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Published October 21, 2019 | Version Published
Journal Article Open

Evaluation of MOPITT Version 7 joint TIR–NIR XCO retrievals with TCCON

Creators

  • 1. ROR icon University of Toronto
  • 2. ROR icon Cooperative Institute for Research in Environmental Sciences
  • 3. ROR icon Earth System Research Laboratory
  • 4. Atmospheric Chemistry Observations & Modeling, National Center for Atmospheric Research, Boulder, Colorado, USA
  • 5. ROR icon Royal Belgian Institute for Space Aeronomy
  • 6. ROR icon University of Wollongong
  • 7. ROR icon Los Alamos National Laboratory
  • 8. ROR icon Ludwig-Maximilians-Universität München
  • 9. ROR icon German Aerospace Center
  • 10. ROR icon Max Planck Institute for Biogeochemistry
  • 11. ROR icon Karlsruhe Institute of Technology
  • 12. ROR icon Ames Research Center
  • 13. ROR icon Sorbonne University
  • 14. ROR icon California Institute of Technology
  • 15. ROR icon Jet Propulsion Lab
  • 16. ROR icon Finnish Meteorological Institute
  • 17. ROR icon University of Science and Technology of China
  • 18. ROR icon National Institute for Environmental Studies
  • 19. ROR icon University of Bremen
  • 20. ROR icon National Institute of Meteorological Sciences
  • 21. ROR icon National Institute of Water and Atmospheric Research
  • 22. ROR icon Japan Aerospace Exploration Agency
  • 23. Oscar M. Lopez Center for Climate Change Adaptation and Disaster Risk Management Foundation, Inc., Pasig City, Philippines
  • 24. ROR icon Anhui Institute of Optics and Fine Mechanics

Abstract

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.

Copyright and License

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. Published by Copernicus Publications on behalf of the European Geosciences Union.

Acknowledgement

This project is undertaken with the financial support of the Canadian Space Agency (CSA) through the Earth System Science Data Analyses program (grant no. 16SUASCOBF).

This paragraph contains TCCON site acknowledgements as requested by site PIs and co-authors. The Ascension Island TCCON station has been supported by the European Space Agency (ESA) under grant no. 3-14737 and by the German Bundesministerium für Wirtschaft und Energie (BMWi) under grant nos. 50EE1711C and 50EE1711E. We thank the ESA Ariane tracking station at North East Bay, Ascension Island, for hosting and local support. The Four Corners and Manaus TCCON stations have been supported by LANL-LDRD. The Eureka TCCON measurements were made at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC), primarily supported by the CSA, NSERC, and Environment and Climate Change Canada (ECCC). The East Trout Lake TCCON station is supported by the Canada Foundation for Innovation, the Ontario Research Fund, and ECCC. Work at Anmyeondo was funded by Korea Meteorological Administration Research and Development Program “Research and Development for KMA Weather, Climate, and Earth System Services” under grant KMA2018-00321. The TCCON projects for Rikubetsu, Tsukuba, and Burgos sites are supported in part by the GOSAT series project. Site support for Burgos is provided by the Energy Development Corporation (EDC, Philippines). Nicholas M. Deutscher is supported by an ARC Future Fellowship, FT180100327.

We thank the MOPITT team for providing the MOPITT data – especially Merritt Deeter and James Drummond for helpful discussions. We thank Geoff Toon for developing the GGG2014 code used to process the TCCON data. We acknowledge the TCCON co-investigators and site technicians who have also helped maintain sites and provide data throughout the years as well as the respective funding organizations that supported the TCCON measurements at the various sites. Specifically we acknowledge Thomas Blumenstock, Youwen Sun, Joseph Mendonca, and Tae-Young Goo.

We thank Roisin Commane, Enrico Dammers, Benjamin Gaubert, Junjie Liu, Anna Michalak, Charles Miller, Katherine Saad, Mahesh Sha, and Felix Vogel for helpful discussions. We especially thank Merritt Deeter, John Gille, and Geoff Toon for providing feedback on the paper.

We thank Chris O'Dell and one anonymous reviewer for reviewing this paper. We thank Andre Butz for serving as editor.

Funding

This research has been supported by the Canadian Space Agency (grant no. 16SUASCOBF), the European Space Agency (grant no. 3-14737), the Bundesministerium für Wirtschaft und Energie (grant no. 50EE1711C), the Los Alamos National Laboratory (grant no. LANL-LDRD), the Korea Meteorological Administration (grant no. KMA2018-00321), the Japan Aerospace Exploration Agency (grant no. GOSAT series), and the Australian Research Council (grant no. FT180100327).

Data Availability

MOPITT data were obtained from the NASA Langley server (ftp://l5ftl01.larc.nasa.gov/MOPITT/, last access: 12 December 2018). TCCON data were obtained through the TCCON data archive hosted by CaltechDATA (TCCON, 2018). See Table 1 for data references for each site. TCCON data without the scaling to the WMO scale were obtained from the site PIs. AirCore data were obtained from Colm Sweeney (v20170918).

Supplemental Material

The supplement related to this article is available online at: https://doi.org/10.5194/amt-12-5547-2019-supplement.

Additional Information

This paper was edited by Andre Butz and reviewed by Christopher O'Dell and one anonymous referee.

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Additional details

Related works

Is new version of
Discussion Paper: 10.5194/amt-2019-201 (DOI)

Funding

Canadian Space Agency
16SUASCOBF
European Space Agency
3-14737
Federal Ministry for Economic Affairs and Climate Action
50EE1711C
Los Alamos National Laboratory
LANL-LDRD
Korea Meteorological Administration
KMA2018-00321
Japan Aerospace Exploration Agency
Australian Research Council
FT180100327

Dates

Accepted
2019-09-13

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Caltech groups
Division of Engineering and Applied Science (EAS), Division of Geological and Planetary Sciences (GPS)
Publication Status
Published