Jacob Hedelius, University of Toronto
Tai-Long He, University of Toronto
Dylan B. A Jones, University of Toronto, University of California
Bianca Baier, University of Colorado, National Oceanic and Atmospheric Administration
Rebecca R. Buchholz, National Center for Atmospheric ResearchFollow
Martine de Maziere, Belgian Institute for Space Aeronomy, BIRA-IASB, Belgium, Royal Belgian Institute for Space AeronomyFollow
Nicholas M. Deutscher, University of WollongongFollow
Manvendra K. Dubey, Los Alamos National Laboratory
Dietrich G. Feist, Max Planck Institute, Max Planck Institute for Biogeochemistry
David W. T Griffith, University of WollongongFollow
Frank Hase, IMK-A-SF, Karlsruhe Institute of Technology, Laboratoire des Sciences du Climat et de L'Environnement
Laura T. Iraci, NASA Ames Research Center, Moffett Field, CA, USA
Pascal Jeseck, PSL Research University
Matthaus Kiel, Karlsruhe Institute of Technology, California Institute of Technology
Rigel Kivi, FMI Arctic Research Center, Finnish Meteorological Institute
Cheng Liu, University of Science and Technology of China, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Chinese Academy Of Sciences
Isamu Morino, National Institute for Environmental Studies
Justus Notholt, University of Bremen
Young-Suk Oh, Hanyang University, National Institute of Meteorological SciencesFollow
Hirofumi Ohyama, Japan Aerospace Exploration Agency, National Institute for Environmental Studies
David F. Pollard, National Institute of Water and Atmospheric Research, New Zealand
Markus Rettinger, Karlsruhe Institute of Technology
Sebastien Roche, University of Toronto
Coleen M. Roehl, California Institute of Technology
Matthias Schneider, IMK-A-SF, Karlsruhe Institute of Technology, Izana Atmospheric Research CentreFollow
Kei Shiomi, Japan Aerospace Exploration Agency
Kimberly Strong, University of TorontoFollow
Ralf Sussmann, Karlsruhe Institute of TechnologyFollow
Colm Sweeney, National Oceanic and Atmospheric Administration, University of Colorado
Yao Te, Sorbonne Universites, PSL Research University
Osamu Uchino, University of Science and Technology of China, National Institute for Environmental StudiesFollow
Voltaire A. Velazco, University of WollongongFollow
Wei Wang, Chinese Academy of Geological Sciences
Thorsten Warneke, University of Bremen, National Institute for Environmental Studies
Paul O. Wennberg, California Institute of TechnologyFollow
Helen Worden, National Center for Atmospheric Research
Debra Wunch, California Institute of Technology, University of TorontoFollow



Publication Details

Hedelius, J. K., He, T., Jones, D. B.A., Baier, B. C., Buchholz, R. R., de Maziere, M., Deutscher, N. M., Dubey, M. K., Feist, D. G., Griffith, D. W.T., Hase, F., Iraci, L. T., Jeseck, P., Kiel, M., Kivi, R., Liu, C., Morino, I., Notholt, J., Oh, Y., Ohyama, H., Pollard, D. F., Rettinger, M., Roche, S., Roehl, C. M., Schneider, M., Shiomi, K., Strong, K., Sussmann, R., Sweeney, C., Te, Y., Uchino, O., Velazco, V. A., Wang, W., Warneke, T., Wennberg, P. O., Worden, H. M. & Wunch, D. (2019). Evaluation of MOPITT Version 7 joint TIR-NIR XCO retrievals with TCCON. Atmospheric Measurement Techniques, 12 (10), 5547-5572.


Observations of carbon monoxide (CO) from the Measurements Of Pollution In The Troposphere (MOPITT) instrument aboard the Terra spacecraft were expected to have an accuracy of 10 % prior to the launch in 1999. Here we evaluate MOPITT Version 7 joint (V7J) thermal-infrared and near-infrared (TIR-NIR) retrieval accuracy and precision and suggest ways to further improve the accuracy of the observations. We take five steps involving filtering or bias corrections to reduce scatter and bias in the data relative to other MOPITT soundings and ground-based measurements. (1) We apply a preliminary filtering scheme in which measurements over snow and ice are removed. (2) We find a systematic pairwise bias among the four MOPITT along-track detectors (pixels) on the order of 3-4 ppb with a small temporal trend, which we remove on a global scale using a temporally trended bias correction. (3) Using a small-region approximation (SRA), a new filtering scheme is developed and applied based on additional quality indicators such as the signal-to-noise ratio (SNR). After applying these new filters, the root-mean-squared error computed using the local median from the SRA over 16 years of global observations decreases from 3.84 to 2.55 ppb. (4) We also use the SRA to find variability in MOPITT retrieval anomalies that relates to retrieval parameters. We apply a bias correction to one parameter from this analysis. (5) After applying the previous bias corrections and filtering, we compare the MOPITT results with the GGG2014 ground-based Total Carbon Column Observing Network (TCCON) observations to obtain an overall global bias correction. These comparisons show that MOPITT V7J is biased high by about 6 %-8 %, which is similar to past studies using independent validation datasets on V6J. When using TCCON spectrometric column retrievals without the standard airmass correction or scaling to aircraft (WMO scale), the ground- and satellite-based observations overall agree to better than 0.5 %. GEOS-Chem data assimilations are used to estimate the influence of filtering and scaling to TCCON on global CO and tend to pull concentrations away from the prior fluxes and closer to the truth. We conclude with suggestions for further improving the MOPITT data products.

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