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形態: カラー図版あり, Physical characteristics: Original contains color illustrations, Accepted: 2016-12-30, 資料番号: PA1710008000

SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) on-board the ESA Envisat satellite platform provided daily solar spectra in the wavelength region from 0.24 μm to 2.4 μm. The instrument was operating for nearly a decade from August 2002 to April 2012. This document reports on the validation of the SCIAMACHY solar spectral irradiances (SSI) in its data version 8. Like other UV satellite sounders, the SCIAMACHY spectrometer suffers from optical degradation due to polymerisation of optical surfaces from the harsh UV radiation in space (e.g. Bramstedt et al., 2009; DeLand et al., 2012; Krijger et al., 2014). In data version 8 of SCIAMACHY a physical model of the scanner unit was implemented to provide a degradation correction (Bramstedt et al., 2009; Krijger et al., 2014). Comparisons with several other established solar reference spectra show agreement to within 4 % in most parts of the visible and near infrared from 350 to 1400 nm.

The MEthane Remote sensing Lidar missioN (MERLIN) aims at demonstrating the spaceborne active measurement of atmospheric methane, a potent greenhouse gas, based on an Integrated Path Differential Absorption (IPDA) nadir-viewing LIght Detecting and Ranging (Lidar) instrument. MERLIN is a joint French and German space mission, with a launch currently scheduled for the timeframe 2021/22. The German Space Agency (DLR) is responsible for the payload, while the platform (MYRIADE Evolutions product line) is developed by the French Space Agency (CNES). The main scientific objective of MERLIN is the delivery of weighted atmospheric columns of methane dry-air mole fractions for all latitudes throughout the year with systematic errors small enough (

This paper reports on the evaluation of long-term cloud products as retrieved from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument with the DLR/ESA processor in its version 5.02 and the operational implementation of the Semi-Analytical CloUd Retrieval Algorithm SACURA. The comparison is performed against spaceborne and ground-based cloud data. The satellite records are the SCIAMACHY/SACURA in its scientific implementation and the Global retrieval of ATSR cloud parameters and evaluation (GRAPE) data set, in its version 3.2, generated for the nadir view of the Advanced Along-Track Scanning Radiometer (AATSR) instrument onboard ENVISAT. Ground-based data are derived from profiles of micro-pulse lidars, continuously operated at three Atmospheric Radiation Measurement (ARM) research facilities. They are, namely, North Slope Alaska, Southern Great Plains and Tropical Western Pacific-Nauru, located in three different latitude belts. It has been found that SCIAMACHY cloud top heights, inferred in the visible-near infrared, have a seasonal dependent overestimation in range 0.6–1.0 km when compared to the thermal infrared-derived AATSR cloud top heights. The comparison with the in-situ cloud retrievals reveals that SCIAMACHY cloud altitudes are more accurate for local cloud cover values > 0.6.

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.

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.

Studies have shown that chlorophyll fluorescence is directly linked to the photosynthetic efficiency of plants. The excess absorbed energy by leaves which has not been used in photosynthesis is re-emitted to the environment, either as heat or fluorescence. Therefore, any potential stress in plants is technically visible through monitoring fluorescence and the Solar-Induced plant Fluorescence (SIF) can thus be monitored as an indicator for vegetation growth and health status. SIF is a broad band spectral feature exhibiting two maxima at about 680 and 740 nm respectively, also known as red and far-red SIF. In the recent decades, there have been several studies addressing SIF, its importance and approaches to measure its value over vegetated regions. Among several measurement approaches, satellite-based remote sensing of SIF is particularly valuable, since the covered (spatial) area can be explicitly larger than is the case with in-situ measurements. With current space-borne instruments, even a full global coverage is attainable within a few days. In the framework of this thesis, two novel methods have been developed, tested and utilized to retrieve SIF from hyper-spectral satellite measurements. In particular, the first developed method, makes use of the Fraunhofer absorption lines in the far-red spectral region (748.5 - 753 nm), to retrieve SIF via its in-filling effect on these absorption lines. However, the satellite-based remote sensing spectrometers, used in this work, typically exhibit an additive spectral feature, which is not fluorescence. This is often accompanying the actual SIF retrieval and can significantly deteriorate the results. To account for this effect, a correction method has been developed and is combined with the retrieval algorithm. The model-based sensitivity studies confirmed the feasibility of the method to disentangle SIF from this additive feature. Additionally, the potential influences of the atmospheric and measurement conditions on the retrieval results have been assessed. Finally, the method has been applied to ten years of SCIAMACHY data and the retrieved results have been mapped on seasonal base. On a global scale, the obtained values are between 0 to 4 mW ma 2 sra 1 nma 1 . In absence of large area ground based validation data, final judgment of the results obtained in the framework of this study, is not possible. Alternatively, comparison of the achieved results with those published by the US National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has been performed. Despite some differences, the comparison also exhibited close results, both qualitatively and quantitatively. It should be noted that comparisons among the retrievals provided by other research groups (not only GSFC) over the same spatial region is also variable depending on the instruments and methods utilized (ranging on average from a few tenths to more than 4 mW ma 2 sra 1 nma 1 ). To further assess the reliability of retrieved SIF, monthly average values have been compared to ground-based flux-tower measurements of Absorbed Photosynthetically Active Radiation by plants (APAR) and Gross Primary Production (GPP), for a time span of several years. The agreement between the seasonal trends of SIF and these parameters was significant. Although the main focus of this PhD work was on retrieving SIF in the far-red wavelength region using a spectral micro-window, there are clear scientific benefits in having an estimation over the full spectral emission range of SIF. Therefore, the second retrieval method, developed in the framework of this work, was to obtain the full spectrum of the emitted SIF by retrieving the leaf and canopy parameters, utilizing a combination of two radiative transfer models. The model-based studies showed the feasibility of the method to retrieve SIF with high accuracy. Moreover, the first results of applying this approach on GOME-2 measurements demonstrated promising outcomes. Examples of the fit quality and retrieved SIF over two different vegetation coverage types have been presented in this thesis, showing clear applicability of the method to retrieve SIF over its full spectral emission range and the potential to derive other vegetation parameters (e.g. Chlorophyll content of the leaves and the so-called leaf area index).

Tropospheric ozone (O3) is one of the most important atmospheric pollutants close to surface. Remote sensing from satellites can provide consistent information of total ozone concentrations over large areas. By removing the stratospheric contributions using the Convective differential technique (CCD) on GOME/ERS-2 (1995- 2003), SCIAMACHY/Envisat (2002-2012), and GOME-2/MetOpA (2007-today) total O3 and cloud data it is feasible to estimate monthly mean tropospheric ozone columns over the tropics. The focus of this thesis was to create an improved CCD-IUP algorithm and to study variability and trends of the unique long-term record (1996-2015) on a regional and tropical scale. A detailed uncertainty analysis of the CCD-IUP algorithm has been performed along with a study upon the trend uncertainties from merging the datasets. Finally, the influence of ENSO on tropospheric ozone and the origin of its anomalies due to dynamics or emissions was investigated.

Volatile Organic Compounds (VOC) are key species in tropospheric chemistry, air pollution and climate. The largest fraction of VOC is emitted from natural sources, but significant contributions are also attributed to anthropogenic emissions and vegetation fires. Despite many studies estimating VOC amounts in the atmosphere and identifying their sources, the uncertainties in estimation are large. Glyoxal (CHOCHO), the smallest and most abundant of the alpha-dicarbonyls in the atmosphere, is an intermediate product in the oxidation of most VOC and an indicator of secondary aerosol formation in the atmosphere. Glyoxal in combination with other VOC (e.g. formaldehyde: HCHO) can be used for source identification of VOC. Glyoxal has been measured from space since 2003 by the SCIAMACHY and GOME-2 (MetOp-A) instruments and provides a unique global long-term dataset. The focus of this thesis is to retrieve glyoxal from measurements by the OMI instrument, to improve the SCIAMACHY and GOME-2 (MetOp-A and-B) analysis, and to investigate the resulting long-term datasets. The first part of this thesis focuses on the development of an improved retrieval for glyoxal from OMI measurements. From sensitivity tests, optimized fit parameters are determined. Two different approaches to reduce the interference of liquid water absorption over oceanic regions are evaluated, achieving a significant reduction of the number of negative columns over clear water regions. The impact of using different absorption cross-sections for water vapour is evaluated and only small differences are found. Finally, a high temperature (boundary layer ambient 294 K) absorption cross-section of nitrogen dioxide (NO2) is introduced in the DOAS retrieval to account for potential interferences with NO2 over regions with large anthropogenic emissions, leading to improved fit quality over these areas. In a sensitivity test, a spectrum of backscattered solar radiation over the Pacific Ocean is used as a reference spectrum, in order to reduce the offsets ("stripes") that sometimes are observed between viewing directions in the OMI instrument. The new retrieval has also been applied to measurements from SCIAMACHY and GOME-2 (MetOp-A and-B) instruments. Using the new CHOCHO dataset, the combination of four instruments provides more than 12 years of glyoxal measurements, which are used for the investigation of the temporal variability of VOC on a global scale. The link between vegetation, fires, anthropogenic activity, and glyoxal columns is investigated both globally and locally. This provides a general picture of where glyoxal comes from and what its temporal behaviour is depending on the region. CHOCHO and HCHO are used synergistically for the identification of VOC emission sources by computing their ratio and correlating it with indicators of biogenic emissions, fires, and anthropogenic activities, giving important information for assigning the ratios of glyoxal to formaldehyde to emission sources of VOC. In a case study, mapped averages are computed for a fire event in Russia between mid-July and mid-August 2010. Enhanced CHOCHO levels are found in close spatial and temporal proximity to elevated levels of fire radiate power, demonstrating that pyrogenic emissions can be clearly identified in the new CHOCHO data product. Also, for the first time long-range transport of glyoxal in the atmosphere has been clearly identified, where elevated levels of glyoxal follow the trajectories of simulated air masses. Finally, CHOCHO, HCHO, and NO2 columns have been retrieved from ground based measurements for two MAX-DOAS stations, which are part of the BREDOM network. Diurnal and seasonal variations have been computed for the three species and also the glyoxal to formaldehyde and formaldehyde to nitrogen dioxide ratios. The results have been compared to results from the satellite observations and with other studies.

Extraterrestrial meteoroids continuously enter the Earth's atmosphere. The bulk of the meteoric mass comes from about 220 µm sized particles coming mostly from asteroids in the asteroid belt between Mars and Jupiter. The particle size ranges from atomic scale particles to macroscopic bodies with a mass of several tons. The input rate is very uncertain, ranging from 2 to 300 tons per day. The meteoroids collide with the Earth's atmosphere at very high velocities (on the order of 10 to several 10 km per second), which leads to frictional heating of the meteoroids. This leads to full or partial ablation of the meteoroids in the upper atmosphere. Since the meteoroids consist partly of metals, this ablation leads to the formation of metal atom layers in the mesosphere and lower thermosphere (MLT). The metals are partly ionized in the MLT and metal ion layers are also formed. The MLT cannot easily be probed by in situ measurements. The pressure is too low for balloons to fly in this region, and the drag on satellites is too high there for stable satellite orbits. Therefore, only rocket-borne in situ measurements can be performed in the MLT. Because of this, remote sensing techniques are preferred to investigate the MLT. The atmospheric metal atoms and ions can be observed by re- mote sensing, because they are strong emitters of resonance fluorescence. Therefore, they are valuable tracer species for wave propagation and other transport processes in the MLT. In addition to their role as tracers, meteoric metals are also important for the chemistry in the middle atmosphere. Information on their absolute number densities is therefore of interest. The metals are involved in the formation of cluster ions and meteoric smoke particles (MSP), which are important for the heterogeneous condensation and nucleation of aerosols and clouds in the middle atmosphere. To estimate the impact of meteoric metals on the chemistry of the middle atmosphere, global observations are necessary. These need to be combined with models, which also include the yet undetectable particle species like, e.g., the metal molecules. Only in the last decades have global long-term satellite observations of the Earth's atmosphere with good local, temporal, and vertical resolution and cover- age been available. One of these data sets comes from the observations of SCIAMACHY/Envisat, which provides daily limb and nadir observations from 2002 to 2012. Beginning in mid-2008, a special limb observation mode for the investigation of the MLT was performed. This data set was used to retrieve the number densities of Mg, Mg , and Na from 2008-2012. Therefore, an existing retrieval algorithm for Mg and Mg was significantly improved and also extended for application in the visible spectral region for Na. The improved retrieval algorithm and the results for Mg, Mg and Na are presented and discussed in this thesis, and the metal's interaction with polar mesospheric clouds is investigated. Furthermore, a survey of spectral signatures of other target species for the retrieval algorithm has been carried out. The measurements have been compared with model results, which include the total daily meteoric mass influx as well as other measurement results. The seasonal, altitudinal and latitudinal variation of metal species is in good agreement with the most recent model results.

This thesis contributes to the understanding of the temporal evolution of stratospheric ozone as well as bromine monoxide, which is an ozone-depleting substance, during the decade 2002-2012. It is based on data from the satellite instrument SCIAMACHY on board of the European research satellite ENVISAT (2002-2012). Vertically resolved time series of ozone and bromine monoxide are investigated. A comprehensive trend analysis is performed using the concept of linear changes/trends. Long-term changes exhibited by the time series are identified and quantified. They are confirmed by instrument comparisons between SCIAMACHY and other measurements. Consistent with a decline of the stratospheric halogen load, decreases of BrO were found throughout the lower stratosphere. Increases of ozone in the upper stratosphere support the onset of an ozone recovery. In addition, an increase in the lower stratosphere as well as a pronounced decrease in the middle stratosphere were detected in tropical ozone. This co-occurrence of positive and negative changes was, until recently, a rather unexpected phenomenon.

This thesis addresses the issue of the accurate measurements of ozone distributions in the atmosphere obtained from different satellite borne atmospheric chemistry spectrometers which represent a major need and pre-requisite for determining whether the atmospheric burden of ozone depleting substances (ODS) are reduced in accordance to the Montreal Protocol, and valuable for long-term trend analysis to detect a subsequent ozone recovery. A consolidated and homogeneous long term dataset requires a careful analysis of the relevant parameters used in the retrievals, one important parameter is the absorption cross section. This work presents the procedures followed to correct the ozone cross section data of SCIAMACHY and GOME-2 spectrometers starting from original raw data (optical density spectra). Using the available versions of SCIAMACHY and GOME-2 FM cross sections in the retrieval of total ozone from each satellite leads to an overestimation in the total ozone by 3-5% and 8-9% compared to collocated GOME data, respectively. The quality of the revised temperature-dependent ozone absorption cross sections is investigated over GOME-2 and SCIAMACHY's entire spectral range. The revised data agree well within 3% with other published ozone cross sections and preserve the correct temperature dependence in the Hartley, Huggins, Chappuis and Wulf bands as displayed by the literature data. SCIAMACHY's total ozone columns retrieved using the revised cross section data are shown to be within 1% compared to the ozone amounts retrieved routinely from SCIAMACHY, which uses Bogumil et al. (2003) data but adjusted with a scaling factor of 5.3% and a wavelength shift of 0.08 nm. The total ozone column retrieved from the GOME-2/MetOp-A satellite using the new cross section data is within 1% compared to the ozone amounts retrieved from the standard retrieval performed for GOME-2. The study also presents a long term statistical trend analysis of total ozone datasets obtained from various satellites. A multi-variate linear regression was applied to annual mean zonal mean data using various natural and anthropogenic explanatory variables that represent dynamical and chemical processes which modify global ozone distributions in a changing climate. The study investigated the magnitude and zonal distribution of the different atmospheric chemical and dynamical factors contributing to long-term total ozone changes. The regression model included the Equivalent Effective Stratospheric Chlorine (EESC), the 11 year solar cycle, the Quasi-Biennial Oscillation (QBO), stratospheric aerosol loading describing the effects from major volcanic eruptions, the El Nino/ Southern Oscillation (ENSO), the Arctic and Antarctic Oscillation, and accumulated eddy heat flux (EHF), the latter representing changes due to the Brewer Dobson circulation. The total ozone column dataset used here comprises the SBUV/TOMS/OMI merged data (1979 - 2012) MOD V8.0. The analysis explained most of the ozone variability. The results show that QBO dominates the ozone variability in the tropics (7 DU) while at higher latitudes, the dynamical indices, AO/AAO and eddy heat flux, have substantial influence on total ozone variations by up to 10 DU. ENSO signal are more evident in the Northern Hemisphere. EESC is found to be a main contributor to the long-term ozone decline and the trend changes after the end of 1990s. A positive significant trend in total ozone columns is found after 1997 (between 1 and 8.2DU/decade) which points at the slowing of ozone decline and the onset of ozone recovery. The EESC based trends are compared with the trends obtained from the statistical piecewise linear trend (PWLT or hockey stick) model to examine the differences between both approaches. The results do indicate that the positive PWLT turnaround trends are larger than indicated by the EESC trends, however, they agree within 2-sigma, thus demonstrating the success of the Montreal Protocol phasing out of the ozone depleting substances (ODS). A sensitivity study is carried out by comparing the regression results, using different satellite merged datasets as well as the ground based measurements (1979 - 2012) in the regression analysis in order to investigate the uncertainty in the long-term trends due to different ozone datasets and data versions. All the datasets show almost identical pre-turnaround trends before 1979 for both EESC and PWLT approaches while the positive trends after 1997 are greatly influenced by the short-term variability. In spite of that, all datasets agree within 2-sigma fit parameters.

This dissertation presents a method for retrieving stratospheric aerosol extinction profiles from a global satellite data set. Ten years of limb radiance measurements with the instrument SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard the European environmental research satellite Envisat provides the unique opportunity to derive a stratospheric aerosol extinction data set over a long time period (2002 2012) with a good global coverage on a daily basis. Stratospheric sulfate aerosols have a significant impact on climate but the determination is still subject to large uncertainties. To improve our understanding of climate relevant processes an accurate determination of stratospheric aerosol properties is crucial. Deriving stratospheric aerosol extinction from limb radiance spectra requires complicated radiative transfer calculations. An algorithm based on a color-index approach combining normalized limb radiance spectra at 470 and 750 nm is applied to retrieve aerosol extinction profiles between 12 and 35 km altitude. A Mie phase function for typical background aerosols is implemented. The resulting SCIAMACHY stratospheric aerosol data set can serve as a foundation for climatological interpretation with respect to natural variability and anthropogenic impact.

The greenhouse gas carbon dioxide (CO2) is the most important human-made contributor to global warming. Despite its importance, our knowledge about its sources and sinks has large gaps. This limits a reliable climate prediction. Satellite observations of atmospheric CO2 combined with modelling can help to reduce these knowledge gaps. However, this requires to meet demanding accuracy and precision requirements for the satellite instrument, the retrieval algorithm and the model. One of the most important error sources for satellite retrievals of CO2 from reflected and backscattered solar radiation is unaccounted scattering by aerosols and clouds. In this context, the objectives of this thesis are to assess the quality of an existing satellite-based CO2 data set focussing on the investigation of these error source and to generate and validate an improved CO2 data set. The CO2 data bases on measurements of the passive remote sensing satellite instrument SCIAMACHY on-board ENVISAT, which has performed more than 10 years of radiance measurements in the short wave infrared spectral region. In the period 2003-2009, SCIAMACHY was the only satellite instrument measuring CO2 with high sensitivity down to the Earth's surface where the sources and sinks of CO2 are located. Therefore, the SCIAMACHY measurements are important in terms of generating an accurate global long-term atmospheric CO2 data set. Starting point for this thesis was an analysis of an existing 7-year (2003-2009) data set of column-averaged dry airmole-fraction of CO2, denoted XCO2, which was generated with version 2.1 of the Weighting Function Modified - Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm (WFMDv2.1). In order to study if differences between satellite-derived and modelled XCO2 are from scattering related retrieval errors, the SCIAMACHY XCO2 data set has been compared with the output of NOAA's modelling and assimilation system CarbonTracker. It has been investigated to what extent the differences between SCIAMACHY and CarbonTracker XCO2 are temporally and spatially correlated with global aerosol and cloud data sets. For this purpose, aerosol information from the European GEMS project and cloud information of NASA's CALIPSO satellite have been utilised. In this analysis, significant correlations with thin clouds especially over tropical and southern hemispheric regions have been found. The maximum temporal (r2=54%) and spatial (r2=46%) correlations have been found for Darwin, Australia. Large temporal correlations with thin clouds have also been observed over other regions of the Southern Hemisphere (e.g. r2=43% for South America and r2=31% for South Africa). Over the Northern Hemisphere the temporal correlations are typically much lower. An exception is India, where large temporal correlations with clouds and aerosols have also been found. These results indicate, that the SCIAMACHY WFMDv2.1 XCO2 data set suffers from scattering related retrieval errors caused especially by thin clouds. In order to reduce the scattering related retrieval errors, a new version of the WFM-DOAS retrieval algorithm has been developed (WFMDv2.2), which is based on a new cloud filtering and correction method. This method is based on radiances from the 1.4 µm strong water vapour absorption and the 0.76 µm O2-A band. The new version of the WFM-DOAS retrieval algorithm has been used to generate an improved SCIAMACHY XCO2 data set covering the period 2003-2009. The new data set has been validated using ground-based Fourier Transform Spectrometer (FTS) observations from the Total Carbon Column Observing Network (TCCON). The validation shows significant improvements of the new version WFMDv2.2 in comparison to the previous version WFMDv2.1. For instance, the standard deviation of the difference to TCCON over Darwin has been improved from 4 ppm to 2 ppm. Overall, the validation of the SCIAMACHY WFMDv2.2 XCO2 can be summarised by a single measurement precision of 3.8 ppm, a regional scale precision of monthly averages of 1.6 ppm and an estimated regional scale relative accuracy of 0.8 ppm. In order to investigate the differences between the new SCIAMACHY WFMDv2.2 XCO2 data set and CarbonTracker XCO2, a comparison between these data sets has been performed. It has been shown that the new data set agrees better with CarbonTracker than the previous version. The new SCIAMACHY XCO2 data set has already been used for interesting applications, for example, for an assessment of regional enhancements of atmospheric CO2 and trends over major anthropogenic CO2 source regions. The data set has also been used as part of the Ensemble Median Algorithm (EMMA). EMMA is a promising candidate for generating a CO2 data set which fulfils the demanding requirements needed to obtain information on regional CO2 surface fluxes via inversion modelling.

Water vapor is a unique atmospheric component, its distribution directly influences the chemistry and dynamics in different parts of the atmosphere. Water vapor observations from satellite borne instruments provide information on its long term seasonal and inter-annual variabilities and are important for climate projections and predictions. In the polar stratosphere, the water vapor amounts control the polar vortex temperatures and the formation temperature of the polar stratospheric clouds (PSCs). Water vapor has a strong relationship with the circulation and transport features related to polar vortex and its amounts define the Formation and deposition of PSCs. SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) aboard Envisat launched in 2002 has observed the Earth s atmosphere in nadir, limb and solar or lunar occultation geometry covering ultraviolet, visible and near ifrared (240-2830 nm) wavelength range at moderate spectral resolution. SCIAMACHY's measurements have provided total columns as well as vertical profiles of atmospheric constituents and climate parameters relevant to the ozone chemistry, air pollution and global climate change issues, from Troposphere upto the Mesosphere. This thesis contributes to exploit the lunar occultation spectra measured by SCIAMACHY at the local night time, with a latitudinal coverage of 56-89°S, to derive vertical stratospheric water vapor number density profiles in the altitude range of 17-50 km, from 2003 till 2010. The water vapor distributions are retrieved using the spectral window 1350-1420 nm in the near infrared region of the SCIAMACHY spectra. SCIATRAN version 3.0, a radiative transfer model and an inversion scheme based on optimal estimation (OE), is optimized and adapted for the retrieval. Within the inversion scheme, the residuals between the measured differential optical depths and the ones calculated by the forward model are in the order of 0.5%. The radiative transfer computation is performed using correlated-k method employing the exponential sum fitting of transmission function (ESFT) approximation instead of the detailed but computationally costly line by line (LBL) model. Since LBL is the most precise representative of reality, the ESFT database (pressure, temperature and coefficient grids) is optimized with an objective to achieve the closest agreement between the two approaches and to obtain a high quality retrieval product. The retrieval is observed to be highly sensitive to the numbers of coefficients in the ESFT grid. Extensive sensitivity studies and optimizations are performed for the key input parameters as slit function, signal to noise ratio, Tikhonov parameter and the climatological profiles to select their optimal values in the retrieval setting. To evaluate the quality of the retrieved lunar occultation water vapor product, validations are performed with collocated measurements from the satellite occultation instruments ACE-FTS and HALOE and the instruments measuring in limb geometry, MLS and MIPAS. In addition SCIAMACHY limb observations are also used for comparison. SCIAMACHY lunar occultation and ACE-FTS measurements agree within 7% on the average. With HALOE, the difference is around 5%. The validation of the coincident lunar occultation and the MLS measurements is exceptionally good with an agreement of 1.5-4% whereas that with MIPAS is in the range of 10%. The comparisons of the lunar occultation product with all the four instruments are found to be well within their reported biases. With the SCIAMACHY limb water vapor measurements, the differences are of the order of 4%. The validation results show that an excellent SCIAMACHY lunar occultation water vapor product is obtained. The dataset of water vapor distributions from SCIAMACHY lunar occultation measurements is expected to facilitate the understanding of physical and chemical processes in the southern mid-latitudes, the dynamical processes related to polar vortex and on the formation of PSCs, which can be studied through our product right at their onset as observed. The product will add as the southern hemispheric measurement coverage to the SCIAMACHY long term global water vapor time series.

As reactive nitrogen amounts in the stratosphere increase, accurate measurements of these trace gases is of high importance. The SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartog raphY) instrument on ENVISAT (European Environmental Satellite) performs measurements in limb geometry since 2002, providing global coverage of NO2 retrieval results every six days. In this study, a novel approach to improve the sensitivity of SCIAMACHY NO2 limb retrieval results at the UTLS (Upper Troposphere/ Lower Stratosphere) altitude layer is described. Additionally, the current NO2 limb retrieval product is validated in detail and both methods are used for case studies at the North Atlantic region.

Phytoplankton play a unique role in the marine ecosystem as the basis of the marine food-web. They are the main drivers of the biogeochemical cycles in the ocean, as well as influencing the ocean-atmosphere exchanges of carbon dioxide and particular gases and particles. Based on these exchanges, phytoplankton influence the chemistry of atmosphere and the balance of global climate. Moreover, through interaction with light (absorption and scattering), phytoplankton have a significant impact on the underwater optics, being also responsible for the variations in ocean color. However, performing all these roles depends significantly on the type of phytoplankton, as indeed they comprise of a wide range of species and groups, with different capabilities and different distribution patterns in the World Ocean. Therefore, distinguishing between different types of phytoplankton is important to improve the knowledge of their actual roles in the ocean and climate system. As the spectral patterns of light absorption (essential for photosynthesis) vary among different groups of phytoplankton, the backscatter light from ocean preserves the spectral fingerprints of the inhabitant groups of phytoplankton. This feature can be used to determine remotely different types of phytoplankton. The purpose of this PhD-work was to improve a phytoplankton retrieval method, which was established to distinguish quantitatively major phytoplankton groups based on their absorption characteristics. The method, called PhytoDOAS, uses high spectrally resolved satellite data, provided by SCIAMACHY sensor. So far, by applying PhytoDOAS method to SCIAMACHY data, two main phytoplankton groups, diatoms and cyanobacteria, have been successfully distinguished. Through this work the method was improved to detect additionally coccolithophores, another important taxonomic group with significant biogeochemical functions. In this improvement, instead of the usual approach of the PhytoDOAS, which was based on single-target fitting, the simultaneous fitting of a certain set of phytoplankton groups was implemented within a wider wavelength window, thereby the new approach is called multi-target fit. Selection of the set of phytoplankton targets was according to the spectral analysis of absorption features of those groups that are most important with respect to the principal biogeochemical impacts, based on which marine microalgae are grouped as phytoplankton functional types, PFTs. The improved method was successfully tested through detecting independently reported blooms of coccolithophores, as well as by comparison of PhytoDOAS coccolithophores with global distributions of Particulate Inorganic Carbon (PIC), which is used as a proxy of coccolithophores. As the next step of this PhD-work, the results of the improved PhytoDOAS method were used to investigate temporal variations of coccolithophore blooms in selected regions. Eight years of SCIAMACHY data, from 2003 to 2010, were processed by the PhytoDOAS triple-target mode to monitor the biomass of coccolithophores in three oceanic regions, characterized by the frequent occurrence of large blooms. Then the PhytoDOAS results, as monthly mean time-series, were compared to appropriate satellite products, including the total phytoplankton biomass (total chl-a) from GlobColour data-set and the PIC distribution from MODIS-Aqua. To study the dynamics of coccolithophore blooms, the variations of coccolithophores, overall chl-a and PIC, as monthly mean time series, were investigated in the context of variations in the main oceanic geophysical parameters: sea-surface temperature (SST), mixed-layer depth (MLD) and surface wind speed. As a general result, it was observed that the inter-annual variations of the coccolithophore bloom cycles followed well the respective variations in the mentioned geophysical parameters, as they have been reported being associated with coccolithophore blooms. Observed anomalies were investigated based on the specific regional features of the geophysical conditions. Using the results of regional time series, the hypothesis that close coccolithophore blooms succeed the diatom blooms was roughly approved, suggesting, however, a weekly-based averaging of coccolithophores and diatoms for a more precise analysis. It has been frequently reported that high reflectance from surface waters in coccolithophore rich areas affects the performance of standard chl-a algorithms. The regional time series studies of this thesis indicated an underestimation of total chl-a by the standard algorithm during the time of occolithophore blooms. However, a comprehensive validation of the ocean color algorithms with in-situ phytoplankton data is needed to reach the final assessment of the short-comings.

The sun's radiative output is the primary energy input to the Earth, planets, and the entire heliosphere. It determines the thermal structure of the Earth s atmosphere, and overall it sustains life as we know it. The solar spectral irradiance (SSI) determines the general circulation, ozone photochemistry, and weather-climate system. Both SSI and the total solar irradiance (TSI or 'solar constant') vary in time. The 'solar constant' is obtained by integrating SSI over the entire electromagnetic spectrum. It is now established to vary about 0.2 0.4% during the 27-day solar rotation due to transit of active region across the solar disk and 0.1% over an 11-year solar cycle due to variations of magnetic surface activity of the sun related to the reversal of the solar magnetic field. While SSI variability in the UV is moderately well understood, little is known about variability in the optical and near IR (vis-IR) spectral range. This is because while the variations in UV are large, vis-IR variations are small, which are within the noise level of the instrument. The overall goal of this dissertation, therefore, is to improve our understanding of SSI variability especially at longer wavelengths beyond the UV. Regular monitoring of SSI from space covering the entire UV and vis-IR has become available at a moderately high spectral resolution with SCIAMACHY aboard ENVISAT since 2002. This cumulative dissertation presents in three published manuscripts the most recent progress in understanding SSI variability not only in the UV but also in the vis-IR spectral region using SCIAMACHY data. The first published manuscript ad- dresses the validation of radiometrically calibrated SSI from SCIAMACHY to existing SSI data (from ground and space) and to compare SCIAMACHY SSI variations with various other satellite data from SIM onboard SORCE, SUSIM onboard UARS, and SBUVs. The second published manuscript describes the parametrization of SCIAMACHY SSI time series in terms of solar proxies: Mg II core-to-wing (ctw) ratio for faculae brightening and photometric sunspot index (PSI) for sunspot darkening. This simple irradiance model is referred to as the SCIA proxy model. This model allows us to estimate past solar irradiance variations over several decades well beyond the observation period of the SCIAMACHY satellite. Most satellites observing in the optical spectral range suffer from hard radiation in space, particular in the UV, therefore these satellites optically degrade with time. The parametrization using the solar proxy model also enables the application of a simple degradation correction with the need for detailed re-calibration of solar irradiance measurements, which is not always possible or feasible. So far these two goals focus on short timescales (days to several months). The third published manuscript deals with the application of the model to reconstruct daily SSI variability from 1978 to present, covering several decades. The reconstructed SSI from SCIA proxy on daily to decadal timescales are compared to the solar atmosphere model SRPM and space observations from SIM/SORCE, SUSIM/UARS, the DeLand and Cebula/SSAI UV composite; and other proxy models such as NRLSSI, SIP (formerly Solar2000) and semi-empirical model SATIRE.

Carbon monoxide (CO) plays an important role in the Earth's atmosphere. Through its reaction with the hydroxyl radicals (OH) (Logan et al., 1981), CO affects the lifetime of atmospheric methane (CH4), and non-methane hydrocarbons (NMHCs). A main product of this oxidation is carbon dioxide (CO2). Therefore, containing no direct green-house potential, CO still has an indirect effect on the global warming. CO is also one of the most important health hazardous pollutants, which can cause diseases of different degrees of complexity. The nadir near-infrared measurements of scattered and reflected solar radiation by SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on board the ENVISAT satellite contain information about CO concentration in all atmospheric layers including the boundary layer, closest to the location of main CO sources. However, the retrieval of CO total column from the radiometric measurements in this spectral region is complicated as the CO overtone lines are weak, and overlapped by strong absorptions of water vapour and methane. Moreover, several known instrumental issues, like an ice layer on the detector and degradation of the detector pixels with time, additionally complicate the retrieval of CO vertical column from the of SCIAMACHY measurements in channel 8. In the scope of this work, the WFM-DOAS (Weighting Functions Modified Differential Optical Absorption Spectroscopy) retrieval algorithm, developed at the University of Bremen, have been improved in order to establish the retrieval of a multi-year CO dataset from SCIAMACHY nadir measurements. The modifications have led to an improved CO fit quality, i.e., to an overall much smaller fit residual. An error analysis and sensitivity studies based on the simulated measurements have shown that the error is generally less than 10%, which is comparable to the required precision for space-based CO measurements. However, due to high instrument noise, the error of the real measurements has been found to be much higher and considerably less stable. The retrieved CO columns have been validated by comparison with ground-based Fourier Transform Spectroscopy (FTS) measurements. A good agreement within 10-20% was found for nearly all considered stations. Furthermore, high correlation between the SCIAMACHY CO and CO from independent space-based total columns measurements performed by the MOPITT (Measurements of Pollution in the Troposphere) instrument onboard the Terra satellite indicates a good performance of the SCIAMACHY CO measurements globally. The overall difference of about 10% can be well explained by the moderate sensitivity of the thermal-infrared MOPITT measurements to lower atmospheric layers.Detailed analysis of the obtained CO dataset has been has been carried out on country level. Due to the presence of strong anthropogenic sources and prevailing west wind conditions, a positive difference of CO concentration is expected from the west to the east side of the United Kingdom. The analysis shows that SCIAMACHY is able to capture the positive 5% west-to-east CO gradient over the UK. These results are consistent with the direct airborne measurements during the AMPEP campaign, which estimated the CO concentration enhancement from the west to the east coast of the UK to be about 10-100 ppb, corresponding to the total column enhancement of 1-10% within the 1 km boundary layer. Over much stronger sources, such as a large biomass burning events, the quantitative potential of SCIAMACHY CO data is expected to be much higher due to much higher levels of CO signal and respectively more available ("good") satellite measurements. To use this fact for further quantitative investigation, the SCIAMACHY simultaneously measurements of CO, nitrogen dioxide (NO2) and formaldehyde (HCHO) over biomass burning events in 2004, were analysed in the scope of the bottom-up emission estimation Excess Mixing Ratios (EMR) method. Good agreement has been found between the calculated SCIAMACHY (Delta CO)/(Delta HCHO) and (Delta CO)/(Delta NO2) and the ER values from referenced literature.

This study deals with the retrieval of stratospheric and lower mesospheric ozone profiles from satellite observations of limb--scattered solar radiation with SCIAMACHY on the Envisat satellite. The retrieval combines spectral information in the Chappuis and Hartley absorption bands of ozone and employs the SCIATRAN radiative transfer model. The retrieved ozone profiles are applied into two aspects.First, the sensitivity of the ozone profile retrieval to tropospheric clouds is examined using the SCIATRAN radiative transfer model. The considered clouds are vertically and horizontally homogeneous. An aerosol-free atmosphere and Mie phase functions for cloud particles are assumed. Neglecting clouds in the retrieval, the relative errors of ozone profile retrievals in a cloudy atmosphere are computed. The cloud sensitivity of the limb ozone retrievals is significant in the Chappuis bands at lower stratospheric altitudes. The relative error in the retrieved ozone concentrations gradually decreases with increasing altitude and becomes negligible above approximately 40 km. Cloud optical thickness, ground albedo and solar zenith angle have a large impact on the ozone retrievals. For a given cloud optical thickness value, clouds with different geometrical thicknesses or different cloud altitudes have a similar impact on the ozone retrievals, if the clouds are outside the field of view of the instrument. The effective radius of water droplets and the solar azimuth angle has a small influence on the error. Neglecting clouds in the ozone profile retrievals generally leads to a low bias. For the most frequent cloud types, the total error is below 6% above 15 km altitude, if clouds are completely neglected in the retrieval. Second, the stratospheric and lower mesospheric ozone profile data set of SCIAMACHY measurements of limb-scattered solar radiation in the period 2002-2009 is used to determine the chemical ozone loss in both the Arctic and Antarctic polar vortices using the vortex average method. The vortex boundary is determined with a potential vorticity (PV) criterion applied to UKMO stratospheric analyses. The chemical ozone loss at the 450-600 K isentropic levels is derived from the difference between observed ozone abundances and the ozone modelled considering diabatic cooling, but no chemical ozone loss. The results show accumulated chemical ozone losses of up to 20-40% between the beginning of January and the end of March inside the Arctic polar vortex. Strong interannual variability of the Arctic ozone loss is observed, with the cold winters 2005 and 2007 showing the largest chemical ozone losses. The ozone loss in the southern polar vortex does not change much from year to year. At the 475 K isentropic level total relative ozone losses of 70-80% between mid-August and mid-November are observed every year inside the vortex, even in the anomalous year 2002. SCIAMACHY mesurements of polar stratospheric clouds and the chemical ozone loss inside polar vortex are in good agreement.Comparisons of the vertical variation of ozone loss derived from SCIAMACHY observations with several independent techniques for the northern hemisphere winter 2004/2005 show very good agreement.

Global water vapour total column amounts have been retrieved from spectral data provided by the Global Ozone Monitoring Experiment (GOME) flying on ERS-2, which was launched in April 1995, and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard ENVISAT launched in March 2002. For this purpose the Air Mass Corrected Differential Optical Absorption Spectroscopy (AMC-DOAS) approach has been used. The combination of the data from both instruments provides a long-term global data set spanning more than 12 years with the potential of extension up to 2020 by GOME-2 data on MetOp. Using linear and non-linear methods from time series analysis and standard statistics the trends of water vapour columns and their errors have been calculated. In this study, factors affecting the trend such as the length of the time series, the variance of the noise and the autocorrelation of the noise are investigated. Special emphasis has been placed on the calculation of the statistical significance of the observed trends, which reveal significant local changes from -5 % per year to 5 % per year. These significant trends are distributed over the whole globe. Increasing trends have been calculated for Greenland, East Europe, Siberia and Oceania, whereas decreasing trends have been observed for the northwest USA, Central America, Amazonia, Central Africa and the Arabian Peninsular. The idea of the comprehensive trend and significance analysis is to get evidence for the truth of these observed changes. While the significance estimation is based on intrinsic properties such as the length of the data sets, the noise and the autocorrelation, an important aspect of assessing the probability that the real trends have been observed is a validation with independent data. Therefore an intercomparison of the global total column water vapour trends retrieved from GOME and SCIAMACHY with independent water vapour trends measured by radiosonde stations provided by the Deutsche Wetter Dienst DWD (German Weather Service) is presented. The validation has been performed in a statistical way on the basis of univariate time series. Information about the probability of agreement between the two independently observed trends, conditional on the respective data, is revealed. On the one hand a standard t-test is used to compare the trends and on the other hand a Bayesian model selection approach has been developed to derive the probability of agreement. The hypothesis of equal trends from satellite and radiosonde water vapour data is preferred in 85 % of compared pairs of trends. Substantial evidence for the hypothesis of agreeing trends is found in 26 % of analysed trends. However, also disagreement has been observed, where the main reason has been identified on the one hand as the different spatial resolutions of the instruments. This means, that the radiosonde measurements can resolve very localised events, which is not possible with the satellite instruments. On the other hand, in contrast to the in principle continuously available (on a monthly mean basis) GOME/SCIAMACHY data, missing data in the radiosonde time series lead to trend discrepancies. The identification and validation of water vapour trends is an important step for a better understanding of climate change, but water vapour is not the only contributing quantity. Beside water vapour, decisive parameters are temperature, clouds, precipitation, vegetation and many more. A promising framework for the investigation of a multivariate data set of environmental variables is given by the Markov chain analysis. As a first approach, the Markov chain analysis has been applied to a bivariate water vapour -- temperature data set, where the global near surface temperatures are provided by the Goddard Institute of Space Studies (GISS) and cover a time span from 1880 to 2005. The temperature data are retrieved from ground stations and are mainly based on the Global Historical Climatology Network (GHCN). In the framework of a Markov chain analysis, the bivariate set of data is reduced to a univariate sequence of symbols, which can be described as a discrete stochastic process, a Markov chain. This Markov chain represents the water vapour -- temperature interaction or state of a region. Several descriptors have been calculated, such as persistence, replacement of and entropy. This approach is new in environmental science. Exemplarily two climate systems, the Iberian Peninsular and a region at the islands of Hawaii in the central Pacific Ocean, are investigated. The Markov chain analysis is able to retrieve significant differences between the two climate systems in terms of the characteristic descriptors, which reflect properties such as climate stability, rate of changes and short term predictability.

Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. Three years (2003-2005) of SCIAMACHY near-infrared nadir measurements have been processed to simultaneously retrieve vertical columns of CO2, CH4, and oxygen using the scientific retrieval algorithm WFM-DOAS. The latest version of WFM-DOAS, version 1.0, which was developed within the scope of this thesis, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed. The greenhouse gas columns are converted to column-averaged dry air mole fractions, denoted XCO2 and XCH4, by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band.The satellite CO2 data set is compared with ground based Fourier Transform Spectroscopy (FTS) measurements and results from the global assimilation system CarbonTracker showing good agreement concerning the annual increase as well as the seasonal cycle over the northern hemisphere. However, for the southern hemisphere, where significantly less data are available for averaging, the amplitude and phase of the seasonal cycle show systematic differences arising partially from the O2 normalisation most likely caused by unconsidered scattering effects due to subvisual cirrus clouds. Based on the error analysis and on the comparison with the reference data it can be concluded that the XCO2 data set can be characterised by a single measurement retrieval precision (random error) of 1-2%, a systematic low bias of about 1.5%, and by a relative accuracy of about 1-2% for monthly averages at a spatial resolution of about 7°x7°. Averaging the retrieved XCO2 over all three years provides elevated CO2 over densely populated and industrialised source regions indicating that strong regional anthropogenic CO2 emissions can be potentially detected from space.The satellite CH4 data set is compared with global model simulations based on the TM5 model optimised versus high-accuracy surface measurements from the NOAA/ESRL network. After accounting for a systematic low bias of circa 2% agreement with TM5 is typically within 1-2%. The single measurement retrieval precision of XCH4 is estimated to be 1.5-1.7%. It is investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from CarbonTracker showing that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with other studies higher methane over the tropics is found compared to the model. Tropical methane is also higher when normalising the CH4 columns with retrieved O2 columns instead of CO2. However, the magnitude of the retrieved tropical methane enhancement is sensitive to changes in spectroscopy and possible inaccuracies in the spectroscopic parameters can thus contribute to a potential overestimation of the tropical methane. First inverse modelling results for methane surface fluxes are presented for the year 2004 performed at the European Commission's Joint Research Centre (EC-JRC) by Peter Bergamaschi.

The scope of this study is the investigation of mesospheric and thermospheric metallic species.The methodology used in this work provides results in the mesosphere/lower thermosphereregion (MLT) extending from approximately 70 to 500 km altitude.The major source of metal species in the upper atmosphere is influx from cosmic dust. Alongwith Earth, a variety of celestial bodies orbit the Sun. The asteroid belt between Earth and Marsand the Kuiper belt outside the orbit of Neptune are well-known regions of high abundance ofthose objects. In addition, a number of regularly returning cometary objects present sources ofcosmic material. The origin of these comets is believed to be the Oort cloud surrounding thesolar system. After entering the atmosphere, particles from either source are then subject tofrictional heating. This leads to sublimation of metallic species from the surface of the particles.The impact of metal species on the chemistry and physics of the upper and middle (and,eventually, the lower) atmosphere is still a field of intense research. The total influx of meteoriccosmic material into the atmosphere is highly uncertain. Metal species are suggested to impactthe removal of ozone in the upper stratosphere and the formation of water vapour in themesosphere. Additionally, the role of meteoric particles in the formation of stratospheric cloudsis of scientific interest.Space-borne measurements present the most powerful method to investigate global distributionsof metal species with moderate vertical and horizontal resolution. The SCIAMACHYinstrument is capable to observe emission signals from mesospheric and thermospheric magnesiumspecies on a global scale with good spatial and temporal coverage. This work comprisesresults from the first six years of measurement (2002 - 2007) of the SCIAMACHY instrument.The results presented here represent the first vertically resolved satellite measurementsof mesospheric magnesium species on a global scale and a long period of time.A comprehensive review of the distribution and variability of the two major atomic mesosphericmagnesium species (Mg and Mg ) in the upper mesosphere and lower thermosphere isprovided. Seasonal variations are investigated. In the northern hemisphere, a pronounced seasonalvariation with summer maxima has been found for the ionized species Mg . The neutralspecies does not exhibit such variation.An estimation of the total influx of meteoric material has been derived from the total contentof Mg. A total amount of approximately 55 t enters the atmosphere per day.A long-term study has been carried out to analyze the impact of meteor showers on the totalcontent of magnesium species in the upper atmosphere. The impact of meteoric showers on thetotal content has been found to be undetectable. It can thus be concluded that the additionalmass influx of meteor showers is negligible compared to the average background flux.The correlation between the abundance of magnesium species and the solar activity is investigated.This includes a general long-term consideration over all six years of measurement aswell as short-term observations made during a large outburst of solar particles in October andNovember 2003. No impact of variations in the solar activity on the total content of either Mg or Mg has been observed. During the October/November 2003 period of high solar particleflux, however, strong enhancements in both magnesium species have been observed.

This thesis presents an analysis of the stratospheric bromine monoxide (BrO) profiles retrieved globally from two years of limb measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography(SCIAMACHY) instrument on board ENVISAT.In order to have a confidence in the quality of the retrieved SCIAMACHY BrO profiles, they need to be validated with BrO measurements, performed using different methods. Hence, as a first step towards a validation of SCIAMACHYBrO retrievals, BrO profiles are compared with the set of balloon-borne BrO measurements. The comparison with a set of four balloon-borne BrO profiles shows mean relative differences in the altitude range from 18 to 30~km between 17% and -42%. In order to validate our current understanding of bromine chemistry, the SCIAMACHY BrO retrievals are compared with modeled BrO profiles, based on estimated inorganic bromine (Bry) from CFC-11 retrievals by the Michelson Interferometer for Passive AtmosphericSounding (MIPAS), also on ENVISAT, and the calculated BrO/Bry ratio from a photochemical model constrained by SCIAMACHY nitrogen di-oxide (NO2) retrievals. The BrO observations are found to be broadly consistentwith our current understanding of stratospheric bromine chemistry and a total stratospheric bromine loading of approximately 18 pptv.Further a global climatology of stratospheric BrO is constructed using the two years' retrievals of BrO. The analysis of SCIAMACHY BrO observations provide for the first time a picture of the seasonal variation of stratospheric BrO on a global scale. At the midlatitudes of both hemispheres BrO shows a strong seasonal cycle with a maximum in winter and a minimum in summer. The seasonal variation of BrO is closely correlated with changes in NO2 in accordance with our present understanding of bromine chemistry.The two years' BrO climatology constructed using the nadir measurements of SCIAMACHY and the climatology constructed in this work is used to calculate the amount of BrO below 15 km in the atmosphere. This calculation shows that aglobal background BrO of 1.4 pptv, averaged over all latitudes and months, exists throughout the year below 15 km in the atmosphere.The knowledge of the total amount of bromine present in the atmosphere is an important issue as it has direct implications on our prediction of the ozone trends. Using the SCIAMACHY BrO observations together with the calculatedbromine partitioning from a photochemical model constrained by the SCIAMACHY NO2 observations, the total stratospheric bromine loading is estimated to be 18.5 /- 4 pptv. This indicates a contribution of about 3.5 /- 4 pptv fromshort lived bromine species in addition to methyl bromide and the halons.

This study exploits nadir spectral measurements in 325-335nm range to infer total column ozone (TCO) from the Global Ozone Monitoring Experiment (GOME) and SCaning Imaging Absorption spectroMeter for Atmospheric CHartographY(SCIAMACHY) instruments. TCO from these two instruments retrieved using the Weighting Function Differential Optical Absorption Spectroscopy (WFDOAS) are presented. Unlike in standard DOAS where the fitting procedure results inozone slant column which needs to be converted into vertical column (TCO) by using air mass factor (AMF), in our novel approach direct retrieval of vertical column amounts of ozone is possible by fitting vertically integratedozone weighting function to the sun-normalized radiances. Other implementations include proper modelling of the Ring effect including Raman correction for ozone absorption, the implicit use of the effective albedo and effective sceneheight accounting for cloud effects, and an ozone temperature correction. The new algorithm has been extensively validated with ground-based Dobson andBrewer TCO measurements. In general, the agreement between GOME WFDOAS and ground stations data is very good and the validation shows that the retrieval accuracy of WFDOAS is within the uncertainty of current ground-based instruments. Better agreements are observed in the comparison withBrewer measurements than with Dobson measurements. This may be explained to a large extent by the neglect of ozone temperature correction in the standard retrieval for Dobson and Brewer. Temperature correction has a larger effect onthe Dobson results. The accuracy of WFDOAS retrievals makes GOME data very attractive for evaluating the ground-based network data. Eight years of GOME data are used to assess the quality of the WOUDC-archived Brewer data. It is shown that monitoring of Brewer data quality and identification ofproblems in Brewer instruments are possible. This method can also be applied to other ground-based instruments. Despite improvement with WFDOAS, somewhat larger differences between satellite TCO and ground based measurements remain at high latitudes under low sun conditions. The persistent TCO differences are due in part to profile shape sensitivity of satellite TCO retrieval algorithms. Improved ozone and temperature profile climatologies, which is prepared and presented in this thesis, will lead to improved satellite ozone measurements. The effect of ozone and temperature profiles on TCO retrievals is explored. The studydemonstrates that an improved and updated ozone and temperature climatological profiles can reduce the systematic errors in the retrieved GOME TCO, inparticular at high solar zenith angles. For SCIAMACHY application, the only change of algorithm is for calculating the reference spectra online in each iteration during retrievals rather than using look-up tables. Scaled SCIAMACHY FM ozone cross-section and wavelength pre-shifted by 0.016nm, as determined from our comprehensive investigation performed in this thesis, is used for the calculation of reference spectra and the Ring spectra. Improved cloud products and the new ozone and temperature profile climatologies are used. Quality of theretrieved TCO is assessed by correlative measurements from GOME and selected Brewer spectrophotometers. In general a good agreement is achieved apart from a scan angle dependent offset of about -1% to -2%. The reason for the offset is not understood but part of the offset might be related to thecalibration errors in the level 1 data. Nevertheless, combined data set from GOME and SCIAMACHY as retrieved from WFDOAS algorithm presented in this thesis will be valuable for long-term ozone studies.

The retrieval of tropospheric NO:sub:2:/sub: from measurements taken by the satellite born instruments GOME and SCIAMACHY takes three steps: (1) Determination of the slant column (SC) by applying the method of the Differential Optical Absorption Spectroscopy (DOAS), (2) separation of the stratospheric amount of NO:sub:2:/sub:, and (3) conversion of the tropospheric SC to the tropospheric vertical column (VC) by applying an Air Mass Factor (AMF), which is determined by a simulation of the radiative transport (RT) by the RT model SCIATRAN.The essence of this thesis is the implementation of a new concept for the determination of the AMF. It leads to a substantial improvement in the retrieval by providing individual AMF for each observation.The sensitivity of the measurement is strongly dependant on the height. Therefore the shape of the NO:sub:2:/sub: profile must be known in order to calculate the AMF. This a priori information is taken from simulations of the chemistry and transport models (CTM) IMAGES, MOZART2 and TOMCAT.Since the explicit calculation of the AMF is rather time consuming, the approximation method block AMF was implemented. It is based on a look-up table of AMF for single atmospheric layers. The lookup table contains a total of 11,618,100 values, for the different combination of 13 albedo values, 6 aerosol types, 91 possible ground heights above sea level

The hyperspectral UV-vis-NIR spectrometer SCIAMACHY will be launched aboard the European satellite Envisat. Its limb measurements will provide vertically resolved profiles of trace gases and other atmospheric parameters. No retrieval algorithms and radiative transfer models have been established for these measurements yet.In this thesis, a unique, fast radiative transfer model for UV-vis-NIR limb radiances has been developed, implemented, and validated. It takes into account the sphericity of the atmosphere and up to two orders of scattering and surface reflection. The weighting functions for all parameters are calculated from analytical formulae. A realistic instrument model with field-of-view integration and signal-to-noise computation and retrieval algorithms have also been implemented. All have been combined in the new program package SCIARAYS. The package has been applied for the characterisation of the limb measurements in several ways:The simulated weighting functions agree well with those due to full multiple scattering. Thus they may be used to calculate theoretical precision estimates and averaging kernels. In conformance with this, test retrievals with approximate weighting functions converge correctly. Therefore, the approximate weighting functions of SCIARAYS are well suited for retrievals from SCIAMACHY´s limb measurements.Detailed theoretical retrieval precisions have been calculated for SCIAMACHY´s trace gas targets. The conclusion is that a UV-vis-NIR limb sensor like SCIAMACHY is well suited for studying the vertical structure of the stratosphere and also of the upper troposphere above cloud top.Further investigations show that the vertical resolution of retrievals from SCIAMACHY´s limb measurements can be improved beyond its geometrical limits. As a trade-off for better vertical resolution, the retrieval precision gets worse. Thus O3 profile features with 1km vertical extent will be detectable with a precision of 20-30%.

Retrieval of atmospheric constituents from remote sensing measurements requires a radiative transfer forward model and appropriate inversion algorithms. A fast and accurate correlated-k (c-k) distribution radiative transfer scheme has been developed for the simulation of radiance spectra to be measured in nadir viewing geometry by the SCIAMACHY satellite diode array grating spectrometer. SCIAMACHY is part of the atmospheric sciences payload of the European Space Agencies ENVISAT-1 satellite to be launched in mid 2001. SCIAMACHY covers the spectral region 240-2385 nm with moderate spectral resolution (0.2-1.6 nm FWHM) and observers solar radiation scattered and reflected back to space by the Earths atmosphere and surface. The spectral region 440-2385 nm is dominated by molecular line absorption due to CO, CO2, CH4, H2O, N2O, and O2. The most accurate approach for the calculation of the spectrally averaged radiance - if line absorption needs to be considered - is the line-by-line approach. This approach, however, is very time consuming and can only be used for reference purposes. Therefore, a much faster c-k scheme has been developed. It is based on parameters that can be interpreted as trace gas absorption cross-sections representative for narrows spectral intervals. In this context a new method (alpha-mixing scheme) has been developed to consider spectrally overlapping line absorption. This method is shown to be more accurate (at SCIAMACHY resolution) and flexiblethan any previously developed method. The c-k and a line-by-line schemes have been implemented in the radiative transfer.

The satellite instrument SCIAMACHY was operational for almost 10 years during the period 2002-2012 aboard the Envisat of the ESA, measuring a number of important atmospheric trace gases in three different modes. SCIAMACHY measured the spectra of the solar light scattered by the atmosphere (or transmitted through the atmosphere in the occultation mode). These spectra were used to retrieve vertical profiles or total columns of the atmospheric trace gases as well as aerosol and cloud parameters. The purpose of this study was to investigate the spatio-temporal changes of stratospheric species such as ozone (O3) and nitrogen dioxide (NO2) and reveal possible drivers of the observed variations. Taking into account the importance of understanding the changes in the atmospheric composition it was crucial to 1) find an atmospheric model, which adequately describes chemical-dynamical processes in the stratosphere and 2) have an accurate knowledge of trace gases distribution.