Longitudinal (UT) effect in the onset of auroral disturbances over two solar cycles as deduced from the AE-index

Hajkowicz, L.A.

doi:10.1007/s00585-998-1573-9

Cited by 19 publications

(16 citation statements)

References 15 publications

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“…Thus, AE indicates the total maximum amplitude of the two-current-system. More-over, the choice of the AE-index as an indicator of the global magnetospheric activity has been made because of the common point of view that AE-indices are able, in some sense, to sample the state space of the magnetospheric system (Hajkowicz, 1998). Also, AE index is a reliable indicator of the auroral activity and will In the present study, AE index time series of one minute duration, representing disturbed and quiet conditions, falling under different seasons of high (1991 with yearly average of solar flux = 208) and low (1994 with yearly average of solar flux = 85.8) solar active years were analysed.…”

Section: Data Analysis and Methodologymentioning

confidence: 99%

Comparison of chaotic aspects of magnetosphere under various physical conditions using AE index time series

Unnikrishnan

2008

Ann. Geophys.

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Abstract. The deterministic chaotic behaviour of magnetosphere was analyzed, using AE index time series. The significant chaotic quantifiers like, Lyapunov exponent, spatiotemporal entropy and nonlinear prediction error for AE index time series under various physical conditions were estimated and compared. During high solar activity (1991), the values of Lyapunov exponent for AE index time series representing quiet conditions (yearly mean = 0.5±0.1 min −1 ) have no significant difference from those values for corresponding storm conditions (yearly mean = 0.5±0.17 min −1 ). This implies that, for the cases considered here, geomagnetic storms may not be an additional source to increase or decrease the deterministic chaotic aspects of magnetosphere, especially during high solar activity. During solar minimum period (1994), the seasonal mean value of Lyapunov exponent for AE index time series belong to quiet periods in winter (0.7±0.11 min −1 ) is higher compared to corresponding value of storm periods in winter (0.36±0.09 min −1 ). This may be due to the fact that, stochastic part, which is D st dependent could be more prominent during storms, thereby increasing fluctuations/stochasticity and reducing determinism in AE index time series during storms. It is observed that, during low solar active period (1994), the seasonal mean value of entropy for time series representing storm periods of equinox is greater than that for quiet periods. However, significant difference is not observed between storm and quiet time values of entropy during high solar activity (1991), which is also true for nonlinear prediction error for both low and high solar activities. In the case of both high and low solar activities, the higher standard deviations of yearly mean Lyapunov exponent values for AE index time series for storm periods compared to those for quiet periods might be due to the strong interplay between stochasticity and determinism during storms.Correspondence to: K. Unnikrishnan (kaleekkal unni@yahoo.com) It is inferred that, the external driving forces, mainly due to solar wind, make the solar-magnetosphere-ionosphere coupling more complex, which generates many active degrees of freedom with various levels of coupling among them, under various physical conditions. Hence, the superposition of a large number of active degrees of freedom can modify the stability/instability conditions of magnetosphere.

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Section: Data Analysis and Methodologymentioning

confidence: 99%

Comparison of chaotic aspects of magnetosphere under various physical conditions using AE index time series

Unnikrishnan

2008

Ann. Geophys.

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“…They also found that the difference between AE and SAE was a strong function of universal time (UT), their correlation being the highest between 00 to 11 UT, and during primarily southward IMF (B z < 0.5 nT). Similarly, Hajkowicz [1998] determined using the standard AE index that there was a UT effect in the onset of auroral disturbances, which tend to peak between 09 and 18 UT and reach a minimum between 03 and 06 UT. A possible explanation for the minimum in the auroral disturbances between 03 and 06 UT has been examined by Ahn et al [2000] who found that that the AL index often underestimated the disturbance conditions between 02 and 08 UT.…”

Section: Introductionmentioning

confidence: 99%

Comparison of auroral electrojet indices in the Northern and Southern Hemispheres

Weygand

Zesta

2008

J. Geophys. Res.

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[ 1 ] The auroral electrojet (AE) index is traditionally calculated from as et of about 10 to 13 ground magnetometer stations located around the typical northern auroral oval location. Similar coverage in the Southern Hemisphere does not exist, so the AE calculation has only been performed using Northern Hemisphere data. In the present paper,w eu se seven southern auroral region ground magnetometers as well as their conjugate Northern Hemisphere data to calculate conjugate AE indices during the Northern Hemisphere winter using the standard method. The correlation coefficient between the northern and southern AE indices for many of the intervals is above 0.7, but in one interval, it is close to 0. We compare our conjugate AE indices with the standard AE index and find an umber of asymmetries because of station coverage gaps both in our conjugate indices and in interplanetary magnetic field (IMF) conditions. When the southern AE index is compared with the standard AE index, we find that for most intervals the correlation is less than 0.7, and in one interval, the correlation is about 0. The correlation between the conjugate northern AE index and the standard AE index is somewhat better,s uggesting true interhemispheric asymmetries. The mean difference between the southern and northern AE indices is largest during southward IMF and for large values of IMF j B y j (>5 nT). This is most likely due to the increased activity levels during southward IMF and the greater twisting of the magnetic field lines during strong IMF B y .I MF B x seems to have no effect on the interhemispheric differences of the AE index. The mean differences between the southern and conjugate northern H component are of the order of 35 nT,with the largest differences occurring in the midnight magnetic local time (MLT) sector.W es uggest that these differences may be related to seasonal effects, ionospheric effects, and MLTeffects.

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“…They suggested that between 02 and 08 UT, the AL index often underestimated the geomagnetic activity. Additionally, Hajkowicz [1998] determined that the UT effect in the Northern Hemisphere was strongest in the winter and weakest in the summer. However, Hajkowicz [1998] acknowledged that auroral disturbances occur simultaneously in both hemispheres, but the UT effect in the summer hemisphere may be obscured by the higher ionospheric conductivity there.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, Hajkowicz [1998] determined that the UT effect in the Northern Hemisphere was strongest in the winter and weakest in the summer. However, Hajkowicz [1998] acknowledged that auroral disturbances occur simultaneously in both hemispheres, but the UT effect in the summer hemisphere may be obscured by the higher ionospheric conductivity there. The UT and seasonal effects noted in those studies on the indices would result in additional interhemispheric asymmetries between the indices derived in the two hemispheres.…”

Section: Introductionmentioning

confidence: 99%

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Auroral electrojet indices in the Northern and Southern Hemispheres: A statistical comparison

2014

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The auroral electrojet (AE) index is traditionally derived from about 12 ground magnetometer observatories located around the average northern auroral oval location. The AE index calculation has only been performed with Northern Hemisphere data, because similar coverage in the Southern Hemisphere does not exist. In this study, eight southern auroral ground magnetometers and their near conjugate Northern Hemisphere counterparts are used to calculate conjugate AE indices for 274 days covering all four seasons from 2005 to 2010. The correlation coefficient between the northern and southern AE indices for many of the intervals is 0.65 indicating strong asymmetries between the two hemispheres. We compare our conjugate AE indices with the standard AE index and find a number of asymmetries because of station coverage gaps in the southern and northern arrays. The mean difference between the southern and northern AE indices is largest during northern summer season, and the smallest mean difference occurs in the spring. The mean differences between the southern and conjugate northern AE indices are about 31 nT with the largest differences occurring in the midnight magnetic local time (MLT) sector. We suggest that these differences may be a function of seasonal, MLT, and ionospheric effects. We also find a difference in the southern and northern AE related to UT and believe that this pertains to the distribution of the magnetometers. The fact that a difference between the southern and northern AE indices exists indicates the importance of examining geomagnetic activity in both hemispheres when considering magnetospheric phenomena.

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Longitudinal (UT) effect in the onset of auroral disturbances over two solar cycles as deduced from the AE-index

Cited by 19 publications

References 15 publications

Comparison of chaotic aspects of magnetosphere under various physical conditions using AE index time series

Comparison of chaotic aspects of magnetosphere under various physical conditions using AE index time series

Comparison of auroral electrojet indices in the Northern and Southern Hemispheres

Auroral electrojet indices in the Northern and Southern Hemispheres: A statistical comparison

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