Browsing by Author "Themens, David R."

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Modeling electron density at high latitudes: development of the Empirical Canadian High Arctic Ionospheric Model (E-CHAIM)
    (University of New Brunswick, 2018) Themens, David R.; Jayachandran, P.
    The ionosphere is an important medium for high frequency (HF) radio communications and remote sensing, as well as a hindrance to the use of the Global Positioning System (GPS); thereby, these systems require accurate ionospheric models in order to function. The highly complex nature of the high latitude ionospheric dynamics, combined with an extreme scarcity of data in the high-latitude region, has, in the past, made this area virtually impossible to model accurately. With the recent explosion of ionospheric remote sensing instruments in the polar region, it has now become possible to monitor these regions with high spatial resolution. Today there exist no accurate ionosphere models specific to the high latitude region and de facto standard ionospheric models, such as the International Reference Ionosphere (IRI), have been shown to be inaccurate at high-latitudes. Here we present the methodology and performance of the new Empirical Canadian High Arctic Ionospheric Model (E-CHAIM), a 3D high latitude electron density model intended to replace the use of the IRI in these regions. To this end, we make use of every available high latitude radio remote sensing ionospheric data set dating back to the very first observations of the ionosphere from 1931 at the Slough ionosonde in Ditton Park, UK. Specifically, we examine lessons learned from the short comings of other empirical ionospheric models, discuss the reasoning behind the parameterizations used, and provide comparisons between the model and real observations that weren’t included in model fitting. Overall, the E-CHAIM model is demonstrated to represent a significant improvement over current standards in the representation of the topside and F2-peak of the ionosphere, while providing comparable performance to current standards in the representation of the bottomside shape.
  • Thumbnail Image
    Item
    The Assimilative Canadian High Arctic Ionospheric Model (A-CHAIM)
    (University of New Brunswick, 2024-06) Reid, Benjamin; Jayachandran, P.T.; Themens, David R.
    The high latitude ionosphere is coupled with the magnetosphere and solar wind, and exhibits a high degree of variability which cannot be captured by existing models. The objective of the research presented in this dissertation is to improve the specification of ionospheric weather, leading to the development of the Assimilative Canadian High Arctic Ionospheric Model, or A-CHAIM. A-CHAIM is a near-real-time data assimilation model of the high latitude ionospheric electron density, combining ionospheric models with low-latency measurements to produce the best possible representation of the current ionospheric state. Beginning in 2021, A-CHAIM is the first operational space weather model to use a particle filter; a nonlinear data assimilation technique. This required the development of several novel methods to avoid sample degeneracy, which has previously prevented the use of particle filters in large-scale geophysical models. A-CHAIM is shown to produce a significantly improved representation of ionospheric electron density when compared to the empirical background model. The flexibility of particle filters is also exploited to include separate models for the electron density enhancements of auroral electron and solar energetic particle precipitation. The use of Rao-Blackwellized particle filtering to solve for instrumental biases allows A-CHAIM to efficiently estimate the hardware-specific differential code biases (DCBs) of the hundreds of global navigation satellite system (GNSS) receivers in the measurement dataset. This bias estimation technique requires fewer assumptions than previous methods, and is able to include independent measurement types. It is shown that there are systematic errors in existing techniques for DCB estimation which use an external ionospheric reference.