SCIAMACHY: The new Level 0-1 Processor

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

Stratospheric CH4 and CO2 profiles derived from SCIAMACHY solar occultation measurements

Stratospheric profiles of methane (CH$_{4}$) and carbon dioxide (CO$_{2}$) have been derived from solar occultation measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The retrieval is performed using a method called onion peeling DOAS (ONPD), which combines an onion peeling approach with a weighting function DOAS (differential optical absorption spectroscopy) fit in the spectral region between 1559 and 1671 nm. By use of updated pointing information and optimisation of the data selection as well as of the retrieval approach, the altitude range for reasonable CH$_{4}$ could be broadened from 20 to 40 km to about 17 to 45 km. Furthermore, the quality of the derived CO$_{2}$ has been assessed such that now the first stratospheric profiles (17–45 km) of CO$_{2}$ from SCIAMACHY are available. Comparisons with independent data sets yield an estimated accuracy of the new SCIAMACHY stratospheric profiles of about 5–10% for CH$_{4}$ and 2–3% for CO$_{2}$. The accuracy of the products is currently mainly restricted by the appearance of unexpected vertical oscillations in the derived profiles which need further investigation. Using the improved ONPD retrieval, CH$_{4}$ and CO$_{2}$ stratospheric data sets covering the whole SCIAMACHY time series (August 2002–April 2012) and the latitudinal range between about 50 and 70° N have been derived. Based on these time series, CH$_{4}$ and CO$_{2}$ 2 trends have been estimated. CH$_{4}$ trends above about 20 km are not significantly different from zero and the trend at 17 km is about 3 ppbvyear$^{-1}$. The derived CO$_{2}$ trends show a general decrease with altitude with values of about 1.9 ppmvyear$^{-1}$ at 21 km and about 1.3 ppmvyear$^{-1}$ at 39 km. These results are in reasonable agreement with total column trends for these gases. This shows that the new SCIAMACHY data sets can provide valuable information about the stratosphere

SCIAMACHY: Level 0-1 Processor V9 and Phase F 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

The SPARC water vapour assessment II: comparison of annual, semi-annual and quasi-biennial variations in stratospheric and lower mesospheric water vapour observed from satellites

In the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), the amplitudes and phases of the annual, semi-annual and quasi-biennial variation in stratospheric and lower mesospheric water were compared using 30 data sets from 13 different satellite instruments. These comparisons aimed to provide a comprehensive overview of the typical uncertainties in the observational database which can be considered in subsequent observational and modelling studies. For the amplitudes, a good agreement of their latitude and altitude distribution was found. Quantitatively there were differences in particular at high latitudes, close to the tropopause and in the lower mesosphere. In these regions, the standard deviation over all data sets typically exceeded 0.2 ppmv for the annual variation and 0.1 ppmv for the semi-annual and quasi-biennial variation. For the phase, larger differences between the data sets were found in the lower mesosphere. Generally the smallest phase uncertainties can be observed in regions where the amplitude of the variability is large. The standard deviations of the phases for all data sets were typically smaller than a month for the annual and semi-annual variation and smaller than 5 months for the quasi-biennial variation. The amplitude and phase differences among the data sets are caused by a combination of factors. In general, differences in the temporal variation of systematic errors and in the observational sampling play a dominant role. In addition, differences in the vertical resolution of the data, the considered time periods and influences of clouds, aerosols as well as non-local thermodynamic equilibrium (NLTE) effects cause differences between the individual data sets

FDR4ATMOS (Task A): Improving SCIAMACHY Level 1 and add calibrated lunar data

The project FDR4ATMOS (Fundamental Data Records in the domain of satellite Atmospheric Composition) has been initiated by the European Space Agency (ESA). Task A of the project covers the improvement of the SCIAMACHY Level 1b degradation correction, with the aim to remove ozone trends from the SCIAMACHY Level 2 data set that were introduced during the development of baseline version 9 (both data sets not released). We will also, for the first time, add calibrated lunar data to Level 1, covering the whole spectral range of SCIAMACHY and the full mission time. The SCIAMACHY processing chain for better Ozone total column data: After the full re-processing of the SCIAMACHY mission with the updated processor versions, the validation showed that the total Ozone column drifted downward by nearly 2% over the mission lifetime. This drift is likely caused by changes in the degradation correction in the Level 1 processor, that led to subtle changes in the spectral structures. These are misinterpreted as an atmospheric signature. We updated the Level 0-1 processor accordingly and a full mission re-processing was done. As a major improvement we additionally incorporated calibrated lunar data in the SCIAMACHY Level 1b product. In the new Level 1b product we will provide the individual scans of the moon as well as disk integrated and calibrated lunar irradiance and reflectance. The instrument performed regular lunar observations building up a unique 10 year data set of lunar spectra from the UV to the SWIR with moderately high spectral resolution. SCIAMACHY scanned the full lunar disk and over the ten year mission time made 1123 observations of the moon. Most satellites can only observe the moon under very specific geometries due to instrument-viewing and orbit restrictions. SCIAMACHY, however, with a two mirror pointing system was much less constrained and was able to observe the moon under an extreme large variation of geometries (especially during dedicated lunar observation campaigns), allowing it thus potentially to tie different satellites and geometry observations together. During the individual lunar observations, SCIAMACHY only saw a small slice of the Moon and scanned over the moon in order to obtain data for the full disk. We combined the individual calibrated scans, correcting for scan speed and the fact the Moon does not fill the entire slit length. The calculation of distance-normalized lunar reflectances did not require an external solar spectrum, but used solar measurements of SCIAMACHY itself. This version of Level 1 will also be the first one that replaces the ENVISAT byte stream format with the netCDF format that is aligned with the product format of other atmospheric sensors like the Sentinels The paper will present the improvements of the Level 1 product, the results of the quality control and validation

The SPARC water vapour assessment II: biases and drifts of water vapour satellite data records with respect to frost point hygrometer records

Satellite data records of stratospheric water vapour have been compared to balloon-borne frost point hygrometer (FP) profiles that are coincident in space and time. The satellite data records of 15 different instruments cover water vapour data available from January 2000 through December 2016. The hygrometer data are from 27 stations all over the world in the same period. For the comparison, real or constructed averaging kernels have been applied to the hygrometer profiles to adjust them to the measurement characteristics of the satellite instruments. For bias evaluation, we have compared satellite profiles averaged over the available temporal coverage to the means of coincident FP profiles for individual stations. For drift determinations, we analysed time series of relative differences between spatiotemporally coincident satellite and hygrometer profiles at individual stations. In a synopsis we have also calculated the mean biases and drifts (and their respective uncertainties) for each satellite record over all applicable hygrometer stations in three altitude ranges (10–30 hPa, 30–100 hPa, and 100 hPa to tropopause). Most of the satellite data have biases <10 % and average drifts <1 % yr−1 in at least one of the respective altitude ranges. Virtually all biases are significant in the sense that their uncertainty range in terms of twice the standard error of the mean does not include zero. Statistically significant drifts (95 % confidence) are detected for 35 % of the ≈ 1200 time series of relative differences between satellites and hygrometers

The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC) and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards) and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically  ∼  1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0–1 % yr−1. In particular, MLS shows a trend of between 0.5 % yr−1 and 0.7 % yr−1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr−1 (at Mauna Loa, Hawaii) and −0.1 % yr−1 (at Lauder, New Zealand)

GOME Ozone Profiles: Improvement and Validation

Height-resolved ozone information on a global scale is required forthe detection of changes in the atmospheric ozone distribution and for researchinto the underlying chemical and dynamical processes. The Global OzoneMonitoring Experiment (GOME) makes an important contribution in thisfield. GOME aboard ESA´s ERS-2 satellite measures the reflected andbackscattered radiation from the Earth in the ultraviolet and visiblespectral range at moderate spectral resolution in nadir viewinggeometry. Vertical ozone profiles can be derived fromtop-of-atmosphere nadir observations using the FUll Retrieval MethodFURM, which is based upon an advanced Optimal Estimation inversionscheme, using the Kozlov-information-matrix method. In the frameworkof this thesis this algorithm was adapted for routineretrieval of GOME ozone profiles. The calibration of the GOMEinstrument was discussed with respect to its impact on ozone profileretrieval, presenting an effective calibration error correctionscheme. The choice of a-priori ozone profiles was investigated, showingthat not only the mean profiles but also there statisticalproperties reflecting the variability of ozone are important. Anup-to-date, statistically correct ozone climatology is needed.A-priori temperature and pressure profiles have to be taken fromassimilated meteorological fields. The ozone profiles have beenvalidated on a global scale by comparison with measurements of theHALogen Occultation Experiment (HALOE). A good agreement within 10%between 15 and 35 km altitude for most seasons and regions isachieved. Total ozone calculated from integrated profiles have beenvalidated with Dobson measurements in the Northern mid-latitudes, theyagree to within -2% with seasonal variation. With the results ofthis work, the GOME ozone profile retrieval algorithm FURM can be (andalready is) used for routine observation and scientific investigationof the ozone layer

Scan-angle dependent degradation correction with the scanner model approach

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) is a grating spectrometer in the UV-Vis-NIR spectral range on-board EnviSat (2002-2012). SCIAMACHY observes Earth’s atmosphere in nadir, limb and occultation geometry. The throughput of the instrument is monitored end-to-end by regular observations of the sun and the internal white light source (WLS). A new (scan-angle dependent) degradation correction is implemented as a joint effort of SRON (scanner model and algorithm prototype), IUP Bremen (operational m-factors) and MF-ATP-DLR (implementation into the L0-1b processor). Described by this technical note is the setup of the operational m–factor calculation, implemented for the next L0-L1b processor version (Version 8). For the degradation correction of Version 8, the radiometric (and the polarization) calibration approach has been changed. Both are split in a scanner unit part and an optical bench module (OBM, including the detectors) part. The scanner unit is described by a physical model of its components, which includes contamination layers on top of the optical components. The increase of these contamination layers accounts to a large extent for the observed degradation of the instrument

GOME Ozonprofile: Weiterentwicklung und Validierung

Height-resolved ozone information on a global scale is required forthe detection of changes in the atmospheric ozone distribution and for researchinto the underlying chemical and dynamical processes. The Global OzoneMonitoring Experiment (GOME) makes an important contribution in thisfield. GOME aboard ESA´s ERS-2 satellite measures the reflected andbackscattered radiation from the Earth in the ultraviolet and visiblespectral range at moderate spectral resolution in nadir viewinggeometry. Vertical ozone profiles can be derived fromtop-of-atmosphere nadir observations using the FUll Retrieval MethodFURM, which is based upon an advanced Optimal Estimation inversionscheme, using the Kozlov-information-matrix method. In the frameworkof this thesis this algorithm was adapted for routineretrieval of GOME ozone profiles. The calibration of the GOMEinstrument was discussed with respect to its impact on ozone profileretrieval, presenting an effective calibration error correctionscheme. The choice of a-priori ozone profiles was investigated, showingthat not only the mean profiles but also there statisticalproperties reflecting the variability of ozone are important. Anup-to-date, statistically correct ozone climatology is needed.A-priori temperature and pressure profiles have to be taken fromassimilated meteorological fields. The ozone profiles have beenvalidated on a global scale by comparison with measurements of theHALogen Occultation Experiment (HALOE). A good agreement within 10%between 15 and 35 km altitude for most seasons and regions isachieved. Total ozone calculated from integrated profiles have beenvalidated with Dobson measurements in the Northern mid-latitudes, theyagree to within -2% with seasonal variation. With the results ofthis work, the GOME ozone profile retrieval algorithm FURM can be (andalready is) used for routine observation and scientific investigationof the ozone layer