Ionospheric electron density over Resolute Bay according to E-CHAIM model and RISR radar measurements

Larson, Bion; Koustov, A. V.; Themens, David R.; Gillies, R. G.

doi:10.1016/j.asr.2023.01.017

Cited by 1 publication

(1 citation statement)

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“…One study focused on E‐CHAIM predictions of ionospheric electron density over Resolute Bay Incoherent Scatter Radar data found that E‐CHAIM underestimates electron density in the topside by 20%, and that topside underestimation is prominent during nighttime in the Fall (Larson et al., 2023). The RISR data used covers altitudes from 100 to 500 km, while the DMSP data focuses on altitudes around 850 km and DEMETER data at 715 km.…”

Section: Discussionmentioning

confidence: 99%

Topside Electron Density Modeling Using Neural Network and Empirical Model Predictions

Dutta,

Cohen

2023

Space Weather

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We model the electron density in the topside of the ionosphere with an improved machine learning (ML) model and compare it to existing empirical models, specifically the International Reference Ionosphere (IRI) and the Empirical‐Canadian High Arctic Ionospheric Model (E‐CHAIM). In prior work, an artificial neural network (NN) was developed and trained on two solar cycles worth of Defense Meteorological Satellite Program data (113 satellite‐years), along with global drivers and indices to predict topside electron density. In this paper, we highlight improvements made to this NN, and present a detailed comparison of the new model to E‐CHAIM and IRI as a function of location, geomagnetic condition, time of year, and solar local time. We discuss precision and accuracy metrics to better understand model strengths and weaknesses. The updated neural network shows improved mid‐latitude performance with absolute errors lower than the IRI by 2.5 × 109 to 2.5 × 1010 e−/m3, modestly improved performance in disturbed geomagnetic conditions with absolute errors reduced by about 2.5 × 109 e−/m3 at high Kp compared to the IRI, and high Kp percentage errors reduced by >50% when compared to E‐CHAIM.

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Section: Discussionmentioning

confidence: 99%