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J P Burrows - One of the best experts on this subject based on the ideXlab platform.
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retrieval of nitric oxide in the mesosphere from SCIAMACHY nominal limb spectra
arXiv: Atmospheric and Oceanic Physics, 2018Co-Authors: Stefan Bender, Miriam Sinnhuber, Martin Langowski, J P BurrowsAbstract:We present a retrieval algorithm for nitric oxide (NO) number densities from measurements from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, on Envisat) nominal limb mode (0--91 km). The NO number densities are derived from atmospheric emissions in the gamma bands in the range 230--300 nm, measured by the SCIAMACHY ultra-violet (UV) channel 1. The retrieval is adapted from the mesosphere and lower thermosphere mode (MLT, 50--150 km) NO retrieval (Bender et al., 2013, arXiv:1808.02388), including the same 3-D ray tracing, 2-D retrieval grid, and regularisations with respect to altitude and latitude. Since the nominal mode limb scans extend only to about 91 km, we use NO densities in the lower thermosphere (above 92 km), derived from empirical models, as a priori input. The priors are the Nitric Oxide Empirical Model (NOEM; Marsh et al., 2004) and a regression model derived from the MLT NO data comparison (Bender et al., 2015). Our algorithm yields plausible NO number densities from 60 to 85 km from the SCIAMACHY nominal limb mode scans. Using a priori input substantially reduces the incorrect attribution of NO from the lower thermosphere, where no direct limb measurements are available. The vertical resolution lies between 5 and 10 km in the altitude range 65--80 km. Analysing all SCIAMACHY nominal limb scans provides almost 10 years (from August 2002 to April 2012) of daily NO measurements in this altitude range. This provides a unique data record of NO in the upper atmosphere and is invaluable for constraining NO in the mesosphere, in particular for testing and validating chemistry climate models during this period.
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tropical tropospheric ozone columns from nadir retrievals of gome 1 ers 2 SCIAMACHY envisat and gome 2 metop a 1996 2012
Atmospheric Measurement Techniques, 2016Co-Authors: Elpida Leventidou, K U Eichmann, M Weber, J P BurrowsAbstract:Abstract. Tropical tropospheric ozone columns are retrieved with the convective cloud differential (CCD) technique using total ozone columns and cloud parameters from different European satellite instruments. Monthly-mean tropospheric column amounts [DU] are calculated by subtracting the above-cloud ozone column from the total column. A CCD algorithm (CCD_IUP) has been developed as part of the verification algorithm developed for TROPOspheric Monitoring Instrument (TROPOMI) on Sentinel 5-precursor (S5p) mission, which was applied to GOME/ERS-2 (1995–2003), SCIAMACHY/Envisat (2002–2012), and GOME-2/MetOp-A (2007–2012) measurements. Thus a unique long-term record of monthly-mean tropical tropospheric ozone columns (20° S–20° N) from 1996 to 2012 is now available. An uncertainty estimation has been performed, resulting in a tropospheric ozone column uncertainty less than 2 DU ( %) for all instruments. The dataset has not been yet harmonised into one consistent; however, comparison between the three separate datasets (GOME/SCIAMACHY/GOME-2) shows that GOME-2 overestimates the tropical tropospheric ozone columns by about 8 DU, while SCIAMACHY and GOME are in good agreement. Validation with Southern Hemisphere ADditional OZonesondes (SHADOZ) data shows that tropospheric ozone columns from the CCD_IUP technique and collocated integrated ozonesonde profiles from the surface up to 200 hPa are in good agreement with respect to range, interannual variations, and variances. Biases within ±5 DU and root-mean-square (RMS) deviation of less than 10 DU are found for all instruments. CCD comparisons using SCIAMACHY data with tropospheric ozone columns derived from limb/nadir matching have shown that the bias and RMS deviation are within the range of the CCD_IUP comparison with the ozonesondes. The 17-year dataset can be helpful for evaluating chemistry models and performing climate change studies.
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retrieval of terrestrial plant fluorescence based on the in filling of far red fraunhofer lines using SCIAMACHY observations
Frontiers in Environmental Science, 2015Co-Authors: Narges Khosravi, V V Rozanov, Marco Vountas, Astrid Bracher, Alexandra Wolanin, J P BurrowsAbstract:Chlorophyll fluorescence is directly linked to the photosynthetic efficiency of plants. As satellite-based remote sensing has been shown to have the potential to derive global information about fluorescence it has become subject of various recently published studies stimulating an upsurge in this research field. This manuscript presents a simple and fast retrieval method for solar induced terrestrial plant fluorescence (SIF) which relies on only a few prerequisites. The spaced 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. The method has been applied to ten years of SCIAMACHY data with promising results. The retrieved SIF values are lying between 0 and 4 mW [m-²,sr-¹,nm-¹]. However, most of the retrieved values are not exceeding 1.5 [m-²,sr-¹,nm-¹], agreeing with previous studies on the subject. Results have been retrieved for SCIAMACHY spatial resolution of 240 x 30 km² and gridded to 80 arc minutes. A clear seasonal variation could be shown utilizing 10 years of SCIAMACHY data (2002-2012). In absence of large area ground based validation data a final judgment of the results presented is not feasible. However, a direct comparison to data of others was showing similar results for most areas.
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improved stratospheric aerosol extinction profiles from SCIAMACHY validation and sample results
Atmospheric Measurement Techniques, 2015Co-Authors: C. Von Savigny, J P Burrows, Alexei Rozanov, Rene Hommel, V V Rozanov, K U Eichmann, Florian Ernst, L W ThomasonAbstract:Abstract. Stratospheric aerosol extinction profiles have been retrieved from SCIAMACHY/Envisat measurements of limb-scattered solar radiation. The retrieval is an improved version of an algorithm presented earlier. The retrieved aerosol extinction profiles are compared to co-located aerosol profile measurements from the SAGE II solar occultation instrument at a wavelength of 525 nm. Comparisons were carried out with two versions of the SAGE II data set (version 6.2 and the new version 7.0). In a global average sense the SCIAMACHY and the SAGE II version 7.0 extinction profiles agree to within about 10 % for altitudes above 15 km. Larger relative differences (up to 40 %) are observed at specific latitudes and altitudes. We also find differences between the two SAGE II data versions of up to 40 % for specific latitudes and altitudes, consistent with earlier reports. Sample results on the latitudinal and temporal variability of stratospheric aerosol extinction and optical depth during the SCIAMACHY mission period are presented. The results confirm earlier reports that a series of volcanic eruptions is responsible for the increase in stratospheric aerosol optical depth from 2002 to 2012. Above about an altitude of 28 km, volcanic eruptions are found to have negligible impact in the period 2002–2012.
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consistent satellite xco 2 retrievals from SCIAMACHY and gosat using the besd algorithm
Atmospheric Measurement Techniques, 2015Co-Authors: J Heymann, Heinrich Bovensmann, M Buchwitz, J P Burrows, M Reuter, Michael Hilker, Oliver Schneising, Akihiko Kuze, Hiroshi Suto, Nicholas M DeutscherAbstract:Abstract. Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate-related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and TANSO-FTS on-board GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System. We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between SCIAMACHY and GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT–SCIAMACHY (linear correlation coefficient r=0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT–TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY–TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (± 2 h, 10° x 10° around TCCON sites), i.e. the observed air masses are not exactly identical but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by also using data from other missions (e.g. OCO-2, GOSAT-2, CarbonSat) in the future.
Heinrich Bovensmann - One of the best experts on this subject based on the ideXlab platform.
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consistent satellite xco 2 retrievals from SCIAMACHY and gosat using the besd algorithm
Atmospheric Measurement Techniques, 2015Co-Authors: J Heymann, Heinrich Bovensmann, M Buchwitz, J P Burrows, M Reuter, Michael Hilker, Oliver Schneising, Akihiko Kuze, Hiroshi Suto, Nicholas M DeutscherAbstract:Abstract. Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate-related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and TANSO-FTS on-board GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System. We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between SCIAMACHY and GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT–SCIAMACHY (linear correlation coefficient r=0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT–TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY–TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (± 2 h, 10° x 10° around TCCON sites), i.e. the observed air masses are not exactly identical but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by also using data from other missions (e.g. OCO-2, GOSAT-2, CarbonSat) in the future.
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stratospheric ozone trends and variability as seen by SCIAMACHY from 2002 to 2012
Atmospheric Chemistry and Physics, 2014Co-Authors: Claus Gebhardt, Heinrich Bovensmann, J P Burrows, Alexei Rozanov, Rene Hommel, M Weber, D A Degenstein, L Froidevaux, Anne M ThompsonAbstract:Abstract. Vertical profiles of the rate of linear change (trend) in the altitude range 15–50 km are determined from decadal O3 time series obtained from SCIAMACHY1/ENVISAT2 measurements in limb-viewing geometry. The trends are calculated by using a multivariate linear regression. Seasonal variations, the quasi-biennial oscillation, signatures of the solar cycle and the El Nino–Southern Oscillation are accounted for in the regression. The time range of trend calculation is August 2002–April 2012. A focus for analysis are the zonal bands of 20° N–20° S (tropics), 60–50° N, and 50–60° S (midlatitudes). In the tropics, positive trends of up to 5% per decade between 20 and 30 km and negative trends of up to 10% per decade between 30 and 38 km are identified. Positive O3 trends of around 5% per decade are found in the upper stratosphere in the tropics and at midlatitudes. Comparisons between SCIAMACHY and EOS MLS3 show reasonable agreement both in the tropics and at midlatitudes for most altitudes. In the tropics, measurements from OSIRIS4/Odin and SHADOZ5 are also analysed. These yield rates of linear change of O3 similar to those from SCIAMACHY. However, the trends from SCIAMACHY near 34 km in the tropics are larger than MLS and OSIRIS by a factor of around two. 1 SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY 2 European environmental research satellite 3 Earth Observing System (EOS) Microwave Limb Sounder (MLS) 4 Optical Spectrograph and InfraRed Imager System 5 Southern Hemisphere ADditional OZonesondes
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YEARS
2013Co-Authors: Manfred Gottwald, Stefan Noel, Kelly Bramstedt, Eckhart Krieg, Heinrich BovensmannAbstract:SCIAMACHY on ENVISAT has successfully finished the originally specified 5 years mission lifetime [1] and has started the mission extension. In order to preserve SCIAMACHY's excellent status, it is necessary to adapt certain aspects of operations to the extended mission. This concerns instrument measurement execution and monitoring. Special attention has to be paid for the life limited items on-board SCIAMACHY. Therefore the mission scenarios must be revised to ensure that in-flight usage does not conflict with specifications but still fulfills scientific requirements. Additional monitoring tasks are required to understand the performance of instrument subsystems which might be subject to degradation in a longer mission lifetime. Particularly interesting in this respect are the scanners and the thermal systems. For this purpose we have developed and implemented an extended monitoring concept. It will permit maintaining SCIAMACHY in a healthy status, a prerequisite for generating high quality scientific data for the years to come
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global stratospheric aerosol extinction profile retrievals from SCIAMACHY limb scatter observations
Atmospheric Measurement Techniques Discussions, 2012Co-Authors: Florian Ernst, Heinrich Bovensmann, C. Von Savigny, A Rozanov, V V Rozanov, K U Eichmann, Lena A Brinkhoff, J P BurrowsAbstract:Abstract. Stratospheric aerosol extinction profiles are retrieved from SCIAMACHY/Envisat limb-scatter observations in the visible spectral range. The retrieval algorithm is based on a colour-index approach using the normalized limb-radiance profiles at 470 nm and 750 nm wavelength. The optimal estimation approach in combination with the radiative transfer model SCIATRAN is employed for the retrievals. This study presents a detailed description of the retrieval algorithm, and a sensitivity analysis investigating the impact of the most important parameters that affect the aerosol extinction profile retrieval accuracy. It is found that the parameter with the largest impact is surface albedo, particularly for SCIAMACHY observations in the Southern Hemisphere where the error in stratospheric aerosol extinction can be up to 50% if the surface albedo is not well known. The effect of errors in the assumed ozone and neutral density profiles on the aerosol profile retrievals is with generally less than 6% relatively small. The aerosol extinction profiles retrieved from SCIAMACHY are compared with co-located SAGE II solar occultation measurements of stratospheric aerosol extinction during the period 2003–2005. The mean aerosol extinction profiles averaged over all co-locations agree to within 20% between 15 and 35 km altitude. However, larger differences are observed at specific latitudes.
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validation of SCIAMACHY limb no 2 profiles using solar occultation measurements
Atmospheric Measurement Techniques, 2012Co-Authors: R Bauer, A Rozanov, C A Mclinden, Larry L Gordley, Wolfhardt Lotz, James M Russell, K A Walker, J M Zawodny, A Ladstatterweisenmayer, Heinrich BovensmannAbstract:Abstract. The increasing amounts of reactive nitrogen in the stratosphere necessitate accurate global measurements of stratospheric nitrogen dioxide (NO2). Over the past decade, the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument on ENVISAT (European Environmental Satellite) has been providing global coverage of stratospheric NO2 every 6 days. In this study, the vertical distributions of NO2 retrieved from SCIAMACHY limb measurements of the scattered solar light are validated by comparison with NO2 products from three different satellite instruments (SAGE II, HALOE and ACE-FTS). The retrieval algorithm based on the information operator approach is discussed, and the sensitivity of the SCIAMACHY NO2 limb retrievals is investigated. The photochemical corrections needed to make this validation feasible, and the chosen collocation criteria are described. For each instrument, a time period of two years is analyzed with several hundreds of collocation pairs for each year. As NO2 is highly variable, the comparisons are performed for five latitudinal bins and four seasons. In the 20 to 40 km altitude range, mean relative differences between SCIAMACHY and other instruments are found to be typically within 20 to 30%. The mean partial NO2 columns in this altitude range agree typically within 15% (both global monthly and zonal annual means). Larger differences are seen for SAGE II comparisons, which is consistent with the results presented by other authors. For SAGE II and ACE-FTS, the observed differences can be partially attributed to the diurnal effect error.
Christian Frankenberg - One of the best experts on this subject based on the ideXlab platform.
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validation of SCIAMACHY hdo h2o measurements using the tccon and ndacc musica networks
Atmospheric Measurement Techniques, 2015Co-Authors: R A Scheepmaker, Christian Frankenberg, Nicholas M Deutscher, Matthias Schneider, Sabine Barthlott, Thomas Blumenstock, O E Garcia, Frank HaseAbstract:Abstract. Measurements of the atmospheric HDO/H2O ratio help us to better understand the hydrological cycle and improve models to correctly simulate tropospheric humidity and therefore climate change. We present an updated version of the column-averaged HDO/H2O ratio data set from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The data set is extended with 2 additional years, now covering 2003–2007, and is validated against co-located ground-based total column δD measurements from Fourier transform spectrometers (FTS) of the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC, produced within the framework of the MUSICA project). Even though the time overlap among the available data is not yet ideal, we determined a mean negative bias in SCIAMACHY δD of −35 ± 30‰ compared to TCCON and −69 ± 15‰ compared to MUSICA (the uncertainty indicating the station-to-station standard deviation). The bias shows a latitudinal dependency, being largest (∼ −60 to −80‰) at the highest latitudes and smallest (∼ −20 to −30‰) at the lowest latitudes. We have tested the impact of an offset correction to the SCIAMACHY HDO and H2O columns. This correction leads to a humidity- and latitude-dependent shift in δD and an improvement of the bias by 27‰, although it does not lead to an improved correlation with the FTS measurements nor to a strong reduction of the latitudinal dependency of the bias. The correction might be an improvement for dry, high-altitude areas, such as the Tibetan Plateau and the Andes region. For these areas, however, validation is currently impossible due to a lack of ground stations. The mean standard deviation of single-sounding SCIAMACHY–FTS differences is ∼ 115‰, which is reduced by a factor ∼ 2 when we consider monthly means. When we relax the strict matching of individual measurements and focus on the mean seasonalities using all available FTS data, we find that the correlation coefficients between SCIAMACHY and the FTS networks improve from 0.2 to 0.7–0.8. Certain ground stations show a clear asymmetry in δD during the transition from the dry to the wet season and back, which is also detected by SCIAMACHY. This asymmetry points to a transition in the source region temperature or location of the water vapour and shows the added information that HDO/H2O measurements provide when used in combination with variations in humidity.
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inverse modelling of ch 4 emissions for 2010 2011 using different satellite retrieval products from gosat and SCIAMACHY
Atmospheric Chemistry and Physics, 2015Co-Authors: M Alexe, Andre Butz, P Bergamaschi, Otto Hasekamp, Arjo Segers, Rob Detmers, S Guerlet, Robert J Parker, Hartmut Boesch, Christian FrankenbergAbstract:At the beginning of 2009 new space-borne observations of dry-air column-averaged mole fractions of atmospheric methane (XCH4) became available from the Thermal And Near infrared Sensor for carbon Observations-Fourier Transform Spectrometer (TANSO-FTS) instrument on board the Greenhouse Gases Observing SATellite (GOSAT). Until April 2012 concurrent methane (CH4) retrievals were provided by the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) instrument on board the ENVironmental SATellite (ENVISAT). The GOSAT and SCIAMACHY XCH4 retrievals can be compared during the period of overlap. We estimate monthly average CH4 emissions between January 2010 and December 2011, using the TM5-4DVAR inverse modelling system. In addition to satellite data, high-accuracy measurements from the Cooperative Air Sampling Network of the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA ESRL) are used, providing strong constraints on the remote surface atmosphere. We discuss five inversion scenarios that make use of different GOSAT and SCIAMACHY XCH4 retrieval products, including two sets of GOSAT proxy retrievals processed independently by the Netherlands Institute for Space Research (SRON)/Karlsruhe Institute of Technology (KIT), and the University of Leicester (UL), and the RemoTeC "Full-Physics" (FP) XCH4 retrievals available from SRON/KIT. The GOSAT-based inversions show significant reductions in the root mean square (rms) difference between retrieved and modelled XCH4, and require much smaller bias corrections compared to the inversion using SCIAMACHY retrievals, reflecting the higher precision and relative accuracy of the GOSAT XCH4. Despite the large differences between the GOSAT and SCIAMACHY retrievals, 2-year average emission maps show overall good agreement among all satellitebased inversions, with consistent flux adjustment patterns, particularly across equatorial Africa and North America. Over North America, the satellite inversions result in a significant redistribution of CH4 emissions from North-East to South-Central United States. This result is consistent with recent independent studies suggesting a systematic underestimation of CH4 emissions from North American fossil fuel sources in bottom-up inventories, likely related to natural gas production facilities. Furthermore, all four satellite inversions yield lower CH4 fluxes across the Congo basin compared to the NOAA-only scenario, but higher emissions across tropical East Africa. The GOSAT and SCIAMACHY inversions show similar performance when validated against independent shipboard and aircraft observations, and XCH4 retrievals available from the Total Carbon Column Observing Network (TCCON).
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mapping of north american methane emissions with high spatial resolution by inversion of SCIAMACHY satellite data
Journal of Geophysical Research, 2014Co-Authors: K Wecht, Christian Frankenberg, Daniel J Jacob, Zhe Jiang, Donald R BlakeAbstract:We estimate methane emissions from North America with high spatial resolution by inversion of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite observations using the Goddard Earth Observing System Chemistry (GEOS-Chem) chemical transport model and its adjoint. The inversion focuses on summer 2004 when data from the Intercontinental Chemical Transport Experiment-North America (INTEX-A) aircraft campaign over the eastern U.S. are available to validate the SCIAMACHY retrievals and evaluate the inversion. From the INTEX-A data we identify and correct a water vapor-dependent bias in the SCIAMACHY data. We conduct an initial inversion of emissions on the horizontal grid of GEOS-Chem (1/2° × 2/3°) to identify correction tendencies relative to the Emission Database for Global Atmospheric Research (EDGAR) v4.2 emission inventory used as a priori. We then cluster these grid cells with a hierarchical algorithm to extract the maximum information from the SCIAMACHY observations. A 1000 cluster ensemble can be adequately constrained, providing ~100 km resolution across North America. Analysis of results indicates that the Hudson Bay Lowland wetlands source is 2.1 Tg a−1, lower than the a priori but consistent with other recent estimates. Anthropogenic U.S. emissions are 30.1 ± 1.3 Tg a−1, compared to 25.8 Tg a−1 and 28.3 Tg a−1 in the EDGAR v4.2 and Environmental Protection Agency (EPA) inventories, respectively. We find that U.S. livestock emissions are 40% greater than in these two inventories. No such discrepancy is apparent for overall U.S. oil and gas emissions, although this may reflect some compensation between overestimate of emissions from storage/distribution and underestimate from production. We find that U.S. livestock emissions are 70% greater than the oil and gas emissions, in contrast to the EDGAR v4.2 and EPA inventories where these two sources are of comparable magnitude.
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a multi year methane inversion using SCIAMACHY accounting for systematic errors using tccon measurements
Atmospheric Chemistry and Physics, 2014Co-Authors: Christian Frankenberg, M C Krol, Sander Houweling, P Bergamaschi, E J Dlugokencky, Isamu Morino, Justus NotholtAbstract:Abstract. This study investigates the use of total column CH4 (XCH4) retrievals from the SCIAMACHY satellite instrument for quantifying large-scale emissions of methane. A unique data set from SCIAMACHY is available spanning almost a decade of measurements, covering a period when the global CH4 growth rate showed a marked transition from stable to increasing mixing ratios. The TM5 4DVAR inverse modelling system has been used to infer CH4 emissions from a combination of satellite and surface measurements for the period 2003–2010. In contrast to earlier inverse modelling studies, the SCIAMACHY retrievals have been corrected for systematic errors using the TCCON network of ground-based Fourier transform spectrometers. The aim is to further investigate the role of bias correction of satellite data in inversions. Methods for bias correction are discussed, and the sensitivity of the optimized emissions to alternative bias correction functions is quantified. It is found that the use of SCIAMACHY retrievals in TM5 4DVAR increases the estimated inter-annual variability of large-scale fluxes by 22% compared with the use of only surface observations. The difference in global methane emissions between 2-year periods before and after July 2006 is estimated at 27–35 Tg yr−1. The use of SCIAMACHY retrievals causes a shift in the emissions from the extra-tropics to the tropics of 50 ± 25 Tg yr−1. The large uncertainty in this value arises from the uncertainty in the bias correction functions. Using measurements from the HIPPO and BARCA aircraft campaigns, we show that systematic errors in the SCIAMACHY measurements are a main factor limiting the performance of the inversions. To further constrain tropical emissions of methane using current and future satellite missions, extended validation capabilities in the tropics are of critical importance.
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improved water vapour spectroscopy in the 4174 4300 cm 1 region and its impact on SCIAMACHY hdo h2o measurements
Atmospheric Measurement Techniques, 2013Co-Authors: R A Scheepmaker, Christian Frankenberg, H Schrijver, Nicholas M Deutscher, Ana Galli, Andre Butz, Debra Wunch, Thorsten Warneke, Sophie FallyAbstract:Abstract. The relative abundance of the heavy water isotopologue HDO provides a deeper insight into the atmospheric hydrological cycle. The SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) allows for global retrievals of the ratio HDO/H2O in the 2.3 micron wavelength range. However, the spectroscopy of water lines in this region remains a large source of uncertainty for these retrievals. We therefore evaluate and improve the water spectroscopy in the range 4174–4300 cm−1 and test if this reduces systematic uncertainties in the SCIAMACHY retrievals of HDO/H2O. We use a laboratory spectrum of water vapour to fit line intensity, air broadening and wavelength shift parameters. The improved spectroscopy is tested on a series of ground-based high resolution FTS spectra as well as on SCIAMACHY retrievals of H2O and the ratio HDO/H2O. We find that the improved spectroscopy leads to lower residuals in the FTS spectra compared to HITRAN 2008 and Jenouvrier et al. (2007) spectroscopy, and the retrievals become more robust against changes in the retrieval window. For both the FTS and SCIAMACHY measurements, the retrieved total H2O columns decrease by 2–4% and we find a negative shift of the HDO/H2O ratio, which for SCIAMACHY is partly compensated by changes in the retrieval setup and calibration software. The updated SCIAMACHY HDO/H2O product shows somewhat steeper latitudinal and temporal gradients and a steeper Rayleigh distillation curve, strengthening previous conclusions that current isotope-enabled general circulation models underestimate the variability in the near-surface HDO/H2O ratio.
M Buchwitz - One of the best experts on this subject based on the ideXlab platform.
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consistent satellite xco 2 retrievals from SCIAMACHY and gosat using the besd algorithm
Atmospheric Measurement Techniques, 2015Co-Authors: J Heymann, Heinrich Bovensmann, M Buchwitz, J P Burrows, M Reuter, Michael Hilker, Oliver Schneising, Akihiko Kuze, Hiroshi Suto, Nicholas M DeutscherAbstract:Abstract. Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate-related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and TANSO-FTS on-board GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System. We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between SCIAMACHY and GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT–SCIAMACHY (linear correlation coefficient r=0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT–TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY–TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (± 2 h, 10° x 10° around TCCON sites), i.e. the observed air masses are not exactly identical but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by also using data from other missions (e.g. OCO-2, GOSAT-2, CarbonSat) in the future.
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atmospheric greenhouse gases retrieved from SCIAMACHY comparison to ground based fts measurements and model results
Atmospheric Chemistry and Physics, 2012Co-Authors: Oliver Schneising, Heinrich Bovensmann, M Buchwitz, J P Burrows, Nicholas M Deutscher, David W T Griffith, J Heymann, P Bergamaschi, Ronald MacatangayAbstract:Abstract. SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO2 and XCH4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the carbon dioxide annual increases of SCIAMACHY and the assimilation system CarbonTracker (2.00 p 0.16 ppm yr−1 compared to 1.94 p 0.03 ppm yr−1 on global average). The XCO2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant for a subset of the analysed TCCON sites when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision (mean standard deviation of the differences) of about 2.2 ppm and a relative accuracy (standard deviation of the mean differences) of 1.1–1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and lower XCH4 values are retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10–20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH4 data set before November 2005 is suitable for regional source/sink determination and regional-scale flux uncertainty reduction via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements.
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retrieval of atmospheric co2 with enhanced accuracy and precision from SCIAMACHY validation with fts measurements and comparison with model results
Journal of Geophysical Research, 2011Co-Authors: Maximilian Reuter, Heinrich Bovensmann, M Buchwitz, J P Burrows, Brian J Connor, Nicholas M Deutscher, David W T Griffith, J Heymann, Gretchen KeppelaleksAbstract:The Bremen Optimal Estimation differential optical absorption spectroscopy (DOAS) (BESD) algorithm for satellite based retrievals of XCO_2 (the column-average dry-air mole fraction of atmospheric CO_2) has been applied to Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) data. It uses measurements in the O_2-A absorption band to correct for scattering of undetected clouds and aerosols. Comparisons with precise and accurate ground-based Fourier transform spectrometer (FTS) measurements at four Total Carbon Column Observing Network (TCCON) sites have been used to quantify the quality of the new SCIAMACHY XCO_2 data set. Additionally, the results have been compared to NOAA's assimilation system CarbonTracker. The comparisons show that the new retrieval meets the expectations from earlier theoretical studies. We find no statistically significant regional XCO_2 biases between SCIAMACHY and the FTS instruments. However, the standard error of the systematic differences is in the range of 0.2 ppm and 0.8 ppm. The XCO_2 single-measurement precision of 2.5 ppm is similar to theoretical estimates driven by instrumental noise. There are no significant differences found for the year-to-year increase as well as for the average seasonal amplitude between SCIAMACHY XCO_2 and the collocated FTS measurements. Comparison of the year-to-year increase and also of the seasonal amplitude of CarbonTracker exhibit significant differences with the corresponding FTS values at Darwin. Here the differences between SCIAMACHY and CarbonTracker are larger than the standard error of the SCIAMACHY values. The difference of the seasonal amplitude exceeds the significance level of 2 standard errors. Therefore, our results suggest that SCIAMACHY may provide valuable additional information about XCO_2, at least in regions with a low density of in situ measurements.
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SCIAMACHY s view of the changing earth s environment
SCIAMACHY - Exploring the Changing Earth's Atmosphere, 2011Co-Authors: Heinrich Bovensmann, M Buchwitz, Christian Frankenberg, S. Kühl, C. Von Savigny, Manfred Gottwald, M Van Roozendael, Ilse Aben, Andreas Richter, P StammesAbstract:Since August 2002 SCIAMACHY delivers a wealth of high-quality data permitting to study the status of the Earth’s atmosphere. Enhanced concentrations of greenhouse gases are identified as the major source of global warming and their atmospheric concentrations are increasing. SCIAMACHY monitors the most prominent species such as CO2, CH4 and water vapour, the latter including isotope variants. Further anthropogenic impacts on the troposphere occur by emission of reactive trace gases contributing to pollution and affecting air quality. With SCIAMACHY their global, regional and even local signatures can be detected. Long-term analyses document how the emissions of NO2, SO2, HCHO, CHOCHO and CO evolve with time. In addition, the halogen cycle of polar BrO and IO, both of natural origin, is studied. The stratosphere is the layer where public interest in the Earth’s atmosphere has begun to grow with the detection of the ozone hole in the mid-1980s. Until the mid-1990s a steady decrease has been observed in the ozone abundance. The most striking feature is the massive loss of stratospheric ozone over Antarctica during each southern spring. In order to detect possible signs of recovery, SCIAMACHY contributes to the continuous monitoring of the ozone layer, the ozone hole, Polar Stratospheric Clouds (PSC) and species impacting the ozone chemistry such as NO2, OClO and BrO. A much more poorly explored region is the mesosphere and lower thermosphere, which forms the transition between interplanetary space and the terrestrial atmosphere. This region is dominated by extraterrestrial impacts as well as couplings to the lower atmosphere. With SCIAMACHY’s limb viewing capabilities Noctilucent Clouds (NLC) are studied providing insight into generation and depletion mechanisms. At times of strong solar activity, SCIAMACHY measurements reveal how the chemistry of the upper atmosphere is disturbed. By analysis of emission lines in SCIAMACHY spectra the composition of the thermosphere above 100 km can be studied. SCIAMACHY is the first instrument to globally observe the metal layers in the upper mesosphere/lower thermosphere (MLT) region. When applying appropriate retrieval techniques it is meanwhile possible to derive vegetation information over land and phytoplankton characteristics in the oceans from SCIAMACHY data. Finally SCIAMACHY even has proven useful in planetary science by measuring spectra of our solar system neighbour Venus.
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long term analysis of carbon dioxide and methane column averaged mole fractions retrieved from SCIAMACHY
Atmospheric Chemistry and Physics, 2010Co-Authors: Oliver Schneising, Heinrich Bovensmann, M Buchwitz, Maximilian Reuter, J Heymann, J P BurrowsAbstract:Abstract. Carbon dioxide (CO 2 ) and methane (CH 4 ) are the two most important anthropogenic greenhouse gases contributing to global climate change. SCIAMACHY onboard ENVISAT (launch 2002) was the first and is now with TANSO onboard GOSAT (launch 2009) one of only two satellite instruments currently in space whose measurements are sensitive to CO 2 and CH 4 concentration changes in the lowest atmospheric layers where the variability due to sources and sinks is largest. We present long-term SCIAMACHY retrievals (2003–2009) of column-averaged dry air mole fractions of both gases (denoted XCO 2 and XCH 4 ) derived from absorption bands in the near-infrared/shortwave-infrared (NIR/SWIR) spectral region focusing on large-scale features. The results are obtained using an upgraded version (v2) of the retrieval algorithm WFM-DOAS including several improvements, while simultaneously maintaining its high processing speed. The retrieved mole fractions are compared to global model simulations (CarbonTracker XCO 2 and TM5 XCH 4 ) being optimised by assimilating highly accurate surface measurements from the NOAA/ESRL network and taking the SCIAMACHY averaging kernels into account. The comparisons address seasonal variations and long-term characteristics. The steady increase of atmospheric carbon dioxide primarily caused by the burning of fossil fuels can be clearly observed with SCIAMACHY globally. The retrieved global annual mean XCO 2 increase agrees with CarbonTracker within the error bars (1.80±0.13 ppm yr −1 compared to 1.81±0.09 ppm yr −1 ). The amplitude of the XCO 2 seasonal cycle as retrieved by SCIAMACHY, which is 4.3±0.2 ppm for the Northern Hemisphere and 1.4±0.2 ppm for the Southern Hemisphere, is on average about 1 ppm larger than for CarbonTracker. An investigation of the boreal forest carbon uptake during the growing season via the analysis of longitudinal gradients shows good agreement between SCIAMACHY and CarbonTracker concerning the overall magnitude of the gradients and their annual variations. The analysis includes a discussion of the relative uptake strengths of the Russian and North American boreal forest regions. The retrieved XCH 4 results show that after years of stability, atmospheric methane has started to rise again in recent years which is consistent with surface measurements. The largest increase is observed for the tropics and northern mid- and high-latitudes amounting to about 7.5±1.5 ppb yr −1 since 2007. Due care has been exercised to minimise the influence of detector degradation on the quantitative estimate of this anomaly.
Nicholas M Deutscher - One of the best experts on this subject based on the ideXlab platform.
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consistent satellite xco 2 retrievals from SCIAMACHY and gosat using the besd algorithm
Atmospheric Measurement Techniques, 2015Co-Authors: J Heymann, Heinrich Bovensmann, M Buchwitz, J P Burrows, M Reuter, Michael Hilker, Oliver Schneising, Akihiko Kuze, Hiroshi Suto, Nicholas M DeutscherAbstract:Abstract. Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate-related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and TANSO-FTS on-board GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System. We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between SCIAMACHY and GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT–SCIAMACHY (linear correlation coefficient r=0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT–TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY–TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (± 2 h, 10° x 10° around TCCON sites), i.e. the observed air masses are not exactly identical but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by also using data from other missions (e.g. OCO-2, GOSAT-2, CarbonSat) in the future.
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validation of SCIAMACHY hdo h2o measurements using the tccon and ndacc musica networks
Atmospheric Measurement Techniques, 2015Co-Authors: R A Scheepmaker, Christian Frankenberg, Nicholas M Deutscher, Matthias Schneider, Sabine Barthlott, Thomas Blumenstock, O E Garcia, Frank HaseAbstract:Abstract. Measurements of the atmospheric HDO/H2O ratio help us to better understand the hydrological cycle and improve models to correctly simulate tropospheric humidity and therefore climate change. We present an updated version of the column-averaged HDO/H2O ratio data set from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The data set is extended with 2 additional years, now covering 2003–2007, and is validated against co-located ground-based total column δD measurements from Fourier transform spectrometers (FTS) of the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC, produced within the framework of the MUSICA project). Even though the time overlap among the available data is not yet ideal, we determined a mean negative bias in SCIAMACHY δD of −35 ± 30‰ compared to TCCON and −69 ± 15‰ compared to MUSICA (the uncertainty indicating the station-to-station standard deviation). The bias shows a latitudinal dependency, being largest (∼ −60 to −80‰) at the highest latitudes and smallest (∼ −20 to −30‰) at the lowest latitudes. We have tested the impact of an offset correction to the SCIAMACHY HDO and H2O columns. This correction leads to a humidity- and latitude-dependent shift in δD and an improvement of the bias by 27‰, although it does not lead to an improved correlation with the FTS measurements nor to a strong reduction of the latitudinal dependency of the bias. The correction might be an improvement for dry, high-altitude areas, such as the Tibetan Plateau and the Andes region. For these areas, however, validation is currently impossible due to a lack of ground stations. The mean standard deviation of single-sounding SCIAMACHY–FTS differences is ∼ 115‰, which is reduced by a factor ∼ 2 when we consider monthly means. When we relax the strict matching of individual measurements and focus on the mean seasonalities using all available FTS data, we find that the correlation coefficients between SCIAMACHY and the FTS networks improve from 0.2 to 0.7–0.8. Certain ground stations show a clear asymmetry in δD during the transition from the dry to the wet season and back, which is also detected by SCIAMACHY. This asymmetry points to a transition in the source region temperature or location of the water vapour and shows the added information that HDO/H2O measurements provide when used in combination with variations in humidity.
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improved water vapour spectroscopy in the 4174 4300 cm 1 region and its impact on SCIAMACHY hdo h2o measurements
Atmospheric Measurement Techniques, 2013Co-Authors: R A Scheepmaker, Christian Frankenberg, H Schrijver, Nicholas M Deutscher, Ana Galli, Andre Butz, Debra Wunch, Thorsten Warneke, Sophie FallyAbstract:Abstract. The relative abundance of the heavy water isotopologue HDO provides a deeper insight into the atmospheric hydrological cycle. The SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) allows for global retrievals of the ratio HDO/H2O in the 2.3 micron wavelength range. However, the spectroscopy of water lines in this region remains a large source of uncertainty for these retrievals. We therefore evaluate and improve the water spectroscopy in the range 4174–4300 cm−1 and test if this reduces systematic uncertainties in the SCIAMACHY retrievals of HDO/H2O. We use a laboratory spectrum of water vapour to fit line intensity, air broadening and wavelength shift parameters. The improved spectroscopy is tested on a series of ground-based high resolution FTS spectra as well as on SCIAMACHY retrievals of H2O and the ratio HDO/H2O. We find that the improved spectroscopy leads to lower residuals in the FTS spectra compared to HITRAN 2008 and Jenouvrier et al. (2007) spectroscopy, and the retrievals become more robust against changes in the retrieval window. For both the FTS and SCIAMACHY measurements, the retrieved total H2O columns decrease by 2–4% and we find a negative shift of the HDO/H2O ratio, which for SCIAMACHY is partly compensated by changes in the retrieval setup and calibration software. The updated SCIAMACHY HDO/H2O product shows somewhat steeper latitudinal and temporal gradients and a steeper Rayleigh distillation curve, strengthening previous conclusions that current isotope-enabled general circulation models underestimate the variability in the near-surface HDO/H2O ratio.
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atmospheric greenhouse gases retrieved from SCIAMACHY comparison to ground based fts measurements and model results
Atmospheric Chemistry and Physics, 2012Co-Authors: Oliver Schneising, Heinrich Bovensmann, M Buchwitz, J P Burrows, Nicholas M Deutscher, David W T Griffith, J Heymann, P Bergamaschi, Ronald MacatangayAbstract:Abstract. SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO2 and XCH4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the carbon dioxide annual increases of SCIAMACHY and the assimilation system CarbonTracker (2.00 p 0.16 ppm yr−1 compared to 1.94 p 0.03 ppm yr−1 on global average). The XCO2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant for a subset of the analysed TCCON sites when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision (mean standard deviation of the differences) of about 2.2 ppm and a relative accuracy (standard deviation of the mean differences) of 1.1–1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and lower XCH4 values are retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10–20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH4 data set before November 2005 is suitable for regional source/sink determination and regional-scale flux uncertainty reduction via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements.
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retrieval of atmospheric co2 with enhanced accuracy and precision from SCIAMACHY validation with fts measurements and comparison with model results
Journal of Geophysical Research, 2011Co-Authors: Maximilian Reuter, Heinrich Bovensmann, M Buchwitz, J P Burrows, Brian J Connor, Nicholas M Deutscher, David W T Griffith, J Heymann, Gretchen KeppelaleksAbstract:The Bremen Optimal Estimation differential optical absorption spectroscopy (DOAS) (BESD) algorithm for satellite based retrievals of XCO_2 (the column-average dry-air mole fraction of atmospheric CO_2) has been applied to Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) data. It uses measurements in the O_2-A absorption band to correct for scattering of undetected clouds and aerosols. Comparisons with precise and accurate ground-based Fourier transform spectrometer (FTS) measurements at four Total Carbon Column Observing Network (TCCON) sites have been used to quantify the quality of the new SCIAMACHY XCO_2 data set. Additionally, the results have been compared to NOAA's assimilation system CarbonTracker. The comparisons show that the new retrieval meets the expectations from earlier theoretical studies. We find no statistically significant regional XCO_2 biases between SCIAMACHY and the FTS instruments. However, the standard error of the systematic differences is in the range of 0.2 ppm and 0.8 ppm. The XCO_2 single-measurement precision of 2.5 ppm is similar to theoretical estimates driven by instrumental noise. There are no significant differences found for the year-to-year increase as well as for the average seasonal amplitude between SCIAMACHY XCO_2 and the collocated FTS measurements. Comparison of the year-to-year increase and also of the seasonal amplitude of CarbonTracker exhibit significant differences with the corresponding FTS values at Darwin. Here the differences between SCIAMACHY and CarbonTracker are larger than the standard error of the SCIAMACHY values. The difference of the seasonal amplitude exceeds the significance level of 2 standard errors. Therefore, our results suggest that SCIAMACHY may provide valuable additional information about XCO_2, at least in regions with a low density of in situ measurements.
