National Institute for Environmental Studies (NIES), Tsukuba (Japan); Akita Prefectural Univ., Akita (Japan)
National Institute for Environmental Studies (NIES), Tsukuba (Japan)
California Inst. of Technology (CalTech), Pasadena, CA (United States); Univ. of Toronto, Toronto, ON (Canada)
California Inst. of Technology (CalTech), Pasadena, CA (United States)
Univ. of Wollongong, NSW (Australia)
Univ. of Wollongong, NSW (Australia); Univ. of Bremen, Bremen (Germany)
Univ. of Bremen, Bremen (Germany)
National Institute of Water and Atmospheric Research, Lauder (New Zealand)
National Institute of Water and Atmospheric Research, Lauder (New Zealand); Lab. de Meteorologie Dynamique, Palaiseau (France)
Karlsruhe Institute of Technology, Karlsruhe (Germany)
Karlsruhe Institute of Technology, Garmisch-Partenkirchen (Germany)
Finnish Meteorological Institute (FMI), Sodankyla (Finland)
Japan Aerospace Exploration Agency (JAXA), Tsukuba (Japan)
Belgian Institute for Space Aeronomy (IASB-BIRA), Brussels (Belgium)
Max Planck Institute for Biogeochemistry (MPI-BGC), Jena (Germany)
Ivy Tech Community College of Indiana, Indianapolis, IN (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
NASA Ames Research Center, Moffett Field, CA (United States)
NASA Ames Research Center, Moffett Field, CA (United States); Bey Area Environmental Research Institute, Petaluma, CA (United States)
Meteorological Research Institute (MRI), Tsukuba (Japan)
National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Japan Meteorological Agency, Tokyo (Japan)
Harvard Univ., Cambridge, MA (United States)
Jet Propulsion Lab., Pasadena, CA (United States); California Inst. of Technology (CalTech), Pasadena, CA (United States); Univ. of Michigan, Ann Arbor, MI (United States)
National Institute for Environmental Studies (NIES), Tsukuba (Japan); Japan Aerospace Exploration Agency (JAXA), Tsukuba (Japan); NASA Ames Research Center, Moffett Field, CA (United States)
We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.
Inoue, Makoto, et al. "Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data." Atmospheric Measurement Techniques (Online), vol. 9, no. 8, Aug. 2016. https://doi.org/10.5194/amt-9-3491-2016
Inoue, Makoto, Morino, Isamu, Uchino, Osamu, Nakatsuru, Takahiro, Yoshida, Yukio, Yokota, Tatsuya, Wunch, Debra, Wennberg, Paul O., Roehl, Coleen M., Griffith, David W. T., Velazco, Voltaire A., Deutscher, Nicholas M., Warneke, Thorsten, Notholt, Justus, Robinson, John, Sherlock, Vanessa, Hase, Frank, Blumenstock, Thomas, ... Tanaka, Tomoaki (2016). Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data. Atmospheric Measurement Techniques (Online), 9(8). https://doi.org/10.5194/amt-9-3491-2016
Inoue, Makoto, Morino, Isamu, Uchino, Osamu, et al., "Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data," Atmospheric Measurement Techniques (Online) 9, no. 8 (2016), https://doi.org/10.5194/amt-9-3491-2016
@article{osti_1379543,
author = {Inoue, Makoto and Morino, Isamu and Uchino, Osamu and Nakatsuru, Takahiro and Yoshida, Yukio and Yokota, Tatsuya and Wunch, Debra and Wennberg, Paul O. and Roehl, Coleen M. and Griffith, David W. T. and others},
title = {Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data},
annote = {We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.},
doi = {10.5194/amt-9-3491-2016},
url = {https://www.osti.gov/biblio/1379543},
journal = {Atmospheric Measurement Techniques (Online)},
issn = {ISSN 1867-8548},
number = {8},
volume = {9},
place = {United States},
publisher = {European Geosciences Union},
year = {2016},
month = {08}}
Wunch, Debra; Toon, Geoffrey C.; Blavier, Jean-François L.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 369, Issue 1943https://doi.org/10.1098/rsta.2010.0240
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 369, Issue 1943https://doi.org/10.1098/rsta.2010.0313