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  • Articles  (31)
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  • 1
    Publication Date: 2012-02-09
    Description: 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 ± 0.16 ppm yr−1 compared to 1.94 ± 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.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 2
    Publication Date: 2013-03-04
    Description: Urban areas, which are home to the majority of today's world population, are responsible for more than two-thirds of the global energy-related carbon dioxide emissions. Given the ongoing demographic growth and rising energy consumption in metropolitan regions particularly in the developing world, urban-based emissions are expected to further increase in the future. As a consequence, monitoring and independent verification of reported anthropogenic emissions is becoming more and more important. It is demonstrated using SCIAMACHY nadir measurements that anthropogenic CO2 emissions can be detected from space and that emission trends might be tracked using satellite observations. This is promising with regard to future satellite missions with high spatial resolution and wide swath imaging capability aiming at constraining anthropogenic emissions down to the point-source scale. By subtracting retrieved background values from those retrieved over urban areas we find significant CO2 enhancements for several anthropogenic source regions, namely 1.3 ± 0.7 ppm for the Rhine-Ruhr metropolitan region and the Benelux, 1.1 ± 0.5 ppm for the East Coast of the United States, and 2.4 ± 0.9 ppm for the Yangtze River Delta. The order of magnitude of the enhancements is in agreement with what is expected for anthropogenic CO2 signals. The larger standard deviation of the retrieved Yangtze River Delta enhancement is due to a distinct positive trend of 0.3 ± 0.2 ppm yr−1, which is quantitatively consistent with anthropogenic emissions from the Emission Database for Global Atmospheric Research (EDGAR) in terms of percentual increase per year. Potential contributions to the retrieved CO2 enhancement by several error sources, e.g. aerosols, albedo, and residual biospheric signals due to heterogeneous seasonal sampling, are discussed and can be ruled out to a large extent.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 3
    Publication Date: 2013-02-15
    Description: We analyze an ensemble of seven XCO2 retrieval algorithms for SCIAMACHY (scanning imaging absorption spectrometer of atmospheric chartography) and GOSAT (greenhouse gases observing satellite). The ensemble spread can be interpreted as regional uncertainty and can help to identify locations for new TCCON (total carbon column observing network) validation sites. Additionally, we introduce the ensemble median algorithm EMMA combining individual soundings of the seven algorithms into one new data set. The ensemble takes advantage of the algorithms' independent developments. We find ensemble spreads being often 〈 1 ppm but rising up to 2 ppm especially in the tropics and East Asia. On the basis of gridded monthly averages, we compare EMMA and all individual algorithms with TCCON and CarbonTracker model results (potential outliers, north/south gradient, seasonal (peak-to-peak) amplitude, standard deviation of the difference). Our findings show that EMMA is a promising candidate for inverse modeling studies. Compared to CarbonTracker, the satellite retrievals find consistently larger north/south gradients (by 0.3–0.9 ppm) and seasonal amplitudes (by 1.5–2.0 ppm).
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
    Publication Date: 2015-02-13
    Description: 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 onboard ENVISAT (March 2002–April 2012) and TANSO-FTS onboard 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 (IFS). 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 the SCIAMACHY and the 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° × 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 using also data from other missions (e.g., OCO-2, GOSAT-2, CarbonSat) in the future.
    Electronic ISSN: 1867-8610
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 5
    Publication Date: 2011-03-28
    Description: Carbon dioxide (CO2) and methane (CH4) 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 CO2 and CH4 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 XCO2 and XCH4) 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 XCO2 and TM5 XCH4) 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 XCO2 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 XCO2 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 XCH4 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.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 6
    Publication Date: 2012-12-06
    Description: Urban areas, which are home to the majority of today's world population, are responsible for more than two-thirds of the global energy-related carbon dioxide emissions. Given the ongoing demographic growth and rising energy consumption in metropolitan regions particularly in the developing world, urban-based emissions are expected to further increase in the future. As a consequence, monitoring and independent verification of reported anthropogenic emissions is becoming more and more important. It is demonstrated using SCIAMACHY nadir measurements that anthropogenic CO2 emissions can be detected from space and that emission trends might be tracked using satellite observations. This is promising with regard to future satellite missions with high spatial resolution and wide swath imaging capability aiming at constraining anthropogenic emissions down to the point-source scale. By subtracting retrieved background values from those retrieved over urban areas we find significant CO2 enhancements for several anthropogenic source regions, namely 1.3 ± 0.7 ppm for the Rhine-Ruhr metropolitan region and the Benelux, 1.1 ± 0.5 ppm for the East Coast of the United States, and 2.4 ± 0.9 ppm for the Yangtze River Delta. The order of magnitude of the enhancements is in agreement with what is expected for anthropogenic CO2 signals. The larger standard deviation of the retrieved Yangtze River Delta enhancement is due to a distinct positive trend of 0.3 ± 0.2 ppm yr−1, which is quantitatively consistent with anthropogenic emissions from the Emission Database for Global Atmospheric Research (EDGAR) in terms of percentual increase per year. Potential contributions to the retrieved CO2 enhancement by several error sources, e.g. aerosols, albedo, and residual biospheric signals due to heterogeneous seasonal sampling, are discussed and can be ruled out to a large extent.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 7
    Publication Date: 2015-09-28
    Description: This study presents results from the European Centre for Medium-Range Weather Forecasts (ECMWF) carbon dioxide (CO2) analysis system where the atmospheric CO2 is controlled through the assimilation of column-average dry-air mole fractions of CO2 (XCO2) from the Greenhouse gases Observing Satellite (GOSAT). The analysis is compared to a free run simulation and they are both evaluated against XCO2 data from the Total Carbon Column Observing Network (TCCON). We show that the assimilation of the GOSAT XCO2 product from the Bremen Optimal Estimation DOAS (BESD) algorithm during the year 2013 provides XCO2 fields with an improved station-to-station bias deviation of 0.7 parts per million (ppm) compared to the free run (1.4 ppm) and an improved estimated precision of ~ 1 ppm compared to the used GOSAT data (3.4 ppm). We also show that the analysis has skill for synoptic situations in the vicinity of frontal systems where the GOSAT retrievals are sparse due to cloud contamination. We finally computed the 10 day forecast from each analysis at 00:00 UTC. Compared to its own analysis the CO2 forecast shows synoptic skill for the largest scale weather patterns even up to day 5 according to the anomaly correlation coefficient.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 8
    Publication Date: 2014-08-26
    Description: Current knowledge about the European terrestrial biospheric carbon sink, from the Atlantic to the Urals, relies upon bottom-up inventory and surface flux inverse model estimates (e.g., 0.27 ± 0.16 Gt C a−1 for 2000–2005 5 (Schulze et al., 2009), 0.17 ± 0.44 Gt C a−1 for 2001–2007 (Peters et al., 2010), 0.45 ± 0.40 Gt C a−1 for 2010 (Chevallier et al., 2014), 0.40 ± 0.42 Gt C a−1 for 2001–2004 (Peylin et al., 2013). Inverse models assimilate in situ CO2 atmospheric concentrations measured by surface-based air sampling networks. The intrinsic sparseness of these networks is one reason for the relatively large flux uncertainties (Peters et al., 2010; Bruhwiler et al., 2011). Satellite-based CO2 measurements have the potential to reduce these uncertainties (Miller et al., 2007; Chevallier et al., 2007). Global inversion experiments using independent models and independent GOSAT satellite data products consistently derived a considerably larger European sink (0.9–1.2 Gt C a−1 for September 2009–August 2010 (Basu et al., 2013), 1.2–1.8 Gt C a−1 in 2010, Chevallier et al., 2014). However, these results have been considered unrealistic due to potential large scale retrieval biases and/or long-range transport errors (Chevallier et al., 2014) or have not been discussed at all (Basu et al., 2013; Takagi et al., 2014). Here we show that the satellite-derived European terrestrial carbon sink is indeed much larger (1.02 ± 0.30 Gt C a−1 in 2010) than previously expected. Our analysis comprises a regional inversion approach using STILT (Gerbig et al., 2003; Lin et al., 2003) short range (days) particle dispersion modelling, rendering it insensitive to large scale retrieval biases and less sensitive to long-range transport errors. The highest gain in information is obtained during the growing season when satellite observation conditions are advantageous and a priori uncertainties are largest. The consistency among an ensemble of five different inversion set-ups and five independent satellite retrievals (BESD (Reuter et al., 2011) 2003–2010, ACOS (O’Dell et al., 2012) 2010, UoL-FP (Cogan et al., 2012) 2010, RemoTeC C (Butz et al., 2011) 2010, and NIES (Yoshida et al., 2013) 2010) using data from two different instruments (SCIAMACHY, Bovensmann et al., 1999 and GOSAT, Kuze et al., 2009) provides evidence that our current understanding of the European carbon sink has to be revisited.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 9
    Publication Date: 2013-08-30
    Description: The terrestrial biosphere is currently acting as a net carbon sink on the global scale exhibiting significant interannual variability in strength. To reliably predict the future strength of the land sink and its role in atmospheric CO2 growth the underlying processes and their response to a changing climate need to be well understood. In particular, better knowledge of the impact of key climate variables like temperature or precipitation on the biospheric carbon reservoir is essential. It is demonstrated using nearly a decade of SCIAMACHY nadir measurements that years with higher temperatures during the growing season can be robustly associated with larger growth rates in atmospheric CO2 and smaller seasonal cycle amplitudes for northern mid-latitudes. We find linear relationships between warming and CO2 growth as well as seasonal cycle amplitude at the 98% significance level. This suggests that the terrestrial carbon sink is less efficient at higher temperatures, which might lead to future sink saturation via a positive carbon-climate feedback. Quantitatively, the covariation between the annual CO2 growth rates derived from SCIAMACHY data and warm season surface temperature anomaly amounts to 1.25±0.32 ppm yr−1 K−1 for the Northern Hemisphere where the bulk of the terrestrial carbon sink is located. In comparison, the relation is less pronounced in the Southern Hemisphere. The covariation of the seasonal cycle amplitudes derived from satellite and temperature anomaly is −1.30±0.31 ppm K−1 for the north temperate zone. These estimates are consistent with those from the CarbonTracker data assimilated CO2 data product indicating that the temperature dependence of the model surface fluxes is realistic.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 10
    Publication Date: 2012-04-17
    Description: Carbon dioxide (CO2) is the most important greenhouse gas whose atmospheric loading has been significantly increased by anthropogenic activity leading to global warming. Accurate measurements and models are needed in order to reliably predict our future climate. This, however, has challenging requirements. Errors in measurements and models need to be identified and minimised. In this context, we present a comparison between satellite-derived column-averaged dry air mole fractions of CO2, denoted XCO2, retrieved from SCIAMACHY/ENVISAT using the WFM-DOAS algorithm, and output from NOAA's global CO2 modelling and assimilation system CarbonTracker. We investigate to what extent differences between these two data sets are influenced by systematic retrieval errors due to aerosols and unaccounted clouds. We analyse seven years of SCIAMACHY WFM-DOAS version 2.1 retrievals (WFMDv2.1) using the latest version of CarbonTracker (version 2010). We investigate to what extent the difference between SCIAMACHY and CarbonTracker XCO2 are temporally and spatially correlated with global aerosol and cloud data sets. For this purpose, we use a global aerosol data set generated within the European GEMS project, which is based on assimilated MODIS satellite data. For clouds, we use a data set derived from CALIOP/CALIPSO. We find significant correlations of the SCIAMACHY minus CarbonTracker XCO2 difference with thin clouds over the Southern Hemisphere. The maximum temporal correlation we find for Darwin, Australia (r2 = 54%). Large temporal correlations with thin clouds are also observed over other regions of the Southern Hemisphere (e.g. 43% for South America and 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. For all other regions the temporal correlations with aerosol are typically low. For the spatial correlations the picture is less clear. They are typically low for both aerosols and clouds, but dependent on region and season, they may exceed 30% (the maximum value of 46% has been found for Darwin during September to November). Overall we find that the presence of thin clouds can potentially explain a significant fraction of the difference between SCIAMACHY WFMDv2.1 XCO2 and CarbonTracker over the Southern Hemisphere. Aerosols appear to be less of a problem. Our study indicates that the quality of the satellite derived XCO2 will significantly benefit from a reduction of scattering related retrieval errors at least for the Southern Hemisphere.
    Electronic ISSN: 1867-8610
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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