scholarly journals Characteristics of greenhouse gas concentrations derived from ground-based FTS spectra at Anmyeondo, South Korea

2018 ◽  
Vol 11 (4) ◽  
pp. 2361-2374
Author(s):  
Young-Suk Oh ◽  
S. Takele Kenea ◽  
Tae-Young Goo ◽  
Kyu-Sun Chung ◽  
Jae-Sang Rhee ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Late Summer ◽  
Total Carbon ◽  
Retrieval Algorithm ◽  
Satellite Measurements ◽  
Data Set ◽  
Spectral Bands ◽  
Meteorological Observatory ◽  
Frame Work ◽  
Highly Correlated

Abstract. Since the late 1990s, the meteorological observatory established in Anmyeondo (36.5382° N, 126.3311° E, and 30 m above mean sea level) has been monitoring several greenhouse gases such as CO2, CH4, N2O, CFCs, and SF6 as a part of the Global Atmosphere Watch (GAW) Program. A high resolution ground-based (g-b) Fourier transform spectrometer (FTS) was installed at this observation site in 2013 and has been operated within the frame work of the Total Carbon Column Observing Network (TCCON) since August 2014. The solar spectra recorded by the g-b FTS cover the spectral range 3800 to 16 000 cm−1 at a resolution of 0.02 cm−1. In this work, the GGG2014 version of the TCCON standard retrieval algorithm was used to retrieve total column average CO2 and CH4 dry mole fractions (XCO2, XCH4) and from the FTS spectra. Spectral bands of CO2 (at 6220.0 and 6339.5 cm−1 center wavenumbers, CH4 at 6002 cm−1 wavenumber, and O2 near 7880 cm−1 ) were used to derive the XCO2 and XCH4. In this paper, we provide comparisons of XCO2 and XCH4 between the aircraft observations and g-b FTS over Anmyeondo station. A comparison of 13 coincident observations of XCO2 between g-b FTS and OCO-2 (Orbiting Carbon Observatory) satellite measurements are also presented for the measurement period between February 2014 and November 2017. OCO-2 observations are highly correlated with the g-b FTS measurements (r2 = 0.884) and exhibited a small positive bias (0.189 ppm). Both data set capture seasonal variations of the target species with maximum and minimum values in spring and late summer, respectively. In the future, it is planned to further utilize the FTS measurements for the evaluation of satellite observations such as Greenhouse Gases Observing Satellite (GOSAT, GOSAT-2). This is the first report of the g-b FTS observations of XCO2 species over the Anmyeondo station.

scholarly journals Characteristics of the Greenhouse Gas Concentration Derived from the Ground-based FTS Spectra at Anmyeondo, Korea

2017 ◽  
Author(s):  
Young-Suk Oh ◽  
Samuel Takele Kenea ◽  
Tae-Young Goo ◽  
Gawon Kim ◽  
Kyu-Sun Chung ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Late Summer ◽  
Satellite Observations ◽  
Total Carbon ◽  
Retrieval Algorithm ◽  
Spectral Bands ◽  
Spectral Residual ◽  
Meteorological Observatory ◽  
Solar Intensity ◽  
Measurement Period

Abstract. Since the late 1990s, the meteorological observatory established in Anmyeondo (36.5382˚ N, 126.3311˚ E, and 30 m above mean sea level), has been monitoring several greenhouse gases such as CO2, CH4, N2O, CFCs, and SF6, as part of the Global Atmosphere Watch (GAW) Program. A high resolution ground-based (g-b) Fourier Transform Spectrometer (FTS, IFS-125HR model) was installed at such observation site in 2013, and has been fully operated within the frame work of the Total Carbon Column Observing Network (TCCON) since August, 2014. The solar spectra recorded by the g-b FTS are covered in the range between 3,800 and 16,000 cm−1 at the spectral resolution of 0.02 cm−1 during the measurement period between 2013 and 2016. In this work, the GGG2014 version of the TCCON standard retrieval algorithm was used to retrieve XCO2 concentrations from the FTS spectra. Two spectral bands (at 6220.0 and 6339.5 cm−1 center wavenumbers) were used to derive the XCO2 concentration within the spectral residual of +0.01 %. All sources of errors were thoroughly analyzed. In this paper, we introduced a new home made OASIS (Operational Automatic System for Intensity of Sunray) system to our g-b FTS instrument and that allows reducing the solar intensity variations (SIV) below 2 %. A comparison of the XCO2 concentration in g-b FTS and OCO-2 (Orbiting Carbon Observatory) satellite observations were presented only for the measurement period between 2014 and 2015. Nine coincident observations were selected on a daily mean basis. It was obtained that OCO-2 exhibited low bias with respect to the g-b FTS, which is about −0.065 ppm with the standard deviation of 1.66 ppm, and revealed a strong correlation (R = 0.85). Based on seasonal cycle comparisons, both instruments were generally agreed in capturing seasonal variations of the target species with its maximum and minimum levels in spring and late summer respectively. In the future, it is planned to exert further works in utilizing the FTS measurements for the evaluation of satellite observations such as Greenhouse Gases Observing Satellite (GOSAT) at observation sites. This is the first report of the g-b FTS observations of XCO2 species over the Anmyeondo station.

scholarly journals Atmospheric greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS measurements and model results

2011 ◽  
Vol 11 (10) ◽  
pp. 28713-28745 ◽  
Author(s):  
O. Schneising ◽  
P. Bergamaschi ◽  
H. Bovensmann ◽  
M. Buchwitz ◽  
J. P. Burrows ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Greenhouse Gases ◽  
Seasonal Cycle ◽  
Relative Accuracy ◽  
Total Carbon ◽  
Inverse Modelling ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Relative Precision ◽  
Data Set

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 SCIAMACHY and CarbonTracker carbon dioxide annual increases (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 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 of about 2.2 ppm and a relative accuracy 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 with respect to model simulations 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 less methane 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 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.

scholarly journals Consistent satellite XCO<sub>2</sub> retrievals from SCIAMACHY and GOSAT using the BESD algorithm

2015 ◽  
Vol 8 (2) ◽  
pp. 1787-1832 ◽  
Author(s):  
J. Heymann ◽  
M. Reuter ◽  
M. Hilker ◽  
M. Buchwitz ◽  
O. Schneising ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Detailed Comparison ◽  
Mean Difference ◽  
Total Carbon ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Data Set ◽  
Time Period ◽  
Comparison Results ◽  
The Future

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 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.

scholarly journals Consistent satellite XCO<sub>2</sub> retrievals from SCIAMACHY and GOSAT using the BESD algorithm

2015 ◽  
Vol 8 (7) ◽  
pp. 2961-2980 ◽  
Author(s):  
J. Heymann ◽  
M. Reuter ◽  
M. Hilker ◽  
M. Buchwitz ◽  
O. Schneising ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Detailed Comparison ◽  
Mean Difference ◽  
Total Carbon ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Data Set ◽  
Time Period ◽  
Comparison Results ◽  
The Future

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.

scholarly journals Downward particle flux and carbon export in the Beaufort Sea, Arctic Ocean; the role of zooplankton

2015 ◽  
Vol 12 (16) ◽  
pp. 5103-5117 ◽  
Author(s):  
J.-C. Miquel ◽  
B. Gasser ◽  
J. Martín ◽  
C. Marec ◽  
M. Babin ◽  
...  
Keyword(s):  
Carbon Flux ◽  
Late Summer ◽  
Beaufort Sea ◽  
Total Carbon ◽  
The Arctic ◽  
Surface Zone ◽  
Calanoid Copepods ◽  
Data Set ◽  
Faecal Pellets

Abstract. As part of the international, multidisciplinary project Malina, downward particle fluxes were investigated by means of a drifting multi-sediment trap mooring deployed at three sites in the Canadian Beaufort Sea in late summer 2009. Mooring deployments lasted between 28 and 50 h and targeted the shelf-break and the slope along the Beaufort-Mackenzie continental margin, as well as the edge between the Mackenzie Shelf and the Amundsen Gulf. Besides analyses of C and N, the collected material was investigated for pigments, phyto- and microzooplankton, faecal pellets and swimmers. The measured fluxes were relatively low, in the range of 11–54 mg m−2 d−1 for the total mass, 1–15 mg C m−2 d−1 for organic carbon and 0.2–2.5 mg N m−2 d−1 for nitrogen. Comparison with a long-term trap data set from the same sampling area showed that the short-term measurements were at the lower end of the high variability characterizing a rather high flux regime during the study period. The sinking material consisted of aggregates and particles that were characterized by the presence of hetero- and autotrophic microzooplankters and diatoms and by the corresponding pigment signatures. Faecal pellets contribution to sinking carbon flux was important, especially at depths below 100 m, where they represented up to 25 % of the total carbon flux. The vertical distribution of different morphotypes of pellets showed a marked pattern with cylindrical faeces (produced by calanoid copepods) present mainly within the euphotic zone, whereas elliptical pellets (produced mainly by smaller copepods) were more abundant at mesopelagic depths. These features, together with the density of matter within the pellets, highlighted the role of the zooplankton community in the transformation of carbon issued from the primary production and the transition of that carbon from the productive surface zone to the Arctic Ocean's interior. Our data indicate that sinking carbon flux in this late summer period is primarily the result of a heterotrophic-driven ecosystem.

scholarly journals The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO<sub>2</sub> and CH<sub>4</sub> retrieval algorithm products with measurements from the TCCON

2014 ◽  
Vol 7 (6) ◽  
pp. 1723-1744 ◽  
Author(s):  
B. Dils ◽  
M. Buchwitz ◽  
M. Reuter ◽  
O. Schneising ◽  
H. Boesch ◽  
...  
Keyword(s):  
Climate Change ◽  
Fourier Transform ◽  
Greenhouse Gases ◽  
Greenhouse Gas ◽  
Weighting Function ◽  
Total Carbon ◽  
Inverse Modelling ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Change Initiative

Abstract. Column-averaged dry-air mole fractions of carbon dioxide and methane have been retrieved from spectra acquired by the TANSO-FTS (Thermal And Near-infrared Sensor for carbon Observations-Fourier Transform Spectrometer) and SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) instruments on board GOSAT (Greenhouse gases Observing SATellite) and ENVISAT (ENVIronmental SATellite), respectively, using a range of European retrieval algorithms. These retrievals have been compared with data from ground-based high-resolution Fourier transform spectrometers (FTSs) from the Total Carbon Column Observing Network (TCCON). The participating algorithms are the weighting function modified differential optical absorption spectroscopy (DOAS) algorithm (WFMD, University of Bremen), the Bremen optimal estimation DOAS algorithm (BESD, University of Bremen), the iterative maximum a posteriori DOAS (IMAP, Jet Propulsion Laboratory (JPL) and Netherlands Institute for Space Research algorithm (SRON)), the proxy and full-physics versions of SRON's RemoTeC algorithm (SRPR and SRFP, respectively) and the proxy and full-physics versions of the University of Leicester's adaptation of the OCO (Orbiting Carbon Observatory) algorithm (OCPR and OCFP, respectively). The goal of this algorithm inter-comparison was to identify strengths and weaknesses of the various so-called round- robin data sets generated with the various algorithms so as to determine which of the competing algorithms would proceed to the next round of the European Space Agency's (ESA) Greenhouse Gas Climate Change Initiative (GHG-CCI) project, which is the generation of the so-called Climate Research Data Package (CRDP), which is the first version of the Essential Climate Variable (ECV) "greenhouse gases" (GHGs). For XCO2, all algorithms reach the precision requirements for inverse modelling (< 8 ppm), with only WFMD having a lower precision (4.7 ppm) than the other algorithm products (2.4–2.5 ppm). When looking at the seasonal relative accuracy (SRA, variability of the bias in space and time), none of the algorithms have reached the demanding < 0.5 ppm threshold. For XCH4, the precision for both SCIAMACHY products (50.2 ppb for IMAP and 76.4 ppb for WFMD) fails to meet the < 34 ppb threshold for inverse modelling, but note that this work focusses on the period after the 2005 SCIAMACHY detector degradation. The GOSAT XCH4 precision ranges between 18.1 and 14.0 ppb. Looking at the SRA, all GOSAT algorithm products reach the < 10 ppm threshold (values ranging between 5.4 and 6.2 ppb). For SCIAMACHY, IMAP and WFMD have a SRA of 17.2 and 10.5 ppb, respectively.

scholarly journals SCIAMACHY WFM-DOAS <i>X</i>CO<sub>2</sub>: reduction of scattering related errors

2012 ◽  
Vol 5 (10) ◽  
pp. 2375-2390 ◽  
Author(s):  
J. Heymann ◽  
H. Bovensmann ◽  
M. Buchwitz ◽  
J. P. Burrows ◽  
N. M. Deutscher ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Regional Scale ◽  
Correction Method ◽  
Surface Fluxes ◽  
Total Carbon ◽  
Set Covering ◽  
Retrieval Algorithm ◽  
Data Set ◽  
Data Product ◽  
Carbon Dioxide Co2

Abstract. Global observations of column-averaged dry air mole fractions of carbon dioxide (CO2), denoted by XCO2 , retrieved from SCIAMACHY on-board ENVISAT can provide important and missing global information on the distribution and magnitude of regional CO2 surface fluxes. This application has challenging precision and accuracy requirements. In a previous publication (Heymann et al., 2012), it has been shown by analysing seven years of SCIAMACHY WFM-DOAS XCO2 (WFMDv2.1) that unaccounted thin cirrus clouds can result in significant errors. In order to enhance the quality of the SCIAMACHY XCO2 data product, we have developed a new version of the retrieval algorithm (WFMDv2.2), which is described in this manuscript. It is based on an improved cloud filtering and correction method using the 1.4 μm strong water vapour absorption and 0.76 μm O2-A bands. The new algorithm has been used to generate a SCIAMACHY XCO2 data set covering the years 2003–2009. The new XCO2 data set has been validated using ground-based observations from the Total Carbon Column Observing Network (TCCON). The validation shows a significant improvement of the new product (v2.2) in comparison to the previous product (v2.1). For example, the standard deviation of the difference to TCCON at Darwin, Australia, has been reduced from 4 ppm to 2 ppm. The monthly regional-scale scatter of the data (defined as the mean intra-monthly standard deviation of all quality filtered XCO2 retrievals within a radius of 350 km around various locations) has also been reduced, typically by a factor of about 1.5. Overall, the validation of the new WFMDv2.2 XCO2 data product can be summarised by a single measurement precision of 3.8 ppm, an estimated regional-scale (radius of 500 km) precision of monthly averages of 1.6 ppm and an estimated regional-scale relative accuracy of 0.8 ppm. In addition to the comparison with the limited number of TCCON sites, we also present a comparison with NOAA's global CO2 modelling and assimilation system CarbonTracker. This comparison also shows significant improvements especially over the Southern Hemisphere.

scholarly journals Atmospheric greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS measurements and model results

2012 ◽  
Vol 12 (3) ◽  
pp. 1527-1540 ◽  
Author(s):  
O. Schneising ◽  
P. Bergamaschi ◽  
H. Bovensmann ◽  
M. Buchwitz ◽  
J. P. Burrows ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Standard Deviation ◽  
Greenhouse Gases ◽  
Seasonal Cycle ◽  
Relative Accuracy ◽  
Total Carbon ◽  
Inverse Modelling ◽  
Data Sets ◽  
Relative Precision ◽  
Data Set

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 &amp;pm; 0.16 ppm yr−1 compared to 1.94 &amp;pm; 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.

scholarly journals Improvement of the retrieval algorithm for GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> and their validation using TCCON data

2013 ◽  
Vol 6 (6) ◽  
pp. 1533-1547 ◽  
Author(s):  
Y. Yoshida ◽  
N. Kikuchi ◽  
I. Morino ◽  
O. Uchino ◽  
S. Oshchepkov ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Greenhouse Gases ◽  
Solar Irradiance ◽  
Short Wavelength ◽  
Environmental Studies ◽  
Total Carbon ◽  
Retrieval Algorithm ◽  
Dry Air ◽  
Aerosol Scattering ◽  
Standard Deviations

Abstract. The column-averaged dry-air mole fractions of carbon dioxide and methane (XCO2 and XCH4) have been retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations and released as a SWIR L2 product from the National Institute for Environmental Studies (NIES). XCO2 and XCH4 retrieved using the version 01.xx retrieval algorithm showed large negative biases and standard deviations (−8.85 and 4.75 ppm for XCO2 and −20.4 and 18.9 ppb for XCH4, respectively) compared with data of the Total Carbon Column Observing Network (TCCON). Multiple reasons for these error characteristics (e.g., solar irradiance database, handling of aerosol scattering) are identified and corrected in a revised version of the retrieval algorithm (version 02.xx). The improved retrieval algorithm shows much smaller biases and standard deviations (−1.48 and 2.09 ppm for XCO2 and −5.9 and 12.6 ppb for XCH4, respectively) than the version 01.xx. Also, the number of post-screened measurements is increased, especially at northern mid- and high-latitudinal areas.

scholarly journals Assessment of errors and biases in retrievals of X<sub>CO<sub>2</sub></sub>, X<sub>CH<sub>4</sub></sub>, X<sub>CO</sub>, and X<sub>N<sub>2</sub>O</sub> from a 0.5 cm<sup>–1</sup> resolution solar-viewing spectrometer

2016 ◽  
Vol 9 (8) ◽  
pp. 3527-3546 ◽  
Author(s):  
Jacob K. Hedelius ◽  
Camille Viatte ◽  
Debra Wunch ◽  
Coleen M. Roehl ◽  
Geoffrey C. Toon ◽  
...  
Keyword(s):  
High Resolution ◽  
Greenhouse Gases ◽  
Significant Error ◽  
Total Carbon ◽  
Retrieval Algorithm ◽  
Atmospheric Gases ◽  
Near Ir ◽  
Atmospheric Variations ◽  
Global Density

Abstract. Bruker™ EM27/SUN instruments are commercial mobile solar-viewing near-IR spectrometers. They show promise for expanding the global density of atmospheric column measurements of greenhouse gases and are being marketed for such applications. They have been shown to measure the same variations of atmospheric gases within a day as the high-resolution spectrometers of the Total Carbon Column Observing Network (TCCON). However, there is little known about the long-term precision and uncertainty budgets of EM27/SUN measurements. In this study, which includes a comparison of 186 measurement days spanning 11 months, we note that atmospheric variations of Xgas within a single day are well captured by these low-resolution instruments, but over several months, the measurements drift noticeably. We present comparisons between EM27/SUN instruments and the TCCON using GGG as the retrieval algorithm. In addition, we perform several tests to evaluate the robustness of the performance and determine the largest sources of errors from these spectrometers. We include comparisons of XCO2, XCH4, XCO, and XN2O. Specifically we note EM27/SUN biases for January 2015 of 0.03, 0.75, –0.12, and 2.43 % for XCO2, XCH4, XCO, and XN2O respectively, with 1σ running precisions of 0.08 and 0.06 % for XCO2 and XCH4 from measurements in Pasadena. We also identify significant error caused by nonlinear sensitivity when using an extended spectral range detector used to measure CO and N2O.

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