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Title: Consistent satellite XCO 2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm

Abstract

Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO 2) 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 XCO 2, the column-averaged dry-air mole fraction of CO 2. BESD has been initially developed for SCIAMACHY XCO 2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO 2 product. GOSAT BESD XCO 2 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 XCO 2 from GOSAT and present detailed comparisons with ground-based observations of XCO 2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparisonmore » results between all three XCO 2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between the SCIAMACHY and the GOSAT XCO 2. 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 XCO 2 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.« less

Authors:
 [1];  [1];  [1];  [1];  [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2];  [2];  [3];  [4];  [5];  [6];  [2];  [7];  [8];  [1];  [9];  [6];  [10] more »;  [11];  [5];  [1];  [9] « less
  1. University of Bremen, Bremen (Germany)
  2. Japan Aerospace Exploration Agency (JAXA), Tsukuba (Japan)
  3. University of Bremen, Bremen (Germany); Univ. of Wollongong, Wollongong (Australia)
  4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  5. University of Wollongong, Wollongong(Australia)
  6. IMK-ASF, Karlsruhe Institute of Technology (KIT), Karlsruhe (Germany)
  7. Finnish Meteorological Institute, Sodankylä (Finland)
  8. National Institute for Environmental Studies (NIES), Tsukuba (Japan)
  9. California Institute of Technology, Pasadena, CA (United States)
  10. National Institute of Water and Atmospheric Research, Wellington (New Zealand); Lab. de Meteorologie Dynamique, Palaiseau (France)
  11. IMK-IFU, Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen (Germany)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1208894
Grant/Contract Number:
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Atmospheric Measurement Techniques Discussions (Online)
Additional Journal Information:
Journal Name: Atmospheric Measurement Techniques Discussions (Online); Journal Volume: 8; Journal Issue: 2; Journal ID: ISSN 1867-8610
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Heymann, J., Reuter, M., Hilker, M., Buchwitz, M., Schneising, O., Bovensmann, H., Burrows, J. P., Kuze, A., Suto, H., Deutscher, N. M., Dubey, M. K., Griffith, D. W. T., Hase, F., Kawakami, S., Kivi, R., Morino, I., Petri, C., Roehl, C., Schneider, M., Sherlock, V., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D. Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm. United States: N. p., 2015. Web. doi:10.5194/amtd-8-1787-2015.
Heymann, J., Reuter, M., Hilker, M., Buchwitz, M., Schneising, O., Bovensmann, H., Burrows, J. P., Kuze, A., Suto, H., Deutscher, N. M., Dubey, M. K., Griffith, D. W. T., Hase, F., Kawakami, S., Kivi, R., Morino, I., Petri, C., Roehl, C., Schneider, M., Sherlock, V., Sussmann, R., Velazco, V. A., Warneke, T., & Wunch, D. Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm. United States. doi:10.5194/amtd-8-1787-2015.
Heymann, J., Reuter, M., Hilker, M., Buchwitz, M., Schneising, O., Bovensmann, H., Burrows, J. P., Kuze, A., Suto, H., Deutscher, N. M., Dubey, M. K., Griffith, D. W. T., Hase, F., Kawakami, S., Kivi, R., Morino, I., Petri, C., Roehl, C., Schneider, M., Sherlock, V., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D. Fri . "Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm". United States. doi:10.5194/amtd-8-1787-2015. https://www.osti.gov/servlets/purl/1208894.
@article{osti_1208894,
title = {Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm},
author = {Heymann, J. and Reuter, M. and Hilker, M. and Buchwitz, M. and Schneising, O. and Bovensmann, H. and Burrows, J. P. and Kuze, A. and Suto, H. and Deutscher, N. M. and Dubey, M. K. and Griffith, D. W. T. and Hase, F. and Kawakami, S. and Kivi, R. and Morino, I. and Petri, C. and Roehl, C. and Schneider, M. and Sherlock, V. and Sussmann, R. and Velazco, V. A. and Warneke, T. and Wunch, D.},
abstractNote = {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 (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.},
doi = {10.5194/amtd-8-1787-2015},
journal = {Atmospheric Measurement Techniques Discussions (Online)},
number = 2,
volume = 8,
place = {United States},
year = {Fri Feb 13 00:00:00 EST 2015},
month = {Fri Feb 13 00:00:00 EST 2015}
}

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