Day-to-Day Variability of the Sq Geomagnetic Field Variation

Hibberd, F. H.

doi:10.1071/ph810081

Cited by 46 publications

(36 citation statements)

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“…Secondly, recordings sometimes exhibit rapid irregular¯uctuations referred to as geomagnetic disturbances or storms, the magnitude of which may be such that the regular Sq variation is swamped and thus not easily discernable. Although the Sq variation is the most regular of all the geomagnetic ®eld variations, tending to repeat itself with a periodicity of 24 h, signi®cant day-to-day di erences do occur (Hibberd, 1981).…”

Section: Geomagnetic ®Eld Variationsmentioning

confidence: 99%

The development of a regional geomagnetic daily variation model using neural networks

Sutcliffe¹

2000

Ann. Geophys.

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Abstract. Global and regional geomagnetic ®eld models give the components of the geomagnetic ®eld as functions of position and epoch; most utilise a polynomial or Fourier series to map the input variables to the geomagnetic ®eld values. The only temporal variation generally catered for in these models is the long term secular variation. However, there is an increasing need amongst certain users for models able to provide shorter term temporal variations, such as the geomagnetic daily variation. In this study, for the ®rst time, arti®cial neural networks (ANNs) are utilised to develop a geomagnetic daily variation model. The model developed is for the southern African region; however, the method used could be applied to any other region or even globally. Besides local time and latitude, input variables considered in the daily variation model are season, sunspot number, and degree of geomagnetic activity. The ANN modelling of the geomagnetic daily variation is found to give results very similar to those obtained by the synthesis of harmonic coe cients which have been computed by the more traditional harmonic analysis of the daily variation.

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Section: Geomagnetic ®Eld Variationsmentioning

confidence: 99%

The development of a regional geomagnetic daily variation model using neural networks

Sutcliffe¹

2000

Ann. Geophys.

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“…Hibberd (1981) introduced a simple technique to deal with this problem. His technique involves a pair of stations that have the same longitude but different latitudes; one station is on the equatorial side of a Sq focus and the other station is on the polar side of the Sq focus.…”

Section: Determination Of Sq Current Intensitymentioning

confidence: 99%

Sq and EEJ—A Review on the Daily Variation of the Geomagnetic Field Caused by Ionospheric Dynamo Currents

2016

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A record of the geomagnetic field on the ground sometimes shows smooth daily variations on the order of a few tens of nano teslas. These daily variations, commonly known as Sq, are caused by electric currents of several μA/m 2 flowing on the sunlit side of the Eregion ionosphere at about 90-150 km heights. We review advances in our understanding of the geomagnetic daily variation and its source ionospheric currents during the past 75 years. Observations and existing theories are first outlined as background knowledge for the nonspecialist. Data analysis methods, such as spherical harmonic analysis, are then described in detail. Various aspects of the geomagnetic daily variation are discussed and interpreted using these results. Finally, remaining issues are highlighted to provide possible directions for future work.

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“…This limitation was noted by Mayaud, who recognised that the SR must be present every day even though it could not always be identified. That the SR is present every day regardless of magnetic disturbance has recently been highlighted by HIBBERD (1981). By choosing pairs of stations having similar longitudes but on opposite sides of the latitude of the path of the Sq focus, Hibberd was able to identify a composite Sq variation, which was found to be more regular and uniform than the H variations at either station.…”

Section: Discussionmentioning

confidence: 80%

On the computer generation of geomagnetic K-indices from digital data.

Hopgood

1986

J. geomagn. geoelec

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Since the advent of digitally recording magnetic variometers and the ready accessibility of computers, there has been a search for a technique to produce K-indices of geomagnetic activity by machine.The principal difficulty in the determination of K-indices is the estimation of the regular solar diurnal variation (SR) for each day, which is used as a reference from which the K-Variations are scaled. A number of methods for the machine estimation of the daily SR are reviewed. These fall into two categories: (i) by use of neighbouring quiet days, or (ii) filtering out the high frequency harmonics. Of the techniques proposed to date, those which are data adaptive are considered preferable.A data adaptive method which divides a magnetogram trace into high and low frequency harmonics is presented. It is found that there is no particular frequency below which can be considered all the SR variations and above which are all the K-variations.The latitude dependence of the tolerace to differences between estimation of the SR by machine and that manually is also discussed.

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Day-to-Day Variability of the Sq Geomagnetic Field Variation

Cited by 46 publications

References 0 publications

The development of a regional geomagnetic daily variation model using neural networks

The development of a regional geomagnetic daily variation model using neural networks

Sq and EEJ—A Review on the Daily Variation of the Geomagnetic Field Caused by Ionospheric Dynamo Currents

On the computer generation of geomagnetic K-indices from digital data.

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