Equatorial electrojet from Ørsted scalar magnetic field observations

Transcription

1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. A2, 1061, doi: /2002ja009310, 2003 Equatorial electrojet from Ørsted scalar magnetic field observations David Ivers School of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia Robert Stening School of Physics, University of New South Wales, Kensington, New South Wales, Australia Jon Turner and Denis Winch School of Mathematics and Statistics, University of Sydney, Sydney, New South Wales, Australia Received 4 February 2002; revised 3 September 2002; accepted 11 September 2002; published 5 February [1] Previous studies of the longitudinal variation of the local noon electrojet have yielded doubtful results either because of the poor data quality or because the local times of equatorial crossings occurred in the early morning or late afternoon. The recent launch of the Ørsted satellite in a near-circular orbit with slow drift in local time of equatorial crossing has provided the opportunity for researchers to study the electrojet more accurately. Most studies remove the main field using a spherical harmonic model and then search the daytime equatorial passes for the distinctive electrojet trough in total intensity. The present study examines the electrojet for two consecutive 6-month periods and consequently two local time ranges. Pure signal processing is used to remove the main field directly. The residuals are binned separately for night and day passes on a 1 by 1 grid to enhance the signal to noise ratio and are bin centered by a least squares fitted linear model to compensate for the variations in satellite altitude. Thereafter, for each period the compensated night and day binned values are subtracted from each other to produce a difference set. Global plots of the subsequently spatially filtered difference sets reveal an almost constant electrojet 1/e half width of 3, as seen at satellite altitude apart from a region in the western Pacific. There are four maxima in the electrojet amplitude at 0 30 E, E, E, and E in each local time range. INDEX TERMS: 2409 Ionosphere: Current systems (2708); 2415 Ionosphere: Equatorial ionosphere; 6974 Radio Science: Signal processing; 1599 Geomagnetism and Paleomagnetism: General or miscellaneous; KEYWORDS: global electrojet, Ørsted, signal processing Citation: Ivers, D., R. Stening, J. Turner, and D. Winch, Equatorial electrojet from Ørsted scalar magnetic field observations, J. Geophys. Res., 108(A2), 1061, doi: /2002ja009310, Introduction 1.1. Overview [2] The equatorial electrojet is an east-west current system that flows, during daylight hours, along the dip equator at an altitude centered around 105 km. Although normally envisaged as a current flowing eastward within 300 km either side of the dip equator, studies of Magsat data at the dusk terminator show a complex circulation within the electrojet. The main effect of the electrojet is to reduce the northwards component of the Earth s main field above it and to augment the same component below. The electrojet is most intense at noon and dissipates almost entirely by dusk. Early electrojet studies relied upon ground based observations and supporting evidence of sounding rocket measurements of current density at various altitudes. [3] There have been several investigations into the electrojet using the geomagnetic satellites OGO-4, OGO-6 Copyright 2003 by the American Geophysical Union /03/2002JA (POGO), and Magsat [see Forbes, 1981; Cohen and Achache, 1990; Ravat and Hinze, 1993; Langel et al., 1993; Stening, 1995; Onwumechili, 1997]. These have been hampered by either the lack of good data, the case with POGO, or a local time regime away from noon, the case with Magsat. Jadhav et al. [2002a, 2002b] have also examined the electrojet using Ørsted satellite data POGO Electrojet Studies [4] POGO is characterized by a wide variation in altitude of km and a rapid transit through local time of 3.87 hours per standard month. In addition, there are frequent breaks in the data, which make analysis difficult. Investigators need to unravel complicated variations of electrojet strength with local time, longitude, and altitude from a relatively small number of good passes. Despite this, an advantage of the POGO data over that of Magsat is that one is able to extract observations within two hours of noon, which is the optimum local time for electrojet studies. All observations contain the near static lithospheric anomaly SIA 5-1

2 SIA 5-2 IVERS ET AL.: BRIEF REPORT signal and to isolate the contribution from the electrojet alone, the observations from a closely adjacent pass (in longitude) near local midnight should be subtracted from the daytime observations. [5] Cain and Sweeney [1973] investigated the variation of electrojet strength with the wide range of altitudes offered by POGO. They found that, contrary to expectations, the strength of the disturbance would sometimes increase with altitude away from the electrojet. Onwumechili and Agu [1980] pursued this investigation and proposed that the current distribution of the electrojet oscillated with altitude in an exponentially decreasing sinusoid with distance from the Earth. The wavelength of this oscillation was estimated to be 180 km. [6] Kim and King [1999], in a recent study of POGO, attempted to quantify the variations in electrojet strength with local time and longitude. Care was taken to account for the effect of the lithospheric field on trough measurements. Owing to the rapid transit through local time regimes and the paucity of good dependable observations spread over the equator, they assumed that all trough depths regardless of local time had a longitude variation, which could be described by a four-term Fourier series. A similar ansatz was invoked for the local time variation with a five-term Fourier series. A pair of least squares fit operations yielded first estimates of these two sets of coefficients. The longitudinal variation coefficients were employed to normalize the original observations to a common longitude datum where they were used to deduce second estimates of the local time coefficients. A similar process was then carried out to normalize the original observations to a common local time datum where they were used to derive second estimates of the longitudinal coefficients. The two sets of second estimate coefficients were then used to renormalize the original data to the longitude datum and local time datum again. When convergence or, more usually, a limit cycle, was achieved for the two sets of coefficients, the outcome was considered satisfactory. The result was a consistent local time model but a rather poor longitudinal model with wide scatter, reduced by restricting the POGO observations to an altitude below 450 km. Contrary to expectations, the form of the longitudinal variation was markedly different to the all altitudes result, leading the authors to surmise that the oscillations in electrojet strength, observed by Onwumechili and Agu [1980] and Cain and Sweeney [1972], were a major factor. The final form of their longitudinal variation shows two peaks and, in that regard, is compatible with the earlier results of Ravat and Hinze [1993] working with the Magsat data. Their peaks were, however, in different positions Magsat Electrojet Studies [7] For their electrojet study with the Magsat data, Ravat and Hinze [1993] were confronted with a different set of problems. Magsat had an almost circular orbit and infrequent data breaks, so that compensation for altitude variations was unnecessary and the data quality was high. However, Magsat followed the dawn dusk terminator so the authors we forced to extract the electrojet signature from observations that essentially fell into either a dawn or dusk data set. Owing to the low altitude of km, both sets contain a large lithospheric anomaly signal and the weakened electrojet is present at both local times. The electrojet cannot therefore be isolated by the simple process of subtracting the dawn data set from the dusk data set. For this reason they relied upon severe averaging of the data across 90 longitudinal sectors of circles of constant latitude under the assumption that the lithospheric field would average to zero, whereas the electrojet would not. Importantly, the meridional slice containing the dominant Bangui anomaly was excluded from this process. The centers of the 90 sectors were staggered by 45 providing eight derived samples per globe and thus seemingly adequate, according to the Nyquist criterion, to determine the longitudinal variation to the fourth equatorial harmonic. A signature containing two broad peaks for both dawn and dusk (but different amplitudes) was the result, which was later reproduced by Kim and King [1999] as explained above Ørsted Electrojet Studies [8] Ørsted [Neubert et al., 2001] is perhaps an ideal satellite for the determination of the longitudinal variation of the electrojet. The orbit is not overly elliptical, the data quality is high, and there is a relatively slow transit through all the local time regimes of 0.46 hours per standard month. Unfortunately, the altitude is km, much higher than Magsat, thus reducing the electrojet signature to the point where it is sometimes difficult to visually isolate it from any other ionospheric contamination. It was therefore thought that Ørsted might not be suitable for the study of low-altitude ionospheric phenomena or of lithospheric magnetic anomalies. [9] Jadhav et al. [2002b] in a contemporaneous study also investigated the electrojet as seen in Ørsted data over a year. They adopt a more conventional approach, extracting parameters pertaining to Onwumechili s [1996a, 1996b] electrojet current model for each acceptable satellite pass during the five quietest days in each month. Owing to this restriction, the amount of data used is quite small although the quantity of significant results claimed is large. From the parameters deduced for each pass model, the authors predict the average longitudinal form of the electrojet signature as well as the seasonal and local time variations associated with it. The veracity of the results is apparently supported by the correlations between predicted ground effects and actual ground based observations at two pairs of stations in India and America, respectively. One aspect of their method of study, which is possibly significant, is that the small number of passes apparently offers no mechanism to account for the lithospheric anomaly field. [10] The present study uses an efficient and effective signal processing technique to extract the very weak 3-nT electrojet signature directly. The conclusions are more modest with the focus on accurately establishing the electrojet signature for two local time regimes. The quantity of data used for each of the 6-month periods is greater than the total used for the Jadhav et al. [2002b] 1-year study. The results are therefore thought to be more dependable and reproducible. 2. Data Used [11] The Ørsted satellite carries two magnetometers, a vector compact spherical coil for recording the geocentric northward, eastward, and downward components of the Earth s field in a MAG_L vector data set and a scalar

3 IVERS ET AL.: BRIEF REPORT SIA 5-3 Overhauser instrument used to record an OVH scalar data set to calibrate the compact spherical coil and also to function as a backup. [12] The MAG_L data set contains frequent and significantly long breaks in the data sequence, due to errors in satellite attitude determination. The OVH data, which is independent of satellite attitude, consequently has greater continuity and is more suitable for the method used to extract the electrojet signal. [13] At the time of the first OVH data acquisition, the Ørsted satellite was placed in a high inclination orbit, which crossed the equator at 1408 local time for daylight passes. The nodal drift of approximately 0.46 hours per month makes each equatorial crossing progressively earlier in local time. This drift has been used here to study the electrojet over two local time ranges by splitting the first year s data into the following 6-month ranges with the corresponding equatorial local times for daylight crossings: (1) data set 1, from 14 March 1999 to 13 September 1999, 1408 to 1123, and (2) data set 2, from 14 September 1999 to 13 March 2000, 1123 to OVH data after 14 March 2000 have not been used in this study because the daytime equatorial crossing is then before 0839 LT. 3. Signal Extraction Method 3.1. Data Binning [14] A brief outline of the along-track-filtering technique used to extract the electrojet signal is included here for completeness; further explanation is given by Ivers et al. [2000]. The OVH data stream is input into a high-pass Kaiser filter to remove all spatial frequencies at and below 13 cycles per orbit. The filter output is then divided into day and night sets, depending on the local time applicable to the central filter sample. Each data set is binned on a 1 by 1 grid. For data sets 1 and 2, the number of observations in each bin is approximately 80 and 60 (for both day or night), respectively, taking the average of the 360 bins around the geographic equator Hyperplane Fitting to Binned Data [15] Least squares hyperplane fitting through observations recorded for a particular bin and day/night combination allows altitude adjustment to the average Ørsted radius of 7130 km (for degree and order less than 45), as well as bin centering. The advantage of accumulating a series of observations into bins is that the addition process can reduce the effects of random noise, from a variety of sources that are associated with any measurement process. Binning, sometimes referred to as stacking, relies on the fact that most noise is Gaussian and adding n observations with noise power P will result in a combined p ffiffiffiffiffiffi sample containing noise power np or rms amplitude np. The signal of amplitude A, present in each observation, is coherent so that observations will produce a combined signal of amplitude na. The anticipated amplitude signal to pnoise ratio of the combined observations would then be A ffiffiffiffiffiffiffiffi n=p thus predicting that more binned samples enhance the result. [16] The observations in each bin are scattered over the range of longitudes and latitudes contained by the boundaries of that bin. There is also a range of altitudes to be considered due to the ellipticity of the satellite orbit. All observations have been normalized within each bin to a common longitude and latitude (located at the bin center) and a common altitude (the mean altitude of the satellite) before combining them for noise reduction. This will also reduce the scatter produced in global plots caused by the possible small bias in magnetic values within the bin. The method used here, which was briefly explained in the earlier paper by Ivers et al. [2000], is so called hyperplane fitting to the data in the bin. The hyperplane is the model function T = al + bf + cr + d, where T is the total intensity and l, f, and r are the distances of the observation from the bin center, in longitude and latitude, and from the mean satellite radius respectively. Parameters a, b, c, and d are derived from a least squares fit to the bin data. [17] Theoretically, the centered, altitude-compensated binned value is obtained directly in d. However, the veracity of the hyperplane fit can be gauged by comparing the values of a, b, and c obtained for neighboring bins. If one or more of the values are found to be unreliable, then they are replaced by values averaged across good neighboring bins. Thereafter, if the final triplet of parameters chosen is denoted by a 0, b 0, and c 0 the value of each observation is essentially adjusted by a 0 l b 0 f c 0 r. Consequently, the process is equivalent to moving all observations parallel to the hyperplane toward the bin center and common radius where they can be combined for noise reduction Spatial Filtering [18] Although the altitude compensation and bin centering afforded by the hyperplane fitting technique does reduce the scatter within the separate binned day and night sets, these still exhibit significant random noise on the one hand and low-amplitude nonrandom furrows in the direction of the tracks on the other. The precise reason for the latter is still under investigation but the prime candidates for this effect are a nonuniform spread of data caused by the satellite having a 5-day quasi-synchronism and/or some residual contamination from the ring current. The latter effect should be quite small with along-track-filtered residuals because the process emulates the anti ring current filter used by previous researchers notably Ridgway and Hinze [1986]. [19] When the day and night binned sets are subtracted from each other to isolate the electrojet, p ffiffiffi the noise contribution is increased by a factor of 2, whereas the electrojet signal, present only in the day set, remains the same. For this reason, further spatial filtering of the difference set is advisable so that the small electrojet signal can be discerned more easily Spatial Band Pass Filtering [20] Spatial filtering is implemented using two-dimensional Fourier transformations of conveniently sized rectangular portions of the global difference set. As calculated by the fast Fourier transform (FFT) algorithm, the Fourier transform of such a spatial matrix with N rows and M columns is a matrix of complex values also of size N by M in an inside-out arrangement where the high-frequency coefficients are concentrated at the matrix center. After appealing to the aliasing property of discrete Fourier transforms, the four transform matrix quadrants, top left, top right, bottom left, and bottom right, may be swapped to the

4 SIA 5-4 IVERS ET AL.: BRIEF REPORT Figure 1. Combined along-track and spatial pass and notch filtering response (solid curves) to model features (dashed curves) with Gaussian function meridional cross sections of 1, 2, 3, 6, and 10 half widths. respective positions of bottom right, bottom left, top right, and top left to facilitate understanding. Here the element at row n column m holds the complex amplitude C nm of the term, n C nm exp 2pi N 1 k þ m 2 M 1 l ; 2 in the Fourier decomposition of the spatial matrix with general row number k and column number l. The extremities of the Fourier transform relate to combinations of high spatial frequencies in either or both of the latitudinal and longitudinal directions and are the ones most badly affected by noise. Improvement in the signal to noise ratio across the spatial matrix is achieved by attenuating these components as much as possible. In addition, the central portion of the transform relates to the average level across the spatial matrix, which can be set to zero to ensure no overall bias in the spatial matrix values. This attenuation of both the high- and low-frequency values is termed band pass filtering Spatial Notch Filtering [21] The quasiperiodic furrows along the tracks (which are almost straight between latitudes 45 and 45 in latitude-longitude Cartesian plots) in the spatial matrix can be described by the Fourier expansion, F kl ¼ XM j¼1 D j exp 2piðakþ blþp j ; for the element at row k, column l, where p j = p M+2 j, Dj = D M+2 j *, and the a and b reflect the angle the furrows make with the lines of latitude. It can be shown that this function will produce a single line of disturbance in the transform. Setting all transform elements lying along that line to zero effectively minimizes the furrows in the spatial matrix, and this procedure is termed notch filtering. The tracks and hence furrows are orientated in different directions for the night and day data sets. When the a day set is subtracted from a night set to produce a difference set, the result will contain two sets of furrows superimposed on each other. There will then be two lines of disturbance in the Fourier transform and hence a double notch filter is required to remove them. The notch and band pass filtering can be combined within a comprehensive spatial filter to make the whole process computationally more efficient Quantifying Combined Filter Effects [22] In Cain and Sweeney [1973] the effect of the electrojet on the main field total intensity at the Ørsted mean altitude of 760 km is characterized by an inverted Gaussian function, which has a depth of around 6 nt and a half widthwidth of 2 3 latitude. The model used therein produces 70 nt at sea level on the magnetic equator. [23] The combination of along-track and spatial filtering obviously modifies the characteristics of the raw electrojet signature. To quantify the overall effects, tests were performed on a series of equatorial inverted Gaussian model features of varying latitudinal width. These are shown by the dashed curves in Figure 1.

5 IVERS ET AL.: BRIEF REPORT SIA 5-5 [24] Although the effect of the along-track filtering on a typical electrojet trough can be ascertained from a onedimensional model, that of the spatial filtering requires a two-dimensional model, and hence a representation of the electrojet notch in both latitudinal and longitudinal directions is appropriate. Ideally, such a model should simulate the slight curve of the trough as it follows the dip equator, which is most marked when crossing South America. However, this is not required when considering the bandwidth of the spatial filter since this will allow through features with a wavelength greater than 3 and will certainly not affect a slow spatial feature such as the deviation of the electrojet from the geographic equator. Thus there is a justification for using the model shown in the Figure 1, which does emphasize the two-dimensional nature of the problem. [25] The result of the combined along-track and spatial band filtering is shown by the corresponding continuous curves in each subplot. As can be seen, the filtering does not overly degrade the amplitude of the 3 half-width model feature. However, the feature acquires artificial positive shoulders on either side of the negative trench. The artificial shoulders themselves are the direct consequence of the along-track filtering alone. Since this removes the average value of the input model feature, the extremities of the output feature inevitably droop while simultaneously the central trough is raised. In addition, wide features that have a substantial proportion of their associated spectra below the along-track filter cutoff at 13 cycles per globe will be greatly attenuated. Conversely, model features with very narrow troughs will not be affected by the along-track filtering but will be reduced by the high-frequency suppression included in the spatial filtering. There is therefore an optimum range within which the attenuation of the combined filtering is minimised, and, from the examples given in Figure 1, this appears to be between 2 and 3 half width. It is important to clarify the fact that the notch part of the spatial filtering has little impact on the input model feature since this is tuned to furrows that are almost orthogonal to the line of the electrojet trough. 4. Measuring the Electrojet Signature 4.1. Overview [26] The difference set is obtained by subtracting the day set from the night set which are themselves obtained from binning the output of the along-track filter. Figure 2 shows two aspects of the differences from data set 1, while Figure 3 performs similar functions for those from data set 2. After carrying out the pass and notch filtering explained above on the difference set, the global contour plots of the day-night differences of data sets 1 and 2, shown in Figures 2a and 3a, respectively, exhibit well-defined electrojet signatures. Although it may be possible to infer the maximum electrojet signature from the contours on the global plots, a more accurate method is to measure it directly from each of the two unfiltered difference sets Attenuation of Wide Features [27] Some researchers have concluded that the width of the electrojet does vary with longitude and so the attenuation in trough amplitude of a wide electrojet caused by the combined along-track and spatial filtering should be addressed here. There are several definitions of width used across this research area since an investigator may be interested in modeled current distributions or magnetic field observations made directly by satellite or ground station pairs. [28] In the first case the type of current distribution model then dictates the measure of width. For example, Agu and Onwumechili [1981] quote the half width of the Onwumechili [1966a, 1966b] current distribution model, i.e., from peak to first zero, whereas Jadhav [2002b], using the same model, quotes the full width measured from first zero to first zero as a, perhaps, more intuitive measure of the same thing. [29] In the second case, where the observed trough is akin to a Gaussian function, a more appropriate measure would seem to be the 1/e half width. Hence it is important to clarify the type of width being discussed at the moment and to recognize that comparison of results from different researchers very often necessitates the employment of conversion factors. [30] Agu and Onwumechili [1981], referring to Onwumechili s [1966a, 1966b] current density model, noted a small variation in half width (peak to first zero) about a mean value of 1. Jadhav et al. [2002b] deduced a very wide variation of up to 6 in current width at longitude 260 E, although this is the full width between first zeros derived from fitting the Ørsted data to Onwumechili s [1966a, 1966b] current model. Using Jadhav et al. s [2002b] correlation plots it is possible to calculate that the trough width should then be about 3.5 times this, i.e., 22 across the shoulders. To emphasize this point again, this is not a direct measurement. There is no doubt that, were the trough to be so wide, the feature would be greatly attenuated by our combined filtering process. A shoulder-to-shoulder width of 22 translates to a half width at 1/e of about 6, and such a trough would have its depth reduced to 50% while at the same time retaining the breadth across the shoulders. However, the applicability of Onwumechili s [1966a, 1966b] model to such a wide current system, if it exists, is moot Determination of Electrojet Position via Cross Correlation [31] The 1 by 1 grid upon which the binning process is implemented is thought to be the best practicable grid size, without reducing the number of hits in each bin to unacceptably low levels. There is a potential problem, though, when attempting to determine accurately the center of the electrojet trough directly from the difference set values, since the half width of the former is of the order of 3 and thus comparable to the spacing of the latter. If the spatially filtered difference set values contained no noise, then determination of the electrojet center could be accomplished directly by cubic interpolation of those values. Unfortunately, the global contour plots belie the fact that the filtering adopted to yield adequate contours does leave behind a certain amount of noise. [32] For this reason, direct interpolation was bypassed in favour of a cross correlation procedure using an inverted Gaussian function of 3 half width as the test function. Cross correlation is akin to using a matched filter and the philosophy here is that the correlation with the additive noise (or features greatly dissimilar to the electrojet trough) will produce virtually zero. By contrast, the cross correla-

6 SIA 5-6 IVERS ET AL.: BRIEF REPORT Figure 2. (a) Global contour plot at 0.5-nT intervals of the electrojet derived from Ørsted data 14 March 1999 to 13 September The local time range for daylight equatorial passes is 1123 to Full contours are negative. (b) Longitude plot of the electrojet signature along the center curve shown as bold in Figure 2a. The RMS scatter is 0.75 nt. tion with the electrojet trough itself and indeed any other features of similar form will produce a significant result Tracking the Electrojet Path [33] With higher-altitude satellites, the problem of distinguishing the electrojet trough (in total intensity) from features caused by other ionospheric contamination becomes severe since the cross correlation function used for a particular meridional slice may exhibit several maxima. If the location of the electrojet center at a particular longitude is known, then its approximate position within the adjacent meridional slice is also known because there are no sudden changes in the electrojet path. This naturally gives rise to the concept of a tracking gate. A tracking gate is merely the restriction of the search for the cross correlation maximum (equal to electrojet center) to a narrow range of latitudes. In the implementation here, the tracking gate is initially set at 20 wide centered on the geographic equator at longitude 335 E. It is known that at this longitude the center of the electrojet will fall in the range ±10 latitude and the electrojet itself is the largest feature within that ambit. Thus the major trough within the initial search gate will certainly be caused by the electrojet. After determination of the correlation function maximum (meaning the electrojet center) at a latitude, say, the predicted position of the electrojet center on the adjacent meridional slice is assumed to be in the range a b to b + a, where b is a maximum slice to slice drift rate. Hence, for the second meridional slice, the tracking gate width can be reduced to 2b, centered on a. The maximum of the correlation function in this range is then found at a 0, say, giving rise to a new tracking gate of width 2b centered on a 0 for the third meridional slice etc. In this way, the path of the electrojet can be tracked successfully through regions where its strength is quite low. If global plots of the electrojet disturbance are the only items of interest, then the above procedure is unnecessary. It is necessary, however, if a precise measurement of the trough depth at the electrojet center is to be undertaken as is the case in the present work Smoothing the Electrojet Position Function [34] Plots of the directly computed electrojet position in latitude against longitude show high-frequency spatial var-

7 IVERS ET AL.: BRIEF REPORT SIA 5-7 Figure 3. (a) Global contour plot at 0.5-nT intervals of the electrojet derived from Ørsted data 14 September 1999 to 13 March The local time range for daylight equatorial passes is 0839 to Full contours are negative. (b) Longitude plot of the electrojet signature along the center curve shown as bold in Figure 3a. The RMS scatter is 0.79 nt. iations. Smoother plots were obtained by low-pass filtering the electrojet position at 13 cycles or less per equatorial great circle. The positions of the electrojet center, as determined by this procedure, are given by the solid bold curves in Figures 2a and 3a Determining the Trough Depth [35] Once the position of the center of the electrojet has been determined at each 1 longitude, the depth of the trough for the associated meridional slice can be calculated. This requires a cubic interpolation of the original global 1 by 1 difference set values to obtain those at the actual electrojet center and at the two assumed shoulders ±7.5 latitude (2.5 times the 1/e half width) relative to that. The assumed position of the shoulders is shown by the dashed curves in Figures 2a and 3a. The justification for this assumption comes from inspection of the global plots, which, as can be seen, do appear to exhibit a constant width apart from the western Pacific minimum. [36] The depth of the trough for a meridional slice, in line with other researchers, is deemed to be the difference between the calculated center and the mean value at the assumed shoulders on either side of it. The results for data sets 1 and 2 (equatorial electrojet signature (EES)) are shown as the jagged curves in Figures 2b and 3b. The high-frequency variations were removed, also by low-pass filtering at 13 cycles per equatorial great circle to produce the smoothed curves shown. 5. Discussion of Results [37] As shown in Figures 2b and 3b, the Ørsted data have revealed four broad maxima in the EES at 0 30 E, E, E, and E modulated by smaller features. Previous workers have variously noted maxima at three of these longitudes. Jadhav et al. [2002b] found maxima in Ørsted data at 100 E and 190 E consistent with earlier observations of POGO. In a POGO electrojet study Cain and Sweeney [1973] found a global maximum in the EES at 290 E and a secondary maximum at 100 E. Recent modeling of the POGO data by Kim and King [1999] produced a global maximum at 290 E but was inconclusive about a maximum at 100 E. Kim and King [1999] concluded that the longitudinal variation of the amplitude of the equatorial electrojet observed in POGO data was not well resolved. Ravat and Hinze [1993] obtained results from Magsat consistent with those of Cain and Sweeney [1973], as did Langel et al. [1993], who

8 SIA 5-8 IVERS ET AL.: BRIEF REPORT observed global and secondary maxima at 280 E and E, respectively. Onwumechili and Agu [1981] included a third peak at 190 E not observed by the other authors. The maximum at 0 E, not found in previous studies, is not due to the Bangui magnetic crustal anomaly, which has been removed by the day-night differencing. [38] Jadhav et al. [2002b] finds a second maximum of counter electrojet occurrence in the western Pacific region at about E. This region corresponds to the western Pacific minimum in the electrojet intensity. In general, Jadhav et al. [2002b] broadly agree with the results here from the two data sets. The Jadhav et al. [2002b] results for 0830 to 0930 LT and 0930 to 1030 LT are able to confirm the main features seen in data set 2 for the local time range 0839 to However, the features that rapidly develop in their local time range 1030 to 1130, especially the double peaks at E and E, remain questionable. Again, the Jadhav et al. [2002b] results for the local time range 1130 to 1230 and 1230 to 1330 are able to confirm the main form of the results for data set 1, although the depressed region at longitude E in their 1230 to 1330 LT results cannot be substantiated. It is unfortunate that Jadhav et al. [2002b] were not able to provide results for 1330 to 1430 LT to enable a better comparison with the results of the present work. [39] It appears that, prenoon (data set 2), the major feature is the large peak between 180 E and 240 E with a gradual tail off toward 360 E. All other peaks in the longitudinal variation can be termed embryonic. However, for data set 1, which is mainly placed postnoon, the large peak E diminishes while a narrow peak at 90 E develops and widens and a broad peak of the same height at E narrows. The depressed region in the prenoon results between 240 E and 290 E develops into a double peak for the postnoon results. Some features remain remarkably consistent during the development of the electrojet through out the day. For example, the western Pacific minimum at 160 E longitude is present in both sets and appears to be a constant feature. [40] Some remarks need to be made here about electrojet width. Jadhav et al. [2002b] have predicted, from their derived Onwumechili [1966a, 1966b] models, that the electrojet current width and hence the trough width seen at satellite altitude should be quite wide, about half width for the latter. This is not borne out by the results here. From Figure 1, it can be seen that when such a wide feature is processed by the combination of along-track and spatial filtering, the trough depth is attenuated by about 50%, but, more importantly, the output zero to zero width is quite broad. This should be seen in the global contour plots, but the zero to zero trough widths at 270 E appear to be much the same as anywhere else. Further, the electrojet signature is not overly degraded at 270 E longitude. A candidate region on the global plot, where it looks as though a very wide feature has not survived the combination of alongtrack and spatial filtering, is the western Pacific minimum at 160 E longitude. It is intriguing, therefore, to see that Jadhav et al. [2002b] predict this to be a region of minimum electrojet current width and hence minimum trough width. [41] As mentioned earlier, because of the small number of passes used in their study, it appears Jadhav et al. [2002b] did not remove the lithospheric field from the electrojet profiles, carried out by most other researchers including ourselves. At Ørsted altitude, the lithospheric field as obtained by Ivers et al. [2000] would be comparable with the electrojet signature. The question is then, Would the inclusion of this component in the electrojet profiles cause the Onwumechili [1966a, 1966b] model used by Jadhav et al. [2002b] to yield a wide current width in some cases? It may be relevant that their maximum current width occurs near the transition from the eastern Pacific to the west coast of South America, a point where there would be a change in the nature of the lithospheric field. [42] The difference between the present and some of the previous studies may be due to several factors: the stronger smoothing of POGO and Magsat data, size of the data sets and the range of local times used in the analysis, or the electrojet amplitude oscillation with altitude [Onwumechili and Agu, 1980]. Comparing Figures 2b and 3b, many features are common to both although the heights and positions differ slightly. Differences may be due to seasonal as well as local time effects. For example, the western Pacific minimum of the electrojet signature near 160 E in Figures 2a and 3a appears to be deeper in data set 2 because of the greater maximum at E in the same. [43] The electrojet shoulder-to-shoulder width as shown in Figures 2a and 3a is about 15, but this translates to a characteristic half width of about 3, in line with expectations. The global plots exhibit positive shoulders of overall width about 20 latitude, but this could be due to the side effect of the combined along-track and spatial filtering as explained earlier (see Figure 1). Further work, such as deconvolution of the data, is required to determine the absolute height of the shoulders. [44] The 6-month EES averages over each local time range at the Ørsted mean altitude are about 2.5 nt and 3 nt for data sets 1 and 2. Allowing for the attenuation of the combined filtering (see Figure 1), the estimated EES is about 3 nt and 3.5 nt, respectively. 6. Conclusions [45] The purpose of this paper has been the detection of the main electrojet features by applying signal processing techniques in the frequency domain to the total intensity data from the Ørsted Overhauser scalar magnetometer without any reliance on the usual main field spherical harmonic modeling. Instead the techniques do involve heavy use of high-pass filtering. It is therefore encouraging to see that these results are, in general, compatible with those derived recently from more conventional time domain analysis. Some of the electrojet characteristics would appear to be still open to question and further work needs to be undertaken in this area. [46] The along-track-filtering method [Ivers et al., 2000] together with hyperplane binning, spatial pass and notch filtering of the Ørsted data yields 6-month global pictures of the electrojet over the local time ranges and In each local time range, there are essentially four maxima in the electrojet signature, 0 30 E, E, E, and E, at the Ørsted mean altitude 760 km. Maxima have been found at the latter three longitudes in some previous studies although the work of Jadhav et al. [2002b] has also found four maxima. The

9 IVERS ET AL.: BRIEF REPORT SIA 5-9 absolute peak signature is about 6.5 nt in data set 2 at 200 E after correction for combined filter attenuation. Global plots reveal an almost constant electrojet 1/e half width of 3 at satellite altitude, apart from a narrow region in the western Pacific. [47] Acknowledgments. This work was supported by the Australian Research Council under grant A1486 ARCL A We are grateful for the support of the Ørsted Project Office and the Ørsted Science Data Centre at the Danish Meteorological Institute in carrying out this study. [48] Arthur Richmond thanks Geeta Jadhav for her assistance in evaluating this paper. References Agu, C. E., and C. A. Onwumechili, Temporal variations of POGO equatorial electrojet parameters, J. Atmos. Terr. Phys., 43, , Cain, J. C., and R. E. Sweeney, POGO Observations of the electrojet, appendices A and B, technical pamphlet, pp. 1 54, Goddard Space Flight Cent., Greenbelt, Md., Cain, J. C., and R. E. Sweeney, The Pogo data, J. Atmos. Terr. Phys., 35, , Cohen, Y., and J. Achache, New global vector magnetic anomaly maps derived from Magsat data, J. Geophys. Res., 95, 10,783 10,800, Forbes, J. M., The equatorial electrojet, Rev. Geophys., 19, , Ivers, D. J., R. J. Stening, J. Turner, and D. E. Winch, Ørsted and Magsat scalar anomaly fields, Earth Planets Space, 52, , Jadhav, G. V., Theoretical modeling of low latitude current system, Ph.D. thesis, Dep. of Physics, Univ. of Mumbai, Fort Mumbai, India, Jadhav, G., M. Rajaram, and R. Rajaram, Equatorial electrojet: A preliminary study based on the Ørsted data, J. Geodyn., 33, , 2002a. Jadhav, G., M. Rajaram, and R. Rajaram, A detailed study of the equatorial electrojet phenomenon using Ørsted satellite observations, J. Geophys. Res., 107(A8), 1175, doi:2001ja000183, 2002b. Kim, H. R., and S. D. King, A study of local time and longitudinal variability of the amplitude of the equatorial electrojet observed in POGO satellite data, Earth. Planets Space, 51, , Langel, R. A., M. Purucker, and M. Rajaram, The equatorial electrojet and associated currents as seen in Magsat data, J. Atmos. Terr. Phys., 55, , Neubert, T., M. Mandea, G. Hulot, R. von Frese, F. Primdahl, J. L. Jørgensen, E. Friis-Christensen, P. Stauning, N. Olsen, and T. Risbo, Ørsted satellite captures high-precision geomagnetic field data, Eos Trans. AGU, 82, 81, 87 88, Onwumechili, C. A., A new model of the equatorial electrojet current, Niger. J. Sci., 1, 11 19, 1966a. Onwumechili, C. A., A three dimensional model of the density distribution in ionospheric currents causing part of quiet day geomagnetic variations, in II Symposium d Aeronomie Equatoriale, Ann. Geophys., spec. publ., , 1966b. Onwumechili, C. A., The Equatorial Electrojet, 626 pp., Gordon and Breach, Newark, N. J., Onwumechili, C. A., and C. E. Agu, General features of the magnetic field of the equatorial electrojet measured by POGO satellites, Planet. Space Sci., 28, , Onwumechili, C. A., and C. E. Agu, Longitudinal variation of equatorial electrojet parameters derived from POGO satellite observations, Planet. Space Sci., 29, , Ravat, D., and W. J. Hinze, Considerations of variations in ionospheric field effects in mapping equatorial lithospheric Magsat magnetic anomalies, Geophys. J. Int., 113, , Ridgway, J. R., and W. J. Hinze, Magsat scalar anomaly map of South America, Geophysics, 51, , Stening, R. J., What drives the equatorial electrojet?, J. Atmos. Terr. Phys., 57, , D. Ivers, J. Turner, and D. Winch, School of Mathematics and Statistics, University of Sydney, Sydney, N. S. W. 2006, Australia. (david@maths. usyd.edu.au; jont@maths.usyd.edu.au; denisw@maths.usyd.edu.au) R. Stening, School of Physics, University of New South Wales, Sydney 2052, N. S. W., Australia. (R.Stening@unsw.edu.au)