Dependencies of high-latitude plasma convection...

Dependencies of high-latitude plasma convection: Consideration of

interplanetary magnetic field, seasonal, and universal time factors in

statistical patterns

J. M. Ruohoniemi and R. A. GreenwaldJohns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA

Received 28 September 2004; revised 28 February 2005; accepted 8 April 2005; published 1 September 2005.

[1] The database of the nine radars of the Super Dual Auroral Radar Network(SuperDARN) in the northern hemisphere has been analyzed for information on factorsthat influence the convection of plasma in the high-latitude ionosphere. The velocitymeasurements were collected over the period 1998–2002. The data were first used toderive a new statistical model of convection that improves upon the earlier one-radarmodel of Ruohoniemi and Greenwald (1996) in its specification of the dependence of theconvection pattern on the magnitude and direction of the IMF in the GSM Y-Z plane. Wethen derived average patterns for secondary sortings by season, year, and radar. Suchdependencies as emerged were most clearly seen by contrasting the results for By+ andBy�. The seasonal effect in the convection pattern is found to have similarities to that ofthe sign of By. In particular, the combination of By+/summer (By�/winter) reinforcesthe tendency of the By sign factor to sculpt the dusk and dawn cells into more round/crescent (crescent/round) shapes and to shift the crescent cell across the midnight MLTmeridian. However, these combinations are associated with lower estimates of the totalcross polar cap potential drop, FPC, while the nonreinforcing combinations produceelevated FPC, especially By�/summer. There is an overall tendency for FPC to increasefrom winter to summer, although the pure seasonal effect on the potential drop is weakerthan that of the By�sign/season factor. We did not find pronounced differences amongthe patterns derived for the 5 individual years, which spanned the most recent interval ofsolar cycle maximum. Sorting by radar, we found few differences among the patterns forBy+, but for By�, variations emerged that are consistent with a possible dependence onuniversal time (UT). The impacts of season and UT on convection in the high-latitudeionosphere thus depends on the IMF, especially the sign of By. We speculate thatvariability in the ionospheric conductivity has a greater effect on magnetosphere-ionosphere coupling under By� conditions.

Citation: Ruohoniemi, J. M., and R. A. Greenwald (2005), Dependencies of high-latitude plasma convection: Consideration of

interplanetary magnetic field, seasonal, and universal time factors in statistical patterns, J. Geophys. Res., 110, A09204,

doi:10.1029/2004JA010815.

1. Introduction

[2] The plasma of the high-latitude ionosphere is kept inmotion by processes that couple energy and momentumfrom the solar wind into Earth’s magnetosphere. Thelarge-scale pattern of plasma circulation most often con-forms to a two-cell configuration with antisunward flowacross the pole returning to the dayside via the dawn anddusk flanks. The size and configuration of the pattern andthe intensity of the plasma flows are strongly linked to theinterplanetary magnetic field (IMF) carried by the solarwind plasma. The reconnection hypothesis of Dungey[1961], subsequently developed by workers such asCrooker [1979] and Reiff and Burch [1985], accounts

for the IMF factor by shifting the location of energizedplasma flows across the magnetopause according to therequirement that coupling occur where the magnetic fieldsof the magnetosheath and magnetosphere are antiparallel.For the case of a southward orientation of the interplan-etary magnetic field (IMF), or Bz�, reconnection isfavored on the subsolar magnetopause near the noonMLT meridian. For azimuthal IMF, i.e., By+ or By�, thesite of reconnection in the northern hemisphere shiftsduskward or dawnward, respectively, and ionosphericconvection at auroral latitudes in the favored sectoracquires a zonal component directed toward noon. In thecase of strongly northward IMF, the site of reconnectionshifts to higher latitudes and the usual sense of two-cellcirculation reverses within small dayside convection cells[Greenwald et al., 1995a]. Even in the absence of IMF,some amount of momentum is transferred across the

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 110, A09204, doi:10.1029/2004JA010815, 2005

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magnetopause by viscous processes and an appreciablezero-level background pattern is maintained [Papitashviliet al., 2002]. The convection is also affected episodicallyby auroral substorms [Weimer, 1999].[3] There is a lengthy history of efforts to utilize

ionospheric measurements to portray the large-scale con-vection as a function of IMF that goes back at least as faras Heppner [1977]. A level of definitiveness was reachedwith the study of Heppner and Maynard [1987]. In thelast decade, statistical models were developed by Richand Hairston [1994] using DMSP satellite data, Weimer[1995] using DE satellite data, and Ruohoniemi andGreenwald [1996] using ground-based HF radar data.Despite the differences in their approaches, these modelslargely agree in their depiction of the basic IMF depen-dencies of the global convection. Less direct measure-ments with ground-based magnetometers have also beenapplied [Friis-Christensen et al., 1985; Papitashvili et al.,1994; Ridley et al., 2000]. The recent study by Papitashviliand Rich [2002] generated a fully parameterized modelbased on DMSP data and compared the current models intheir characterization of the total cross polar cap potentialvariation, FPC, as a function of IMF and season. Themodels show some seasonal effect but no consensus hasemerged that matches the agreement regarding IMFfactors.[4] In this study we apply the data set of measurements

collected with the northern radars of the Super Dual AuroralRadar Network (SuperDARN) to derive an improvedmodel to replace the one-radar model of Ruohoniemi andGreenwald [1996] and to characterize secondary depen-dencies of the convection. The statistics are vastly im-proved over those of the earlier study (RG96) because ofthe increase in radars from one to nine and the generalavailability of upstream IMF data from the ACE satellite.After presenting the new model (RG05), we proceed tosort the database by season, year, and radar. We focus onthe connection between the IMF factor and the secondarydependencies, especially that of the sign of By. The sortingby year relates to the possible impact of solar cyclefactors. The sorting by radar relates to the possibility ofa dependence on UT. In the course of a day the offset ofthe geomagnetic pole from the rotational axis causes thesolar illumination across the polar cap and auroral zone tovary and this might perturb the convection.[5] We emphasize that this study focuses on the prop-

erties of the convection in its representation as a statisticalmean of a large set of measurements. Another body ofwork addresses the behavior of the instantaneous convec-tion, e.g., Greenwald et al. [1999], Ruohoniemi et al.

[2002]. The convection on timescales of minutes is knownto be quite variable, even for relatively stable IMFconditions [Bristow et al., 2004]. This variability mustadversely affect the ability of the models to predict theinstantaneous convection. Nonetheless, the general consis-tency of the recent models in terms of their depictions ofIMF dependencies shows that mean, or background,convection patterns can be sensibly determined. An un-derstanding of this reproducible aspect of the convectionis necessary as a basis for understanding convectiondynamics generally. The statistical approach also givesus a practical means to identify the influence of secondaryfactors that would not be apparent in instantaneousobservations.

2. SuperDARN HF Radars

[6] SuperDARN is an international collaboration involv-ing scientists and funding agencies of over a dozencountries that operates chains of HF radars in both thenorthern and southern hemispheres. Greenwald et al.[1995b] has described the concept of the collaborationand its utility for making large-scale, continuous observa-tions in the high-latitude ionosphere. Software developedmainly by the Johns Hopkins University Applied PhysicsLaboratory (JHUAPL) is used to operate the radars and togenerate data in common formats. Table 1 identifies thenorthern radars, their institutional affiliations, and dates ofinception. The data considered in this study were collectedexclusively in the northern hemisphere through the years1998–2002. This interval encompasses about half theperiod of the current solar cycle, which reached its peakin 2000–2001.[7] Figure 1 shows a map of the fields of view of the

SuperDARN radars in the north. Usually the radars sweepthrough scans in azimuth every 1 or 2 min. Except foroutages due to equipment malfunction or repair work, theradars operate continuously under computer control. Theydetect backscatter from ionization irregularities in the ion-osphere that have been amplified far above thermal fluctu-ation levels by plasma instability processes. At F regionaltitudes the predominant motion of these irregularities isdue to the E � B drift of the ambient plasma [Villain et al.,1985; Ruohoniemi et al., 1987]. Among other measure-ments, the Doppler velocity imparted to backscattered HFsignal is recorded as a function of time, direction, and range.The SuperDARN radar thus provides snapshots of the line-of-sight component of the plasma convection velocity.Further discussion of the factors that affect the measurementof ionospheric plasma convection with HF radars can be

Table 1. SuperDARN Radars–Northern Hemisphere

Radar Location Inception PI Host Institution

King Salmon Alaska 2001 T. Kikuchi Communication Research Laboratory, JapanKodiak Alaska 2000 W. Bristow University of Alaska Fairbanks, USAPrince George British Columbia 2000 G. Sofko University of Saskatchewan, CanadaSaskatoon Saskatchewan 1993 G. Sokfo University of Saskatchewan, CanadaKapuskasing Ontario 1993 R. Greenwald The Johns Hopkins University Applied Physics Laboratory, USAGoose Bay Labrador 1983 R. Greenwald The Johns Hopkins University Applied Physics Laboratory, USAStokkseyri Iceland 1994 J.-P. Villain Centre National de la Recherche Scientifique, FrancePykkvibaer Iceland 1995 M. Lester University of Leicester, UKHankasalmi Finland 1995 M. Lester University of Leicester, UK

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found in the work of Villain et al. [1984] and Ruohoniemiand Greenwald [1997].

3. Data Processing

[8] An assimilative mapping technique has been devel-oped to combine the velocity data from all the radars into amap of the global convection pattern [Ruohoniemi andBaker, 1998]. Analysis of time series of convection mapshas demonstrated the sensitivity of the instantaneous con-vection to variations in the IMF [Greenwald et al., 1999;Ruohoniemi et al., 2002]. The technique is also the basis forderiving a nowcast of the convection pattern using datadownloaded in near real-time from the northern radars[Ruohoniemi et al., 2001] (available at http://superdarn.jhuapl.edu/). For the work described here it provides ameans of reducing global sets of line-of-sight velocity dataobtained for selected conditions to estimates of the globaldistribution of electrostatic potential, F, where E = �gradF.[9] Our source of information on the IMF is the

Advanced Composition Explorer (ACE) MAG instrument.The spacecraft varies its position but is most often situatednear the L1 Lagrangian point, which is nearly 200 RE

sunward of the Earth. For this study we are interested inthe quasi-static condition of the convection velocity whenan IMF condition is known to prevail at the magneto-pause. Toward this end, we have performed a rudimentary

analysis of the propagation of features in the solar windfrom the position of the ACE satellite using the radialcomponent of the solar wind velocity measured by the ACESWEPAM instrument. When velocity data are selected foran IMF sorting, the conditions must have prevailed at themagnetopause for a period of at least 36 min. We have notspecifically included a delay for the pattern to reconfigurefollowing the arrival of an IMF change at the magneto-pause; however, our requirement of IMF constancy at themagnetopause easily accommodates the 10–20 min delaythat is expected [Ridley et al., 1998]. Owing to the ratherlonger timescales that are typical of variation in the IMF, theresults of the data selection turn out to be insensitive to thedetails of the propagation/persistence analysis.[10] In its usual operating mode a SuperDARN radar

obtains velocity measurements over the fan-shaped areathat is defined by steering the radar beam through 16successive azimuths with a step of 3.3 deg. Backscatteredsignal is collected within 75 independent range gates thatbegin at 180 km and have a separation of 45 km. As shownin Figure 1, the radar fields of view are mainly orientedtoward the geomagnetic pole, with the exceptions of theIceland radars which are directed more zonally. A scan isrepeated every 1 or 2 min. Since the resolution available inthese measurements exceeds the needs of this statisticalstudy, it is convenient to reduce the data to a coarser formatthat reduces the data handling requirement and aids in data

Figure 1. Fields of view of the radars of the SuperDARN collaboration in the northern hemisphere.


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visualization. First, the velocity data from the individualradars are mapped into a global grid of equal-area cells thatis similar to the grid defined by Ruohoniemi and Baker[1998] except that the coordinate system is MLT/latituderather than latitude/longitude. Each cell measures 1 deg inlatitude. Within each cell, the velocities are averaged within10-deg sectors of magnetic azimuth that are centered onazimuths of 0 deg, ±10 deg, ±20 deg, etc. Finally, the dataare averaged within 12-min UT intervals. The result is aseries of monthly files that summarize the velocity infor-mation that is available for reduction to statistical convec-tion maps. These files can be filtered in chronological orderfor that subset of the records that were collected underspecific conditions. As an example, we select those intervalswhen the IMF magnitude in the GSM Y-Z plane was in the3–5 nT range and the IMF clock angle corresponded topredominantly By+ conditions. Figure 2a shows the numberof velocity measurements that were obtained within the cellsof the mapping grid. The counts reach into the thousandsand extend to the pole. Among other features, it is possibleto make out some ordering of the distribution by the daysidecusp/cleft geometry [Ruohoniemi and Greenwald, 1997].The aggregate velocity information can be presented in asingle plot, as shown in Figure 2b. Each cell within theMLT-latitude grid is populated by a set of velocities at10-deg step that spans the range of azimuths sampled bythe radars. Each velocity represents the statistical mean of

the line-of-sight velocity measurement within the givencell in the given direction for the stated IMF conditions.[11] The derivation of mean line-of-sight velocities

generates information on the variability of the velocitymeasurements. For each setting of position and direction,the root-mean-square scatter of the individual velocitymeasurements about the mean can be determined. Figure 3ashows a map of variability associated with the velocities ofFigure 2b. The variability, depicted here as a scalar functionof position, has been obtained by averaging over themagnetic azimuths within each cell. The magnitude of thevariability is substantial compared with the mean velocityand its distribution reflects in part the structure of theconvection pattern. In future studies we will analyze thebehavior of the variability and consider its geophysicalsignificance. Here, we make use of the variability byassigning it as the uncertainty in the associated mean line-of-sight velocity. A fitting analysis can be expected toreproduce the velocities only to within these uncertainties.[12] Ultimately, we will reduce the set of velocity data

to a map of the distribution of the electrostatic potential,F. As discussed by Ruohoniemi and Greenwald [1998],the result will represent a solution for the data that isoptimal in a global sense, that is, the average offset ofinput and fitted velocities will have been minimized.Alternatively, one can derive a map of the convection thatis optimal in a local sense. We briefly consider this option

Figure 2. (a) Map of the number of velocity measurements made by the SuperDARN radars forconditions of predominantly IMF By+ and magnitude in the 3–5 nT range over the interval 1998–2002.The dashed red line indicates the solution for the equatorward boundary of the convection zone asdescribed in the text. (b) Map of the corresponding binned and averaged line-of-sight velocities.


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for the data of Figure 2b. As discussed above, within eachgrid cell the average value of the line-of-sight componentof the convection velocity is expressed as a function ofazimuth at 10-deg step. The local velocity vector can beestimated by fitting the velocity variation to a cosinedependence on the azimuth. The result is the map of twodimensional convection velocities shown in Figure 3b. Thelocal solution is of course insensitive to any larger con-straints on the convection pattern, such as a condition ofzero divergence imposed by the incompressibility of iono-spheric plasma. The map shows a two-cell convectionpattern with flows circulating within a larger, rounderdusk cell and a distinctively crescent-shaped dawn cell.(Some vectors near the pole are poorly determined owingto the coarseness of the sampling in azimuth there.) Theflow magnitude peaks near 600 m/s within the throat-likechannel on the dayside. Large-scale features such as theconvection reversal boundary (CRB) in the dawn sectorcan be discerned, indicating a high degree of globalcoherence across the local velocity determinations.[13] The most useful representation of the global convec-

tion is obtained by solving for the distribution of F. Theresult for this data set is shown in Figure 4a. As describedby Ruohoniemi and Greenwald [1998], the line-of-sightvelocities are fitted to an expansion of F in terms ofspherical harmonic functions. The spatial resolution is setby the order and degree of the expansion, L = 8 and M = 8,respectively. For reference, we note that these L and M

values are sufficient to exactly reproduce an arbitrary set ofvelocity measurements distributed along a line (as might begenerated by cross-track measurement from a low-altitudesatellite) at a spatial step equivalent to the resolution(�100 km) of the SuperDARN mapping grid. As describedabove, the uncertainties used in the fitting were takenfrom the variabilities in the mean line-of-sight velocities.The value of the chi-squared parameter obtained in thefitting was c2 = 0.2, indicating that the velocities were,on average, reproduced to well within these uncertainties.Locally, the fitted velocities might be more inconsistentwith the measured velocities. To examine this, we haveplotted in Figure 4b the convection velocities implied bythe solution for the global pattern. This can be comparedwith the locally optimized velocities shown in Figure 3b.As expected, the local velocities are not exactly repro-duced but the overall structure of the convection patternand the average condition of the flows are quite similar.The global solution renders an estimate for the total crosspolar cap potential variation, FPC, of 36 kV.[14] The fitting procedure requires a specification of the

equatorward edge of the convection zone, i.e., the positionof the zero potential boundary. For mathematical simplicitythis boundary is taken to be circular in shape and centeredon the geomagnetic pole. Variation in the size of theconvection zone is accommodated by adjusting the latitudeof the boundary. As discussed by Shepherd and Ruohoniemi[2000], the fitting results can be improved by taking into

Figure 3. (a) Map of the variability associated with the velocity data presented in Figure 2.(b) Convection velocity vectors obtained by locally solving the variation of the line-of-sight velocitywith azimuth.


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account the more realistic boundary shape described byHeppner and Maynard [1987]. The Heppner-Maynard(H-M) boundary as defined by Shepherd and Ruohoniemi[2000] is circular on the nightside but withdraws to higherlatitudes on the dayside. The distribution of HF backscat-ter usually conforms to this shape and thus provides uswith a means of gauging the spatial extent of the con-vection zone. For this study we determined the H-Mboundary for each data set by scaling the boundaryaccording to the characteristics of the backscatter andvelocity distributions. The latitude at which the boundarycrosses the midnight MLT meridian, LHM, identifies thesetting. In the example of Figure 2a the H-M boundarycorresponding to LHM = 60 deg is shown by the dashedred curve. On the nightside the boundary is circular andcoincides exactly with the zero potential boundary. In thefitting to obtain a potential pattern, the region on thedayside that is equatorward of the H-M boundary butpoleward of the zero potential boundary contributes a setof zero velocity pads to the data set [Shepherd andRuohoniemi, 2000] reflecting the expectation that thisregion is subauroral. In the example of Figure 2a the H-Mboundary on the dayside corresponds to a steep decrease incounts with decreasing latitude and defines an edge to thezone of well-organized velocities. The principal impact ofapplying the H-M boundary condition on the fitting is toprevent the solution for potential contours from wanderinginto the dayside subauroral region. Appendix A lists the

settings of LHM that were obtained for the data sets consid-ered in this paper.[15] We note one important departure from the procedure

described by Ruohoniemi and Greenwald [1998]. Thefittings described here did not utilize statistical model data.In solving for instantaneous maps, for which the coverageprovided by the radars is not truly global, a sparse set ofvelocity measurements from the model of Ruohoniemi andGreenwald [1996] is generally used to stabilize the resultsover areas of no observations. The exact selection of modeldata is keyed to the IMF. In this study, summing up theindividual observations over many events typically resultsin very extensive coverage (e.g., Figure 2a) and no suchstabilization is required.

4. RG05 Convection Model

[16] To obtain a basic characterization of the IMF depen-dencies of the convection, we have performed a standardbinning by magnitude and clock angle in the GSM Y-Zplane. The magnitude intervals selected were 0–3, 3–5, and5–10 nT. The step in clock angle was 45 deg and data wereaccepted for a solution if the direction of the associated IMFlay within 22.5 deg of the designated orientation. Thus atotal of eight IMF orientations (Bz+, Bz+/By+, By+, Bz�/By+,Bz�, Bz�/By�, By�, Bz+/By�) were obtained per magnitudeinterval. We note that the stated magnitude intervals differfrom those considered by RG96, which were 0–4, 4–6,

Figure 4. (a) Map of the distribution of the electrostatic potential, F, obtained by fitting the velocitydata of Figure 3 to an expansion of the potential in terms of spherical harmonic functions. (b) Map ofconvection velocity vectors implied by the solution for F.


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and 6–9 nT. We made this change in order to balance theoccurrence statistics more evenly between the IMF mag-nitude intervals and to better resolve the IMF effects atsmaller magnitude.[17] The revised convection model, consisting of

24 patterns in total, is illustrated in Figures 5–7. Thisshows all the well-known dependencies, including thesculpting of the dawn and dusk cells into more roundedor crescent shapes depending on the sign of By, intensi-

fication of the two-cell pattern for increased magnitude ofsouthward or azimuthal IMF, pronounced expansion of thepattern for increasing Bz�, and the emergence of sunwardconvection on the dayside for increasing Bz+. We alsonote the systematic rotation to later MLTs of the linejoining the cell centers with progression of the IMF clockangle from By+ through Bz� to By�. Values of FPC areconsistently higher for By+ than for By�. Unsurprisingly,in the lowest interval of IMF magnitude the dependence

Figure 5. Statistical convection patterns sorted by clock angle in the GSM Y-Z plane for the 0–3 nTinterval of IMF magnitude.


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on clock angle is fairly muted and the pattern can bedescribed as two-cell for all orientations with flow magni-tudes that are roughly twice as large for Bz� as for Bz+. Forthe most expanded pattern, namely Bz� in the 5–10 nTinterval, the centers of the convection cells still lie polewardof 70 deg latitude and hence the full magnitude of theantisunward flow across the polar cap can still be mappedby the SuperDARN radars and the estimate of FPC remainswell-determined.

[18] One other noteworthy aspect of the patterns is theappearance of a By� sign effect in the nightside convec-tion. The sculpting of the cells into rounder and morecrescent shapes persists into the nightside. The flowsemerging from the polar cap in the vicinity of midnightskew toward the dusk (dawn) side for By+ (By�). Takingthe crossover of the 70 deg latitude contour with themidnight meridian as a reference point, we see that withincreasing magnitude of azimuthal IMF the crescent-



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shaped cell extends further across the midnight sector. Weconclude that the sign of IMF By has an impact on theaverage flows on the nightside that is almost as pro-nounced and systematic as that on the dayside. This setof patterns defines the RG05 convection model andreplaces the RG96 model. A primary application of theHF-radar based models is to provide realistic backgroundvelocity data to support the reduction of radar measure-ments to instantaneous maps of the convection pattern, as

described by Ruohoniemi and Baker [1998] and Shepherdand Ruohoniemi [2000].

5. Convection Dependencies

5.1. Seasonal Dependencies

[19] With the much larger data set of the RG05 model, wecan explore the impact of sortings beyond those associatedwith the IMF. One factor that has been cited is season. The



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first report of a seasonal dependence in the convection wasdue to de la Beaujardiere et al. [1991], who summed ionvelocity data obtained with the Sondrestrom incoherentscatter radar and reported a larger potential drop in winterthan in summer. The statistics of that study were insufficientto support simultaneous sortings by IMF and season,however. Subsequent satellite studies refined the descriptionof the seasonal/dipole tilt factor [Rich and Hairston, 1994;Weimer, 1995] and an effect second-order compared withthat of IMF was described. A limited radar study byRuohoniemi and Greenwald [1995] reported a seasonaleffect in the nightside convection that somewhat mimickedthe effect of By sign, with more extreme sculpting of thedusk and dawn cells for the combinations of By+/summerand By�/winter. Milan et al. [2001] described a seasonalfactor in the By dependence of the dayside convectionvelocities observations with the SuperDARN radar atHankasalmi.[20] For the analysis described here, we initially selected

intervals of 90-day length for the winter, spring, and autumnseasons. Since little difference was found between theresults obtained for spring and autumn, we combined thesedata sets into one equinoctial ‘‘season’’ of length 180 days.The rate of backscattering is significantly lower in summercompared to the other seasons [Ruohoniemi and Greenwald,

1997], likely owing to the dampening effect of increased HFabsorption in the D and lower E regions of the ionosphere.To compensate, we set the interval for capture of summerdata to 150 days. Consequently, we can expect the resolvedpatterns to somewhat underestimate the seasonal effect forsummer.[21] Figure 8 shows the set of patterns found for By+

conditions and IMF magnitude in the 3–5 nT range. Recallthat for this IMF orientation the dawn cell is more crescent-shaped and the dusk cell is more round. The most strikingcontrast with the mean pattern described by the RG05model (also shown) is found with the summer pattern. Here,the dusk cell is distinctly more round and the dawn cell ismore elongated, the skew of the flow across the midnightmeridian is greater, and the flows associated with theelongated dawn cell extend further across the midnightmeridian. The tendency of the summer season to reinforcethe effect of By+ in the convection of the midnight sectorwas first described by Ruohoniemi and Greenwald [1995].On the dayside the convection streamlines are also moreseverely sculpted into round and crescent shapes, indicatingthat the By/season effect is global. The potential drop, FPC =33 kV, associated with the ‘‘reinforcing’’ combination ofBy+/summer is low relative to the other combinations ofBy+ with season.

Figure 8. Statistical convection patterns sorted by season for predominantly IMF By+ conditions in the3–5 nT interval of IMF magnitude. The corresponding RG05 pattern, which combines all seasons, is alsoshown.


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[22] Figure 9 shows the same progression with seasonfor By� conditions and IMF in the 5–10 nT range ofmagnitude. For this sign of By the dusk cell becomes moreelongated with clear definition of a convection reversalboundary that extends from noon through dusk to themidnight sector. With advance of season from winter tosummer, there is greater variation in the pattern than wasseen in the case of By+ conditions. The most obviousdevelopment is the intensification of the dawn cell thatreverses the usual dominance of the dusk cell over thedawn cell in terms of area and potential variation. Thesummer pattern also shows a pronounced rotation ofthe line joining the cell centers to earlier MLTs, so muchso that it more closely resembles the RG05 By+ patterns inthis respect.[23] In a manner analogous to the situation for By+/

summer, the combination of By� with winter shows en-hanced By� character in the nightside convection. Theflows across the midnight meridian are then the mostskewed and the crescent cell extends furthest across themidnight sector. In addition, the potential drop is suppressedrelative to that of the associated RG05 pattern (35 kV versus39 kV). Thus we find that the combinations of By+/summerand By�/winter, for which By� sign and season are rein-forcing in terms of their sculpting effects on the convection,are associated with reduced values of FPC.

[24] Another surprising result is the elevated potentialdrop recorded for the nonreinforcing combination of By�and summer, i.e., 47 kV versus 39 kV. The impact ofthe pairings of By and season on FPC can be reviewedwith the aid of Table 2. The reinforcing combinations ofBy+/summer and By�/winter result in lowered values ofFPC for all three IMF magnitude intervals. The nonrein-forcing combination of By+/winter leads to values of FPC

that are basically equal to those of the associated RG05patterns and higher than those of the reinforcing combi-nations. The nonreinforcing combination of By�/summerresults in markedly larger FPC. For an IMF in the 5–10 nTinterval the potential drop for By� in summer is 47 kVversus 35 kV in winter. For By� conditions the changefrom winter to summer is sufficient to boost FPC over itsaverage value by as much as the increase incurred instepping up by one interval in IMF magnitude.[25] Table 2 also shows the results for seasonal pairings

with Bz� and Bz+. These indicate that FPC is generallyelevated in summer. We can thus identify the followingtendencies in the convection: (1) higher FPC for the non-reinforcing By/season combinations and (2) higher FPC insummer.[26] The highest values of FPC occur for By�/summer, for

which the two tendencies act in the same sense. The impactof the By/season factor appears to be as large or larger than

Figure 9. Statistical convection patterns sorted by season for predominantly IMF By� conditions in the5–10 nT interval of IMF magnitude.


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that of season alone, as the By+/winter and By+/summerpairings lead to values of FPC that are equal to and lowerthan those of the associated RG05 patterns, respectively,despite the countervailing effect of season. The minimumvalues of FPC are obtained when the suppressive factor ofreinforcing By/season combines with that of season alone,i.e., By�/winter.[27] We consider the origin in the convection pattern of

the By/season factor. As noted for By� conditions (e.g.,Figure 9), with advance of season from winter to summerFPC increases and the convection pattern rotates to earlierMLTs (Figure 9). In terms of potential variation, thepattern progresses from domination by the dusk cell todomination by the dawn cell. A closer examination revealsthat most of the change occurs in the dawn cell where boththe area covered and the magnitude of the flow velocities(implied by the density of the potential contours) increasesignificantly. For By+ conditions (e.g., Figure 8), therelationship between the cells is much less sensitive tochange of season and the flow velocities do not varydramatically. Thus the seasonal effect in the convectionthat is linked to the sign of By is larger for By� conditionsand its source lies mainly on the dawn side. The impact ofthe By/season factor on the convection is comparable tothat of the variations in IMF magnitude and directionfound in the discrete sampling of the RG05 and otherstatistical convection models.

5.2. Yearly Dependence

[28] We consider the possibility that the high-latitudeconvection exhibits year-to-year variations. It is known thationization densities in the ionosphere fluctuate widely withvariation in the 10.7 cm solar radio flux and that thisfactor has a strong dependence on the 11-year solar cycle.Ruohoniemi and Greenwald [1997] attributed a significantyearly variation seen in the backscattering occurrencestatistics of the RG96 database to the impact of solarcycle factors. The variability in the ionosphere that arisesfrom solar cycle factors could impart a secular variation tothe convection pattern. Given the length of the solar cycleit seems appropriate to search for evidence of such avariation on a yearly basis. We note that the RG05 databaseencompasses 2 years of increasing solar activity (1998–1999), 2 years of peak activity (2000–2001), and 1 year ofdeclining activity (2002).[29] Figure 10 shows the results obtained for By+ in the

3–5 nT range of IMF magnitude for each calendar year. Thepattern for the RG05 model (obtained by summing and

averaging over all the years) is shown for comparison. Theimmediate impression is that the pattern is remarkably thesame from year to year. This stability can be contrasted withthe acute sensitivity of the pattern to IMF and seasonalfactors that we have already discussed. An analysis (notshown) of the location of the convection reversal boundariesin the two cells reveals essentially no differences. The valueof FPC varies by only 2 kV (35–37 kV), which, in light ofrounding off to obtain integer values, cannot be consideredsignificant. The constancy of the pattern seen in Figure 10 istypical of the results for all 24 sets of IMF sortingconditions. As something of a contrary example, we showin Figure 11 the yearly variation for By� in the 5–10 nTrange of IMF magnitude. Here, the value of FPC varies over7 kV (36–43 kV). A close inspection reveals that the sizeand configuration of the pattern change little from year toyear. The variable part of the potential is due mostly tofluctuating magnitude of the dawn cell but represents in anycase less than a 10% variation about the RG05 value of39 kV. There is no sensible trend in the variation of FPC

with phase of the solar cycle. The slight year-to-yeardifferences are likely due to fluctuations in the occurrencestatistics within the IMF sorting intervals. We thus concludethat through the 5 years that bound the peak of the solarcycle, the dependence of the mean convection pattern onyear or phase of the solar cycle is minor compared to thoseof the IMF and season.

5.3. Radar/UT Dependence

[30] Finally, we consider the possibility that the resultsfor a statistical convection pattern derived from individualradar data sets might vary. This could arise from a UTdependence in the coupling of electric fields between themagnetosphere and ionosphere. Because of the offset ofthe geomagnetic pole from the rotational axis, observa-tions carried out over the course of a day at a fixedposition in (MLT, L) coordinates will be associated with arange of geographic latitudes and hence with differentconditions of solar illumination and ionospheric conduc-tivity. The offset between geographic and geomagneticlatitude varies from 0 deg in the Kodiak sector, through�10 deg in the Kapuskasing sector, to +4 deg in theHankasalmi sector while all three radars are sited at nearlythe same geomagnetic latitude (59 ± 2 deg). The cusp,which is located at a mean latitude of 78 deg L [Newelland Meng, 1992], will be observed at geographic latitudesthat range from 68 deg to 82 deg over the course of a day.We search for a UT dependence in the convection byexamining the patterns derived from the data sets of theindividual radars.[31] Factors peculiar to individual radars might also

cause differences. One such known factor is variation inthe latitudinal coverage provided by the radars. TheIceland radars in particular are located at relatively highgeomagnetic latitude (�65 deg L) and are oriented morezonally than the others. Consequently, the observationswith these radars do not extend to the equatorward limitof the convection zone under conditions of even moderateexpansion and also do not extend to the pole.(The effective poleward limits of coverage are 85 degfor Stokkseyri and 80 deg for Pykkvibaer.) These limi-tations can be expected to adversely impact the results for

Table 2. FPC for Secondary Sorting by Season Versus FPC for

IMF Sorting Only (RG05) in kV

IMF/Season

IMF Magnitude in the GSM Y-Z Plane

0–3 nT 3–5 nT 5–10 nT

By+/winter 29 (30) 35 (36) 43 (43)By+/summer 29 (30) 33 (36) 41 (43)By�/winter 23 (27) 28 (32) 35 (39)By�/summer 32 (27) 40 (32) 47 (39)Bz�/winter 39 (38) 52 (52) 60 (63)Bz�/summer 43 (38) 57 (52) 67 (63)Bz+/winter 13 (16) 14 (15) 13 (14)Bz+/summer 18 (16) 17 (15) 16 (14)


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the global pattern determined from these radars.In addition, the data set of the westernmost radar at KingSalmon (operational only since 2001) is insufficient tosupport a radar-specific derivation of IMF-sorted convec-tion patterns.[32] Figure 12 shows the convection patterns derived on

the basis of the individual radar data sets for the case of By+in the 3–5 nT range of IMF magnitude. The RG05 pattern(obtained by averaging over all the data sets) is also shown.(As expected, the patterns obtained from the data sets of theIceland radars were less well constrained and their estimates

for FPC correspondingly unreliable. For these radars onlypartial maps of the distribution of equipotential contours areshown.) Overall, there is little evidence of a significant radarfactor in the convection pattern. Any systematic trend withUT might be expected to peak for the Kapuskasing radarwhich observes the convection over the lowest range ofgeographic latitudes yet this pattern is essentially the sameas those for the Kodiak and Hankasalmi radars. There isessentially no variation in the value of FPC. Some slightvariation in the positions of the cell centers can be perceivedbut these locations are not sharply defined by the potential

Figure 10. Statistical convection patterns sorted by year for predominantly IMF By+ in the 3–5 nTinterval of IMF magnitude.


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gradients along the convection reversal boundaries. Ofgreater significance is the fact that the locations of theCRBs themselves are very nearly the same from radar toradar. Examining the situation across the three intervals ofIMF magnitude, we conclude that for predominantly By+conditions there is no obvious radar (or UT) dependence inthe convection pattern.[33] The situation for By� in the same interval of IMF

magnitude is shown in Figure 13. The configurations of theradar-specific patterns are again all broadly similar to that of

the RG05 pattern. However, some surprising differencesemerge between the western and eastern radars. The valuesof FPC obtained from the Goose Bay and Hankasalmi datasets are relatively low, 32 and 27 kV respectively, comparedwith the 34–36 kV range of the three western radars. Interms of potential variation the dusk cell dominates thepattern for the central (Kapuskasing) and eastern radarswhile the dawn cell equals or exceeds the dusk cell for thewestern radars. Variability in the dawn sector makes thelarger contribution to the variation. The value of FPC

Figure 11. Statistical convection patterns sorted by radar for predominantly IMF By� in the 5–10 nTinterval of IMF magnitude.


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obtained for the mean (RG05) statistical pattern, 32 kV, isnotably low compared with the results for the radar-specificsolutions, with only one radar (Hankasalmi) recording alower value. This suggests some measure of inconsistentbehavior in the contributing data sets.

[34] Rather than show another set of figures we commentbriefly on the radar dependence of the patterns for Bz+ andBz� conditions. The results for the Bz+ pattern areremarkably the same for all six radars that are capableof generating a global map. As shown in Figures 5–7, the

Figure 12. Statistical convection patterns sorted by radar for predominantly IMF By+ in the 3–5 nTinterval of IMF magnitude.


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convection is weakly two-cell for small Bz+ but developsmulticell character with the emergence of sunward flow onthe noon meridian with increasing IMF magnitude. Thevalue of FPC for northward IMF averages 15 kV andvaries over a limited range (12–17 kV). For Bz� con-

ditions, there is again very good consistency between thepatterns derived for the specific radars. As the IMFmagnitude increases, the convection pattern expands be-yond the field of view of the radars and greater uncertain-ties are incurred in the mapping results but there are still

Figure 13. Statistical convection patterns sorted by radar for predominantly IMF By� in the 3–5 nTinterval of IMF magnitude.


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no obvious radar dependencies. We find, however, thatthe RG05 estimates of FPC for Bz� consistently under-estimate the values obtained from the individual radars.For the three intervals of IMF magnitude considered weobtain 38 kV versus 38–43 kV, 52 kV versus 56–60 kV,and 62 kV versus 63–74 kV. We conclude that a pro-nounced radar dependence is not found for predominantlynorthward or southward IMF but there are some incompat-ibilities in the data sets for Bz�.[35] We return to consideration of the singular case of

By�. Figure 14 shows the progression in the convectionpattern upon increase in IMF magnitude for the Kodiak andHankasalmi radars. These radars lie at the furthest ends ofthe SuperDARN radar chain and their patterns express thedifferences between the results from the eastern and westernportions most clearly. As expected, with increase in IMFmagnitude the value of FPC increases. For Hankasalmi,the dusk cell is always dominant and the increase in FPC isshared roughly proportionately between the two cells. ForKodiak, the cells are almost equal for small IMF but thedawn cell intensifies more dramatically and dominates in

the 5–10 nT interval of IMF magnitude. The greatestdifference between the patterns is the asymmetry in thedevelopment of the dawn cell. The increase in FPC withchange of radar from Hankasalmi to Kodiak is as largeas the increase incurred for a step of one in IMFmagnitude interval. The radar dependence of the By�convection is thus as pronounced as the classical IMFdependencies.[36] It is interesting that the differences between the

radar-specific patterns of Figure 14 resemble the differencesbetween the winter and summer patterns of Figure 9.Specifically, the Kodiak pattern shows more of the characterof the By�/summer pattern and the Hankasalmi patternmore By�/winter character. This raises the possibilitythat the variation with radar is attributable to seasonalfactors, or vice versa, due to bias in the backscatteroccurrence statistics. To check on this, we have also derivedpatterns for the individual radars with a simultaneoussorting by season. The statistics are considerably reducedfrom those associated with the previous patterns and we donot complicate this presentation with the plots. For the

Figure 14. Progression of the statistical convection patterns derived for the Kodiak and Hankasalmiradars with increase in IMF magnitude for predominantly IMF By�.


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winter and equinoctial seasons the coverage suffices toconfirm that the trends seen in Figure 13 and 14 are alsoseen within the seasonally sorted data. The radar factor isthus independent of the seasonal effect and comparable to itin magnitude.[37] Summing over these results, we find very little

variation among the patterns derived for individual radarsfor By+ conditions. However, there are pronounced differ-

ences among the By� patterns. These show a degree oforganization by the UT factor in that the patterns derivedfrom the radars located to the east and west of the centralradar at Kapuskasing show common behavior. For Bz+ weobtain very similar results for all the radars while for Bz�there are somewhat greater uncertainties but also overallsimilarity. Indirectly, we sense a greater amount of variationin the results for Bz� in that these patterns of the RG05

Figure 15. Statistical convection patterns of Ruohoniemi and Greenwald [1996] sorted by IMF clockangle in the GSM Y-Z plane in the 4–6 nT interval if IMF magnitude.


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model, which have been averaged over all the radar datasets, underestimate the values of FPC obtained from theindividual radar data sets.

6. Discussion

[38] The RG05 convection model can be compared withnumerous other models. First we make a detailed compar-ison with its antecedent, the RG96 model.[39] The earlier model was derived for a similar run of

years centered on solar cycle maximum (1987–1993). Forease of comparison, we reproduce in Figure 15 the set ofRG96 patterns for the 4–6 nT range of IMF magnitude.As noted earlier, the intervals of IMF magnitude chosenfor the RG96 model, 0–4, 4–6, and 6–12 nT, differ fromthose adapted in the derivation of the new model. Sincethe occurrence of IMF magnitude falls off steeply beyondabout 4 nT, the more appropriate comparison for RG96 inthe 4–6 nT magnitude interval is the RG05 model in the5–10 nT interval, i.e., Figure 15 with Figure 7. Overall,the patterns are quite similar. In the RG05 model theglobal shaping of the cells according to the sign of By ismore pronounced and the dayside flows for Bz+ are moreconvoluted. This apparent improvement reflects a largernumber of measurements and an increase in the order ofthe fitting from L = 6 to L = 8. The equipotential contoursof the RG05 model show more curvature at higherlatitudes. Because the earlier data set was incompleteabove 85 L, a simple interpolation scheme was adoptedto extend the mapping across the high polar cap; theimproved coverage in the RG05 data set makes possiblea more accurate depiction of these flows. There is anoverall impression of greater consistency in the progres-sion of cell size, shape, and orientation with IMF variationin the RG05 model. For example, the line joining the cellcenters rotates more systematically in a counterclockwisesense as the IMF rotates from northward through +Y tosouthward to �Y. The imposition of the Heppner-Maynardboundary condition on the fitting has kept the RG05equipotentials from meandering unrealistically to subauro-ral latitudes on the dayside and suppressed the emergenceof weak, extraneous cells there.[40] There is a difference in the magnitude of the cross

polar cap potential drop, or FPC. Generally, FPC is smallerin the RG05 model. This is seen in the comparison ofFigures 7 and 15 despite the higher interval of IMFmagnitude associated with the RG05 patterns. The reasonsfor systematically lower potential values are not clear,although minor differences in the reduction and processingof the two data sets may be a factor. We have also seen thatinconsistencies between the radar data sets can suppressFPC upon averaging. Allowing for this discrepancy, weobserve very similar behavior in the two models, withgenerally greater FPC for By+ than for By� and morepotential variation across the dusk cell than the dawn cell.[41] Comparable statistical models have been based on

analysis of satellite data, e.g. Rich and Hairston [1994] andWeimer [1995], and magnetometers, e.g., Papitashvili et al.[1994] and Ridley et al. [2000]. Several of these have beenupgraded into parameterized models that specify the con-vection pattern as a continuous function of solar windvariables, e.g., Weimer et al. [1996] and Papitashvili and

Rich [2002]. These last authors also carried out a detailedcomparison of the IMF and seasonal dependencies of FPC

reported in the current models. They concluded that themodels are in good agreement in terms of the overalldependence on IMF magnitude and direction. The RG05model somewhat improves upon the RG96 model in depict-ing the details of the convection pattern but is essentiallyconsistent with this and the other models. The similaritiesare especially striking between the radar models and theearlier satellite-derived models.[42] As discussed in the introduction, the value of the

statistical models for prescribing the instantaneous pattern isdegraded by the pronounced variability of the convectionphenomenon. The averaged velocities do not show the fullrange of velocity magnitudes that are encountered in obser-vations. The good agreement among the statistical modelsshows that there is nevertheless a background convectionpattern for each IMF state that is reliably reproducedacross a range of instrumental and analysis techniques.The instantaneous convection can then be interpreted interms of the addition of transient convection features to apersistent global pattern of plasma circulation.[43] There remains some disagreement regarding the

magnitude of the convection as gauged by the value ofFPC. RG96 produced somewhat lower values of potentialdrop than the satellite models of the same vintage and theRG05 model clearly does not close this discrepancy. Thereis better agreement with the new satellite-derived DICMmodel of Papitashvili and Rich [2002]. Given the high levelof consistency between the models in terms of the mor-phology of the pattern, it is perhaps surprising that asubstantial variation in FPC is reported. As an example,for By+ and an IMF magnitude of about 5 nT, FPC rangesfrom 40 kV (DICM, RG05) to about 60 kV (e.g., Weimer[1995]). The spread in results for FPC decreases for Bz+ andincreases for Bz�.[44] We have found a rather complicated dependence of

the convection pattern on season. It has been usual todescribe a general increase or decrease in FPC with pro-gression from winter to summer. We find it necessary to linkseason with the sign of IMF By to fully characterize thedependence. Stated simply, the combinations of By+/sum-mer and By�/winter produce the most extreme configura-tions in terms of the round/crescent cell dichotomy and theshifting of the crescent cell across the midnight MLTmeridian. The modulation of the convection on the night-side was first described by Ruohoniemi and Baker [1995]on the basis of very limited radar data. Here we see itconfirmed on global scales and related to other dependen-cies. The nonreinforcing combinations of By�/summer andBy+/winter lead to elevated values of FPC. We find anoverall tendency for FPC to be larger in summer but theeffect is not large enough to compensate for a contrarysetting in the By/season combination. Thus the seasonalfactor in isolation is of secondary importance to that of By/season.[45] The first to describe effects in high-latitude convec-

tion specific to certain combinations of IMF By and seasonwere apparently Friis-Christensen and Wilhjelm [1975].They examined the dependence of magnetic variations inthe polar cap. Vennerstrom and Friis-Christensen [1987]subsequently examined the dependencies of the polar cap


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index PC and found the response maximizes for By�/summer and By+/winter. The data used in both studies ofcourse incorporated the effects of dependencies in both theconvection electric field and ionospheric conductivity butthere is a telling coincidence with our findings of peak FPC

for these same combinations. These authors also called outthe variable condition of the westward electrojet, whichcorresponds to our finding of greater variability in the dawnconvection cell.[46] Our results on the impact of season on convection

can be compared more directly with those of the DICMmodel of Papitashvili and Rich [2002]. These authorsdescribed an overall decrease of 10–15% in FPC in passingfrom winter to summer, which is the opposite sense of theseasonal effect that we have described. However, theseasonal variation of FPC reported in the DICM study isalso conditioned by the orientation of the IMF and, in theBy� case, FPC is larger in summer. It is also noteworthythat the convection pattern in the DICM model variesmuch more between the seasons for By� than for By+. Weadd that, in terms of overall configuration, our seasonalpatterns for By+ are rather similar to those of the DICMmodel but the patterns for By� differ significantly, espe-cially for By�/summer.[47] The model of Weimer [1996] includes a sorting by

dipole tilt angle that corresponds to season. The value ofFPC was found to increase from winter to summer for allorientations of the IMF. The sculpting effect of thereinforcing combinations of By/season on the shapes ofthe dawn and dusk cells is found in the Weimer [1996]patterns although it is less dramatic than in our results.Again, the variation of the pattern with season is greaterfor By�. The Weimer patterns show a peak value of FPC

for the nonreinforcing combination of By�/summer butnot for the By+/winter combination. The Weimer modelthus describes a seasonal effect on FPC that is strongerthan that of the combination of By� sign/season.[48] Milan et al. [2001] analyzed line-of-sight velocity

data collected with the Hankasalmi HF radar for evidence ofa seasonal factor in the By dependence of dayside convec-tion flows. They found a strong asymmetry between theconvection response in summer and winter. In summer thevelocities measured in the prenoon sector were stronglymodulated by the sign of By, but not in winter, and less so inthe postnoon sector. As the analysis was limited to the line-of-sight component of the convection velocity, it is notpossible to easily characterize this result in terms ofbehavior the large-scale convection pattern but it is consis-tent with our finding of greater variability in the convectionof the dawn cell. An inspection of the patterns of Figures 8and 9 suggests that the dayside flows do vary moredramatically with a change in the sign of By in summerthan in winter. We note that our results for specific radarsshowed that the convection observed from Hankaslamidiffers significantly from that seen with other radars forBy� conditions; this might affect the generality of thefindings obtained with this radar.[49] Crooker and Rich [1993] considered the origin of the

seasonal factor in the By dependence of the convectionreported by Rich and Hairston [1994]. The observations hadindicated that the dusk cell dominates the pattern, more sofor By+, and still more for summer conditions. This was

interpreted in terms of the impact of the quasi-permanentday-night conductivity gradient, the merging geometry onthe dayside magnetopause, and the addition in summer oflobe cell convection to the dusk cell for By+. For By� thecomplementary addition of lobe cell convection to the dawncell in summer was cited as the reason for the reduceddominance of the dusk cell. In our study we have found thatindeed the dawn cell dominates the pattern for By� insummer. The corresponding total potential variation, FPC,is much larger than in winter. Our results are more consis-tent than those of Rich and Hairston [1994] with thepredictions of Crooker and Rich [1993], in that the additionof lobe cell convection should cause an intensification of thedawn cell for By� in summer and an increase in FPC (Richand Hairston [1994] obtained a decrease). However, theequivalent development with respect to By+ is not apparentin our results. In fact, the dusk cell is somewhat weaker insummer than in winter and FPC is reduced. The samediscrepancy was noted by Crooker and Rich [1993] in theresults of Rich and Hairston [1994], although the dusk cellbecame more dominant as the result of an unexplaineddiminution in the dawn cell. We speculate that the lobe cellmechanism is more effective in enhancing convection forBy� conditions in the northern hemisphere. This may be thesource of the greater variability in the dawn sector reportedhere and in other studies.[50] Although not presented here, we have also consid-

ered the seasonally sorted patterns for the slant IMF con-ditions of Bz+/By+ and Bz+/By�. As expected, these show amore pronounced development of possible lobe cell con-vection in summer than the pure By+ and By� cases and thecorresponding cell (dusk or dawn) is enhanced over winterfor the positive as well as the negative sign of By. However,the intensification of the dawn cell for negative sign of By

remains much more dramatic.[51] An asymmetric occurrence of lobe cell convection

will give rise to hemispheric differences in the cross polarcap potential drop. Such differences are implied by ourresults, most dramatically for combinations of By andseason, as expected, but also for season alone. Indeed, forpredominantly Bz� conditions, the potential drop in sum-mer exceeds that in winter by about 10% (Table 2). Thecontribution to the potential drop from merging processesthat open and close field lines must be the same for bothhemispheres. If the southern hemisphere experiences thesame seasonal variation in total potential drop for Bz�conditions, the resulting hemispheric asymmetry must havea source in continued lobe cell circulation or in a seasonaleffect in the viscous interaction along the magnetosphericflanks. Crooker et al. [1998] have argued that lobe cells area consequence of merging site asymmetries. As these are ageneral feature of solar wind–magnetosphere coupling,they might occur in combination with merging cells evenfor a negative sign of Bz. Examination of the seasonalfactors will be eventually be aided by comparison of thesenorthern results with those obtained in the southern hemi-sphere with the Antarctic suite of SuperDARN radars.[52] Newell et al. [1996] showed that ionospheric con-

ditions related to variable solar illumination affects theprecipitation of auroral particles. Subsequent studies haveexamined the roles of season and solar cycle factors onauroral particles and field-aligned currents, e.g., Morooka


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and Mukai [2003]. Although the circumstances of thecoupling of the solar wind and the magnetosphere haveprimary importance, it is becoming increasingly clear thatvariability in the ionosphere also impacts the system ofelectric fields, particle acceleration, and currents.[53] Tanaka [2001] utilized a numerical MHD simulation

to examine the interplay of IMF and ionospheric conduc-tivity on convection. He found that when the conductivity istaken to be uniform, there is mirror symmetry in the patternswith respect to By. A realistic ionospheric conductivitymodifies the pattern such that in the northern hemisphere,the distinctive features of the By+ pattern are enhanced.Furthermore, the flows at auroral latitudes in the midnightsector become more dominated by the crescent cell. Tanaka[2001] did not explicitly consider seasonal variations inconductivity but his results show that the IMF By factorshould strongly influence convection on the nightside.Although Tanaka [2001] was apparently unaware of thefindings of Ruohoniemi and Baker [1995], he reported invery similar terms that the impact of By on the convectionwas ‘‘accentuated’’ (reinforced) by the introduction of arealistic ionospheric conductivity. This suggests that theexplanation of the seasonal factor in our observations isrelated to ionospheric conductivity. To the findings ofRuohoniemi and Baker [1995] we add that the reinforcingcombinations of By and season are associated with lowervalues of FPC while the nonreinforcing combination ofBy�/summer produces an anomalously high FPC. Thelarger part of the seasonal variation for By� conditionswas due to variability in the flows of the dawn convectioncell. Tanaka [2001] argued that the ionospheric convectionpattern should be considered the synthesized effect ofmagnetospheric and ionospheric factors. Specifically, theprojection of the plasma convection from the magneto-sphere needs to be balanced with the requirement offield-aligned current closure in the ionosphere. The By

asymmetry in the nightside convection in particular isattributed to the condition of closure of ionospheric Hallcurrent. We propose that one more test in the applicationof the numerical simulation will be to reproduce theseasonal dependencies.[54] Noda et al. [2003] recently described the average By

dependence of convection in the near-Earth tail lobe usingmeasurements from the Cluster/EDI instrument. They foundthat the sense of velocity shear in the Y-Z plane reverseswith a change in the sign of By in a manner consistent withthe results of Ruohoniemi and Greenwald [1995]. Thus theimpact of IMF orientation on nightside convection that wehave more fully characterized with the RG05 database issubstantiated by both MHD simulation and direct satelliteobservation. Our findings further show the presence of acomparable seasonal factor in the convection. Although wefind a tendency for the potential to be larger in summer, themore significant, and surprising, seasonal impact dependson the IMF, especially the sign of By. Consideration of therole of ionospheric conductivity, possibly modulated bytransport processes, may provide the key to understandingthese dependencies.[55] We note in passing that the patterns of Figure 8 show

evidence of the impact of ionospheric conductivity onthe convection pattern. As discussed by Atkinson andHutchinson [1978], the conductivity gradient that is asso-

ciated with the day-night terminator results in a deflectionof the antisunward flow of the polar cap toward theduskside. For By+ conditions the effect is to enhance theshaping of the dusk and dawn cells [Crooker and Rich,1993]. With progression of season from winter to summer,Figure 8 shows that the turning of the antisunward flow todistinctly duskward shifts across the polar cap in a mannerconsistent with the movement of the terminator, suggestingthat this significant feature of the convection is controlledby the ionosphere.[56] We have determined that the average convection

pattern showed very little variation from year to year inthe period 1998–2002. The stability of the patterns isremarkable, considering that the IMF and seasonal depen-dencies are so pronounced that even a small amount ofskewing within the yearly statistics for a given IMF condi-tion would be enough to produce significant differenceswith the mean pattern. The implication is that variability inthe ionosphere related to solar cycle does not have a majorimpact on the average global convection. Strictly speaking,we have demonstrated this result for the half of the solarcycle centered on solar cycle maximum and there is thepossibility of effects on less than global scales.[57] We have derived and compared statistical convection

patterns for the individual radars. Our expectation was thatthe varying offset of geomagnetic and geographic latitudeacross the radar chain might give rise to a systematic UTdependence. Because of their more limited latitudinal cov-erage, the Icelandic radars (Stokkseyri and Pykkvibaer)were less useful for this study. Overall, the statisticalpatterns derived for the other radars were similar. Thisresult is somewhat reassuring in that it demonstrates theessential equivalence of the radars for mapping convection.The case of By� turned out to be exceptional, as adependence could be made out in the variation of FPC,namely, higher/lower values to the west/east of the centralradar at Kapuskasing. The difference could be traced largelyto the condition of the dawn cell, which has a greaterpresence in the observations of the western radars whereit intensifies very rapidly upon increase in IMF magnitude.There is a dramatic contrast between the results for By+,where no radar dependence can be discerned, and By�, forwhich the radar dependence is as pronounced as those of theclassical IMF dependencies.[58] Why should a UT dependence emerge for By� but

not for the other orientations of the IMF? More generally,why are the results for By� convection more variable withchange of season or radar? If one were to appeal to theconductivity factor to explain this surprising aspect of the By

dependence, the relation of the convection geometry toionospheric conductivity gradients may be the key. Thedistinctive transformation of the convection pattern thatoccurs upon rotation of the IMF from By+ to By� consistsof (1) enlargement of the dawn cell relative to the dusk cell,(2) reversal in the shaping of the dawn/dusk cells fromcrescent/round to round/crescent, (3) rotation of the overallpattern to later MLTs, and (4) displacement of the patternduskward along the dawn-dusk meridian. We have observedthat the flows in the dawn sector appear to be more variablethan those in the dusk sector. Detailed consideration of theinterplay of realistic ionospheric conductivities and theconvection is beyond the scope of this paper. However, it


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is interesting to note that for By+ the dawn cell is stronglycrescent shaped and displaced to distinctly lower latitudes;the center of the cell lies at least 5 deg lower in latitude forBy+ than for By�. Hence for this sign of azimuthal IMF thedawn cell is strongly constrained by the circumstances ofsolar wind–magnetosphere coupling which in this casefavors reconnection on the duskside. For By� the geometryof the dawn cell is less constrained by the coupling factorsand so conductivity variations may play a larger role. Forthis sign of By reconnection in the northern hemisphere isfavored on the dawnside and at MLTs that are closer to thedawn-dusk line, and hence the conductivity gradient that isassociated with the terminator, than is the case for By+. Thiscould provide a basis for conductivity factors to impact theconvection more for By� conditions. We found the sharpestcontrast in the statistical patterns between summer andwinter for By�. Across the radar chain the variation in theoffset of geographic and geomagnetic latitude alters therelationship of the ionospheric conductivity to the convec-tion pattern over the course of a day but the impact issimilarly limited to conditions of By�.[59] Our results have been obtained from observations

carried out exclusively in the northern hemisphere. Theseasonal variations in particular imply the existence ofsignificant hemispheric asymmetries. An extensive databaseof measurements that is being accumulated by SuperDARNradars in the southern hemisphere will eventually provide abasis for examining conjugacy and help to resolve theimpact of ionospheric factors on convection.

7. Summary

[60] Using the entire data set of velocity measurementscollected with the northern SuperDARN radars over theyears 1998–2002, we have derived a new statistical modelof convection in the high-latitude ionosphere. The modelreplaces that derived by Ruohoniemi and Greenwald [1996]on the basis of data from the Goose Bay radar alone. Theclassic dependencies of the global convection on the mag-nitude and direction of the IMF in the GSM Y-Z plane arereproduced. We have also tabulated the size of the convec-tion zone as a function of IMF settings used in the model.[61] The database of the new model was then analyzed for

information on the other dependencies of the convection.We extended to global scales the finding of Ruohoniemi andGreenwald [1995] that the seasonal effect is similar to thatof the sign of By. In summer, the convection associated withBy+ is composed of more severely shaped round andcrescent cells in the dusk and dawn sectors, respectively,and the dawn cell protrudes further across the midnightmeridian. In winter, the complementary situation for By� isrealized, with more severe shaping of the of the crescentdusk cell and round dawn cell and a displacement of thedusk cell across the midnight meridian. These combinationsof By sign and season ‘‘reinforce’’ the tendencies of the signof By in terms of shaping the global pattern. The reinforcingcombinations are, however, associated with lower values ofthe cross polar cap potential drop, FPC. The nonreinforcingcombinations of By sign and season lead to patterns that areintermediate in their morphology but have elevated valuesof FPC. Overall, there is an increase in FPC in going fromwinter to summer but the effect of season alone is smaller

than that of the By/season factor. Most of the variabilityassociated with the seasonal factor is found in the dawncell.[62] The database of the new model comprises 5 years for

which the level of solar activity rose, peaked, and fell. Weexamined the IMF-sorted convection patterns derived forthe individual years to search for a related secular variationbut found nothing that rose to the level of significance of theIMF and seasonal dependencies.[63] Finally, we considered the possibility of a depen-

dence on radar. Such a dependence could arise from thevariation in solar illumination and hence ionospheric con-ductivity across the convection pattern that accompanies theprogression in UT of the magnetic pole about the rotationalaxis. For the six radars with sufficient coverage to map theglobal pattern, we found overall strong similarity in theresults. Specifically, for By+, Bz+, and Bz� conditions nosystematic dependence on UT could be discerned. However,differences were found for By�. These included lowervalues of FPC for the radars to the east of the central radarat Kapuskasing and a pronounced difference in the behaviorof the dawn cell.[64] We speculate that the seasonal and UT dependencies

of the convection are related to variable conductivity in theionosphere. Sensitivities to ionospheric conductivity havebeen reported in the processes that control auroral particleacceleration in the magnetosphere [Newell et al., 1996;Morooka and Mukai, 2003] and demonstrated in MHDmodeling of convection in the ionosphere [Tanaka, 2001].Our most surprising finding is that the impact of theseasonal and UT factors depends on the sign of By; theyare pronounced for By� but hardly apparent for By+. Thisstudy and many others have demonstrated that the couplingof magnetic fields at the magnetopause is the primary factorin setting the global convection pattern. The IMF alsoappears to modulate the secondary role played by iono-spheric conductivity.

Appendix A: Size of the Convection Zone Scaledby the Heppner-Maynard Boundary

[65] Table A1 lists the settings of the Heppner-Maynard(H-M) boundary as determined for the IMF conditionsconsidered in this study. As discussed in relation toFigures 2 and 3, for each selection of IMF magnitudeand direction in the GSM Y-Z plane the H-M boundary isadjusted until it encompasses the convection patterndetermined from the radar data. The shape of the H-Mboundary is fixed while its size is parameterized by the

Table A1. Reference Latitude of the Heppner-Maynard Boundary

in Degrees

IMF Direction

IMF Magnitude

0–3 nT 3–5 nT 5–10 nT

Bz+ 65 65 65Bz+/By+ 63 63 62By+ 62 60 58Bz�/By+ 61 59 56Bz� 60 58 54Bz�/By� 61 59 56By� 62 60 58Bz+/By� 63 63 62


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latitude at which the boundary crosses the midnight MLTmeridian [Shepherd and Ruohoniemi, 2000]. The step inlatitude for the fitting to data is 1 deg. Two aspects of theradar data are chiefly examined: (1) the location of theequatorward edge of the zone of significant backscattercounts and (2) the spatial extent of sizeable, well-organizedconvective velocities. These boundaries largely coincide andthe uncertainty in determining the location of the H-Mboundary is about 1 deg. For Bz� conditions the fittingcan only be performed on the dayside as the convection zoneon the nightside then extends equatorward of the edge of theSuperDARN field of view. In this situation the radars do notdirectly observe the entire convection pattern. The solutionfor the global distribution of electrostatic potential willprescribe flows in the subhorizon region that are requiredto accommodate the flows seen at higher latitudes. We findthat variation of a few degrees in the setting of the H-Mlatitude has little effect on the overall pattern or on thedetermination of FPC.[66] As expected, for strongly Bz+ conditions an increase

in the magnitude of the IMF has little effect on the size of theconvection zone. The size of the zone also does not dependappreciably on the sign of By. For a fixed IMF magnitude thepattern expands as the IMF vector rotates away fromnorthward and especially when the sign of Bz turns negative.For strongly Bz� conditions, the latitude of the H-Mboundary crossing on the midnight MLT meridian reachesas low as 54 deg and so a sizeable fraction of the returnflows associated with the two-cell pattern then lies equa-torward of the SuperDARN field of view.

[67] Acknowledgments. We gratefully acknowledge the support pro-vided by NSF grant ATM-9819891 and by NSA grants NAG5-8361 andNAG5-8037. Operation of the SuperDARN radars in the northern hemi-sphere is supported by the national funding agencies of the US, Canada,UK, France, and Japan.[68] Arthur Richmond thanks Stephen Milan and Takeshi Tanaka for

their assistance in evaluating this paper.

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��R. A. Greenwald and J. M. Ruohoniemi, Johns Hopkins University

Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, MD20723-6099, USA. ([email protected])


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