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Published November 16, 2021 | Published + Supplemental Material
Journal Article Open

Spatial distributions of X_(CO₂) seasonal cycle amplitude and phase over northern high-latitude regions

Abstract

Satellite-based observations of atmospheric carbon dioxide (CO₂) provide measurements in remote regions, such as the biologically sensitive but undersampled northern high latitudes, and are progressing toward true global data coverage. Recent improvements in satellite retrievals of total column-averaged dry air mole fractions of CO₂ (X_(CO₂)) from the NASA Orbiting Carbon Observatory 2 (OCO-2) have allowed for unprecedented data coverage of northern high-latitude regions, while maintaining acceptable accuracy and consistency relative to ground-based observations, and finally providing sufficient data in spring and autumn for analysis of satellite-observed X_(CO₂) seasonal cycles across a majority of terrestrial northern high-latitude regions. Here, we present an analysis of X_(CO₂) seasonal cycles calculated from OCO-2 data for temperate, boreal, and tundra regions, subdivided into 5∘ latitude by 20∘ longitude zones. We quantify the seasonal cycle amplitudes (SCAs) and the annual half drawdown day (HDD). OCO-2 SCAs are in good agreement with ground-based observations at five high-latitude sites, and OCO-2 SCAs show very close agreement with SCAs calculated for model estimates of X_(CO₂) from the Copernicus Atmosphere Monitoring Services (CAMS) global inversion-optimized greenhouse gas flux model v19r1 and the CarbonTracker2019 model (CT2019B). Model estimates of X_(CO₂) from the GEOS-Chem CO₂ simulation version 12.7.2 with underlying biospheric fluxes from CarbonTracker2019 (GC-CT2019) yield SCAs of larger magnitude and spread over a larger range than those from CAMS, CT2019B, or OCO-2; however, GC-CT2019 SCAs still exhibit a very similar spatial distribution across northern high-latitude regions to that from CAMS, CT2019B, and OCO-2. Zones in the Asian boreal forest were found to have exceptionally large SCA and early HDD, and both OCO-2 data and model estimates yield a distinct longitudinal gradient of increasing SCA from west to east across the Eurasian continent. In northern high-latitude regions, spanning latitudes from 47 to 72∘ N, longitudinal gradients in both SCA and HDD are at least as pronounced as latitudinal gradients, suggesting a role for global atmospheric transport patterns in defining spatial distributions of X_(CO₂) seasonality across these regions. GEOS-Chem surface contact tracers show that the largest X_(CO₂) SCAs occur in areas with the greatest contact with land surfaces, integrated over 15–30 d. The correlation of X_(CO₂) SCA with these land surface contact tracers is stronger than the correlation of X_(CO₂) SCA with the SCA of CO₂ fluxes or the total annual CO₂ flux within each 5∘ latitude by 20∘ longitude zone. This indicates that accumulation of terrestrial CO2 flux during atmospheric transport is a major driver of regional variations in X_(CO₂) SCA.

Additional Information

© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 03 Mar 2021 – Discussion started: 12 Mar 2021 – Revised: 21 Aug 2021 – Accepted: 24 Sep 2021 – Published: 16 Nov 2021. The Simpson Research Laboratory at the University of Alaska Fairbanks acknowledges the Alaska Space Grant graduate fellowship and OCO Science Team grant (NNH17ZDA001N-OCO2) for support. Kelly A. Graham and Christopher Holmes acknowledge support from the NSF Office of Polar Programs (grant 1602883) and the NASA Earth and Space Science Fellowship (grant 80NSSC17K0361). KIT acknowledges support by ESA via the projects COCCON-PROCEEDS, COCCON-PROCEEDS II, and FRM4GHG. Manvendra K. Dubey thanks NASA CMS, LANL LDRD, and UCOP support for the LANL EM27/SUN deployments. Debra Wunch acknowledges CFI, ORF, and NSERC support for the ETL TCCON station. This research has been supported by the National Aeronautics and Space Administration (grant nos. NNH17ZDA001N-OCO2 and 80NSSC17K0361) and the National Science Foundation (grant no. 1602883). Author contributions. NJ composed this paper and conducted the analysis under the supervision of WRS. KAG and CH ran GEOS-Chem simulations and provided essential guidance in interpreting results. FH, TB, QT, MF, MKD, and HAP all contributed to data collection with the EM27/SUN measurements in Fairbanks, including instrument evaluations, maintenance, and establishing long-term operations in Fairbanks. DW contributed data from the East Trout Lake TCCON site, as well as a thorough evaluation of the manuscript. RK and PH contributed data from the Sodankylä TCCON site. JN, CP, and TW contributed data from the Białystok and Bremen TCCON sites. All coauthors have provided essential feedback and insights on the content of the paper and Supplement. Code and data availability. OCO-2 data and quality control parameters used here are taken from OCO-2 Lite files (version 9, "B9"), and quality filtering and bias corrections are applied following Jacobs et al. (2020), as described in Sect. 2.1. OCO-2 Lite files are produced by the NASA OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the NASA Goddard Earth Science Data and Information Services Center (https://daac.gsfc.nasa.gov/, NASA, 2020). TCCON data are available from the TCCON data archive, hosted by CaltechDATA: https://tccondata.org/ (TCCON, 2020). EM27/SUN GGG2014 retrievals from Fairbanks, Alaska, are available on the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC): https://doi.org/10.3334/ORNLDAAC/1831 (Jacobs et al., 2021). Methods used to bias correct EM27/SUN data to TCCON are described in the Supplement for Jacobs et al. (2020). All ground-based datasets are also cited individually in Sect. 2.2. The CAMS-optimized flux inversion model output is available on the Copernicus website: https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-greenhouse-gas-inversion (Copernicus, 2020). GEOS-Chem source code is publicly available (https://doi.org/10.5281/zenodo.3701669, The International GEOS-Chem Community, 2020). Model outputs analyzed in this work are archived on Zenodo (https://doi.org/10.5281/zenodo.5640670, Graham et al., 2021). The supplement related to this article is available online at: https://doi.org/10.5194/acp-21-16661-2021-supplement. The authors declare that they have no conflict of interest. This paper was edited by Abhishek Chatterjee and reviewed by two anonymous referees.

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Additional details

Created:
September 15, 2023
Modified:
October 23, 2023