Comparison of observed and predicted MUF(3000)F2 in the polar cap region

Athieno, R.; Jayachandran, P. T.; Themens, David R.; Danskin, D. W.

doi:10.1002/2015rs005725

Cited by 14 publications

(15 citation statements)

References 33 publications

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“…Themens et al [2013] demonstrated that the sparsity of data in high-latitude regions contributes to significant errors in the representation of TEC in these regions by global TEC maps, and Themens et al [2015] showed that the strong gradients in TEC at high latitudes significantly degrade the performance of standard Global Positioning System (GPS)-based TEC calibration techniques. Also, Athieno et al [2015] and Athieno and Jayachandran [2016] show that standard HF communication models exhibit significant errors at high latitudes, largely due to errors in the URSI and International Radio Consultative Committee critical frequency maps, which are also used in the IRI. All of these studies highlight the need for a new representation of the high-latitude ionosphere.…”

Section: Introductionmentioning

confidence: 99%

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂

et al. 2017

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We present here the Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM) quiet NmF2, perturbation NmF2, and quiet hmF2 models. These models provide peak ionospheric characteristics for a domain above 50°N geomagnetic latitude. Model fitting is undertaken using all available ionosonde and radio occultation electron density data, constituting a data set of over 28 million observations. A comprehensive validation of the model is undertaken, and performance is compared to that of the International Reference Ionosphere (IRI). In the case of the quiet NmF2 model, the E‐CHAIM model provides a systematic improvement over the IRI Union Radio Scientifique Internationale maps. At all stations within the polar cap, we see drastic RMS error improvements over the IRI by up to 1.3 MHz in critical frequency (up to 60% in NmF2). These improvements occur primarily during equinox periods and at low solar activities, decreasing somewhat as one tends to lower latitudes. Qualitatively, the E‐CHAIM is capable of representing auroral enhancements in NmF2, as well as the location and extent of the main ionospheric trough, not reproduced by the IRI. The included NmF2 storm model demonstrates improvements over the IRI by up to 35% and over the quiet time E‐CHAIM model by up to 30%. In terms of hmF2, over the validation periods used in this study, we found overall RMS errors of ~13 km for E‐CHAIM, with IRI2007 overall hmF2 errors ranging between 16 km and 22 km. The E‐CHAIM performs comparably to or slightly better than the IRI within the polar cap; however, significant improvements are found within the auroral oval.

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Section: Introductionmentioning

confidence: 99%

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂

et al. 2017

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“…In spite of such tireless efforts, recent studies by Themens et al [2014] and Themens and Jayachandran [2016] still show persistent limitations of the IRI at high latitudes especially in the polar cap. Previous research has also emphasized the disadvantage of data scarcity to the exploration of the polar ionosphere especially in the empirical modeling and prediction of important HF and ionospheric parameters [e.g., Oyeyemi and McKinnell, 2008;Themens et al, 2014;Athieno et al, 2015]. The Canadian High Arctic Ionospheric Network (CHAIN), an array of ground-based radio instruments deployed and operated by the University of New Brunswick, has made a tremendous improvement in data availability especially in the high arctic which includes the polar cap region [Jayachandran et al, 2009].…”

Section: Introductionmentioning

confidence: 99%

A neural network-based foF2 model for a single station in the polar cap

2017

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A neural network (NN) model has been developed for the critical frequency of the F2 layer (foF2) at Resolute (74.70°N, 265.10°E) using data obtained from the Space Physics Interactive Data Resource (no longer available) for the period between 1975 and 1995. This model is a first step toward addressing the discrepancies of the International Reference Ionosphere (IRI) foF2 or peak electron density (NmF2) at high latitudes recently presented by Themens et al. (2014). The performance of the NN model has been evaluated using foF2 data obtained from the Canadian Advanced Digital Ionosonde at Resolute (74.75°N, 265.00°E) for the period between 2009 and 2013, in comparison with the IRI predictions. The 2012 version and the International Union of Radio Science option of IRI have been used. The NN nighttime monthly median foF2 variation demonstrates good agreement with observations compared to the IRI. The NN model is able to reproduce the enhancements in foF2 during the equinoxes and also shows an improvement during disturbed days. Root mean square errors were computed between hourly and monthly median model predictions and observations, and on the whole, the NN model seems to perform better during low solar activity and the equinoxes. The NN model shows an improvement in performance on average by 26.638% for hourly foF2 and 32.636% for monthly median foF2, compared to 7.877% obtained for the same station by the most recent NN model that attempted to predict foF2 at a polar cap station (Oyeyemi and Poole, 2005).

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“…The International Reference Ionosphere (IRI) is the accepted standard for the climatological representation of the ionosphere by the International Organization for Standardization (ISO) [ Bilitza et al , ]. It is regularly applied in ionospheric assimilation frameworks [ Komjathy and Langley , ; Komjathy et al , ; Hernandez‐Pajares et al , ; Bust et al , ; Schmidt et al , ; Zeilhofer et al , ; Pezzopane et al , ; Galkin et al , ], in radar altimetry [ Ovodenko et al , ], in theoretical ring current models [ Ebihara et al , , ], and in high‐frequency (HF) communications forecasting [ Jodalen et al , ; Settimi et al , ; Athieno et al , ]. While several studies speak to the accuracy of the IRI at midlatitude and low latitude [ Sethi et al , ; Ehinlafa et al , ; Ezquer et al , ; Bilitza et al , ; Wichaipanich et al , ], the same cannot necessarily be said for its application to high‐latitude regions, where transport and particle precipitation events dominate ionospheric variability for large portions of the year [ Carlson , ; MacDougall and Jayachandran , ; Jayachandran et al , , ].…”

Section: Introductionmentioning

confidence: 99%

Solar activity variability in the IRI at high latitudes: Comparisons with GPS total electron content

Themens

Jayachandran

2016

JGR Space Physics

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Total electron content (TEC) measurements from 10 dual‐frequency GPS receivers in the Canadian High Arctic Ionospheric Network (CHAIN) are used to evaluate the performance of International Reference Ionosphere (IRI)‐2007 within the Canadian sector. Throughout the region, we see systematic underestimation of daytime TEC, particularly at solar maximum, where summer and equinox root‐mean‐square errors reach as high as 14 total electron content units, 1 TECU = 1016 el m−2 (TECU). It is also shown that the use of a monthly IG index, in place of the IRI's standard IG12 index, leads to an improvement in TEC specification by up to 3 TECU in the polar cap and up to 6 TECU in the subauroral region during periods of short‐term, large amplitude changes in solar activity. On diurnal timescales, variability in TEC is found to be underestimated by the IRI, during equinox periods, by up to 40% at subauroral latitudes and up to 70% in the polar cap region. During the winter, diurnal variations are overestimated by up to 40% in the subauroral region and are underestimated within the polar cap by up to 80%. Using collocated ionosonde data, we find IRI bottomside TEC to be within 1 TECU of observation with errors largest during the equinoxes. For the topside we find good agreement during the winter but significant underestimation of topside TEC by the IRI during summer and equinox periods, exceeding 6 TECU at times. By ingesting measured NmF2 into the IRI, we show that the topside thickness parameterization is the source of the bulk of the observed TEC errors.

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Comparison of observed and predicted MUF(3000)F2 in the polar cap region

Cited by 14 publications

References 33 publications

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂

A neural network-based foF2 model for a single station in the polar cap

Solar activity variability in the IRI at high latitudes: Comparisons with GPS total electron content

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Comparison of observed and predicted MUF(3000)F2 in the polar cap region

Cited by 14 publications

References 33 publications

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): NmF2 and hmF2

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): NmF2 and hmF2

A neural network-based foF2 model for a single station in the polar cap

Solar activity variability in the IRI at high latitudes: Comparisons with GPS total electron content

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Product

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The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂

The Empirical Canadian High Arctic Ionospheric Model (E‐CHAIM): N_mF₂ and h_mF₂