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  • Greenhouse gases  (2)
  • American Geophysical Union  (2)
  • American Institute of Physics (AIP)
  • Association for the Sciences of Limnology and Oceanography
  • Nature Publishing Group
  • Wiley
  • 2020-2023  (2)
Collection
Publisher
  • American Geophysical Union  (2)
  • American Institute of Physics (AIP)
  • Association for the Sciences of Limnology and Oceanography
  • Nature Publishing Group
  • Wiley
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  • 2020-2023  (2)
Year
  • 1
    Publication Date: 2022-10-26
    Description: Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Atmospheres 124 (17-18), (2019): 9773-9795, doi: 10.1029/2018JD029933.
    Description: National Aeronautics and Space Administration's Orbiting Carbon Observatory‐2 (OCO‐2) satellite provides observations of total column‐averaged CO2 mole fractions (XCO2 ) at high spatial resolution that may enable novel constraints on surface‐atmosphere carbon fluxes. Atmospheric inverse modeling provides an approach to optimize surface fluxes at regional scales, but the accuracy of the fluxes from inversion frameworks depends on key inputs, including spatially and temporally dense CO2 observations and reliable representations of atmospheric transport. Since XCO2 observations are sensitive to both synoptic and mesoscale variations within the free troposphere, horizontal atmospheric transport imparts substantial variations in these data and must be either resolved explicitly by the atmospheric transport model or accounted for within the error covariance budget provided to inverse frameworks. Here, we used geostatistical techniques to quantify the imprint of atmospheric transport in along‐track OCO‐2 soundings. We compare high‐pass‐filtered (〈250 km, spatial scales that primarily isolate mesoscale or finer‐scale variations) along‐track spatial variability in XCO2 and XH2O from OCO‐2 tracks to temporal synoptic and mesoscale variability from ground‐based XCO2 and XH2O observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of along‐track, high‐frequency variability for OCO‐2 XH2O. For XCO2 , both mesoscale transport variability and spatially coherent bias associated with other elements of the OCO‐2 retrieval state vector are important drivers of the along‐track variance budget.
    Description: The authors thank the leadership and participants of the NASA OCO‐2 mission and acknowledge financial support from NASA Award NNX15AH13G. A.D. Torres also acknowledges support from the NASA Earth and Space Science Fellowship Award 80NSSC17K0382. We thank TCCON for providing observations. We thank A. Jacobson and the National Oceanographic and Atmospheric Administration Earth System Research Laboratory in Boulder, CO, for providing CarbonTracker CT2017 data, available online (http://carbontracker.noaa.gov). We thank S. Wofsy for providing HIPPO data, funded by the National Science Foundation and NOAA and available online (https://www.eol.ucar.edu/field_projects/hippo). The TCCON Principal Investigators acknowledge funding from their national funding organizations. TCCON data were obtained from the archive at the https://tccondata.org Web site. NARR data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site (https://www.esrl.noaa.gov/psd/).
    Keywords: Atmospheric transport ; Greenhouse gases ; CO2 ; Mesoscale ; OCO‐2 ; TCCON
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-10-20
    Description: Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 47 (2020): e2020GL087669, doi:10.1029/2020GL087669.
    Description: We present a year‐round time series of dissolved methane (CH4), along with targeted observations during ice melt of CH4 and carbon dioxide (CO2) in a river and estuary adjacent to Cambridge Bay, Nunavut, Canada. During the freshet, CH4 concentrations in the river and ice‐covered estuary were up to 240,000% saturation and 19,000% saturation, respectively, but quickly dropped by 〉100‐fold following ice melt. Observations with a robotic kayak revealed that river‐derived CH4 and CO2 were transported to the estuary and rapidly ventilated to the atmosphere once ice cover retreated. We estimate that river discharge accounts for 〉95% of annual CH4 sea‐to‐air emissions from the estuary. These results demonstrate the importance of resolving seasonal dynamics in order to estimate greenhouse gas emissions from polar systems.
    Description: All data generated by the authors that were used in this article are available on PANGAEA (https://doi.org/10.1594/PANGAEA.907159) and model code for estimating CH4 transport is available on GitHub (https://doi.org/10.5281/zenodo.3785893). We acknowledge the use of imagery from the NASA Worldview application (https://worldview.earthdata.nasa.gov), part of the NASA Earth Observing System Data and Information System (EOSDIS), and data from Ocean Networks Canada, and Environment Canada. We thank everyone involved in the fieldwork including C. Amegainik, Y. Bernard, A. Cranch, F. Emingak, S. Marriott, and A. Pedersen. Laboratory analysis and experiments were performed by A. Cranch, R. McCulloch, A. Morrison, and Z. Zheng. We thank J. Brinckerhoff, the Arctic Research Foundation, and the staff of the Canadian High Arctic Research Station for support with field logistics. Funding for the work was provided by MEOPAR NCE funding to B. Else, a WHOI Interdisciplinary Award to A. Michel., D. Nicholson. and S. Wankel, and Canadian NSERC grants to P. Tortell. and B. Else. Authors received fellowships, scholarships, and travel grants including an NSERC postdoctoral fellowship to C. Manning, an NDSEG fellowship to V. Preston, NSERC PGS‐D and Izaak Walton Killam Pre‐Doctoral scholarships to S. Jones, and Northern Scientific Training Program funds (Polar Knowledge Canada, administered by the Arctic Institute of North America, University of Calgary) to S. Jones and P. Duke. We also thank Polar Knowledge Canada (POLAR) and Nunavut Arctic College for laboratory space and field logistics support.
    Description: 2020-10-23
    Keywords: Greenhouse gases ; Biogeochemistry ; Arctic coastal waters ; Biogeochemical sensing ; Seasonal cycles ; Methane
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Expected Availability
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