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.