In this study, we use measurements from over 4,735 globally distributed Global Navigation Satellite System receivers to track the progression of traveling ionospheric disturbances (TIDs) associated with the 15 January 2022 Hunga Tonga‐Hunga Ha'apai submarine volcanic eruption. We identify two distinct Large Scale traveling ionospheric disturbances (LSTIDs) and several subsequent Medium Scale traveling ionospheric disturbances (MSTIDs) that propagate radially outward from the eruption site. Within 3,000 km of epicenter, LSTIDs of >1,600 km wavelengths are initially observed propagating at speeds of ∼950 and ∼555 ms−1, before substantial slowing to ∼600 and ∼390 ms−1, respectively. MSTIDs with speeds of 200–400 ms−1 are observed for 6 hrs following eruption, the first of which comprises the dominant global ionospheric response and coincides with the atmospheric surface pressure disturbance associated with the eruption. These are the first results demonstrating the global impact of the Tonga eruption on the ionospheric state.

As L‐band radio waves travel through the ionosphere, such as those transmitted by the Global Positioning System (GPS) satellites, changes in the electron density along the ray path may induce refractive and/or diffractive variations in the signal's phase; where refractive variations are deterministic and diffractive variations are stochastic. Typically, the refractive component of these variations is thought to be slow varying, associated with frequencies less than 0.1 Hz. Therefore, if the refractive contribution is assumed to be associated with frequencies less than 0.1 Hz, the frequencies greater than 0.1 Hz are then assumed and treated as diffractive. These variations are usually referred to as scintillation. In scintillation studies the deterministic refractive variations are very often ignored. We propose that rapid changes in the electron density, and therefore changes in the refractive index along the ray path of the GPS signal, can induce dominantly refractive variations at frequencies greater than 0.1 Hz. The increased drift speeds observed in the high‐latitude region create conditions suitable for these high‐frequency refractive variations; the GPS ray path will sweep through large‐scale irregularities at higher speeds, resulting in high‐frequency refractive variations. Using recent advances in GPS, most importantly an improved signal tracking technique, we present examples of rapid refractive variations in the GPS signal's phase. These high‐frequency variations are shown to be refractive using a combination of techniques, one adapted from a previous technique used for the low‐frequency refractive contributions and a new technique only possible with advances in GPS tracking.

In this study, we present a bottomside model representation to be used by the Empirical Canadian High Arctic Ionospheric Model (E-CHAIM). This model features a new approach to modeling the bottomside electron density; namely, instead of modelling electron density directly, E-CHAIM models the altitude profile of the scale thickness of a single bottomside layer. In this approach, the curvature in the bottomside associated with the E region and F1 layer is represented in the scale thickness domain as a peak function centered at the layer peak altitude. The use of this approach ensures the production of explicitly doubly differentiable bottomside electron density profiles and directly avoids issues known to exist within current standards, such as the International Reference Ionosphere (IRI), which has discontinuities in space, time, and in the vertical electron density gradient. In terms of performance, after removing the impacts of hmF2 and NmF2, the new E-CHAIM profile function generally performs comparably to the IRI, with bottomside TEC from both models within 2.0 TECU (1 TECU = 10 16 e/m 3 ) of observations. More specifically, the E-CHAIM bottomside is demonstrated to outperform the IRI bottomside function in the F region during low solar activity periods with respect to incoherent scatter radar observations. At high latitudes, E-CHAIM tends to outperform the IRI during winter months by between 10% and 40% of NmF2 while being outperformed by the IRI by between 10% and 25% of NmF2 during summer periods, mainly during the daytime at high solar activity.

Recently, Rino et al. (2019) (herein referred to as CR2019) published an interesting paper on the single power-law nature of high-latitude Ionospheric structures. The goal of the work presented in CR2019 is important for the global positioning system (GPS) total electron content (TEC) and scintillation research community. Determining the real TEC structure in our ground-based measurements and knowing how non-TEC effects influence the TEC measurement is a must. However, as we move forward with these types of works, we must be sure to clearly and thoughtfully define our new terms and we must be careful with the methods we use, so as not to allow for erroneous assumptions to be made and to prevent a further muddying of the waters within this community. There is also growing evidence in the literature that various parameters affect the determination of the TEC and phase scintillation index (e.g., McCaffrey & Jayachandran, 2017;Wang et al., 2018) accuracy.Our concerns with CR2019 can be summed up in two points: the way "stochastic TEC" is defined, and the overall approach to the data-driven portion of the paper. BackgroundThe majority of the concerns with CR2019 that will be addressed refer to the work in McCaffrey and Jayachandran (2019), therefore, the relevant work is summarized here. The major theme is the differentiation between the purely refractive effects of the ionosphere on the GPS observables (focusing on the carrier phase observable) and the diffractive effects, also known as scintillation.A simplified version of the GPS carrier phase can be expressed by the following:where L refers to the carrier frequency, 𝐴𝐴 𝐴𝐴 refers to the constant and low-frequency components of the carrier phase (e.g., the true geometric range, clock errors, tropospheric effects, etc.), I represents the ionospheric effects on the carrier phase, and 𝐴𝐴 𝐴𝐴 is any noise sources in the signal that are not represented by the other two terms (e.g., thermal noise, phase jitter, multipath, etc.).

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