Date of Award

5-2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Physics and Astronomy

Committee Chair/Advisor

Xian Lu

Committee Member

Nicholas Pedatella

Committee Member

Jens Oberheide

Committee Member

Bradley Meyer

Abstract

The predictability of the ionosphere-thermosphere (IT) system is a critical objective in space weather research. Because the IT system is continuously modulated by vertical coupling—specifically forcing from above (solar and geomagnetic activity) and forcing from below (lower atmospheric meteorology)—accurate predictions of the IT state fundamentally depend on the accurate specification and prediction of these boundary drivers. This dissertation systematically quantifies the influence of these respective forcings and evaluates how driver predictability translates into IT forecast accuracy.

Utilizing satellite and ground-based observations, this work first quantifies the portion of IT variance attributable to forcing from above. Using Global-scale Observations of the Limb and Disk (GOLD), we quantify the variance in thermospheric column O/N₂ as a function of latitude and season. Similarly, we assess the influence of top-down forcing on electron density (Ne) at high latitudes by developing a model of Poker Flat Incoherent Scatter Radar (PFISR) observations driven by geomagnetic indices. By isolating the variance driven from above, these studies simultaneously establish an upper bound for the influence of forcing from below by analyzing the residual variance.

The specific influence of key lower-atmospheric drivers on upper atmospheric variability is then directly quantified. We analyze the impact of polar vortex variations—a canonical driver of vertical coupling—using both GOLD observations and SD-WACCM-X simulations. Furthermore, using Ionospheric Connection Explorer (ICON) observations, we quantify the relationship between mesosphere-lower thermosphere (MLT) tidal activity and low-latitude IT wave structures.

Finally, this dissertation evaluates how forecast errors in lower boundary drivers propagate into IT predictions using numerical modeling frameworks. To evaluate forcing from below, we investigate how forecast errors in high-top lower atmosphere models translate to the IT by driving the lower boundary of the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) with Whole Atmosphere Community Climate Model (WACCM) forecasts. Through these predictive modeling efforts, we ultimately demonstrate and characterize the accurate predictability of the IT system during, and in response to, Sudden Stratospheric Warming (SSW) events.

Available for download on Monday, May 31, 2027

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