The Limits of Empirical Electron Density Modeling: Examining the Capacity of E‐CHAIM and the IRI for Modeling Intermediate (1‐ to 30‐Day) Timescales at High Latitudes

Themens, David R.; Jayachandran, P. T.; Reid, Benjamin; McCaffrey, Anthony M.

doi:10.1029/2018rs006763

Cited by 17 publications

(18 citation statements)

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“…Maltseva and Nikitenko (2019) examined the performance of E-CHAIM in the representation of NmF2 in the Russian sector during a number of storms, where E-CHAIM performance appeared comparable to that of a GNSS TEC assimilation approach in reproducing nighttime enhancements in electron density associated with increased geomagnetic activity and capturing negative ionospheric storm responses. The recent Themens et al (2020) study further diagnosed the performance of E-CHAIM in the representation of the short time scale variability in NmF2, concluding that E-CHAIM is able to capture ∼25% of the variability of the ionosphere at sub-monthly time scales, mainly through its representation of negative ionospheric storm responses. In order to get a better idea of the model's performance as a whole and to identify potential shortcomings in this performance, further validation with respect to observations, not incorporated into the model during development, must be undertaken.…”

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confidence: 90%

E‐CHAIM as a Model of Total Electron Content: Performance and Diagnostics

et al. 2021

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The Empirical Canadian High Arctic Ionospheric Model (E-CHAIM) is an empirical climatological model of high latitude (above 50°N geomagnetic latitude) ionospheric electron density. The source code for E-CHAIM in the C, Matlab, and IDL languages is currently openly available online at https://e-chaim. chain-project.net. E-CHAIM was designed as an alternative to the use of the International Reference Ionosphere (IRI; Bilitza, 2018) at high latitudes, which was previously demonstrated to suffer significant limitations in that region (

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confidence: 90%

E‐CHAIM as a Model of Total Electron Content: Performance and Diagnostics

et al. 2021

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“…The reader may wish to consult Themens et al. (2018) for a full explanation of E‐CHAIM's storm perturbation model; however, the model mainly captures the decrease in ionospheric electron density on daily timescales that occurs during storms at high latitudes as a result of a relative increase recombination (Themens et al., 2020). This relative increase in recombination rate can result in a reduction to the plasma density by a factor of up to two in the F‐Region (Prölss, 1995).…”

Section: Discussionmentioning

confidence: 99%

“…In the night sector, the D‐region model option plays virtually no role due to the lack of ionization; however, for rays that do propagate into the day sector, the inclusion ensures that this region is correctly modeled. The NmF2 Storm model option in E‐CHAIM represents the decrease in NmF2 in response to thermospheric composition changes and enhanced recombination during geomagnetic storms (Themens et al., 2018). The effect of this model is seen in Figure 2 by the clear reduction of the F‐region peak density compared to the default model.…”

Section: Methodology and Propagation Modelmentioning

confidence: 99%

“…The increased horizontal resolution and consideration of particle precipitation (Watson et al, 2021) make E-CHAIM far more suitable for representing the Arctic ionosphere as the basis of the OTHR propagation study. E-CHAIM makes use of several sub models to form a holistic consideration of the ionosphere to ensure the output electron density profile is reliable and covers a full range of altitudes and conditions (Themens, Jayachandran, McCaffrey, Reid, & Varney, 2019;Themens et al, 2017Themens et al, , 2018. Like the IRI, E-CHAIM takes NmF2 (F2 peak density) and hmF2 (F2 height) as the anchor point for the full electron density profile, with sub models used to represent the different regions.…”

Section: Ionospheric Modelmentioning

confidence: 99%

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Impacts of Auroral Precipitation on HF Propagation: A Hypothetical Over‐the‐Horizon Radar Case Study

Ruck

Themens

2021

Space Weather

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Over‐the‐horizon radar (OTHR) systems operating in the high‐frequency (HF) band (3–30 MHz) are unique in their ability to detect targets at extreme ranges, offering cost‐effective large‐area surveillance. Due to their reliance on the reflective nature of the ionosphere in this band, OTHR systems are extremely sensitive to ionospheric conditions and can expect significant variations in operational performance. At high latitudes, the presence of auroral enhancements in the E‐Region electron density can substantially modify the coverage area and frequency management of OTHR systems. In this study, HF raytracing is utilized to investigate these impacts for a hypothetical radar under different auroral conditions simulated using the Empirical Canadian High Arctic Ionospheric Model. Aurora were seen to increase maximum usable frequency from 8.5 to 26 MHz whilst also reducing median available range from 2,541 to 1,226 km and changing coverage area by −50.4% to 58.6%, for the greatest differences. Target interception showed large variations in path coverage of between 33%–115% and 0%–107% for two flight paths tested with precipitation toggled. Two distinct auroral propagation modes were observed, noted as the F‐E ducted and Auroral E‐modes. Long‐range coverage provided by the auroral F‐E ducted mode was of limited capacity with low solar activity due to reduced NmF2. F‐mode propagation transitioned to the dominating Auroral E‐mode between Auroral Electrojet index values of 50‐ and 200‐nT. The significant variations in both frequency and coverage observed within this study highlight some aspects of the importance of considering aurora in OTHR modeling and design.

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“…In recent years, the Empirical Canadian High Artic Ionospheric Model (E‐CHAIM) (Themens et al., 2017, 2018; Themens, Jayachandran, & McCaffrey, 2019) has emerged as the most reliable representation of electron densities at northern high latitudes (>50° geomagnetic latitude; Maltseva & Nikitenko, 2020; Themens et al., 2020; Themens, Jayachandran, McCaffrey, Reid, & Varney, 2019). E‐CHAIM is a significant improvement over other models such as the International Reference Ionosphere (IRI) at high latitudes, providing, for example, improvements of up to 60% in N m F 2 in the polar cap (Themens et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Development and Validation of Precipitation Enhanced Densities for the Empirical Canadian High Arctic Ionospheric Model

2021

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The precipitation of energetic electrons and ions of magnetospheric and solar origin play a significant role in governing the structure and dynamic behavior of the high latitude ionosphere. Persistent particle precipitation in the auroral region, and to a lesser extent in the polar cap, is a significant source of neutral atmospheric ionization, which results in multi-scale ionosphere density structures that are complex in terms of Abstract The Empirical Canadian High Artic Ionospheric Model (E-CHAIM) provides the fourdimensional ionosphere electron density at northern high latitudes (>50° geomagnetic latitude). Despite its emergence as the most reliable model for high-latitude ionosphere density, there remain significant deficiencies in E-CHAIM's representation of the lower ionosphere (below ∼200 km) due to a sparsity of reliable measurements at these altitudes, particularly during energetic particle precipitation events. To address this deficiency, we have developed a precipitation component for E-CHAIM to be driven by satellite-based far-ultraviolet (FUV) imager data. Satellite observations of FUV emissions may be used to infer the characteristics of energetic particle precipitation and subsequently calculate the precipitationenhanced ionization rates and ionosphere densities. In order to demonstrate the improvement of E-CHAIM's ionosphere density representation with the addition of a precipitation component, this paper presents comparisons of E-CHAIM precipitation-enhanced densities with ionosphere density measurements of three auroral region incoherent scatter radars (ISRs) and one polar cap ISR. Calculations for 29,038 satellite imager and ISR conjunctions during the years 2005-2019 revealed that the root-meansquare difference between E-CHAIM and ISR measurements decreased by up to 2.9 × 10 10 ele/m 3 (altitude dependent) after inclusion of the precipitation component at auroral sites, and by 2.6 × 10 9 ele/m 3 in the polar cap. Improvements were most substantial in the winter season and during active auroral conditions. The sensitivity of precipitation-enhanced densities to uncertainties inherent to the calculation method was also examined, with the bulk of the errors due to uncertainties in FUV imager data and choice of distribution function for precipitation energy spectra. Plain Language SummaryThe Empirical Canadian High Artic Ionospheric Model (E-CHAIM) is a measurement-based model which provides the electron density of the upper atmosphere (the ionosphere) for a user-specified date, time, and location at northern high latitudes (>50° geomagnetic latitude). The Earth's ionosphere can aid or disrupt the operation of technologies such as global navigation and radio communication systems, and thus ionosphere models are a critical component for reliable operation of these systems. E-CHAIM is currently the most reliable model for high-latitude ionosphere densities, which are particularly dynamic and complex due to the vertical orientation of Earth's high latitude magnetic field. A lack of reliable, widespre...

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The Limits of Empirical Electron Density Modeling: Examining the Capacity of E‐CHAIM and the IRI for Modeling Intermediate (1‐ to 30‐Day) Timescales at High Latitudes

Cited by 17 publications

References 56 publications

E‐CHAIM as a Model of Total Electron Content: Performance and Diagnostics

E‐CHAIM as a Model of Total Electron Content: Performance and Diagnostics

Impacts of Auroral Precipitation on HF Propagation: A Hypothetical Over‐the‐Horizon Radar Case Study

Development and Validation of Precipitation Enhanced Densities for the Empirical Canadian High Arctic Ionospheric Model

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