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Long–term variability in thermospheric mass density (TMD): insights from Singular Spectrum Analysis (SSA) and model comparisons

Korlaelci, Serhat, Sagir, Selcuk, Yapali, Seval, and Atici, Ramazan, 2026. Long–term variability in thermospheric mass density (TMD): insights from Singular Spectrum Analysis (SSA) and model comparisons. Advances in Space Research, 77(5):6225–6249, doi:10.1016/j.asr.2025.12.097.

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@ARTICLE{2026AdSpR..77.6225K,
       author = {{Korlaelci}, Serhat and {Sagir}, Selcuk and {Yapali}, Seval and {Atici}, Ramazan},
        title = "{Long-term variability in thermospheric mass density (TMD): insights from Singular Spectrum Analysis (SSA) and model comparisons}",
      journal = {Advances in Space Research},
     keywords = {Thermospheric mass density (TMD), Singular Spectrum Analysis (SSA), Solar cycle, JB2008, Low Earth Orbit (LEO)},
         year = 2026,
        month = mar,
       volume = {77},
       number = {5},
        pages = {6225-6249},
     abstract = "{Operations in Low Earth Orbit (LEO) necessitate precise specifications
        of thermospheric mass density (TMD) that account for variability
        across altitudes over multiple solar cycles. However, most long-
        term studies continue to report aggregate error metrics or
        concentrate on singular altitudes. In this study, we employed
        Singular Spectrum Analysis (SSA) on daily JB2008 model densities
        at fixed altitudes ranging from 250 to 575 km for the period
        1967─2019. This approach yielded altitude-resolved long-term
        trends and a JB2008-referenced background state. SSA effectively
        decomposes density variability into a slowly varying component
        linked to solar cycles and secular changes, a series of seasonal
        and recurrent solar rotation oscillations, and higher-frequency
        storm-time residuals without imposing a specific temporal model.
        The leading components accounted for approximately 96 \% of the
        variance in log$_{10}${\ensuremath{\rho}} and closely followed
        the Sunspot Number across all analyzed altitudes, while the
        residual subset encompassed storm-time and wave-driven
        disturbances. Bootstrap experiments demonstrated that the
        statistical uncertainty of the trends was minimal compared to
        the amplitude of the solar cycle signal, thereby affirming the
        robustness of the extracted backgrounds. Comparisons with the
        CHAMP, GRACE, and Swarm accelerometer-derived densities revealed
        mission-dependent concordance that improved with orbital
        stability and altitude. Time─altitude maps illustrating the
        differences between JB2008, its SSA trend, and NRLMSISE-00
        underscore the structured, regime-dependent discrepancies
        between the two climatologies, particularly in the upper
        thermosphere during periods of heightened solar activity. These
        SSA products offer a JB2008-referenced, altitude-sensitive
        diagnostic baseline for evaluating thermospheric models and
        refining drag-critical density specifications for orbit
        prediction and space-traffic management.}",
          doi = {10.1016/j.asr.2025.12.097},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026AdSpR..77.6225K},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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