GRACE and GRACE-FO Related Publications (no abstracts)

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Data-Driven Inference of Thermosphere Composition During Solar Minimum Conditions

Mehta, Piyush M., Linares, Richard, and Sutton, Eric K., 2019. Data-Driven Inference of Thermosphere Composition During Solar Minimum Conditions. Space Weather, 17(9):1364–1379, doi:10.1029/2019SW002264.

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@ARTICLE{2019SpWea..17.1364M,
       author = {{Mehta}, Piyush M. and {Linares}, Richard and {Sutton}, Eric K.},
        title = "{Data-Driven Inference of Thermosphere Composition During Solar Minimum Conditions}",
      journal = {Space Weather},
         year = 2019,
        month = sep,
       volume = {17},
       number = {9},
        pages = {1364-1379},
     abstract = "{Mass density variations can deviate from the expected behavior caused by
        temperature due to changes in the composition. Such deviations
        can be especially significant during solar minimum conditions.
        Model-data differences are typically resolved through
        temperature corrections while overlooking the role of errors in
        lower boundary composition. In this work, we use a data-driven
        methodology to simultaneously estimate thermosphere composition
        and temperature contributions to model-data differences. The
        methodology uses modal decomposition to extract high-
        dimensional, reduced order basis functions for the covariance of
        the neutral thermospheric species and temperature. The extracted
        basis functions are combined with CHAllenging Minisatellite
        Payload and Gravity Recovery And Climate Experiment mass density
        measurements using a nonlinear least squares solver. We
        demonstrate the methodology using the Naval Research
        Laboratory's empirical Mass Spectrometer and Incoherent Scatter
        (MSIS) model to derive the high-dimensional basis functions. We
        characterize and quantify the contribution of temperature and
        lower boundary effects with oxygen and helium since the two
        species have a direct impact on drag and orbit prediction
        through gas-surface interactions and mass density. We analyze
        the month of December in 2008, based on the work of Thayer et
        al. (2012), and estimate that lower boundary composition errors
        contribute approximately 50\% of the model-data differences.}",
          doi = {10.1029/2019SW002264},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019SpWea..17.1364M},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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