The generation ofK indices from digitally recorded magnetic data

Riddick, John C.; Stuart, W.F.

doi:10.1007/bf01465559

Cited by 15 publications

(2 citation statements)

References 3 publications

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“…They are derived for each magnetometer station from the range of variation observed in each of eight 3-hour intervals (0-3 UT, 3-6 UT, up to 21-24 UT). Originally scaled manually, K-value derivation was increasingly automated as magnetometer data recording moved from analogue to digital (Riddick & Stuart, 1984). The range of the irregular variations (i.e., after subtraction of the regular daily variation) in either of the horizontal components (X northward or Y eastward, whichever gives the larger value), DH X or DH Y , is ranked into one of 10 classes using quasi-logarithmic band limits that are specific to the observatory and to which a K value of 0-9 is assigned.…”

Section: K Indicesmentioning

confidence: 99%

Time-of-day/time-of-year response functions of planetary geomagnetic indices

Lockwood

Chambodut

Finch

et al. 2019

J. Space Weather Space Clim.

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Aims: To elucidate differences between commonly-used mid-latitude geomagnetic indices and study quantitatively the differences in their responses to solar forcing as a function of Universal Time (UT), time-of-year (F), and solar-terrestrial activity level. To identify the strengths, weaknesses and applicability of each index and investigate ways to correct for any weaknesses without damaging their strengths. Methods: We model how the location of a geomagnetic observatory influences its sensitivity to solar forcing. This modelling for a single station can then be applied to indices that employ analytic algorithms to combine data from different stations and thereby we derive the patterns of response of the indices as a function of UT, F and activity level. The model allows for effects of solar zenith angle on ionospheric conductivity and of the station’s proximity to the midnight-sector auroral oval: it employs coefficients that are derived iteratively by comparing data from the current aa index stations (Hartland and Canberra) to simultaneous values of the am index, constructed from chains of stations in both hemispheres. This is done separately for eight overlapping bands of activity level, as quantified by the am index. Initial estimates were obtained by assuming the am response is independent of both F and UT and the coefficients so derived were then used to compute a corrected F-UT response pattern for am. This cycle was repeated until it resulted in changes in predicted values that were below the adopted uncertainty level (0.001%). The ideal response pattern of an index would be uniform and linear (i.e., independent of both UT and F and the same at all activity levels). We quantify the response uniformity using the percentage variation at any activity level, V = 100 (σS/〈S〉), where S is the index’s sensitivity at that activity level and σS is the standard deviation of S: both S and σS were computed using the eight UT ranges of the 3-hourly indices and 20 equal-width ranges of F. As an overall metric of index performance, we take an occurrence-weighted mean of V, Vav, over the eight activity-level bins. This metric would ideally be zero and a large value shows that the index compilation is introducing large spurious UT and/or F variations into the data. We also study index performance by comparisons with the SME and SML indices, compiled from a very large number of stations, and with an optimum solar wind “coupling function”, derived from simultaneous interplanetary observations. Results: It is shown that a station’s response patterns depend strongly on the level of geomagnetic activity because at low activity levels the effect of solar zenith angle on ionospheric conductivity dominates over the effect of station proximity to the midnight-sector auroral oval, whereas the converse applies at high activity levels. The metric Vav for the two-station aa index is modelled to be 8.95%, whereas for the multi-station am index it is 0.65%. The ap (and hence Kp) index cannot be analyzed directly this way because its construction employs tabular conversions, but the very low Vav for am allows us to use 〈ap〉/〈am〉 to evaluate the UT-F response patterns for ap. This yields Vav = 11.20% for ap. The same empirical test applied to the classical aa index and the new “homogenous” aa index, aaH (derived from aa using the station sensitivity model), yields Vav of, respectively, 10.62% (i.e., slightly higher than the modelled value) and 5.54%. The ap index value of Vav is shown to be high because it exaggerates the average semi-annual variation and has an annual variation giving a lower average response in northern hemisphere winter. It also contains a strong artefact UT variation. We derive an algorithm for correcting for this uneven response which gives a corrected ap value, apC, for which Vav is reduced to 1.78%. The unevenness of the ap response arises from the dominance of European stations in the network used and the fact that all data are referred to a European station (Niemegk). However, in other contexts, this is a strength of ap, because averaging similar data gives increased sensitivity and more accurate values on annual timescales, for which the UT-F response pattern is averaged out.

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Section: K Indicesmentioning

confidence: 99%

Time-of-day/time-of-year response functions of planetary geomagnetic indices

Lockwood

Chambodut

Finch

et al. 2019

J. Space Weather Space Clim.

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“…Originally, the K indices were scaled manually [Mayaud 1967] from analog (photographic) magnetograms with a standard recording speed of about 20 mm/h. With advances in electronic equipment and computer technologies, however, the data acquisition and processing, plus the subsequent production of the K indices, have gradually shifted to using these new (digital) technologies [Van Wijk and Nagtegaal 1977, Niblett et al 1984, Riddick and Stuart 1984, Hopgood 1986, Wilson 1987, Menvielle 1990]. Several computer-based methods for calculating the K indices have been developed along the way [Jankowski et al 1988, Pirjola et al 1990, Nowozynsky et al 1991, Sucksdorff et al 1991, Menvielle et al 1995.…”

Section: Introductionmentioning

confidence: 99%

K-type geomagnetic index nowcast with data quality control

Stankov

Stegen

Warnant

2011

Annals of Geophysics

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A nowcast system for operational estimation of a proxy K-type geomagnetic index is presented. The system is based on a fully automated computer procedure for real-time digital magnetogram data acquisition that includes screening of the dataset and removal of the outliers, estimation of the solar regular variation (SR) of the geomagnetic field, calculation of the index, and issuing of an alert if storm-level activity is indicated. This is a timecontrolled (rather than event-driven) system that delivers the regular output of: the index value, the estimated quality flag, and eventually, an alert. The novel features provided are first, the strict control of the data input and processing, and second, the increased frequency of production of the index (every 1 h). Such quality control and increased time resolution have been found to be of crucial importance for various applications, e.g. ionospheric monitoring, that are of particular interest to us and to users of our service. The nowcast system operability, accuracy and precision have been tested with instantaneous measurements from recent years. A statistical comparison between the nowcast and the definitive index values shows that the average root-mean-square error is smaller than 1 KU. The system is now operational at the site of the Geophysical Centre of the Royal Meteorological Institute in Dourbes (50.1ºN, 4.6ºE), and it is being used for alerting users when geomagnetic storms take place.

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The Digital Recording System Operated at the U.K. Magnetic Observatories

Forbes

Riddick

1984

Geomagnetic and Observatory and Survey Practice

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The generation ofK indices from digitally recorded magnetic data

Cited by 15 publications

References 3 publications

Time-of-day/time-of-year response functions of planetary geomagnetic indices

Time-of-day/time-of-year response functions of planetary geomagnetic indices

K-type geomagnetic index nowcast with data quality control

The Digital Recording System Operated at the U.K. Magnetic Observatories

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