SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) is a spectrometer designed to measure sunlight transmitted, reflected, and scattered by the earth's atmosphere or surface in the ultraviolet, visible, and near-infrared wavelength region (240-2380 nm) at moderate spectral resolution (0.2-1.5 nm, /⌬ ഠ 1000-10 000). SCIAMACHY will measure the earthshine radiance in limb and nadir viewing geometries and solar or lunar light transmitted through the atmosphere observed in occultation. The extraterrestrial solar irradiance and lunar radiance will be determined from observations of the sun and the moon above the atmosphere. The absorption, reflection, and scattering behavior of the atmosphere and the earth's surface is determined from comparison of earthshine radiance and solar irradiance. Inversion of the ratio of earthshine radiance and solar irradiance yields information about the amounts and distribution of important atmospheric constituents and the spectral reflectance (or albedo) of the earth's surface. SCIAMACHY was conceived to improve our knowledge and understanding of a variety of issues of importance for the chemistry and physics of the earth's atmosphere (troposphere, stratosphere, and mesosphere) and potential changes resulting from either increasing anthropogenic activity or the variability of natural phenomena. Topics of relevance for SCIAMACHY are R tropospheric pollution arising from industrial activity and biomass burning, R troposphere-stratosphere exchange processes, R stratospheric ozone chemistry focusing on the understanding of the ozone depletion in polar regions as well as in midlatitudes, and R solar variability and special events such as volcanic eruptions, and related regional and global phenomena. Inversion of the SCIAMACHY measurements enables the amounts and distribution of the atmospheric constituents O 3 , O 2 , O 2 (1 ⌬), O 4 , BrO, OClO, ClO, SO 2 , H 2 CO, NO, NO 2 , NO 3 , CO, CO 2 , CH 4 , H 2 O, N 2 O, and aerosol, as well as knowledge about the parameters pressure p, temperature T, radiation field, cloud cover, cloudtop height, and surface spectral reflectance to be determined. A special feature of SCIAMACHY is the combined limb-nadir measurement mode. The inversion of the combination of limb and nadir measurements will enable tropospheric column amounts of O 3 , NO 2 , BrO, CO, CH 4 , H 2 O, N 2 O, SO 2 , and H 2 CO to be determined.

Abstract. The near-infrared nadir spectra measured by SCIAMACHY on-board ENVISAT contain information on the vertical columns of important atmospheric trace gases such as carbon monoxide (CO), methane (CH 4 ), and carbon dioxide (CO 2 ). The scientific algorithm WFM-DOAS has been used to retrieve this information. For CH 4 and CO 2 also column averaged mixing ratios (XCH 4 and XCO 2 ) have been determined by simultaneous measurements of the dry air mass. All available spectra of the year 2003 have been processed. We describe the algorithm versions used to generate the data (v0.4; for methane also v0.41) and show comparisons of monthly averaged data over land with global measurements (CO from MOPITT) and models (for CH 4 and CO 2 ). We show that elevated concentrations of CO resulting from biomass burning have been detected in reasonable agreement with MOPITT. The measured XCH 4 is enhanced over India, south-east Asia, and central Africa in September/October 2003 in line with model simulations, where they result from surface sources of methane such as rice fields and wetlands. The CO 2 measurements over the Northern Hemisphere show the lowest mixing ratios around July in qualitative agreement with model simulations indicating that the large scale pattern of CO 2 uptake by the growing vegetation can be detected with SCIAMACHY. We also identified potential problems such as a too low inter-hemispheric gradient for CO, a time dependent bias of the methane columns on the order of a few percent, and a few percent too high CO 2 over parts of the Sahara.

(2015). The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets. Remote Sensing of Environment: an interdisciplinary journal, 162 344-362. The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets Abstract The GHG-CCI project is one of several projects of the European Space Agency's (ESA) Climate Change Initiative (CCI). The goal of the CCI is to generate and deliver data sets of various satellite-derived Essential Climate Variables (ECVs) in line with GCOS (Global Climate Observing System) requirements. The "ECV Greenhouse Gases" (ECV GHG) is the global distribution of important climate relevant gases-atmospheric CO2 and CH4-with a quality sufficient to obtain information on regional CO2 and CH4 sources and sinks. Two satellite instruments deliver the main input data for GHG-CCI: SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT. The first order priority goal of GHG-CCI is the further development of retrieval algorithms for near-surface-sensitive column-averaged dry air mole fractions of CO2 and CH4, denoted XCO2 and XCH4, to meet the demanding user requirements. GHG-CCI focuses on four core data products: XCO2 from SCIAMACHY and TANSO and XCH4 from the same two sensors. For each of the four core data products at least two candidate retrieval algorithms have been independently further developed and the corresponding data products have been quality-assessed and inter-compared. This activity is referred to as "Round Robin" (RR) activity within the CCI. The main goal of the RR was to identify for each of the four core products which algorithms should be used to generate the Climate Research Data Package (CRDP). The CRDP will essentially be the first version of the ECV GHG. This manuscript gives an overview of the GHG-CCI RR and related activities. This comprises the establishment of the user requirements, the improvement of the candidate retrieval algorithms and comparisons with ground-based observations and models. The manuscript summarizes the final RR algorithm selection decision and its justification. Comparison with ground-based Total Carbon Column Observing Network (TCCON) data indicates that the "breakthrough" single measurement precision requirement has been met for SCIAMACHY and TANSO XCO2 (< 3 ppm) and TANSO XCH4 (< 17 ppb). The achieved relative accuracy for XCH4 is 3-15 ppb for SCIAMACHY and 2-8 ppb for TANSO depending on algorithm and time period. Meeting the 0.5 ppm systematic error requirement for XCO2 remains a challenge: approximately 1 ppm has been achieved at the validation sites but also larger differences have been found in regions remote from TCCON. More research is needed to identify the causes for the observed differences. In this context GHG-CCI suggests taking advantage of the ensemble of existing data products, for example, via the EnseMble Median Algorithm (EMMA). Abstract 41 The GHG-CCI pr...

Abstract. The three carbon gases carbon monoxide (CO), carbon dioxide (CO 2 ), and methane (CH 4 ) are important atmospheric constituents affecting air quality and climate. The near-infrared nadir spectra measured by SCIAMACHY on ENVISAT contain information on the vertical columns of these gases which we retrieve using a modified DOAS algorithm (WFM-DOAS or WFMD). Our main data products are CO vertical columns and dry-air column averaged mixing ratios of methane (CH 4 ) and CO 2 (denoted XCH 4 and XCO 2 ). For CO and CH 4 we present new results for the year 2003 obtained with an improved version of WFM-DOAS (WFMDv0.5) retrieved from Level 1 version 4 (Lv1v4) spectra. This data set has recently been compared with a network of ground based FTIR stations. Here we describe the WFMDv0.5 algorithm, present global and regional maps, and comparisons with global reference data. We show that major problems of the previous versions (v0.4 and v0.41) related to the varying ice-layer on the SCIAMACHY channel 8 detector have been solved. Compared to MOPITT the SCIAMACHY CO columns are on average higher by about 10-20%. Regionally, however, especially over central South America, differences can be much larger. For methane we present global and regional maps which are compared to TM5 model simulations performed using standard methane emission inventories. We show that methane source regions can be clearly detected with SCIAMACHY. We also show that the methane data product can be significantly further improved using Lv1v5 spectra with improved calibration. For CO 2 we present three years of SCIAMACHY CO 2 measurements over Park Falls, Wisconsin, USA, retrieved from Lv1v5. We show that the quality of CO 2 retrieved from Correspondence to: M. Buchwitz (michael.buchwitz@iup.physik.uni-bremen.de) these spectra is significantly higher compared to WFMDv0.4 XCO 2 retrieved from Lv1v4.

Abstract. First results concerning the retrieval of tropospheric carbon monoxide (CO) from satellite solar backscatter radiance measurements in the near-infrared spectral region (∼2.3 µm) are presented. The Weighting Function Modified (WFM) DOAS retrieval algorithm has been used to retrieve vertical columns of CO from SCIA-MACHY/ENVISAT nadir spectra. We present detailed results for three days from the time periode January to October 2003 selected to have good overlap with the daytime CO measurements of MOPITT onboard EOS Terra. Because the WFM-DOAS Version 0.4 CO columns presented in this paper are scaled by a constant factor of 0.5 to compensate for an obvious overestimation we focus on the variability of the retrieved columns rather than on their absolute values. It is shown that plumes of CO resulting from, e.g. biomass burning in Africa, are detectable with single overpass SCIA-MACHY data. Globally, the SCIAMACHY CO columns are in reasonable agreement with the Version 3 CO column data product of MOPITT. For example, for measurements over land, where the quality of the data is typically better than over ocean due to higher surface reflectivity, the standard deviation of the difference with respect to MOPITT is in the range 0.4-0.6×10 18 molecules/cm 2 and the linear correlation coefficient is between 0.4 and 0.7. The level of agreement between the data of both sensors depends on time and location but is typically within 30% for most latitudes. In the southern hemisphere outside Antarctica SCIAMACHY tends to give systematically higher values than MOPITT. More studies are needed to find out what the reasons for the observed differences with respect to MOPITT are and how the algorithm can be modified to improve the quality of the CO columns as retrieved from SCIAMACHY.

Abstract. The growth rate of atmospheric carbon dioxide (CO2) reflects the net effect of emissions and uptake resulting from anthropogenic and natural carbon sources and sinks. Annual mean CO2 growth rates have been determined from satellite retrievals of column-averaged dry-air mole fractions of CO2, i.e. XCO2, for the years 2003 to 2016. The XCO2 growth rates agree with National Oceanic and Atmospheric Administration (NOAA) growth rates from CO2 surface observations within the uncertainty of the satellite-derived growth rates (mean difference ± standard deviation: 0.0±0.3 ppm year−1; R: 0.82). This new and independent data set confirms record-large growth rates of around 3 ppm year−1 in 2015 and 2016, which are attributed to the 2015–2016 El Niño. Based on a comparison of the satellite-derived growth rates with human CO2 emissions from fossil fuel combustion and with El Niño Southern Oscillation (ENSO) indices, we estimate by how much the impact of ENSO dominates the impact of fossil-fuel-burning-related emissions in explaining the variance of the atmospheric CO2 growth rate. Our analysis shows that the ENSO impact on CO2 growth rate variations dominates that of human emissions throughout the period 2003–2016 but in particular during the period 2010–2016 due to strong La Niña and El Niño events. Using the derived growth rates and their uncertainties, we estimate the probability that the impact of ENSO on the variability is larger than the impact of human emissions to be 63 % for the time period 2003–2016. If the time period is restricted to 2010–2016, this probability increases to 94 %.

Abstract.A new method for the retrieval of global atmospheric vertical column amounts of water vapor from measurements of the Global Ozone Monitoring Experiment (GOME) is presented. The method is based on a modified Differential Optical Absorption Spectroscopy (DOAS) approach, taking into account the effects arising from strong wavelength dependent absorptions. In this paper the feasibility of this approach is demonstrated and first estimates on the retrieval precision and the accuracy of the H20 data product are given by comparison with selected Special Sensor Microwave Imager (SSM/I) data.

Abstract. 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 us with a long-term global data set spanning more than 11 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 H 2 O columns and their errors have been calculated. In this study, factors affecting the trend such as the length of the time series, the magnitude of the variability 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 north-