Intense dayside Joule heating during the 5 April 2010 geomagnetic storm recovery phase observed by AMIE and AMPERE

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1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 117,, doi: /2011ja017262, 2012 Intense dayside Joule heating during the 5 April 2010 geomagnetic storm recovery phase observed by AMIE and AMPERE F. D. Wilder, 1 G. Crowley, 1 B. J. Anderson, 2 and A. D. Richmond 3 Received 13 October 2011; revised 27 March 2012; accepted 27 March 2012; published 3 May [1] When the interplanetary magnetic field (IMF) is northward, dawnward, or duskward, magnetic merging between the IMF and the geomagnetic field occurs near the cusp of the magnetosphere. While these periods are usually considered quiet, they can lead to intense, but highly localized, energy deposition into the dayside ionosphere. We identify such an occurrence during a series of two geomagnetic storms on 5 April Using data from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) for the first time as an input to the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) algorithm, we show that during the recovery phase of the first storm there is intense ionospheric Joule heating in the dayside polar regions. This is associated with an intense field-aligned current pair near the noon meridian that is associated with northward IMF and a strong IMF By component. AMIE outputs are used to drive the thermosphere-ionosphere-mesosphere electrodynamics general circulation model to demonstrate that the intense levels of Joule heating can lead to anomalous thermospheric density enhancements and traveling disturbances. Citation: Wilder, F. D., G. Crowley, B. J. Anderson, and A. D. Richmond (2012), Intense dayside Joule heating during the 5 April 2010 geomagnetic storm recovery phase observed by AMIE and AMPERE, J. Geophys. Res., 117,, doi: /2011ja Introduction [2] Recent efforts to improve satellite drag prediction have identified several magnetic storm events with anomalous thermospheric density signatures. Most of these storms have prolonged periods with near-zero or northward interplanetary magnetic field (IMF) Bz and strong IMF By components. Under such IMF orientations, merging between geomagnetic field lines and the IMF is most likely to occur in the cusp region either on the nightside or the dawndusk flanks of the magnetosphere [Crooker, 1992; Tanaka, 1999]. This will have two effects on the magnetosphereionosphere system. First, strong field-aligned currents (FACs) will couple into the dayside ionosphere at high latitudes due to magnetic merging in the cusp regions. These FACs have been called NBZ for northward IMF and DPY for strong IMF By components [Friis-Christensen and Wilhjelm, 1975]. The NBZ currents are associated with high-latitude reverse convection cells typically observed 1 Atmospheric and Space Technology Research Associates, Boulder, Colorado, USA. 2 Johns Hopkins University Applied Physics Laboratory, Johns Hopkins University, Laurel, Maryland, USA. 3 National Center for Atmospheric Research, Boulder, Colorado, USA. Corresponding Author: F. D. Wilder, Atmospheric and Space Technology Research Associates, 5777 Central Ave., Ste. 221, Boulder, CO 80301, USA. (rwilder@astraspace.net) Copyright 2012 by the American Geophysical Union /12/2011JA under northward IMF [Crooker, 1992; Crowley et al., 1992; Wilder et al., 2010]. The DPY currents serve to stretch either the dawn or dusk convection cells across the dayside depending on the IMF By orientation [Weimer, 2001]. [3] Second, because the associated merging cycles will have little effect on magnetotail reconnection, they should not affect geomagnetic indices such as Kp or Dst. Therefore, the large amounts of dayside, high-latitude Joule heating associated with these events is considered anomalous. Crowley et al. [2010] identified such an event when the IMF By was strong, Bz was near zero, and the Challenging Minisatellite Payload (CHAMP) satellite saw an anomalous thermospheric density enhancement in the high-latitude dayside polar region. The DPY-FACs associated with the event led to intense Joule heating of the dayside ionosphere. When the measurement-driven Joule heating was ingested by the thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM), the model accurately reproduced for the first time the large cusp-region neutral density enhancements observed by CHAMP. The ability to accurately map the structure of dayside FACs and ionospheric Joule heating is therefore of utmost importance in order to understand and identify the individual sources of thermospheric density increases. [4] The present study identifies a new event where intense, localized Joule heating occurs in the dayside ionosphere. On 5 April 2010, there was a series of two consecutive geomagnetic storms where the Dst index dipped to 40, recovered, and then fell again to 50 later in the day. During the first recovery phase, the IMF Bz component turned strongly 1of14

2 northward and By became strongly negative. The event therefore provides another opportunity to observe intense Joule heating at high latitudes on the dayside of the ionosphere. Further, the 5 April 2010 storm was the first major storm where data from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) were available. [5] AMPERE performs a spherical harmonic fit on highrate engineering magnetometer data from the Iridium constellation of satellites, allowing detailed calculation of ionospheric FAC patterns at two minute cadence [Anderson et al., 2000; Waters et al., 2001]. This new specification of FACs is a major improvement over single-satellite measurements that needed to be bin averaged statistically to obtain an FAC distribution. AMPERE is also an improvement on the previous use of Iridium satellite magnetometers due to the higher time resolution of the AMPERE data. Previously, Iridium data had to be accumulated over more than an hour to obtain an FAC map. With AMPERE, the accumulation time is reduced to 10 min corresponding to the intersatellite spacing in each orbit plane. [6] In the present study, rather than simply using the AMPERE data to produce field-aligned currents, we assimilate the AMPERE data into the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) algorithm, along with other electrodynamics data sets. The use of AMIE has the advantage that in addition to computing FACs, we can also compute the Electric Potential and Joule heating patterns which can be obtained with and without the added AMPERE data set to identify the effect of AMPERE on the AMIE output. The resulting calculations show that without the ingestion of AMPERE data by AMIE, anomalous Joule heating during a period of northward IMF Bz and strongly negative IMF By is both underestimated and mislocated. The output of the AMIE run with AMPERE is then used to specify the high-latitude electrodynamics in the TIME-GCM. The results demonstrate that the Joule heating is strong enough to produce neutral upwelling and a localized dayside neutral density enhancement at 400 km. The model output also predicts that the upwelling of neutral gas launches an equatorward propagating large-scale gravity wave in the morning sector. This wave and the localized neutral density enhancement are not apparent in the runs without AMPERE. 2. Data Analysis and Models [7] Maps of the high-latitude ionospheric electrodynamic parameters used in this study were calculated using the AMIE procedure with multiple inputs, including magnetic perturbations from ground magnetometers and convection measurements from both radars and satellites. In addition, magnetic perturbations from AMPERE were ingested by AMIE to take advantage of the broad spatial coverage now available from the AMPERE mission. AMIE outputs that included data from AMPERE were then used as high-latitude specification for the TIME-GCM. Each of these tools will be described in more detail in the subsequent sections AMPERE [8] In the past, space based imaging of FAC distributions was performed statistically using multiple single-satellite measurements averaged over a long period of time [Iijima and Potemra, 1978; Weimer, 2001; Papitashvili et al., 2002]. While these studies allowed for statistical understanding of FACs under various seasonal and geomagnetic conditions, it was not feasible to produce real-time FAC maps due to the lack of near-simultaneous coverage of the polar cap by multiple satellites. To solve this problem, Anderson et al. [2000] used engineering magnetometer data from the Iridium satellite network to produce maps of magnetic perturbations due to FACs at approximately an hour cadence. [9] The advantage of using Iridium is that there are more than seventy satellites. At any given time, there will be six spacecraft crossing over the polar cap. Magnetic residuals from these polar passes can be fit to a spherical harmonic expansion to obtain a spatially uniform map of perturbations from which FAC maps can be derived [Waters et al., 2001]. These FAC maps have been used in a variety of case studies, as well as for statistical analysis [Anderson et al., 2005, 2008; Korth et al., 2005; Green et al., 2007; Eriksson et al., 2008]. [10] While these patterns provided a drastic improvement in the capability for measuring FACs, they were constrained by the temporal resolution of Iridium data. In the past, Iridium engineering magnetometers only stored data every 200 s. Because of this, data had to be accumulated over at least one hour to provide a coherent map of FACs, which in turn required assumptions about the stability of geomagnetic conditions. Starting in 2010, under the AMPERE project, Iridium magnetic perturbations were returned at a sampling period of 20 s, allowing for approximately one degree latitudinal resolution. Using these higherrate data, magnetic perturbations only need to be collected over 10 min, commensurate with the time spacing between Iridium satellites in each orbit plane, to obtain reliable FAC maps, greatly improving the temporal resolution of global FAC maps. These maps produced with 10 min data windows are calculated at a cadence of 2 min. The present study uses the fitted magnetic perturbations from data at this new higher data rate as an input to the AMIE procedure The AMIE Procedure [11] The AMIE procedure [Richmond and Kamide, 1988; Richmond, 1992] fits two-dimensional distributions of ionospheric conductances and electric potential over the polar region to a combination of background statistical models and a wide array of observations. Both direct and indirect observations can be used. Observations related to the auroral component of the conductances can include radar measurements of electron density as well as measurements of auroral energetic particle precipitation, auroral images, and estimates obtained from statistical correlations with geomagnetic perturbations [e.g., Ahn et al., 1983, 1998; Robinson et al., 1987; Lummerzheim et al., 1997]. The distributions of Pedersen and Hall conductances are used to link electric fields and currents through Ohm s law, neglecting any dynamo effect of thermospheric winds. Observations related to the electric potential can include ionospheric electric fields, ion drift velocities, and geomagnetic perturbations on the ground and in space associated with ionospheric currents and FACs. Although AMIE is based on optimal estimation theory, much of the statistical information needed to obtain an optimal fit, including measurement 2of14

3 errors of the data and their correlations, as well as model error covariances, is not independently available. Consequently, the weightings of the data and statistical models used in AMIE s fits have generally been chosen by trial and error, such that the results have physically realistic properties while also providing a reasonable fit to the data used. The results depend not only on the types, amounts and distributions of input data [e.g., Lu et al., 2001], but also on limitations of assumptions and approximations used in AMIE. Among these are the assumptions that the ionospheric conductance distribution has been well determined for relating electric fields and currents, that wind effects and nonlinear effects on the current/field relation are negligible, and that magnetic perturbations can be calculated from the currents by treating horizontal currents as flowing in a thin sheet at 110 km. Further assumptions include: treating FACs as radial, treating induced Earth currents as though they mirror the ionospheric equivalent currents at a depth of 250 km below the Earth s surface, and neglecting all magnetospheric currents other than the (radial) FACs. [12] For a given conductance distribution, the fitted electric potential is uniquely tied to the distributions of horizontal currents and vertical FACs, and the height-integrated Joule heating is given by the Pedersen conductance times the squared electric field. The greatest uncertainties in the AMIE results arise from limitations of the data distributions and large uncertainties in the estimated auroral contributions to the Pedersen and Hall conductances. In reality, the auroral conductances can be highly structured in space, but AMIE usually relies heavily on smooth statistical models. Since FACs are related to the divergence (and therefore spatial derivatives) of the ionospheric currents, errors in the spatial distribution of the conductances strongly affect the relation between FACs and the electric potential in AMIE. If the primary data used in AMIE are well-distributed measurements of electric fields and ion drifts, then the electric potential is relatively well estimated, but the currents can have much larger errors. On the other hand, if the primary data used are from dense coverage by satellite magnetometers like AMPERE, then the FACs are well estimated, but the electric potential and fields can have large errors. If the primary data are well-distributed ground magnetometers, then the ionospheric electrojet currents are relatively well estimated, but both the electric potential and the FACs can have large errors. A good distribution of different data types can help avoid large errors in any estimated parameter. [13] The selection of background models for AMIE is crucial to obtaining meaningful electrodynamics. For the present study, we ran AMIE using two different conductance models. First, we used a static low-activity conductance model to demonstrate the effects of different data sets on the calculated FACs and potentials. The choice of a static background conductance allows for changes in the pattern over time to be driven by the data as opposed to an assumed activity level. Second, we emulated Emery et al. [2008] by using a dynamic conductance model based on the hemispheric power index to investigate Joule heating in the ionosphere during a geomagnetically active period. Further, we used the Weimer [2001] model for the background electric potential based on solar wind conditions. The minimum wavelengths of the basis functions used for the conductances and the electric potential are about 6.6 degrees in latitude and 30 degrees in longitude. This limits the smallest scales of estimated features to about one half the minimum wavelength, or 3.3 degrees in latitude and 15 degrees in longitude. This minimum spatial resolution affects the ability to fit closely to individual data values and to estimate the full intensity of localized electric fields, currents, and Joule heating. [14] For this study, we also modified the conductance at locations where ground-based magnetometers were available, using the Ahn et al. [1998] formulas for conductance based on ground magnetic perturbations. For electromagnetic data, we use vector ground magnetic perturbations from multiple sites in the northern hemisphere, along with available ion drift data from the SuperDARN radars [Chisham et al., 2007] and the DMSP drift meters [Rich and Hairston, 1994]. Assimilations that either included or excluded the AMPERE magnetic data were performed to demonstrate how much these data improved the estimated FACs in AMIE, as well as how they affected the estimation of Joule heating. The AMPERE data are differenced along a given satellite track, and it is these differences that are input to AMIE. This procedure weights smallscale fields more strongly than large-scale fields, and was originally developed as a way of filtering out spurious long-wavelength magnetic features that can be caused by incomplete removal of the main geomagnetic field when the satellite attitude is not precisely known. When all data are ingested, AMIE provides a relatively complete picture of both the electric fields and currents, allowing a realistic specification of the distribution of ionospheric Joule heating Merging AMPERE Data Into AMIE [15] Figure 1 shows the effect of including different data types in AMIE, with four different AMIE estimates of FACs at 0:30 UT on 5 April 2010, when B Z was slightly negative ( 2 nt) and B Y was near zero. These FACs were calculated by the AMIE procedure using the static conductance model. Figure 1a was calculated by the AMIE procedure using only measurements from ground magnetometer stations. The coverage (shown by black dots) is sparse, and there is a strong FAC pair on the dawn side with the downward current density reaching 1.45 ma/m 2. Note that this dawnside pair is in a region where there are no measurements and there is no reason to attribute any physical significance to it this is a common problem when relying only on ground-based magnetometers to drive AMIE. It can also be a problem, even when other data sets are available to augment the ground-based magnetometers. In Figure 1b, we show the equivalent plot that includes additional data from DMSP and SuperDARN along with the magnetometer measurements. The inclusion of the additional data results in a pattern that is more constrained and no longer has the large dawnside peaks. Comparing this pattern with the FACs obtained from simply performing the curl operation on AMPERE residuals (Figure 1c) however, shows that AMIE is not capturing the currents that are reaching approximately 0.7 ma/m 2 in the postdusk sector. [16] Figure 1d shows FACs calculated by AMIE using the full complement of ground magnetometer measurements, data from SuperDARN and DMSP, as well as fitted AMPERE magnetic residuals. In this case, the currents computed by AMIE now agree to a higher degree of 3of14

4 Figure 1. Observations of FACs at 0:30 UT: (a) FACs calculated by AMIE using only ground magnetometers, (b) FACs calculated by AMIE using ground magnetometers along with DMSP and Super Dual Auroral Radar Network (SuperDARN) plasma drift measurements, (c) FACs calculated by taking the curl of spherically harmonic fitted AMPERE magnetic residuals, and (d) FACs calculated by AMIE using ground magnetometers, SuperDARN and DMSP plasma drift measurements, and AMPERE fitted magnetic residuals. The lowest latitude shown is 60 degrees magnetic latitude. accuracy with the AMPERE current patterns. We anticipated that using these currents would also lead to an improved specification of ionospheric Joule Heating. [17] Figure 2 shows two Joule heating patterns calculated by AMIE for the same time period as Figure 1. The pattern on the left uses both ground magnetometers and plasma drift measurements from SuperDARN and DMSP. The pattern on the right includes the same distribution of AMPERE magnetic residuals used in Figure 1. By more accurately specifying the field aligned currents as in Figure 1, the Joule heating pattern on the right of Figure 2 is consistent with the southward IMF conditions and the corresponding statistical pattern from Weimer [2005]. In particular, the Joule heating occurs in the dawn and dusk sectors in the auroral zone, where enhanced conductivity allows for larger Hall current and fast sunward flow channels [Carlson and Egeland, 1995]. [18] Finally, to demonstrate the effect of ingesting AMPERE data into AMIE, we compare a time series of currents derived from the curl of the residuals with the currents obtained by ingesting AMPERE residuals into the AMIE data. Again, a static conductance model is used. Figure 3 shows a time series of the maximum positive and negative FAC density for each UT during 5 April FAC values calculated by taking the curl of AMPERE magnetic residuals are shown with a solid line, and FAC 4of14

5 Figure 2. Joule heating maps calculated by AMIE on 5 April 2010 at 0:30 UT. The left pattern uses data from ground magnetometer stations as well as plasma drift measurements from DMSP and SuperDARN. The right pattern includes data from AMPERE. The minimum latitude shown is 60 degrees magnetic latitude. values calculated by AMIE using AMPERE as an input are shown with a dashed line. When AMIE ingests AMPERE data, it mostly captures the FAC trend seen by AMPERE throughout the day. At around UT, both methods observe a positive spike in FAC density. Around 14:00 UT, however, a spike in negative FAC density is observed by AMPERE but not by AMIE. It is important to note that some of the differences between the AMIE and AMPERE maximum FACs for a given UT might be related to spatial resolution. The fitted perturbations calculated by AMPERE have a latitudinal resolution of approximately one degree, while fitting the AMIE procedure s basis functions will further smooth the data to three degrees. Later sections will show that regardless of any differences in the maximum FAC values for any given UT, AMIE still captures the 14:00 UT peak in the integrated total FAC. [19] Figure 3 shows that there is a large amount of variation in the maximum positive and negative values of the FAC density throughout the day. Figures 1 and 2 both showed patterns from 0:30 UT, when the FACs were at their weakest in order to demonstrate the benefit of including AMPERE data into AMIE. However, the remainder of this study will investigate the more disturbed periods in greater detail TIME-GCM [20] In order to predict the impact of the intense Joule heating on the high-altitude thermosphere (400 km), neutral densities and winds will be calculated using the NCAR TIME-GCM [Roble and Ridley, 1994]. TIME-GCM solves the momentum, continuity and energy equations for charged particles and neutrals, and then specifies the electrodynamics using current continuity. In addition, mesospheric tides are included to specify coupling from lower altitudes. F10.7 data are input to specify solar flux. Traditionally, high-latitude electrodynamic forcing has been specified by empirical or theoretical models such as Weimer [1996, 2001, 2005] or Heelis et al. [1982]. However, Crowley et al. [2010] used outputs from AMIE to drive the TIME-GCM and produced density enhancements associated with Joule Heating on flow channels between a DPY current pair. The present study will also use AMIE outputs that include AMPERE data to specify high-latitude Joule heating, which will allow us to predict the Figure 3. Time variation of the maximum upward and downward field-aligned currents at 5 min cadence as calculated by taking the curl of AMPERE residuals (solid line) and from AMIE after ingesting AMPERE residuals into the AMIE algorithm (dashed line) for 5 April of14

6 Figure 4. Solar wind and geophysical conditions for 5 April effects of an intense NBZ current pair on the upper thermospheric neutral dynamics. 3. Results and Discussion [21] The first major geomagnetic storm period of the current solar cycle occurred on 5 April It is also the first major geomagnetic storm since AMPERE data became available Solar Wind and Geophysical Indices [22] Figure 4 shows the solar wind conditions from the OMNI database [King and Papitashvili, 2005] and geophysical indices for 5 April Solar wind conditions were propagated from L1 to 17 Re. Through the early portion of the day, the solar wind magnetosphere ionosphere system was quiet, with nominal solar wind velocity and weak IMF By and Bz. At approximately 9:30 UT, a sudden impulse in the solar wind encountered the Earth, leading to a sudden increase in Dst. In addition, the K P index increased to almost 8 shortly afterward. Following the impulse, the IMF Bz turned southward, with sharp fluctuations from approximately 0 to 10 nt. The IMF By was also strong and fluctuating. This continued until the Dst reached a minimum of approximately 35 at 10:30 UT. [23] After 10:30 UT, the Dst index started to recover and the IMF turned strongly northward, reaching a peak of 20 nt two hours later at approximately 12:30 UT. During this period, the IMF By component also became strongly negative. This behavior of the IMF By and Bz components should lead to conditions where reconnection occurs near the cusp, generating intense dayside FACs. After 12:30 UT, the IMF turned weakly southward with a strong negative By, leading to typical storm behavior in the Dst index Evolution of Ionospheric Electrodynamics and Localized Anomalous Ionospheric Joule Heating [24] Figure 5 shows time series of the cross polar cap potential (Figure 5, top) and globally integrated downward FAC (Figure 5, bottom). The solid lines are parameters calculated by AMIE with the inclusion of AMPERE data, and the dashed lines are calculated without AMPERE. In both cases, the static conductance model was used. The largest values in the integrated FAC occurred at approximately 10:00 and 14:00 UT, corresponding to the times when the Dst index was at a minimum. Throughout the day, the FAC values derived directly from AMPERE are 30 40% higher than those from AMIE. We attribute this to the use of an unrealistic (fixed) conductance model, and below we show the effect of using a dynamic conductance model. In Figure 3, it was noted that when AMIE ingested AMPERE data, it missed a spike in the maximum value for downward FAC density at approximately 14:00 UT. However, the integrated FAC in Figure 5 shows that the overall trend was, indeed, captured by AMIE. [25] Figure 6 shows time series of the cross polar cap potential (Figure 6, top) and globally integrated downward FAC (Figure 6, bottom) in the same format as Figure 5. The difference is that in Figure 6, the AMIE runs used a dynamic conductance model determined by the hemispheric power index. In comparing Figures 5 and 6, one can determine the role of conductance in the calculation of the potential and FACs. The CPCP calculated without AMPERE does not change significantly when the conductance model changes, but the CPCP calculated with AMPERE does. Conversely, the AMIE integrated downward FAC including AMPERE ingestion does not change when the conductance model changes, while the FAC calculated from AMIE without AMPERE does change. This is due to the fact that without AMPERE, a majority of the measurements contributing to the AMIE potential and FAC pattern are convection measurements 6of14

7 on the integrated FAC and CPCP in Figure 6, there are local maxima in the integrated joule heating at both 10:00 UT and 14:00 UT. In the maximum Joule heating (Figure 7, left), there is a local peak at 12:05 UT of approximately 65 mw/m 2 that is not observed when AMPERE is not included in AMIE. At this time, the IMF Bz component was strongly northward and the By component was strongly negative. In the spatially integrated Joule heating, the peak at 12:05 is considerably less pronounced. This suggests that the region of enhanced Joule heating is highly localized, which is consistent with past observations of anomalous Joule heating cases [e.g., Crowley et al., 2010]. [27] Figure 8 depicts four different AMIE output fields (all used the dynamic conductance model) for 12:05 UT on the study day. Figures 8a and 8b are the FAC and Joule heating distribution calculated by AMIE without AMPERE data as an input. Figures 8c and 8d are the FAC and Joule heating distribution calculated by AMIE including AMPERE data as an input. Comparing the two pairs of maps, two differences are immediately apparent. In Figures 8a and 8b, the currents have a DPY configuration, with the peak Joule heating spread over an hour of MLT duskward from local noon and reaching mw/m 2. In Figures 8c and 8d, the currents have an NBZ configuration that is tilted duskward, Figure 5. (top) Time series of the cross polar cap potential (CPCP) on 5 April (bottom) Time series of the globally integrated downward FAC on 5 April The solid lines are calculations by AMIE using data from ground magnetometers, SuperDARN, DMSP, and AMPERE. The dashed lines are calculations by AMIE that do not include AMPERE data in the input. from SuperDARN and DMSP, which are directly fit to the electric potential and rely on the conductance model and current continuity to obtain the FACs. Likewise, the along-track derivatives of AMPERE magnetic perturbations are directly fitted to a radial current, and rely on the conductance model and current continuity to obtain the potential. It is important to note that without the dynamic conductance model, AMIE drastically overestimates the CPCP when AMPERE is included. Because of this, the dynamic conductance model is used for the remainder of the study in order to obtain more realistic Joule Heating calculations. It should be noted that Figures 1 and 2 were from the quiet period early in the day, and therefore the dynamic and static conductances were similar. [26] Ionospheric Joule heating is related to the polar cap potential and field aligned current. Figure 7 shows a time series of the maximum joule heating for each given UT (Figure 7, left) and the globally integrated joule heating (Figure 7, right) as calculated by AMIE using the dynamic conductance model. Again, the solid lines are calculated by AMIE runs that include AMPERE data and the dashed lines are from AMIE runs without AMPERE. As might be expected based Figure 6. Time series of the (top) CPCP and (bottom) FAC on 5 April 2010, given in the same format as Figure 5 and calculated using a dynamic conductance model based on hemispheric power. 7of14

8 Figure 7. (left) Time series of the peak Joule heating. (right) Time series of the globally integrated Joule heating. Both plots are for 8:00 to 20:00 UT on 5 April The solid lines are calculations by AMIE using data from ground magnetometers, SuperDARN, DMSP, and AMPERE. The dashed lines are calculations by AMIE that do not include AMPERE data in the input. with peak Joule heating at noon MLT and reaching mw/m 2. This peak value is comparable to the mw/m 2 that was shown by Crowley et al. [2010] and which caused observed anomalous thermospheric density enhancements on 24 August Due to the NBZ current configuration in this case, the intense dayside Joule heating is much more localized than the feature modeled and observed by Crowley et al. [2010]. [28] Due to the lack of electrodynamic input data at high latitudes, the AMIE dayside FACs and Joule heating in Figures 8a and 8b were mainly a result of the background model used in the AMIE procedure (in this case, Weimer [2001]). By the time the DMSP satellite crosses the noon meridian to better specify the electric field at high latitudes, the short-lived peak in the joule heating has already passed. This reiterates that the occurrence of anomalous Joule heating associated with dayside FACs is not only difficult to observe directly without steady data coverage, but also that it does not appear in empirical models based on average conditions Modeled Impacts of Localized High-Latitude Joule Heating on the Neutral Atmosphere [29] In order to model the impact of the intense localized Joule heating in Figure 8d on the neutral atmosphere, the TIME-GCM was driven by the output of the AMIE run that included AMPERE ingestion. Figure 9 shows two polar plots of TIME-GCM outputs at 400 km altitude on 5 April 2010 at 12:05 UT. This time period was coincident with the localized peak in ionospheric Joule heating seen in Figure 8. Both plots are given in solar local time (SLT) and geographic latitude (GLAT) format, with a perimeter latitude of 37.5 degrees. Figure 9a shows a localized high-latitude density cell centered at 10 SLT which is approximately 64% more dense than the surrounding gas. This cell is colocated with the flow channel that produced intense ionospheric Joule heating in Figure 8d, and is due to upwelling of neutral gas caused by the direct heating. This upwelling is evident in the vertical neutral wind pattern shown in Figure 9b, which includes strong upward winds in the region of the neutral density enhancement. [30] Although more localized and weaker in magnitude, the density enhancement and upwelling in Figure 9 is comparable to the enhancement modeled and observed using CHAMP on 24 August 2005 by Crowley et al. [2010]. During the 24 August 2005 period, CHAMP s orbit was at approximately 400 km altitude, and was able to capture the extreme density enhancement. By 2010, CHAMP had dropped to 300 km altitude, where the scale height will not change as dramatically in response to Joule heating, and thus, the density enhancement will not be as prominent. Figure 10 shows CHAMP densities (black line) as a function of Universal Time (UT) for one orbit on 5 April The data set used in this study consists of total mass densities processed by the Space Physics and Aeronomy group at the University of Colorado at Boulder, Version 2.3 [Sutton et al., 2007]. Shortly before 12:30 UT, CHAMP observed a spike in density as the satellite passed over the northern geomagnetic pole. This spike in density was also coincident with the highlatitude density enhancement simulated by the TIME-GCM. The red line shows TIME-GCM predicted densities, which simulated the spike near 12:30 UT. As discussed above, the neutral density at CHAMP s 300 km orbital altitude is already large, and therefore the density enhancement is not as extreme as it would be at the higher altitudes shown in Figure 9. 8of14

9 Figure 8. AMIE patterns at 12:05 UT on 5 April 2010: (a) ionospheric FACs as calculated by AMIE with no AMPERE data, (b) ionospheric Joule heating as calculated by AMIE with no AMPERE data, (c) ionospheric FACs as calculated by AMIE with AMPERE data included as an input, and (d) ionospheric Joule heating as calculated by AMIE with AMPERE data included as an input. The minimum latitude shown is 60 degrees magnetic latitude. [31] The large enhancement in Joule heating during the event being studied generated large-scale gravity waves that propagated equatorward from the polar regions. Figure 11 shows the latitude-time evolution of two TIME-GCM parameters sampled at 8:00 SLT between 12:00 and 15:00 UT on 5 April Figure 11a is the neutral density at 400 km. The density enhancement associated with the Joule heating in Figure 8 is apparent between 12:00 and 12:30 UT near the north geographic pole. But Figure 11a reveals that between 12:30 and 14:00 UT, a region of enhanced density appears to propagate equatorward at speeds of about 740 m/s until it merges with a larger-scale thermospheric density structure. These speeds are commensurate with other large-scale waves that have been reported previously [e.g., Immel et al., 2001, and references therein]. [32] The equatorward propagation of the density enhancement becomes more apparent when examining the evolution of the vertical neutral wind. Figure 11b shows the corresponding vertical component of the neutral wind at 400 km. At 12:00 UT, near the north geographic pole, intense upward winds coincide with the density enhancement visible in Figure 11a. The region of upward winds then propagates equatorward with the density enhancement. [33] It should be noted that these features are not observed if AMPERE is not included in the AMIE data. Figure 12 shows the latitude-time evolution of the same TIME-GCM parameters at the same local and universal time as Figure 11. 9of14

10 Figure 9. Polar plots of TIME-GCM outputs on 5 April 2010 at 12:05 UT. These include thermospheric (a) neutral density and (b) vertical neutral winds at 400 km in altitude. All plots are given in geographic SLT-GLAT format. The lowest latitude shown is 37.5 degrees. Figure 10. (top) Line plot showing densities measured (black line) during a single orbit of the CHAMP satellite as a function of UT on 5 April TIME-GCM predicted densities (red line) are superposed. A high-latitude density spike is pointed out between the two vertical blue lines. (bottom) Geomagnetic latitude and longitude of CHAMP. 10 of 14

11 Figure 11. Geographic latitudinal slices of Northern Hemisphere TIME-GCM thermospheric parameters fixed at 8:00 SLT between 12:00 and 15:00 UT on 5 April These include (a) neutral density and (b) vertical neutral winds at 400 km in altitude. The difference is that to generate the time series in Figure 12, AMIE runs without AMPERE as an input were used to specify high-latitude electrodynamics in TIME-GCM. In Figure 12a, the density enhancement at 12 UT in the highlatitude region is significantly weaker and in Figure 12b, the upward vertical wind structure does not appear to propagate out of the auroral zone. [34] Large-scale waves are a mechanism by which features in the high-latitude region can couple into the middle and equatorial latitudes. While the electromagnetic coupling between the magnetosphere and ionosphere under northward IMF is generally considered to be highly localized, waves such as the one shown in Figure 12 allow small-scale density structures to couple to lower-latitude regions. A similar wave was launched by the strong BY event on 24 August 2005 studied by Crowley et al. [2010]. These waves have fast phase speeds and can cover large regions of the globe in only a few hours [e.g., Immel et al., 2001]. As a result, they can produce large neutral density enhancements at low latitudes 2 3 h after a high-latitude Joule heating event. This propagation time delay accounts for a high density at low latitudes that might not otherwise be expected to have any good explanation if observed in isolation. 4. Conclusions [35] The present study investigates the geomagnetic storm event on 5 April During this event, there was a slight recovery of Dst between local minima, associated with a northward turning of the IMF. This was the first major geomagnetic storm since the availability of AMPERE data. Using the AMIE procedure with AMPERE data as an input, the spatial distribution of electrodynamic quantities was calculated throughout the day. The study demonstrated that 11 of 14

12 Figure 12. The same as Figure 11, except the output is from TIME-GCM driven by AMIE without AMPERE. the inclusion of AMPERE into AMIE allows the model to capture medium-scale structure in the electrodynamic quantities, and corresponding neutral density structures, which were not readily observed in the past. [36] With the inclusion of AMPERE data, anomalous dayside Joule heating reaching 64 mw/m2 was observed at 12:05 UT. At this time, the Dst index was recovering, the IMF Bz was strongly northward, and the IMF By was strongly negative. Without the presence of AMPERE in this region, AMIE was specified largely by the background model, and under predicted the maximum Joule heating by more than a factor of 3. In itself, this would make it difficult to accurately predict the thermospheric density distribution at high latitudes. However, in addition, the location of the peak Joule heating was misplaced by over an hour MLT (15 degrees magnetic longitude), which would further reduce the fidelity of any thermospheric density simulation. Crowley et al. [2010] observed similar extreme levels of dayside Joule heating when the IMF Bz was near zero and the IMF By was strongly positive. In addition, they showed that the dayside Joule heating produced the anomalous thermospheric density enhancements that had been occasionally observed by the CHAMP satellite. In their case, a DMSP satellite passed through the region of anomalous Joule heating at the appropriate time, and AMIE was able to capture the event. [37] For the 5 April 2010 event studied here, as well as the event studied by Crowley et al. [2010], the anomalous Joule heating was not observed or predicted by empirical models. Additional data were required. Very often, empirical models of ionospheric heating and thermospheric density are smooth at high latitudes because there are not enough data at a resolution to capture higher harmonics in their basis functions. It is via these higher harmonics that anomalous events such as the one reported in this paper will be properly modeled. With the recently released AMPERE data set, high-fidelity maps of ionospheric FACs may now be produced at an 12 of 14

13 acceptable time resolution for event studies. The inclusion of AMPERE data into the AMIE algorithm allows for the anomalous Joule heating to be consistently specified by AMIE, even when coverage by other instruments is lacking. In addition, using AMIE as opposed to AMPERE alone allows for the specification of the high-latitude ionospheric convection pattern, which is needed to simulate events using first principles models such as TIME-GCM. [38] Output from AMIE runs including AMPERE data were used to drive the TIME-GCM and demonstrate that the extreme levels of Joule heating at 12:05 UT caused upwelling of thermospheric neutral gas and a highly localized density enhancement on the dayside at high latitudes. The model output also predicted that the localized upwelling led to a large-scale wave, which propagated equatorward. This prediction is significant to magnetosphere-ionospherethermosphere (MIT) coupling, because the sunward flow channel between NBZ FACs is very narrow, extending between 80 and 90 degrees MLAT and only a few degrees dawnward and duskward of the noon meridian. Therefore, the coupling under northward IMF is usually considered to be geomagnetically quiet, implying that its effects are restricted to high latitudes. [39] Several studies, however, have demonstrated that while the solar wind magnetosphere ionosphere coupling is highly localized under northward IMF, there is still intense energy deposition in the region of reverse convection associated with NBZ currents. The reverse convection potential has been shown to saturate in response to the interplanetary electric field in a manner similar to the polar cap potential under southward IMF [Wilder et al., 2008, 2009; Sundberg et al., 2009]. Studies have also shown that under strong IMF magnitude, the reverse convection under northward IMF flows at speeds comparable to the antisunward cross polar cap flow typical of southward IMF [Clauer and Friis- Christensen, 1988; Wilder et al., 2010]. The present study also demonstrates that intense Joule heating can occur on the flow channel between NBZ currents, and predicts that disturbances in the thermosphere caused by the localized Joule heating can propagate equatorward at speeds of about 700 m/s. While MIT coupling under strongly northward, dawnward, or duskward IMF has largely been studied at very high latitudes, observational evidence is needed to determine the global effect of strong localized Joule heating during these periods. The upcoming solar maximum should provide an excellent opportunity to further understand these complex interactions. [40] Acknowledgments. F.D.W. and G.C. were supported at ASTRA by AFOSR MURI award FA and by NSF GEM award ATM F.D.W. is currently funded by the NSF AGS Postdoctoral Research Fellowship to the Laboratory of Atmospheric and Space Physics at the University of Colorado. AMPERE is supported under NSF grant ATM to The Johns Hopkins University Applied Physics Laboratory. Participation in AMPERE by the Boeing Services Company and Iridium Communications is gratefully acknowledged. A.D.R. was supported in part by NASA grant NNX08AG09G. The National Center for Atmospheric Research is sponsored by the National Science Foundation. We are grateful to the following data providers: The Center for Space Sciences at the University of Texas at Dallas provided DMSP SSIES data; SuperDARN data were provided by J. M. Ruohoniemi and Space at Virginia Tech. Magnetometer data were provided by the Solar-Terrestrial Environment Laboratory, Nagoya University; the World Data Centre (WDC) for Solar-Terrestrial Science (STS) operated by IPS Radio and Space Services, Australia; the Canadian Space Science Data Portal and the University of Alberta; the Geophysical Institute of the University of Alaska and PURAES (Project for Upgrading Russian AE Stations); Danish Meteorological Institute and Space Physics Research Laboratory at the University of Michigan; INTERMAGNET; Eftyhia Zesta; Space Plasma Environment and Radio Science (SPEARS) in the Department of Communication Systems at the University of Lancaster; Institute for Physical Science and Technology at the University of Maryland; and WDC for Geomagnetism, Edinburgh. Satellite magnetometer data were provided by the Johns Hopkins University Applied Physics Laboratory. We thank Delores Knipp and Gang Lu for helpful comments on a draft of the manuscript. 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