A seasonal anomaly in the ionospheric E-layer

Appleton, Sir Edward

doi:10.1016/0021-9169(63)90178-8

Cited by 15 publications

(6 citation statements)

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“…Early studies of the E region revealed a seasonal anomaly at mid-latitudes, with N K E 5-15% higher in winter than in summer (Appleton, 1963;Muggleton, 1972). A detailed analysis by Kouris and Muggleton (1973a, b) used monthly median data from 45 stations, averaged over a full sunspot cycle.…”

Section: Seasonal Changesmentioning

confidence: 99%

Model results for the ionospheric E region: solar and seasonal changes

Titheridge

1997

Ann Geophysicae

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Abstract.A new, empirical model for NO densities is developed, to include physically reasonable variations with local time, season, latitude and solar cycle. Model calculations making full allowance for secondary production, and ionising radiations at wavelengths down to 25 A s , then give values for the peak density N K E that are only 6% below the empirical IRI values for summer conditions at solar minimum. At solar maximum the difference increases to 16%. Solar-cycle changes in the EUVAC radiation model seem insufficient to explain the observed changes in N K E, with any reasonable modifications to current atmospheric constants. Hinteregger radiations give the correct change, with results that are just 2% below the IRI values throughout the solar cycle, but give too little ionisation in the E-F valley region. To match the observed solar increase in N K E, the high-flux reference spectrum in the EUVAC model needs an overall increase of about 20% (or 33% if the change is confined to the less well defined radiations at (150 A s ). Observed values of N K E show a seasonal anomaly, at mid-latitudes, with densities about 10% higher in winter than in summer (for a constant solar zenith angle). Composition changes in the MSIS86 atmospheric model produce a summer-to-winter change in N K E of about !2% in the northern hemisphere, and #3% in the southern hemisphere. Seasonal changes in NO produce an additional increase of about 5% in winter, near solar minimum, to give an overall seasonal anomaly of 8% in the southern hemisphere. Near solar maximum, reported NO densities suggest a much smaller seasonal change that is insufficient to produce any winter increase in N K E. Other mechanisms, such as the effects of winds or electric fields, seem inadequate to explain the observed change in N K E. It therefore seems possible that current satellite data may underestimate the mean seasonal variation in NO near solar maximum. A not unreasonable change in the data, to give the same 2:1 variation as at solar minimum, can produce a seasonal

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Section: Seasonal Changesmentioning

confidence: 99%

Model results for the ionospheric E region: solar and seasonal changes

Titheridge

1997

Ann Geophysicae

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“…As the photon flux from the Sun to the atmosphere varies with altitude, local time, location and season, so do the EDPs in the E‐layer (E. Appleton, 1963; E. Appleton & Lyon, 1961; Chu et al., 2009), and N m E varies accordingly. Both solar and magnetic activity strongly influence the magnitude and variability of electron densities at all ionospheric altitudes.…”

Section: Discussionmentioning

confidence: 99%

“…As the photon flux from the Sun to the atmosphere varies with altitude, local time, location and season, so do the EDPs in the E-layer (E. Appleton, 1963;E. Appleton & Lyon, 1961;Chu et al, 2009), and N m E varies accordingly.…”

Section: Discussionmentioning

confidence: 99%

Validation of E‐Region Model Electron Density Profiles With AURIC Utilizing High‐Resolution Cross Sections

Sakib,

Soto,

Yiğit

et al. 2023

JGR Space Physics

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E‐region models have traditionally underestimated the ionospheric electron density. We believe that this deficiency can be remedied by using high‐resolution photoabsorption and photoionization cross sections in the models. Deep dips in the cross sections allow solar radiation to penetrate deeper into the E‐region producing additional ionization. To validate our concept, we perform a study of model electron density profiles (EDPs) calculated using the Atmospheric Ultraviolet Radiance Integrated Code (AURIC; D. Strickland et al., 1999, https://doi.org/10.1016/s0022-4073(98)00098-3) in the E‐region of the terrestrial ionosphere. We compare AURIC model outputs using new high‐resolution photoionization and photoabsorption cross sections, and solar spectral irradiances during low solar activity with incoherent scatter radar (ISR) measurements from the Arecibo and Millstone Hills observatories, Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC‐1) observations, and outputs from empirical models (IRI‐2016 and FIRI‐2018). AURIC results utilizing the new high‐resolution cross sections reveal a significant difference to model outputs calculated with the low‐resolution cross sections currently used. Analysis of AURIC EDPs using the new high‐resolution data indicate fair agreement with ISR measurements obtained at various times at Arecibo but very good agreement with Millstone Hills ISR observations from ∼96–140 km. However, discrepancies in the altitude of the E‐region peak persist. High‐resolution AURIC calculations are in agreement with COSMIC‐1 observations and IRI‐2016 model outputs between ∼105 and 140 km while FIRI‐2018 outputs underestimate the EDP in this region. Overall, AURIC modeling shows increased E‐region electron densities when utilizing high‐resolution cross sections and high‐resolution solar irradiances, and are likely to be the key to resolving the long standing data‐model discrepancies.

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“…A midlatitude seasonal anomaly in the E region was noted initially by Appleton [] and studied in more detail by Muggleton []. Subsequent studies by Kouris and Muggleton [, ] employed a larger database of ionospheric data from which equation was derived.…”

Section: E Region Trace Identificationmentioning

confidence: 99%

Autonomous identification and classification of ionospheric sporadicEin digital ionograms

Ghosh

Berkey

2015

Earth and Space Science

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This paper introduces a methodology to autonomously identify and classify ionospheric sporadic E layers (E s ) from digital ionograms acquired using a NOAA dynasonde operated at the Bear Lake Observatory (BLO) in northern Utah. This approach uses a windowed-fuzzy clustering technique to group ionospheric echoes present in digital ionograms, employing the transitive property of equivalence. The algorithm introduces a variance constraint to automatically determine the number and size of the clusters present in the data set. Principal component analysis (PCA) of the cluster shapes is employed for curvature estimation and to enable classification of the data into the four principal types of temperate latitude sporadic E. A visual evaluation of the autonomously classified ionograms suggests that the algorithm accurately identifies ∼95% of the sporadic E echoes present in the BLO data set. The paper also includes a "proof-of-concept" analysis of the methodology, deriving E s parameters for summer and winter intervals, that explicitly characterizes the diurnal and seasonal variations present in the E region at 42 ∘ N. This analysis was derived from approximately 34,000 digital ionograms acquired over 4 months. While the experimental data show lower peak E region heights than predicted by modeling studies, they are generally consistent with GPS satellite occultation measurements. Our analysis of the temporal variation of f o E during summer and winter intervals is inconsistent with previous results that suggest a seasonal E region density anomaly. The results confirm, however, the ionospheric effect of increased NO densities in both the summer and winter E region, as predicted by modeling studies. The identification of sporadic E using the approach outlined in this work markedly facilitates the analysis of E s parameters, as well as eliminating any human biases from the ionogram analysis process.

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A seasonal anomaly in the ionospheric E-layer

Cited by 15 publications

References 1 publication

Model results for the ionospheric E region: solar and seasonal changes

Model results for the ionospheric E region: solar and seasonal changes

Validation of E‐Region Model Electron Density Profiles With AURIC Utilizing High‐Resolution Cross Sections

Autonomous identification and classification of ionospheric sporadicEin digital ionograms

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