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A geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals

Torres, Anthony D. and Keppel‐Aleks, Gretchen and Doney, Scott C. and Fendrock, Michaela and Luis, Kelly and De Mazière, Martine and Hase, Frank and Petri, Christof and Pollard, David F. and Roehl, Coleen M. and Sussmann, Ralf and Velazco, Voltaire A. and Warneke, Thorsten and Wunch, Debra (2019) A geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals. Journal of Geophysical Research. Atmospheres, 124 (17-18). pp. 9773-9795. ISSN 2169-897X. https://resolver.caltech.edu/CaltechAUTHORS:20190730-080906654

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Abstract

National Aeronautics and Space Administration's Orbiting Carbon Observatory‐2 (OCO‐2) satellite provides observations of total column‐averaged CO2 mole fractions (X_(CO₂)) 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 X_(CO₂) 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 X_(CO₂) and X_(H₂O) from OCO‐2 tracks to temporal synoptic and mesoscale variability from ground‐based X_(CO₂) and X_(H₂O) 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 X_(H₂O). For X_(CO₂), 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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1029/2018jd029933DOIArticle
ORCID:
AuthorORCID
Torres, Anthony D.0000-0002-0531-5883
Keppel‐Aleks, Gretchen0000-0003-2213-0044
Doney, Scott C.0000-0002-3683-2437
Fendrock, Michaela0000-0002-6147-1215
Luis, Kelly0000-0001-9975-3480
Petri, Christof0000-0002-7010-5532
Pollard, David F.0000-0001-9923-2984
Roehl, Coleen M.0000-0001-5383-8462
Velazco, Voltaire A.0000-0002-1376-438X
Warneke, Thorsten0000-0001-5185-3415
Wunch, Debra0000-0002-4924-0377
Additional Information:© 2019 American Geophysical Union. Received 2 NOV 2018; Accepted 19 JUL 2019; Accepted article online 29 JUL 2019; Published online 2 SEP 2019. 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/).
Funders:
Funding AgencyGrant Number
NASANNX15AH13G
NASA Earth and Space Science Fellowship80NSSC17K0382
NSFUNSPECIFIED
National Oceanic and Atmospheric Administration (NOAA)UNSPECIFIED
Issue or Number:17-18
Record Number:CaltechAUTHORS:20190730-080906654
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190730-080906654
Official Citation:Torres, A. D., Keppel‐Aleks, G., Doney, S. C., Fendrock, M., Luis, K., De Mazière, M., et al (2019). A geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals. Journal of Geophysical Research: Atmospheres, 124, 9773–9795. https://doi.org/10.1029/2018JD029933
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:97504
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:30 Jul 2019 15:30
Last Modified:02 Apr 2020 16:26

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