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The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) is part of the European satellite ENVISAT launched at 1st March 2002. It is a follow-on instrument of the Global Ozone Monitoring Experiment (GOME) flying on ERS-2 and, compared to GOME, has extended capabilities. Using measurements of the direct extra-terrestrial solar spectrum and sun-light reflected and scattered by the earth atmosphere or surface SCIAMACHY detects atmospheric absorption of several trace species absorbing in spectral regions from the ultraviolet to the near infrared (240–2380 nm). Vertical columns of H2O, N2O, CO, and CH4 can be retrieved using SCIAMACHY Channel 8 near-infrared nadir measurements. In this study, selected atmospheric and instrument specific errors relevant for the retrieval are analysed. Spectral windows of Channel 8 are considered, which are currently used for the operational near-real-time processing. For this purpose, spectral error patterns have been simulated as well as sun-normalised model radiances for nadir scanning mode, the latter using the radiative transfer model SCIATRAN. Focus are the polarisation sensitivity and dark signals of the instrument. Further on, accuracy estimates for a number of different atmospheric scenarios are presented. [Copyright &y& Elsevier]

A radiative transfer model, SCIATRAN, has been developed mainly for the retrieval of atmospheric constituents from global nadir radiance measurements of the SCIAMACHY satellite spectrometer. This is a further development of the successful GOMETRAN. SCIATRAN solves the radiative transfer equation using the Finite Difference Method for a plane-parallel vertically inhomogeneous atmosphere taking into account multiple scattering. The present program version utilizes the pseudo-spherical approach, including refraction, appropriate for solar zenith angles up to about 92°. SCIATRAN comprises, amongst others, the following features: (i) quasi-analytical calculation of weighting functions of atmospheric and surface parameters, (ii) DOAS airmass factor calculations, (iii) height resolved radiation fluxes, including actinic fluxes for photolysis rate calculations, (iv) inelastic rotational Raman scattering by N2 and O2 molecules, (v) parameterization schemes for aerosols and clouds, (vi) a line-by-line and a correlated-k distribution mode for line absorption, and (vii) thermal emission. This paper presents an overview of the SCIATRAN model, focusing on the pseudo-spherical approach developed to consider the sphericity of the Earth. SCIATRAN will be made available via the world wide web for non-commercial scientific applications. [Copyright &y& Elsevier]

A method for the retrieval of vertical column amounts of atmospheric water vapour from measurements of the Global Ozone Monitoring Experiment (GOME) in the visible spectral region is presented. Originally developed for the determination of global ozone concentrations, the GOME instrument is operating successfully on ERS-2 since 1995, providing information also on several other atmospheric constituents like NO2, BrO, OClO, H2CO, SO2, and recently also H2O. The method for the derivation of water vapour amounts is based on the Differential Optical Absorption Spectroscopy (DOAS) approach, which has been extended to take into account effects arising from a strongly wavelength dependent absorption. Further improvements of the algorithm now allow to retrieve water vapour column densities under all cloud conditions. First results show an acceptable agreement between total water vapour columns derived from GOME measurements and H2O columns obtained from the Special Sensor Microwave Imager SSM/I data, although the scatter of the GOME data is high, which needs to be further investigated. [Copyright &y& Elsevier]

Abstract: Pressing open questions about the carbon cycle can be addressed with precise measurements of the three most abundant CO2 isotopologues 16O12C16O, 16O13C16O, and . Such measurements can, e.g., help to further constrain oceanic and biospheric net fluxes or to differentiate between the gross biospheric fluxes photosynthesis and respiration. The (about ) spectral region contains separated absorption lines of the three most abundant CO2 isotopologues. Their spectral properties make this spectral region well suited for the use of a light path proxy method for the retrieval of and (the ratio of heavier to lighter isotopologues relative to a standard). An optimal estimation based light path proxy retrieval for and has been set up, applicable to GOSAT (Greenhouse gases Observing Satellite) and ground-based FTS (Fourier transform spectrometer) measurements. Initial results show that it is possible to retrieve and from ground-based FTS instruments with a precision of and from GOSAT with a precision of about . Comparison of the achievable precision with the expected atmospheric signals shows that ground-based FTS remote sensing measurements have the potential to gain valuable information on and if averaging a sufficient number of measurements. It seems unlikely that this applies also to GOSAT because of the lower precision and a conceptual larger sensitivity to scattering related errors in satellite viewing geometry. [Copyright &y& Elsevier]

Abstract: A successor version of the SCIATRAN radiative transfer model (RTM) has been developed to perform radiative transfer modeling in any observation geometry appropriate to measurements of the scattered solar radiation in the Earth’s atmosphere. The model is designed to be used as a forward model in the retrieval of atmospheric constituents from measurements of scattered solar light by satellite, ground-based, or airborne instruments in UV–Vis–NIR spectral region. Furthermore, it can be used to calculate air mass factors or fluxes. The new generation of the SCIATRAN model comprises all features of the latest SCIATRAN 1.2 RTM supporting additionally radiative transfer calculations in a spherical atmosphere. The program is written in FORTRAN 95 and suitable for parallel execution using the OpenMP standard. The wavelength range covered by the radiative transfer model is extended to 175–2380nm including Schuman-Runge and Herzberg absorption bands of oxygen. The SCIATRAN 2.0 model exhibits the following new capabilities: (i) modeling of the scattered solar radiation in limb viewing geometry as well as any kind of measurements of the scattered radiation within the atmosphere, (ii) corresponding quasi-analytical calculation of weighting functions of atmospheric parameters, (iii) airmass factor calculations for ground-based, space and airborne measurements including off-axis geometry, (v) accounting for photochemically active species, i.e., radiative transfer calculations can be performed using solar zenith angle dependent vertical distributions of atmospheric species, (iv) height resolved radiation fluxes, including actinic fluxes for photolysis rate calculations, (vi) inelastic rotational Raman scattering in any supported viewing geometry, (vii) new effective approximations for radiative transfer modeling in presence of clouds. The SCIATRAN model is freely available via the world wide web for non-commercial scientific applications. [Copyright &y& Elsevier]

Since 1995, the Global Ozone Monitoring Experiment (GOME) on board the second European Remote Sensing satellite provides information about spatial distribution and temporal variation of total ozone. Current operational data products are generated using the Differential Optical Absorption Spectroscopy (DOAS) technique. Various validation exercises indicate shortcomings in the current retrieval using the standard DOAS approach. Especially under ozone hole conditions at high polar latitudes GOME tends to overestimate total ozone as compared to ground-based measurements. In this study, we introduce a modified DOAS method for ozone retrieval from GOME which fits directly the vertical columns rather than slant columns. We present preliminary results which demonstrate the advantage of the new approach. It will be shown that not only the differences to ground-based data are reduced but also the fit residuals are improved in comparison with the operational retrieval. [Copyright &y& Elsevier]

Under the Paris Agreement (PA), progress of emission reduction efforts is tracked on the basis of regular updates to national greenhouse gas (GHG) inventories, referred to as bottomup estimates. However, only top-down atmospheric measurements can provide observation-based evidence of emission trends. Today, there is no internationally agreed, operational capacity to monitor anthropogenic GHG emission trends using atmospheric measurements to complement national bottom-up inventories. The European Commission (EC), the European Space Agency, the European Centre for Medium-Range Weather Forecasts, the European Organisation for the Exploitation of Meteorological Satellites, and international experts are joining forces to develop such an operational capacity for monitoring anthropogenic CO2 emissions as a new CO2 service under the EC's Copernicus program. Design studies have been used to translate identified needs into defined requirements and functionalities of this anthropogenic CO2 emissions Monitoring and Verification Support (CO2MVS) capacity. It adopts a holistic view and includes components such as atmospheric spaceborne and in situ measurements, bottom-up CO2 emission maps, improved modeling of the carbon cycle, an operational data-assimilation system integrating top-down and bottom-up information, and a policy-relevant decision support tool. The CO2MVS capacity with operational capabilities by 2026 is expected to visualize regular updates of global CO2 emissions, likely at 0.05° x 0.05°. This will complement the PA's enhanced transparency framework, providing actionable information on anthropogenic CO2 emissions that are the main driver of climate change. This information will be available to all stakeholders, including governments and citizens, allowing them to reflect on trends and effectiveness of reduction measures. The new EC gave the green light to pass the CO2MVS from exploratory to implementing phase. [ABSTRACT FROM AUTHOR]

Long-term time series of CO 2 concentrations are required for studying e.g., the effects of rising CO 2 concentrations on plants and ecosystems. Different methods for approximating column-averaged dry-air mole fractions of CO 2 (XCO 2) have been developed to substitute missing local CO 2 measurements. This study presents a novel method (XCO 2 SAT+) for determining monthly XCO 2 concentrations for selected sites, based entirely on observations from multiple satellites as well as statistical methods in the case of missing satellite data. The product currently covers a period of 16 years from 2003 to 2018. XCO 2 SAT+ results were validated against data of five European sites of the Total Carbon Column Observing Network (TCCON) and compared to two established XCO 2 approximation methods. All three approximation methods were compared to CO 2 measurements of German towers from the Integrated Carbon Observation System (ICOS). The mean absolute error (MAE) between the XCO 2 SAT+ method and TCCON site Karlsruhe, Germany ranges between 0.5 and 1.1 ppm (0.1–0.3%) for years 2014–2018. Mean differences between XCO 2 SAT+ and XCO 2 approximation method CAMS-GCM shows a slightly better MAE of 0.1–0.3 ppm for CAMS-GCM at two German TCCON sites. Multi-year comparisons with ground-level ICOS measurements revealed a comparable seasonality of CO 2 concentrations during the vegetation period, but underestimated high winter concentrations, a pattern also observed when comparing with CAMS-GCM. XCO2SAT+ is a suitable alternative and simple method for providing long-term time series of monthly averaged XCO 2 concentrations for selected sites, expanding the methodological toolbox for in-situ CO 2 research. The new method, which so far provides XCO 2 concentrations, will thus serve as a first step towards providing further CO 2 data sources, which could be used to further improve numerical models such as atmospheric models or crop growth models and to study CO 2 impacts in agriculture and natural ecosystems. [Display omitted] • Novel method (XCO 2 SAT+) determining multi-year timeseries of XCO 2 concentrations. • Method uses observations from 3 satellites of the EU, JP and USA. • Missing satellite observations are compensated by statistical interpolation. • MAE of 1.02 ppm compared to European TCCON stations - comparable to GCM simulations. • Alternative XCO 2 data source for research areas like numerical models or ecosystems. [ABSTRACT FROM AUTHOR]

We present two novel earth observation products derived from the BESD and EMMA XCO 2 products which were respectively retrieved from SCIAMACHY and GOSAT observations within the GreenHouse Gas project of ESA's Climate Change Initiative (GHG-CCI). These products are inferred by a Carbon Cycle Data Assimilation System (CCDAS) and consist of net and gross biosphere-atmosphere fluxes of carbon dioxide on a global 0.5° grid. As a further dataset provided by the CCI, the burnt area product developed by its Fire忌i project was used in the CCDAS to prescribe the emission component from biomass burning. The new flux products are provided with per-pixel uncertainty ranges. Fluxes with uncertainty ranges can also be provided aggregated in space and time, e.g. over given regions or as annual means. For both, posterior flux fields inferred from BESD and EMMA products, transport model simulations show reasonable agreement with the atmospheric carbon dioxide concentration observed at flask sampling stations. This means that the information provided by the terrestrial and transport models, the respective GHG ECV product, the burnt area ECV product, a product of the Fraction of Absorbed Photosynthetically Active Radiation used to drive the model, and the atmospheric flask samples is largely consistent. The most prominent feature in the posterior net flux is the tropical source of CO 2 inferred from both products. But for the EMMA product this release, especially over South America, is with 300 gC/m 2 /year much more pronounced than for BESD. This confirms findings by a recent intercomparison of transport inversions using GOSAT data by Houweling et al. (2015) . The reason for the larger net flux is increased heterotrophic respiration. For both products the posterior 2010 sink over Europe (without Russia) is in the range of a recent compilation of European flux estimates by Reuter et al. (2016b) . The posterior 2010 uptake of Australia (including Oceania) inferred from the EMMA product is 1.3 ± 0.2 PgC/year and appears to confirm the high sink also derived from GOSAT by Detmers et al. (2015) over a slightly different period and area. While for some regions (USA, Canada, Europe, Russia, Asia) the one standard deviation uncertainty ranges derived from BESD and EMMA do overlap, for some other regions (Brazil, Africa, Australia) this is not the case. It is not clear yet whether this is due to the uncertainty specifications in the respective products or the handling of uncertainty in the assimilation chain. Assumptions on correlation of observational uncertainty in space and time have a considerable impact on the inferred flux fields (≈ 60 gC/m 2 /year). The effect of adding an uncertainty that approximates the error in the retrieval system is of similar size. [ABSTRACT FROM AUTHOR]

Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties. There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together. This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science. [ABSTRACT FROM AUTHOR]

Emissions of methane (CH 4 ) in the Permian basin (USA) have been derived for 2019 and 2020 from satellite observations of the Tropospheric Monitoring Instrument (TROPOMI) using the divergence method, in combination with a data driven method to estimate the background column densities. The resulting CH 4 emission data, which have been verified using model data with known emissions, have a spatial resolution of approximately 10 km. The CH 4 emissions show moderate spatial correlation with the locations of oil and gas production and drilling activities in the Permian basin, as well as with emissions of nitrogen oxides (NO x ). Analysis of the emission maps and time series indicates that a significant fraction of methane emissions in the Permian basin is from frequent widespread emissions sources, rather than from a few infrequent very large unplanned releases, which is important considering possible CH 4 emission mitigation strategies. In addition to providing spatially resolved emissions, the divergence method also provides the total emissions of the Permian basin and its main sub-basins. The total CH 4 emission of the Permian is estimated as 3.0 ± 0.7 Tg yr -1 for 2019, which agrees with other independent estimates based on TROPOMI data. For the Delaware sub-basin, it is estimated as 1.4 ± 0.3 Tg yr -1 for 2019, and for the Midland sub-basin 1.2 ± 0.3 Tg yr -1 . In 2020 the emissions are 9% lower compared to 2019 in the entire Permian basin, and respectively 19% and 27% for the Delaware and Midland sub-basins., (© 2023. The Authors.)

Background: Satellite imagery will offer unparalleled global spatial coverage at high-resolution for long term cost-effective monitoring of CO 2 concentration plumes generated by emission hotspots. CO 2 emissions can then be estimated from the magnitude of these plumes. In this paper, we assimilate pseudo-observations in a global atmospheric inversion system to assess the performance of a constellation of one to four sun-synchronous low-Earth orbit (LEO) imagers to monitor anthropogenic CO 2 emissions. The constellation of imagers follows the specifications from the European Spatial Agency (ESA) for the Copernicus Anthropogenic Carbon Dioxide Monitoring (CO2M) concept for a future operational mission dedicated to the monitoring of anthropogenic CO 2 emissions. This study assesses the uncertainties in the inversion estimates of emissions ("posterior uncertainties")., Results: The posterior uncertainties of emissions for individual cities and power plants are estimated for the 3 h before satellite overpasses, and extrapolated at annual scale assuming temporal auto-correlations in the uncertainties in the emission products that are used as a prior knowledge on the emissions by the Bayesian framework of the inversion. The results indicate that (i) the number of satellites has a proportional impact on the number of 3 h time windows for which emissions are constrained to better than 20%, but it has a small impact on the posterior uncertainties in annual emissions; (ii) having one satellite with wide swath would provide full images of the XCO 2 plumes, and is more beneficial than having two satellites with half the width of reference swath; and (iii) an increase in the precision of XCO 2 retrievals from 0.7 ppm to 0.35 ppm has a marginal impact on the emission monitoring performance., Conclusions: For all constellation configurations, only the cities and power plants with an annual emission higher than 0.5 MtC per year can have at least one 8:30-11:30 time window during one year when the emissions can be constrained to better than 20%. The potential of satellite imagers to constrain annual emissions not only depend on the design of the imagers, but also strongly depend on the temporal error structure in the prior uncertainties, which is needed to be objectively assessed in the bottom-up emission maps.

Rapid and accurate industrial inspection to ensure the highest quality standards at a competitive price is one of the biggest challenges in the manufacturing industry. This paper shows an application of how a Deep Learning soft sensor application can be combined with a high-resolution optical quality control camera to increase the accuracy and reduce the cost of an industrial visual inspection process in the Printing Industry 4.0. During the process of producing gravure cylinders, mistakes like holes in the printing cylinder are inevitable. In order to improve the defect detection performance and reduce quality inspection costs by process automation, this paper proposes a deep neural network (DNN) soft sensor that compares the scanned surface to the used engraving file and performs an automatic quality control process by learning features through exposure to training data. The DNN sensor developed achieved a fully automated classification accuracy rate of 98.4% . Further research aims to use these results to three ends. Firstly, to predict the amount of errors a cylinder has, to further support the human operation by showing the error probability to the operator, and finally to decide autonomously about product quality without human involvement.

Ichniotherium tracks with a relatively short pedal digit V (digit length ratio V/IV < 0.6) form the majority of yet described Late Carboniferous to Early Permian diadectomorph tracks and can be related to a certain diadectid clade with corresponding phalangeal reduction that includes Diadectes and its close relatives. Here we document the variation of digit proportions and trackway parameters in 25 trackways (69 step cycles) from nine localities and seven further specimens with incomplete step cycles from the type locality of Ichniotherium cottae (Gottlob quarry) in order to find out whether this type of Ichniotherium tracks represents a homogeneous group or an assemblage of distinct morphotypes and includes variability indicative for evolutionary change in trackmaker locomotion. According to our results, the largest sample of tracks from three Lower Permian sites of the Thuringian Forest, commonly referred to I. cottae , is not homogeneous but shows a clear distinction in pace length, pace angulation, apparent trunk length and toe proportions between tracks from Bromacker quarry and those from the stratigraphically older sites Birkheide and Gottlob quarry. Three Late Carboniferous trackways of Ichniotherium with relatively short pedal digit V from Haine's Farm, Ohio, and Alveley near Birmingham, United Kingdom, that have been referred to the ichnotaxa " Baropus hainesi ," " Megabaropus hainesi" and " Ichniotherium willsi ," respectively, share a marked outward rotation of foot imprints with respect to walking direction. Apart from this feature they are in many aspects similar to the Birkheide and Gottlob records of I. cottae . With the possible exception of the Maroon Formation (Early Permian, Colorado) sample, Early Permian Ichniotherium trackways with a relatively short pedal digit V fall into the morphological spectrum of the three well defined "Hainesi-Willsi," "Birkheide-Gottlob" and "Bromacker" morphotypes. With their more obtuse pace angulations and higher body-size-normalized pace and stride lengths the Bromacker type tracks imply higher walking speeds of their trackmakers compared to all other Ichniotherium tracks. More generally, a trend towards higher locomotion capability from the last common ancestor of all Ichniotherium producers to the last common ancestor of all " Ichniotherium with relatively short pedal digit V" and from the latter to the trackmakers of the mid-Early Permian Bromacker type can be deduced-with the reservation that overall sample size is relatively small, making this scenario a preliminary assessment. Whether the presumed advancements represent a more general pattern within diadectomorphs remains open until the non-European Ichniotherium trackway record improves. Ichnotaxonomic implications are discussed., Competing Interests: Michael Buchwitz is an employee of the city administration of Magdeburg, the state capital of Saxony-Anhalt. Sebastian Voigt is an employee of the Pfalzmuseum für Naturkunde/Pollichia Museum.

Of the recent sauropsid skin appendage types, only feathers develop from a cylindrical epidermal invagination, the follicle, and show hierarchical branching. Fossilized integuments of Mesozoic diapsids have been interpreted as follicular and potential feather homologues, an idea particularly controversially discussed for the elongate dorsal skin projections of the small diapsid Longisquama insignis from the Triassic of Kyrgyzstan. Based on new finds and their comparison with the type material, we show that Longisquama's appendages consist of a single-branched internal frame enclosed by a flexible outer membrane. Not supporting a categorization either as feathers or as scales, our analysis demonstrates that the Longisquama appendages formed in a two-stage, feather-like developmental process, representing an unusual early example for the evolutionary plasticity of sauropsid integument.

The Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) onboard the European Envisat spacecraft performs continuous spectral observations of reflected, scattered and transmitted sunlight in various observation geometries. A unique feature of SCIAMACHY is the capability of probing the atmosphere in three different observation geometries:The nadir, limb, and occultation measurement modes. In nadir mode, column densities of trace gases are retrieved with a spatial resolution of typically 30 x 60 km using the Differential Optical Absorption Spectroscopy (DOAS) technique (Platt and Perner, 1983). Alternating with the nadir measurement, vertical profiles of absorber concentration in the stratosphere are derived in limb and occultation. In this paper we present an overview over some applications of SCIAMACHY data in space-based monitoring of atmospheric pollution. The DOAS algorithms for the retrieval of total column amounts from nadir spectra are briefly described and case studies of pollution events are presented. We also illustrate the technique used to derive stratospheric concentration profiles from limb observations and show comparisons with other remote sensing systems. Special emphasis will be given to techniques, which take advantage of SCIAMACHY's different viewing geometries. In particular, we will discuss the potential and limits of strategies to infer tropospheric abundances of O3 and NO2.

Eighteen radiative transfer models in use for calculation of UV index are compared with respect to their results for more that 100 cloud-free atmospheres, which describe present, possible future and extreme conditions. The comparison includes six multiple-scattering spectral models, eight fast spectral models and four empirical models. Averages of the results of the six participating multiple-scattering spectral models are taken as a basis for assessment. The agreement among the multiple-scattering models is within +/- 0.5 UV index values for more than 80% of chosen atmospheric parameters. The fast spectral models have very different agreement, between +/- 1 and up to 12 UV index values. The results of the empirical models agree reasonably well with the reference models but only for the atmospheres for which they have been developed. The data to describe the atmospheric conditions, which are used for the comparison, together with the individual results of all participating models and model descriptions are available on the Internet: http://www.meteo.physik.uni-muenchen.de/++ +strahlung/cost/.