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Record W2043185767 · doi:10.1109/ursigass.2014.6929716

D-region HF absorption models incorporating real-time riometer measurements

2014· article· en· W2043185767 on OpenAlexaboutno aff
Neil Rogers, F. Honary

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research Council
KeywordsRiometerAbsorption (acoustics)Remote sensingEnvironmental scienceMeteorologyComputer scienceGeologyIonosphereGeophysicsOpticsPhysics

Abstract

fetched live from OpenAlex

Absorption of HF (3-30 MHz) radio waves is largely determined by the electron density in the ionospheric D region (50-90 km altitude). During solar proton events (SPE), when the flux of >10 MeV solar protons exceeds 10 cm-2s-1sr-1, the D region ionization may be significantly enhanced at high latitudes where geomagnetic shielding is weaker. This results in polar cap absorption (PCA) events which can cause HF communications outages lasting several days. Models of PCA events are being improved to provide accurate real-time and short-term forecast models of HF absorption for use by HF radio users such as aircraft operating on trans-polar routes. The models are based on the D-region Absorption Prediction model (D-RAP) from the US Space Weather Prediction Service [1, 2] which predicts absorption from real-time measurements of solar X-ray and integral proton flux at one of the Geostationary Operational Environmental Satellites (GOES). Protons with energy below a cut-off energy Ecat a given invariant latitude - a function of geomagnetic indices Kpand Dst[3] - lack the rigidity (momentum per unit charge) required to overcome geomagnetic shielding, whilst protons with energy less than thresholds Etnand Etdfor night and daytime ionospheres respectively, fail to penetrate down to the D-region. Coefficients of the D-RAP model were based on physical modelling and absorption measurements from a single riometer in Thule, Greenland [3] which measures cosmic noise absorption at 30 MHz. The accuracy of the model was validated for 11 SPEs at Thule by Sauer and Wilkinson [2] and for five further riometers in Canada and Finland by Akmaev et al. [4] who suggested possible errors in the location of the rigidity cut-off at high geomagnetic latitudes. In this paper we extend validation of D-RAP to measurements from 13 riometers in the Canadian NORSTAR array and a riometer in Kilpisjärvi, Finland for 93 solar proton events (SPE) spanning the whole of solar cycle 23 (1996-2008). To improve model performance, coefficients are optimized using a non-linear least-squares fit to minimize the root-mean-squared error (RMSE) of the absorption estimate. Using optimized coefficients the RMSE reduces from 0.78 dB to 0.72 dB (using all 14 riometers) or from 0.82 dB to 0.53 dB taking only the single highest latitude riometer, Taloyoak (64.5°N, 93.6°W). By introducing linear terms characterizing the Magnetic Local Time (MLT) dependence, the RMSE may be further reduced to 0.66 dB (all riometers). The inclusion of further linear terms proportional to the hardness of the proton energy spectrum and on solar-zenith angle yielded no significant improvement to the RMSE. The benefits of two modifications to D-RAP suggested by Neal et al. [5] based on Polar Operational Environmental Satellite (POES) measurements - a 1-2° correction in the rigidity cut-off invariant latitude and a 3-hour time lag in the Kpindex used in its determination - will also be presented. A short-term forecast capability may be implemented by measuring proton flux at the Advanced Composition Explorer satellite (ACE) located at the L1 libration point which provides 25-70 minute forewarning of proton flux changes (depending on solar wind velocity). An optimized model using ACE integral proton flux measurements (time-shifted to Earth's location) instead of D-RAP reduces the RMSE from 0.57 dB to 0.47 dB (Taloyoak riometer) and from 0.69 dB to 0.64 dB (all riometers). The nowcast accuracy of the PCA model may be improved by finding model parameters coefficients using a weighted least-squares fit, with higher weights assigned in the most recent 30-minute period of riometer measurements. An example of this technique is presented for the 6-day SPE following the particularly intense solar flare of 14 July 2000, known as the “Bastille-day event”.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.222
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2014
Admission routes1
Has abstractyes

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