume of data generated by each mission / sensor, to manage their variety. Tools are needed to be able to rapidly and trustfully identify, from all available datasets of a specific region for a specific timeframe, all available products for a selected field (e.g. Ozone, trace gases) and prepare these data into a format that is ready to be extracted and used /analysed (Analysis-Ready Data, ARD). Creating synergies among the different datasets will be key to exploit the full potential of the available information. In summary, there is a need of an “intelligent” packaging of subsets of the available data tailored to the users´ needs.

The scope of the “Atmospheric Mission Data Packaging” (AMiDA) project is to design, implement and demonstrate the functionalities of an infrastructure for access and distribution of a wide variety of EO data in the field of Atmospheric Sciences: heritage, current, and future missions will be managed by the platform, to allow the users accessing, visualizing and downloading a meaningful subset of this growing data stream.

The main AMiDA platform will be based on the existing TAMP platform ([1], [2]) that already allows accessing and manipulating a large variety of satellite, model and ground measurements data. The platform will be empowered with an effective spatial and temporal homogenization module and packaging module, that will allow creating, from heterogeneous data sources (e.g. SO2 total column data different satellites and numerical models) a single data structure (data cube) that will permit simultaneous exploitation of the various data sources. A product descriptor will be associated to the result keeping track of all original products and related metadata, processing parameters and results metadata. The resulting data cube can be exploited in platform (web application, Jupyter notebook) as well as being downloaded by the user.

A comprehensive demonstration campaign will be performed through five main use cases to demonstrate the capability of AMiDA to improve the usability of various satellite, model and ground measurement data.

Since the project is on its early stage, the scope of the contribution is to present the initiative and discuss with potential users their needs that can be successively integrated within the platform.

Aerosol extinction profiles in the upper troposphere - lower stratosphere were retrieved from ground-based measurements of twilight sky brightnesses at 780 and 870 nm wavelengths. The measurements were carried out using a CCD-camera with a grating spectrometer. The retrieval algorithm was based on a fully spherical Monte Carlo radiative transfer code Siro used as a forward model. The measurements covered the period 2011-2018. The aerosol cloud passed above Georgia, South Caucasus in summer 2011 after the Nabro eruption (Eritrea) in June 2011 was observed. The measured enhancements of stratospheric extinctions in summer 2018 may be connected with the eruption of Klyuchevskoy (Russia) in May 2018.

The Sentinel-4 (S4) mission, the first imaging spectrometer instrument to be flown on Meteosat Third Generation Sounding (MTG-S) satellite in geostationary orbit, will provide accurate data on an hourly basis of trace gases and aerosols over Europe and Northern Africa for climate, air quality, ozone and surface UV applications. It features bands in the ultraviolet (305-400 nm), and visible (400-500 nm) with a spectral resolution of 0.5 nm and in the near-infrared (750-775 nm) ranges with a spectral resolution of 0.12 nm.

To provide simulated S4-UVN instrument data, we are working to prepare the Instrument Data Simulator (IDS). IDS is supposed to provide test data for the L1b Processor and provide capability for instrument performance and calibration monitoring. The IDS consists of two main blocks: the Scene Generator (SG) simulates the radiance/irradiance at the entrance of the instrument and the Instrument Simulator (IS) simulates the response of the instrument on the input signal. The S4-UVN IS follows as much as possible the instrument forward model and will be developed using a ’travelling spectrum’ approach. In this approach, the flux in the instrument or signal and noise is modified step-by-step by a series of algorithms representing the effects of the different components of the instrument on signal when flowing through the instrument. The IDS architecture and instrument forward model will be introduced.

In the framework of its Earth Observation Programmes the European Space Agency (ESA) carries out ground based and airborne campaigns to support geophysical algorithm developments, calibration/validation activities, simulation of future space-borne Earth Observation missions, as well as application developments related to atmosphere, land, oceans, solid Earth and cryosphere.

ESA has conducted over 150 airborne and ground based measurement campaigns in the last 37 years, of which more than 80 were carried out since 2005. During this period a number of campaigns have supported the preparation of ESA’s atmospheric satellite missions. While these campaigns aim to provide fundamental information to address specific topics related to technology or satellite developments, the resulting datasets are also made available to the atmospheric science community as a whole for research and development activities.

In recent years a number of campaigns have specifically addressed atmospheric dynamics and composition topics in preparation of the Aeolus and Sentinel-5 Precursor missions.

A series of campaigns have been supporting the development of the Aeolus Doppler Wind Lidar mission. Key for these activities is DLR’s A2D instrument, an airborne demonstrator for the ATLID satellite instrument on-board of the DLR Falcon aircraft. A2D is working with the same laser frequency and has a similar optical and electronic design as the space-borne instrument, which is ideal for supporting the development of the hardware, calibration procedures and retrieval algorithms. Already two campaigns have been completed: (1) The WindVal I was performed from Iceland in May 2015 as a joint ESA/DLR/NASA airborne campaign with a total of four airborne Doppler wind lidars. (2) WindVal II was conducted in September/October 2016 from Iceland with three research aircrafts and in the Mediterranean region. After the successful launch of Aeolus in August 2018, WindVal III is planned for November 2018, before in 2019 two calibration and validation campaigns over central Europe and Iceland, respectively, will be performed. An additional dedicated campaign in the tropics is planned for 2020 to specifically address the importance of Aeolus wind observations in this region. 

In support of the development for new atmospheric composition instruments, ESA has carried out the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaigns. This series of campaigns was implemented in Romania in September 2014, August 2015 and June 2016. In addition, the AROMAPEX campaign was carried out in Berlin in April 2016. Main target species were NO₂, SO₂, formaldehyde and aerosols measured in urban and industrial environments with the aim to support the preparation and validation of the atmospheric composition missions such as Copernicus Sentinel-5 Precursor, Sentinel-4 and Sentinel-5. Dedicated Sentinel-5 Precursor validation campaign activities are currently prepared for summer 2019 and beyond, building on the experience AROMAT and additional national and international projects. 

The WindVal, AROMAT and other atmospheric datasets together with their project descriptions are available from ESA’s Earth Observation Campaigns Data web site: https://earth.esa.int/campaigns. Future campaigns supporting ESA’s atmospheric mission will further enrich the campaign database providing scientist opportunities to enhance their research.

The summer of 2018 saw unusually high temperatures across much of the northern hemisphere as a result of a weak jet stream, resulting in hot, cloudless regions of high pressure persisting over large areas. Temperatures were significantly higher than usual over swaths of North America, Northeast Asia, and much of Europe. The European heat wave was exacerbated by drought, particularly affecting northern and central Europe, and leading to significant reduction in yields and early harvests in some regions. Fires were also unusually intense and widespread. This has significant effects on the carbon budget, with potential reductions in photosynthesis and increases in respiration and biomass burning emissions expected. With a short latency compared to ground-based measurements, remote sensing data are providing us with a first look at what this means for the carbon dioxide budget. This study uses total column measurements of atmospheric carbon dioxide from OCO-2 and GOSAT until the end of summer 2018, as well as remotely-sensed land surface reflectances from MODIS to derive the prior flux estimates. Fire emissions are estimated from the remote-sensing-driven GFAS near-real-time product. Signals in both concentrations and fluxes are compared to those in previous years, and preliminary inversions are carried out both globally and over a nested domain over Europe. The global inversions allow the continental separation of the flux anomaly, and provide reasonable boundary conditions for the local inversion. Measurements of Solar-induced Fluorescence from OCO-2 are used a posteriori to interpret the flux signal in terms of a partitioning into anomalies in uptake vs. respiration.

ICARE Data and Services Center has been estabished in 2005 to provide services to the science community and facilitate access to and utilization of satellites and ground-based observations of atmospheric aerosols and clouds properties, water cycle, and radiation. Its mission is to support research studies in atmospheric and climate sciences. ICARE is supported by the CNES and the Hauts-de-France Regional Council as part of a partnership with the University of Lille and the CNRS.

ICARE is one of the 4 data centers of AERIS, the French Atmospheric Data Infrastructure and contributes to numerous national and international collaborative projects (MACC, IAOOS, ORAURE, ROSEA, CaPPA, GEWEX, CHARMEX, ACTRIS, CCI, AEROCLUB, GAIA-CLIM, …).

ICARE partners with French and worldwide experts in the fields of atmospheric and climate sciences and with the international space agencies (CNES, NASA, ESA, EUMETSAT, ISRO, etc.). In particular, ICARE can support the development and exploitation of scientific ground segment for spaceborne missions related to atmospheric monitoring.

The main philosophy for development of science products at ICARE is to provide scientists and agencies with a flexible environment for implementation of science retrieval processors requiring minimal specifications while ensuring careful quality assessment and documentation of developped softwares and products. This relies partly on agile approach for interactions between scientists and ICARE development team and a robust and highly flexible production system that allows both massive reprocessing and near real time routine production for several  on-going missions.

We will illustrate here the possibilities offered by ICARE/AERIS in terms of science products development and services through the example of the CALIPSO mission. Both standalone and synergistic CALIOP products developped within the A-Train mission will be illustrated. Potential opportunities for the support of Aeolus and EarthCARE missions will be discussed.

Novel Earth Observations of atmospheric greenhouse gases and the cryosphere have the potential to fundamentally increase our understanding of the carbon cycle at high Northern latitudes. In this poster, we present our newly started ESA project on quantifying methane (CH₄) emissions in the Northern Hemisphere, and investigating their connection to the soil freezing and thawing at boreal latitudes. We combine methods for the quantification of CH₄ emissions by applying data from Earth Observing (EO) satellites and global atmospheric methane inversion model estimates. The EO data consist of a global soil freeze/thaw estimate obtained from the ESA Soil Moisture and Ocean Salinity (SMOS) mission as well as retrievals of atmospheric column-averaged methane obtained from the Greenhouse Gases Observing Satellite (GOSAT) and Sentinel 5 Precursor TROPOMI (S5P-TROPOMI) observations. These EO data will be used in global atmospheric methane inversion model, CarbonTracker Europe – CH4, simulations, focusing on (1) the identification of CH₄ sources in the Northern Hemisphere and (2) providing trend analysis on the total methane emissions in the past two decades. EO data will be used to assess the spatial variability of the emissions and to better quantify the contributions from regions dominated by anthropogenic emissions and by natural emissions, especially those from wetlands. Further, EO data will be used to create proxies of the seasonality of the natural methane emissions, focusing on the timing and length of the autumn freezing period and springtime melting period.

The ESA Atmospheric Toolbox is one of the ESA Sentinel Toolboxes.
It consists of a set of software components to read, analyze, process and visualize a wide range of atmospheric data products. In addition to the Sentinel-5P mission it supports a wide range of other atmospheric data products, including those of previous ESA missions, ESA Third Party missions, Copernicus Atmosphere Monitoring Service (CAMS), ground based data, etc.

The toolbox consists of four main components that are called CODA, HARP, VISAN, and QDOAS

CODA provides interfaces for direct reading of data from earth observation data files. These interfaces consist of command line applications, libraries, direct interfaces to scientific applications (IDL and MATLAB), and direct interfaces to programming languages (C, Fortran, Python, and Java).
CODA provides a single interface to access data in a wide variety of data formats, including ASCII, binary, XML, netCDF, HDF4, HDF5, CDF, GRIB, RINEX, and SP3.

HARP is a toolkit for reading, processing and inter-comparing satellite remote sensing data, model data, in-situ data, and ground based remote sensing data.
The main goal of HARP is to provide easy access to data and to assist in the inter-comparison of datasets. By appropriately chaining calls to HARP command line tools one can pre-process datasets such that two datasets that need to be compared end up having the same temporal/spatial grid, same data format/structure, and same physical unit.
The toolkit comes with its own data format conventions, the HARP format, which is based on netCDF/HDF. Ingestion routines (based on CODA) allow conversion from a wide variety of atmospheric data products to this common format. In addition, the toolbox provides a wide range of operations to perform conversions on the data such as unit conversions, quantity conversions (e.g. number density to volume mixing ratios), regridding (including L2 to L3 gridding), vertical smoothing using averaging kernels, collocation of two datasets, etc.

VISAN is a cross-platform visualization and analysis application for atmospheric data and can be used to visualize and analyze the data that you retrieve using the CODA and HARP interfaces. The application uses the Python language as the means through which you provide commands to the application. The Python interfaces for CODA and HARP are included so you can directly ingest product data from within VISAN. Powerful visualization functionality for 2D plots and geographical plots in VISAN will allow you to directly visualize the ingested data.

QDOAS is a cross-platform application which performs DOAS retrievals of trace gases from spectral measurements (satellite, ground-based, mobile or aircraft-based instruments). This application already existed for many years but has recently been added to the toolbox as one of its components.

All components from the ESA Atmospheric Toolbox are Open Source and freely available.

After the hardware and the testing phase and after delivering the fully calibrated TROPOMI instrument to ESA, Airbus DS in the Netherlands has started the development of air composition services that make use of the TROPOMI measurements. In this role of air composition information services provider we will play a pivotal role between current scientific development and commercial clients, where we make use of our instrument expertise as instrument prime for TROPOMI. We do this by maintaining close contact with numerous universities and institutes on the one hand and on the other hand, by developing relations with potential customers in order to better understand their needs. We have built mockups and demonstration models of the information services that we intend to provide in order to obtain direct feedback from the clients. In this paper we describe the status of the ongoing effort and we will highlight three specific cases. The three specific cases that we will describe in some details are [1] global monitoring service on atmospheric composition and emission allocation, [2] methane emission monitoring service (MEMS) and [3] Sulphur emission monitoring from ships. Air composition and meteorological data from satellites and local sensors are combined into a chemical transport model to build up or validate trace gas and particulate matter emission sources and their impact on air quality. The global monitoring service on atmospheric composition and emission allocation is using TROPOMI measurements to be able to quickly disclose new regions around the globe at low cost, as has been done for eastern Asia and the Indian continent. This yields a database of emission sources at a spatial resolution of about 3.5 km (and in the near future 1km) and provides daily observation data on regional and transboundary transport of pollutants. Target constituents are NO2, particulate matter, CH4, (tropospheric) ozone and SO2. For the methane emission monitoring service we are involved in a joint research project, which intends to develop methods for detection and quantification of localized CH4 emission sources. Key attention will be on gas leaks in the energy sector;other markets such as mining industry, agriculture and landfills will also be explored. For the Sulphur emission monitoring case TROPOMI measurements are expected to provide statistical information on potential offenders of current and future limits on the sulphur content in the exhaust. In this case, the TROPOMI data will be used as a stepping stone in the development of a service that will make use of more dedicated SO2 measurements.