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The European Space Agency (ESA)’s Earth Explorer Aeolus was launched in August 2018 carrying the world’s first spaceborne wind lidar, the Atmospheric Laser Doppler Instrument (ALADIN). ALADIN uses a high spectral resolution Doppler wind lidar operating at 355nm to determine profiles of line-of-sight wind components in near-real-time (NRT). ALADIN samples the atmosphere from 30km altitude down to the Earth’s surface or to the level where the lidar signal is attenuated by optically thick clouds.The global wind profiles provided by ALADIN help to improve weather forecasting and the understanding of atmospheric dynamics as they fill observational gaps in vertically resolved wind profiles mainly in the tropics, southern hemisphere, and over the northern hemisphere oceans. Since 2020, multiple national and international weather centres (e.g. ECMWF, DWD, Météo France, MetOffice) assimilate Aeolus observations in their operational forecasting. Additionally, the scientific exploitation of the Aeolus dataset has started.A main prerequisite for beneficial impact and scientific exploitation is data of sufficient quality. Such high data quality has been achieved through close collaboration of all involved parties within the Aeolus Data Innovation and Science Cluster (DISC), which was established after launch to study and improve the data quality of Aeolus products. The tasks of the Aeolus DISC include the instrument and platform monitoring, calibration, characterization, retrieval algorithm refinement, processor evolution, quality monitoring, product validation, and impact assessment for NWP.The achievements of the Aeolus DISC for the NRT data quality and the one currently available reprocessed dataset will be presented. The data quality of the Aeolus wind measurements will be described and an outlook on planned improvements of the dataset and processors will be provided.

Already within the first weeks after the launch of ESA's Earth Explorer mission Aeolus on 22 August 2018, the spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) provided atmospheric backscatter measurements on 5 September and wind profiles on 12 September 2018. This swift availability of observations from ALADIN after launch is considered as a great success for ESA, space industry and algorithm and processor developer teams. These teams from scientific institutes, numerical weather prediction (NWP) centres, companies and ESA continuously improved and tested the retrieval algorithms and processors using sophisticated end-to-end simulation tools and experience gained with the airborne demonstrator for Aeolus for more than 15 years before launch. This cooperation from the pre-launch phase of Aeolus was extended within a new framework for exploitation activities of Earth Explorer missions named Data Innovation and Science Cluster (DISC) starting in January 2019. The Aeolus DISC activities range from instrument monitoring including calibration to algorithm refinement resulting in updates of the complete processor chain for all product levels every 6 months. DISC teams perform continuous monitoring of the product quality and provide regular reports in supports of external validation teams and ESA. Finally, wind product monitoring and impact experiments with NWP models are building an essential activity within the Aeolus DISC in order to achieve the objective of the Aeolus mission. In order to cover the broad range of activities, a multi-disciplinary team of experts, institutes and companies was established for the Aeolus DISC coordinated by DLR with ECMWF, KNMI, CNRS/Météo-France, DoRIT, ABB, S&T and Serco. During the presentation the Aeolus instrument performance for wind products, the discovered causes of the systematic errors and their correction will be discussed. Main achievements in this area are related to the characterization and correction of enhanced dark signal levels for single "hot" pixels in June 2019, the identification of the harmonic error contribution caused by the varying telescope primary mirror temperature variation in September- October 2019, the error in the on-board computation of the satellite induced Doppler frequency shift, and finally the observed temporal drift of a constant bias caused by drifts in the internal reference path. An outlook to the implementation of these corrections for real-time and reprocessed data products will be given.

Compartmentalization is likely to have been essential for the emergence of life. Compartmentalization allows for the creation of unique chemical conditions that can be maintained out of equilibrium with the environment and the exclusion of parasites. Confining organic molecules also helps limit diffusion, increases concentration and can thus influence both the thermodynamics and kinetics of prebiotic reactions. Biology currently predominantly uses phospholipids to construct cell membranes. However, there are many other types of organic compounds that can form stable compartments in water, and many of these may have been abundant in the prebiotic environment. In this study we explore this alternative lipid chemical space by using structure enumeration algorithms to compute an exhaustive combinatorial library of surfactant molecules. We then predict the propensity of these compounds to self-assemble into membranes using quantitative structure-property relationship (QSPR) models on critical micelle concentration (CMC). Combined with critical packing parameter calculations, these models can allow identification of novel molecule types which can be experimentally assayed as candidates for the emergence of protocells.

From its very beginnings the development of algorithms for the enumeration of chemical space was closely related to NASA's early exobiology activities. The complete and non-redundant generation of all connectivity isomers corresponding to a given molecular formula was part of the DENDRAL program, established in the mid-1960s. In the 1970s mathematicians provided new techniques to increase efficiency of the first approaches, and starting with the 1990s implementations became available as software packages for customary computers. In this talk some of the most essential principles of exhaustive and non-redundant structure enumeration are reviewed: starting from simple labeled graphs we will see how to avoid isomorphic duplicates, introduce structural constraints and how to generate molecular graphs in an efficient way. Recently these methods have been rediscovered for application in astrobiology and origins of life research, particularly for generating and analyzing virtual chemical compound libraries surrounding the most important biomolecules. Results concerning the genetically encoded amino acid alphabet, nucleotide analogs and the core of intermediary metabolism are summarized.

The European Space Agency (ESA)’s Earth Explorer Aeolus was launched in August 2018 carrying the world’s first spaceborne wind lidar, the Atmospheric Laser Doppler Instrument (ALADIN). ALADIN uses a high spectral resolution Doppler wind lidar operating at 355nm to measure profiles of line-of-sight wind components in near-real-time (NRT). ALADIN samples the atmosphere from 30km altitude down to the Earth’s surface or to the level where the lidar signal is attenuated by optically thick clouds.The global wind profiles provided by ALADIN help to improve weather forecasting and the understanding of atmospheric dynamics as they fill observational gaps in vertically resolved wind profiles mainly in the tropics, southern hemisphere, and over the northern hemisphere oceans. In January 2020, the European Centre for Medium-Range Weather Forecasts (ECMWF) became the first numerical weather prediction (NWP) centre to assimilate Aeolus observations for operational forecasting.A main prerequisite for beneficial impact is data of sufficient quality. Such high data quality has been achieved through close collaboration of all involved parties within the Aeolus Data Innovation and Science Cluster (DISC), which was established after launch to study and improve the data quality of Aeolus products. The tasks of the Aeolus DISC include the instrument and platform monitoring, calibration, characterization, retrieval algorithm refinement, processor evolution, quality monitoring, product validation, and impact assessment for NWP.The achievements of the Aeolus DISC for the NRT data quality and the current status of Aeolus wind measurements will be described and summarized. Further, an outlook on future improvements and the availability of reprocessed datasets with enhanced data quality will be provided.

How the transition of disorganized, inanimate matter to organized, living systems took place on our planet and might have occurred on other bodies of our solar system or elsewhere in the universe is one of the fundamental questions studied in the field of astrobiology. The only instance of life known so far is the terrestrial one, and all living organisms on Earth share many of the same biochemical foundations with respect to reproduction and metabolism. These biochemical foundations rely on a small pool of biomolecules, which represent a minute subset of plausible structural analogs, which themselves form only a very small fraction of all possible chemical compounds in chemical space. We believe that one key to understanding the origins of life is to study biomolecules in the context of their surrounding neighborhood in chemical space. Using unique software tools, so-called structure generators, we are able to exhaustively construct well defined subsets of chemical space. These virtual compound libraries are then computationally analyzed with respect to the physico-chemical properties of their constituents. In this talk some basic mathematical models and computational aspects of generating molecular structures are presented, results concerning the amino acid alphabet, nucleotide analogs and the core of intermediary metabolism are summarized, and perspectives of ongoing studies related to astrobiology exploration missions are outlined.

Already within the first weeks after the launch of ESA´s Earth Explorer mission Aeolus on 22 August 2018, the spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) provided atmospheric backscatter measurements on 5 September and wind profiles on 12 September. This swift availability of observations from ALADIN after launch is considered as a great success for ESA, space industry and algorithm and processor developer teams. These teams from scientific institutes, numerical weather prediction (NWP) centres, companies and from ESTEC and ESRIN continuously improved and tested the retrieval algorithms and processors using sophisticated end-to-end simulation tools and experience gained with the airborne demonstrator for Aeolus. ALADIN as the first wind-lidar in space is not only based on new technologies for lasers, optical interferometers and detectors, but also the retrieval algorithms had to be developed without any heritage from earlier space-borne wind lidars. This cooperation from the development phase of Aeolus will be continued and extended within a new framework for exploitation activities of Earth Explorer missions named Data Innovation and Science Cluster (DISC) during the phase E2 starting after completion of the commissioning phase activities. The Aeolus DISC activities range from instrument monitoring including calibration and characterization to algorithm refinement, and towards a continuous evolution of the processors for all product levels. Product quality monitoring plays an essential role including validation of products from external validation teams, whose results will be synthesised by DISC experts and eventually will lead to further algorithm updates. The DISC consortium will provide support to ESA ranging from anomaly resolving for the payload data ground segment to support in decisions for instrument operation, calibration and providing support to the Aeolus Quality Working Group (QWG). Also support to Aeolus users from the validation teams, science and NWP communities will be provided by DISC experts. The aim of the Aeolus mission is to provide global observations of vertical profiles of one component of the horizontal wind vector with sufficient accuracy and precision to demonstrate a positive impact on NWP analysis and forecasts. All activities within the DISC are targeted towards supporting this overall objective. Therefore impact experiments with NWP models are building a major activity within DISC. These impact experiments, the product monitoring activities, or the feedback from the user community will eventually guide further recommendations for algorithm and processor evolution. Both forward-engineering (or bottom-up) approaches as well as complementary reverse-engineering (or top-down) approaches will be practiced. The monitoring of the Aeolus data product quality and instrument performance, the refinement of retrieval algorithms or the evolution of the processors strongly benefit from monitoring of Aeolus data with NWP models. This NWP monitoring provides temporally continuous comparisons of Aeolus observations with NWP models for all altitudes and over all geographical regions, and this with almost immediate feedback on the data quality. The large potential of this approach was already successfully demonstrated during the commissioning phase, where a systematic error in Rayleigh winds for one specific range gate was spotted by comparison of several orbits of Aeolus data with the ECMWF model. This bias in Rayleigh winds could be traced back to one suspicious pixel on the Rayleigh ACCD. Investigations for correcting these effects on pixel level are on-going. This clearly demonstrates the successful approach of combining the expertise on the instrument, retrieval algorithms, and NWP monitoring. An overview of the DISC activities as well as first results from instrument performance and data product quality will be discussed.

Soon after its successful launch in August 2018, the spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) on-board ESA's Earth Explorer satellite Aeolus has demonstrated to provide atmospheric wind profiles on a global scale. Being the first ever Doppler wind lidar instrument in space, ALADIN contributes to the improvement in numerical weather prediction by measuring one component of the wind vector along the instrument's line-of-sight from ground throughout the troposphere up to the lower stratosphere. The measurements are performed with the single payload ALADIN, which is a direct-detection Doppler wind lidar operating at an ultraviolet wavelength of 354.8 nm. ALADIN uses a frequency-tripled Nd:YAG laser, a large 1.5 m Cassegrain telescope, and 2 interferometers for detection of the Doppler frequency shift from molecules and particles. Challenges during the development of the ALADIN instrument are highlighted and first results are discussed including validation with an airborne instrument demonstrator.

VirES is a Virtual workspace for Earth-observation Scientists, a service provided by the European Space Agency (ESA). VirES has firstly been established for ESA's magnetic field mission Swarm as "VirES for Swarm" and has been extended to ESA's atmospheric dynamics mission Aeolus, which is scheduled for launch in August 2018. The service is developed by the Austrian IT company EOX in strong collaboration with missions' scientists. VirES is a web-based service (https://vires.services) that enables scientists to discover, visualize, select and download data of Earth-observation missions through an easy to operate graphical user interface. "VirES for Aeolus" will provide access to Aeolus L1B, L2A, L2B, L2C products and auxiliary data. The first version 1.0 passed acceptance tests in April 2018 and developments towards Version 1.1 (launch version) are in progress. The service is planned to be accessible for public use as soon as the mission's commissioning phase is completed and first data products are released by ESA.

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.

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.

Since its inception six decades ago, astrobiology has diversified immensely to encompass several scientific questions including the origin and evolution of Terran life, the organic chemical composition of extraterrestrial objects, and the concept of habitability, among others. The detection of life beyond Earth forms the main goal of astrobiology, and a significant one for space exploration in general. This goal has galvanized and connected with other critical areas of investigation such as the analysis of meteorites and early Earth geological and biological systems, materials gathered by sample-return space missions, laboratory and computer simulations of extraterrestrial and early Earth environmental chemistry, astronomical remote sensing, and in-situ space exploration missions. Lately, scattered efforts are being undertaken towards the R&D of the novel and as-yet-spaceunproven 'life-detection' technologies capable of obtaining unambiguous evidence of extraterrestrial life, even if it is significantly different from Terran life. As the suite of space-proven payloads improves in breadth and sensitivity, this is an apt time to examine the progress and future of life-detection technologies.

Since its inception six decades ago, astrobiology has diversified immensely to encompass several scientific questions including the origin and evolution of Terran life, the organic chemical composition of extraterrestrial objects, and the concept of habitability, among others. The detection of life beyond Earth forms the main goal of astrobiology, and a significant one for space exploration in general. This goal has galvanized and connected with other critical areas of investigation such as the analysis of meteorites and early Earth geological and biological systems, materials gathered by sample-return space missions, laboratory and computer simulations of extraterrestrial and early Earth environmental chemistry, astronomical remote sensing, and in-situ space exploration missions. Lately, scattered efforts are being undertaken towards the R&D of the novel and as-yet-space-unproven life-detection technologies capable of obtaining unambiguous evidence of extraterrestrial life, even if it is significantly different from Terran life. As the suite of space-proven payloads improves in breadth and sensitivity, this is an apt time to examine the progress and future of life-detection technologies., 6 pages, the white paper was submitted to and cited by the National Academy of Sciences in support of the Astrobiology Science Strategy for the Search for Life in the Universe

After water vapor and carbon dioxide, methane ($CH_4$)is the most abundant greenhouse gas in the Earth atmosphere. The new generation space borne Lidar mission MERLIN (Methane Remote Sensing Lidar Mission) will make very sensitive measurements of the $CH_4$ distribution with unprecedented quality, with an accuracy

The formation of compartments, through which an internal environment is separated from its surrounding medium, is essential for all modern life. Compartmentalisation enables specific molecules to be concentrated, thus facilitating biochemistry. The existence of individuals also facilitates competition for survival, and provides a driving force for evolution. Modern cell membranes are incredibly complex structures, containing a myriad of lipid species, alongside various structural and functional proteins. However, protocells may not have had access to or required such a wide range of components to survive. Therefore the earliest membranes may have been composed of simple amphiphiles or simple mixtures of amphiphiles. A number of computationally intensive methods have proved ineffective at predicting the properties of these systems and so we developed chemoinformatics approaches to try to uncover the essential requirements for such molecules. Methods for generating compound libraries will be described as well as refinements to reduce the number of molecules generated or to control the similarity of the molecules to the known lipids of modern biology. The goal of this work is to understand which classes of simpler amphiphiles can self-assemble to form compartments and what the properties of the earliest membranes may have been. The limited molecular complexity of these amphiphiles may have enabled a variety of adaptive physical properties, such as enhanced permeability. Whilst this may compromise the level of protection from the external environment compared with modern biology, more permeable barriers could have facilitated more rapid introduction of greater diversity of chemical species and process. The generation of a novel large-scale library provides excellent coverage of chemical space, and the characterisation of these molecules provides insight into the aggregation properties of these chemical species.

How the transition of disorganized, inanimate matter to organized, living systems took place on our planet and might have occurred on other bodies of our solar system or elsewhere in the universe is one of the fundamental questions studied in the field of Astrobiology. The only instance of life known so far is the terrestrial one, and all living organisms on Earth share many of the same biochemical foundations with respect to reproduction and metabolism. These biochemical foundations rely on a small pool of biomolecules, which represent a minute subset of plausible structural analogs, which themselves form only a very small fraction of all possible chemical compounds in chemical space. We believe that one key to understanding the origins of life is to study biomolecules in context of their surrounding neighborhood in chemical space. Using unique software tools, so-called structure generators, we are able to construct well defined subsets of chemical space exhaustively. These virtual compound libraries are then computationally analyzed with respect to the physico-chemical properties of their constituents. In this talk some basic algorithmic aspects of generating molecular structures are presented, results concerning the amino acid alphabet, nucleotide analogs and the core of intermediary metabolism are summarized, and perspectives of ongoing studies are outlined.

Starting from the data obtained in 2014 by the COSAC instrument on board the lander of the ROSETTA mission this presentation shows problems and sketches solutions towards the identification of small organic compounds detected by mass spectrometers on future astrobiology-related exploration missions for solar system targets. Several approaches towards mass spectrometry-based compound identification and life detection are discussed. It is concluded that machine learning and pattern recognition methods will play an important role for computationally separating samples of biotic and abiotic origin.

Biological information storage for life as we know it is carried out by the nucleic acids DNA and RNA. However, these may be optimized end-states for life on Earth, or there may be other types of molecules which are similarly capable of carrying out these functions, perhaps used in alien biochemistries or in earlier biochemical states. A number of these have already been synthesized in the lab, however the set of molecules compatible with this function may be far larger. Understanding this wider "chemical space" may give insights into what makes the biological isomers unique, as well as whether there are other isomers more easily accessed by abiotic chemistry.

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. SCIAMACHY's 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 standard spectral calibration of the SCIAMACHY detectors is done with an on-board Spectral Line Source (SLS) by comparing theoretical line positions with line positions retrieved during calibration measurements. However, the used PtCrNe lamp does not have enough strong lines in the SWIR range (channels 6 -8 ) upwards of 1000 nm. The retrieval of in-flight line positions is additionally hampered by many damaged detector pixels of the SWIR detectors. An analysis of the mission data showed that for channels 6-8 no in-flight correction of the on-ground spectral calibration can be done with the standard approach, even at the beginning of the mission with a significant lower number of damaged pixels. We therefore started a study to investigate an alternative spectral calibration approach. In this approach a highly resolved reference spectrum is fitted with a DOAS like algorithm to retrieve the wavelength for each detector pixel. This approach was already tested by us for the Sentinel-4 UVN and the former Earth Explorer 8 candidate mission CarbonSat. For the method to work it is essential to have a good knowledge of the in-flight spectral response function and its change over time. Preliminary results show that the shape of the response function deviates from the current assumption of a Gaussian. For a successful fit it is also necessary to handle the many outliers caused by the bad pixels in an appropriate way. In this paper we present the first results of our investigations, focussing on channel 6 and the methane retrieval window.

SCIAMACHY is a passive imaging spectrometer mounted on board ESA’s ENVISAT satellite to probe a large number of atmospheric trace gas species, such as methane, and their global distribution and evolution. Methane (CH4) is particularly interesting as it is one of the most abundant greenhouse gas in the Earth atmosphere. To analyze SCIAMACHY methane measurements, we used the DLR BIRRA (Beer InfraRed Retrieval Algorithm) to retrieve nadir methane concentrations from its infrared spectra in channel 6. By integrating the DLR BIRRA code into ESAs operational Level 2 processor, we expanded it to include atmospheric CH4 column measurements. We have therefore performed an extensive test and verification operation. Our tests are based on separate comparisons with existing space and ground-based obtained measurements of methane column density. We present here our strategy for quality check of this first version of a CH4 product. We will further discuss specific geographical areas we used to validate the products.

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. SCIAMACHY�s 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. Currently Version 9 of the Level 0-1 processor is being implemented. It will include An updated degradation correction Several improvements in the SWIR spectral range like a better dark correction, an improved dead & bad pixel characterisation and an improved spectral calibration Improvements to the polarisation correction algorithm Improvements to the geolocation by a better pointing characterisation Additionally a new format for the Level 1b and Level 1c will be implemented. The version 9 products will be available in netCDF version 4 that is aligned with the formats of the GOME -1 and Sentinel missions. We will present the first results of the new Level 0-1 processing in this paper.

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 planned 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 by SCIAMACHY, data processors are still being updated. This presentation will highlight three new developments that are currently being incorporated into the forthcoming Version 7 of ESA’s operational Level 2 processor: 1. Tropospheric BrO, a new retrieval based on the scientific algorithm of (Theys et al., 2011). This algorithm had originally been developed for the GOME-2 sensor and was later adapted for SCIAMACHY. 2. Improved cloud flagging using limb measurements (Liebing, 2015). Limb cloud flags are already part of the SCIAMACHY L2 product. They are currently calculated employing the scientific algorithm developed by (Eichmann et al., 2015). Clouds are categorized into four types: water, ice, polar stratospheric and noctilucent clouds. High atmospheric aerosol loadings, however, often lead to spurious cloud flags, when aerosols had been misidentified as clouds. The new algorithm will better discriminate between aerosol and clouds. It will also have a higher sensitivity w.r.t. thin clouds. 3. A new, future-proof file format for the level 2 product based on NetCDF. The data format will be aligned and harmonized with other missions, particularly GOME and Sentinels. The final concept for the new format is still under discussion within the SCIAMACHY Quality Working Group.

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 planned in-orbit lifetime of five years before the communication to ENVISAT was severed in April 2012, and the mission entered its postoperational phase F. The SCIAMACHY Quality Working Group (SQWG) was established in 2007. The group coordinates evolution of algorithms and processors, aiming at improving the quality of the operational data products. University of Bremen (IUP), BIRA, DLR-IMF, SRON (Netherlands Institute for Space Research) and KNMI (The Royal Netherlands Meteorological Institute) are the members providing expertise in this group. In order to preserve the best quality of the outstanding data obtained by SCIAMACHY, data processors are still being updated. This presentation will highlight new developments that are currently being incorporated into the forthcoming Version 7 of ESA’s operational Level 2 processor

From its very beginnings the development of algorithms for the enumeration of chemical space was closely related to NASA's early exobiology activities. The complete and non-redundant generation of all connectivity isomers corresponding to a given molecular formula was part of the DENDRAL program, established in the mid-1960s. In the 1970s mathematicians provided new techniques to increase efficiency of the first approaches, and starting with the 1990's implementations became available as software packages for customary computers. Recently these methods have been rediscovered for application in astrobiology and origins of life research, particularly for generating and analyzing virtual chemical compound libraries of amino acids and nucleotide analogs.

Understanding the origins of life is a central question of Astrobiology. Computer methods offer unique means to approach this challenge. In order to obtain a better understanding of the selection rules which guided chemical and early biochemical evolution, our approach is to computationally generate exhaustive sets of biomolecule analogues, to calculate their physico-chemical properties, and to simulate adaptive processes that might have led to the biochemical foundations of life as we know it. Results on the amino acid alphabet will be presented and ongoing studies of nucleotide analogue libraries will be discussed.

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. Limb and nadir geometries were the main operation modes for the retrieval of scientific data. The new version 6 of ESA's level 2 processor now provides for the first time an operational algorithm to combine measurements of these two geometries in order to generate new products. As a first instance the retrieval of tropospheric NO2 has been implemented based on IUP-Bremen's reference algorithm [1]. We will detail the single processing steps performed by the operational limb-nadir matching algorithm and report the results of comparisons with the scientific tropospheric NO2 products of IUP and TEMIS [2]. The operational limb-nadir matching has been programmed in a generic way, meaning that the application to further trace gas species will require moderate adaptations only. Retrieval of tropospheric BrO by limb-nadir matching is planned for the next operational processor version. References: [1] A. Hilboll, A. Richter, A. Rozanov, Ø. Hodnebrog, A. Heckel, S. Solberg, F. Stordal, and J. P. Burrows. Retrieval of tropospheric NO2 columns from SCIAMACHY combining measurements from limb and nadir geometries. Atmos. Meas. Tech. Discuss., 5, 5043-5105, 2012. [2] K. F. Boersma, H. J. Eskes and E. J. Brinksma: Error Analysis for Tropospheric NO2 Retrieval from Space. J. Geophys. Res., 109 D04311, 2004.

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

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) was 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 ESA's ENVISAT platform. After the platform failure in April 2012, the space agencies continue to support the operational product evolution in the frame of the SCIAMACHY Quality Working Group and Expert Support Laboratory. Note that SCIAMACHYs in-orbit lifetime was twice the planned lifetime. The instrument was designed to measure column densities and vertical profiles of trace gas species in the troposphere, in the stratosphere and in the mesosphere (Bovensmann et al., 1999). It can detect a wide range of trace gases and can provide information about aerosols and clouds. The operational processing of SCIAMACHY aims to deliver continuously high quality data products to the scientific community. It 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. A better degradation correction was implemented that now takes into account the dependence of transmission on the incidence angle of light on the mirror. The stray light correction now uses a matrix correction scheme for all channels. The handling of calibration data was completely overhauled: instead of using a collection of files we use a database that allows proper traceability of used calibration data for any given Earth measurement and that allows immediate quality checks. With the improved Level 1 products it is expected that the Level 2 products are also improved (see related contribution on operational Level 2 products from SCIAMACHY). Both datasets were re-processed. Here we will report on the quality of the Level 1 data. In addition future planned improvements such as a new bad pixel mask in the SWIR channel will be discussed.

Astrobiology is the study of the origin, distribution and future of life in the universe, biomolecules are molecules produced by living organisms. This talk reviews known facts and open questions about biomolecules in the context of Astrobiology and introduces a research project on "Creating a Reference Set of Amino Acids Structures for Use in Multiple Astrobiology Investigations" that tries to find answers using computational methods.

In sommer of 2010 version 6 of the SCIAMACHY operational processor is planned to be delivered to ESA. The SCIAMACHY Quality Working Group recommended an implementation of the formaldehyde (HCHO) and glyoxal (CHOCHO) vertical columns into version 6 of the off-line processor. They are formed during the oxidation of volatile organic compounds (VOCs) emitted by plants, anthropogenic activities, and biomass burning. Due to a rather short lifetime of formaldehyde and glyoxal, their distribution maps, obtained by the SCIAMACHY, represent the emission fields of their precursors, VOCs. The descriptions of reference algorithm as well as all the cross-sections for formaldehyde and glyoxal retrievals were delivered to DLR by the Belgian Institute for Space Aeronomy (BIRA) (I. De Smedt, 2008) and by the IUP (F. Wittrock, 2006), respectively. Both retrievals are based on the DOAS technique. For the formaldehyde retrieval the spectral region of 328.5-346 nm was recommended. The absorption cross-sections of HCHO, O3, NO2, BrO, OClO, a Ring spectrum and a polynomial of the fifth order are included into the fitting procedure. Before conversion to the vertical columns, the slant columns have to be normalized by subtracting the slant columns measured over Pacific ocean, where the only source of formaldehyde is methane oxidation. After the conversion to the vertical columns, part of HCHO removed during the previous procedure has to be re-added to the final vertical column by adding of the mean vertical column calculated by the tropospheric chemistry model IMAGES (J.-F. Müller, 1995). This normalization is necessary to compensate for the offset introduced by the solar reference measurements and interferences by other absorbers. For the determination of glyoxal columns, the spectral region 435-457 nm was selected. In this case, the absorption cross-sections of CHOCHO, O3, NO2, H2O, O4, a Ring spectrum and a cubic polynomial are included in the fitting procedure. The normalization of the CHOCHO slant columns is performed in the same way as for formaldehyde.

Limb measurements performed by the Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) on the ENVISAT satellite enable a retrieval of stratospheric profiles for various trace gases on a global scale. The operational SCIAMACHY L1b-2 processor was developed on behalf of ESA at German Aerospace Center (DLR). The more sophisticated, so called “scientific”, version of the operational processor without any operational constraints is developed parallel and give us free hand for all sorts of experiments. In this paper we analyze different inversion models suitable for the ozone retrieval from SCIAMACHY limb measurement data. This analysis is performed by means of the scientific processor. The inversion algorithms comprise differential and absolute radiance models with multiple spectral windows as well as the radiance model together with Chappuis triplets. The sensitivity of the retrieval algorithm in dependance on the chosen inversion model is investigated and discussed. Since till now the operational ozone limb retrieval was performed up to 45 km only, special attention is given to the upper stratosphere (45 - 65 km). A large class of regularization methods as for instance, the Tikhonov regularization, the iteratively regularized Gauss-Newton method, the regularizing Levenberg-Marquardt method, the asymptotical regularization approach and the regularized total least-squares method can be used in the scientific processor. Their efficiency is tested and test results are presented in the paper. The impact of a Picard iteration model for simulating the radiating transfer in a two-dimensional spherical shell atmosphere is also discussed.

Due to the strict requirements regarding the computation time, the off-line processor of the SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY) instrument is forced to operate with several approximations. These approximations are incorporated in both the forward and the inversion models. Here we would like to investigate the impact of these approximations. The main simplification which is done in the forward model concerns the treatment of the multiple scattering. Only the single scattering term accounts on the actual atmospheric state, and it is apparent that this approximation is valid if the a priori state is sufficiently close to the true atmospheric state. Note that not only the forward model but also the Jacobian are affected by the multiple scattering approximation. The regularization method which is used in the inversion process is the Tikhonov regularization with an a priori regularization parameter. This means that the regularization parameter, which should balance the residual and the constraint, is chosen in advance and is not correlated with the true measurement. The a priori selection of the regularization parameter is performed for synthetic data, and therefore the method can be problematic especially when the measurement is affected by large systematic errors. The scientific processor developed at the German Aerospace Center is the counterpart of the offline processor, which is not, however, limited by any time constraints. This brings the opportunity to employ more time-consuming approaches and study their impact. The processor uses the Picard iteration method to simulate the radiance field in a full spherical atmosphere and includes polarization as well as Ring effects. A large class of regularization methods as for instance, the Tikhonov regularization, the iteratively regularized Gauss-Newton method, the regularizing Levenberg-Marquardt method, the asymptotical regularization approach and the regularized total least-squares method can be used for a specific application. Here a comparison between limb retrieval results obtained by the operational and the scientific processor for the SCIAMACHY instrument is presented.

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

In this poster we present a comparison between limb retrieval results obtained by using the operational and a scientific processor for the SCIAMACHY instrument. The scientific processor uses as forward model, a Picard iteration model, and as inversion model, direct and iterative regularization methods. By contrast, the operational processor uses an approximate forward model with multiple scattering correction and the Tikhonov regularization with a constant value of the regularization parameter.

A general mathematical description, mostly in terms of graph theory, is given for reactions of organic chemistry. The corresponding computer program generates all products that can result from a given set of starting materials interacting according to a given set of reaction schemes. Example reactions from combinatorial chemistry, synthetic organic chemistry, and mass spectroscopic structure elucidation are considered in detail.

Two important tasks in computer-aided structure elucidation (CASE) are the generation of candidate structures from a given molecular formula, and the ranking of structure candidates according to compatibility with an experimental spectrum. Candidate ranking with respect to electron impact mass spectra is based on virtual fragmentation of a candidate structure and comparison of the fragments’ isotope distributions against the spectrum of the unknown compound, whence a structure–spectrum compatibility matchvalue is computed. Of special interest is the matchvalue’s ability to distinguish between the correct and false constitutional isomers. Therefore a quality score was computed in the following way: For a (randomly selected) spectrum–structure pair from the NIST MS library all constitutional isomers are generated using the structure generator MOLGEN. For each isomer the matchvalue with respect to the library spectrum is calculated, and isomers are ranked according to their matchvalues. The quality of the ranking can be quantified in terms of the correct structure’s relative ranking position (RRP). This procedure was repeated for 100 randomly selected spectrum–structure pairs belonging to small organic compounds. In this first approach the RRP of the correct isomer was 0.27 on average.