Key features of >30 kev electron precipitation during high speed solar wind streams: A superposed epoch analysis

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 117,, doi:10.1029/2011ja017320, 2012 Key features of >30 kev electron precipitation during high speed solar wind streams: A superposed epoch analysis A. J. Kavanagh, 1,2 F. Honary, 1 E. F. Donovan, 3 T. Ulich, 4 and M. H. Denton 1 Received 31 October 2011; revised 16 April 2012; accepted 25 April 2012; published 7 June 2012. [1] We present an epoch analysis of energetic (>30 kev) electron precipitation during 173 high speed solar wind streams (HSS) using riometer observations of cosmic noise absorption (CNA) as a proxy for the precipitation. The arrival of the co-rotating interaction region (CIR) prior to stream onset, elevates the precipitation which then peaks some 12 h after stream arrival. Precipitation continues for several days following the HSS arrival. The MLT distribution of CNA is generally consistent with the statistical pattern explained via the substorm process, though the statistical deep minimum of CNA/precipitation does change during the HSS suggesting increased precipitation in the 15 20 MLT sector. The level of precipitation is strongly controlled by the average state of the IMF B Z component on the day prior to the arrival of the stream interface. An average negative IMF B Z will produce higher CNA across all L-shells and MLT, up to 100% higher than an average positive IMF B Z. Citation: Kavanagh, A. J., F. Honary, E. F. Donovan, T. Ulich, and M. H. Denton (2012), Key features of >30 kev electron precipitation during high speed solar wind streams: A superposed epoch analysis, J. Geophys. Res., 117,, doi:10.1029/2011ja017320. 1. Introduction [2] The high speed solar wind streams (HSS) that emanate from coronal holes at mid to low solar latitudes drive corotating interaction regions (CIR) in the solar wind. These form as the fast solar wind pushes into the preceding slow plasma resulting in a pile-up of plasma density and magnetic field [e.g., Borovsky and Steinberg, 2006]. When a CIR, and subsequent HSS, passes over the Earth it can drive sustained periods of geomagnetic activity [e.g., Borovsky and Denton, 2010]. Comparisons have been made between CIR-driven storms and those driven by interplanetary coronal mass ejections (ICME) showing differences in magnetospheric response [e.g., Borovsky and Denton, 2006; Denton et al., 2006; Turner et al., 2006]. CIR tend not to produce such large geomagnetic storms when using the D st index as the measure of strength; however CIR have been shown to be more geoeffective with greater overall energy output than CME driven storms, particularly focused in the recovery phase. [3] Although energy output is higher during CIR storms the relatively low D st points to only a small enhancement of the ring current yet the Kp index is often moderate to high 1 Department of Physics, Lancaster University, Lancaster, UK. 2 Now at British Antarctic Survey, Cambridge, UK. 3 Department of Physics and Astronomy, University of Calgary, Calgary, Alberta, Canada. 4 Sodankylä Geophysical Observatory, Sodankylä, Finland. Corresponding author: A. J. Kavanagh, British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 0ET, UK. (andkav@bas.ac.uk) 2012. American Geophysical Union. All Rights Reserved. indicating that HSSs drive significant convection. This goes hand in hand with an increase in auroral activity associated with injections of energetic particles from the magnetotail. During HSSs dramatic dropouts can occur in the flux of relativistic electrons in the outer radiation belt, these are followed by gradual increases to levels higher than before the HSS via acceleration of the newly injected population. HSSs also generate ultra-low-frequency (ULF) waves in the magnetosphere due to the increased solar wind acting on the magnetosphere; these may play a role in energizing electrons in the radiation belts. A recent summary of the geomagnetic effects of HSS is provided by Kavanagh and Denton [2007], who highlight several outstanding questions regarding the effect that HSSs have on the Earth s near-space environment. Key questions include determining the cause of the relativistic electron dropouts and the dominant plasma waves responsible for the heating and loss of those electrons. Understanding the role (or lack thereof) of the solar wind in driving high D st and why it is so low for HSSs, is another outstanding question as is evaluating the importance of fluctuations in the interplanetary magnetic field compared with the solar wind velocity in determining the solar wind magnetosphere coupling efficiency. [4] Other recent summaries of HSS-effects on geospace may be found in Denton et al. [2008], Borovsky and Denton [2006], Tsurutani et al. [2006], McPherron and Weygand [2006], and Turner et al. [2006]. [5] One aspect of geomagnetic activity that is increasingly recognized as important is the precipitation of energetic electrons. Beyond their substantial influence on ionospheric electrodynamics [e.g., Senior et al., 2007] these particles affect the Earth s atmosphere through the generation of odd 1of13

Table 1. Riometers Used in This Study Riometer Magnetic Coordinates Geographic Coordinates L-Shell Earth Radii IRIS (Kilpisjärvi) 66.10, 103.9 69.05 N, 20.79 E 6.09 Dawson 66.10, 272.6 64.05 N, 139.11 W 6.09 Eskimo Point 71.12, 332.0 61.11 N, 94.05 W 9.55 Fort McMurray 64.64, 308.0 56.66 N, 111.21 W 5.45 Fort Simpson 67.57, 292.9 61.76 N, 121.23 W 6.87 Fort Smith 67.72, 303.6 60.02 N, 111.95 W 6.96 Gillam 66.65, 332.0 56.38 N, 94.64 W 6.36 Island lake 64.25, 332.2 53.86 N, 94.66 W 5.3 Pinawa 60.59, 330.8 50.20 N, 96.04 W 4.15 Rabbit Lake 67.36, 317.9 58.22 N, 103.68 W 6.75 Rankin Inlet 72.58, 335.4 62.8 N, 92.11 W 11.15 Taloyoak 78.83, 329.3 69.54 N, 93.55 W Polar cap Fort Churchill 68.67, 332.9 62.82 N, 92.11 W 7.56 nitrogen (NO x ) species in the thermosphere and mesosphere. Additional NO x is an important factor in the heat balance of the atmosphere as it is a catalyst in the process of ozone destruction. NO x is destroyed by sunlight above 75 km but during polar winter large amounts can build up and be transported downward in the polar vortex [Randall et al., 2005; Clilverd et al., 2006, 2007]. Seppälä et al. [2009] showed a link between geomagnetic activity and surface air temperature in the Polar Regions; cooling in some regions, warming in others. Thus energetic electron precipitation may play an important role in modulating surface climate in the Polar Regions. [6] Meredith et al. [2011] recently examined the response of >30 kev, >100 kev, >300 kev and >1 MeV electron precipitation obtained from polar satellite observations during HSS for 42 events that produced storms. They found that the >30 kev electrons increased immediately following storm onset and remained elevated during the passage of the high-speed stream. This confirmed the results of Longden et al. [2008] who used a riometer in the auroral zone to show that the precipitation persisted. The >1 MeV electron precipitation immediately following storm onset did not increase in the study by Meredith et al. [2011] suggesting that flux dropouts during the main phase of HSS storms are not primarily due to precipitation. [7] Longden et al. [2008] compared and contrasted the effect that storms driven by CIR and ICME have on the >30 kev electron precipitation in the auroral zone, close to the footprint of geostationary orbit. An epoch analysis of 33 CIR and 36 CME driven events found that the CIR storms produced longer lasting precipitation though the ICME storms-related loss was more intense. Thus the effect of HSS on precipitation is worth further consideration. [8] In this paper we concentrate on the effect that HSS have on sub-relativistic electrons generally assumed to be the seed population for the radiation belts. In particular we consider the loss of these electrons to the atmosphere and expand the work of Longden et al. [2008] by examining a larger set of HSSs across a greater range of latitudes. We perform an epoch analysis on several riometers in the European and Canadian sectors and across a range of L-shells, finding distinct differences in the response to the HSSs. We compare the effect of dominant northward/ southward IMF B Z on the precipitation during HSSs, using it as a simple proxy for changing the energy input to the magnetosphere. 2. Instrumentation [9] The riometer (relative ionospheric opacity meter) is essentially a sensitive radio receiver that measures cosmic radio noise in the 20 50 MHz range [Little and Leinbach, 1959]. By comparing the received noise level to a known quiet day it is possible to determine by how much additional radio noise has been absorbed by the ionosphere during the period under investigation. This cosmic noise absorption (CNA) occurs primarily in the D-layer of the ionosphere and in the absence of solar protons is primarily caused by enhanced electron density due to precipitating electrons with energy in excess of 30 kev [e.g., Baker et al., 1982]. There are several varieties of riometer ranging from single wide beam systems to multiple beam imaging systems [e.g., Detrick and Rosenberg, 1990], and from analogue to digital systems [Honary et al., 2011]. In this study we use data both from a number of simple wide-beam systems and an imaging riometer. These facilities form part of the Global Riometer Array (GLORIA) [Alfonsi et al., 2008]. [10] The University of Calgary operates 13 wide beam riometers across Canada; these are vertical pointing, 30 MHz systems with a temporal resolution of 5 s. Lancaster University operates an Imaging Riometer for Ionospheric Studies (IRIS) at Kilpisjärvi, in northern Finland [Browne et al., 1995]. This is a phased array that produces 49 imaging beams, sampled every second, and monitors CNA at 38.2 MHz. Since we are interested more in the large scale features of the precipitation we do not utilize the imaging capability of IRIS and instead limit ourselves to measurements from the central beam. [11] All of the data have been averaged to one minute resolution. Negative values of absorption have been removed below a given value ( 0.5 db for IRIS and 0.8 db for NORSTAR); this removes some of the worst effects of contamination by solar radio emission [e.g., Kavanagh et al., 2004b] while allowing for variation in the fitting of the quiet day curve. [12] Table 1 gives the locations of each of the riometers in geographic and geomagnetic coordinates. McIlwain L-shell 2of13

Figure 1. Epoch analysis of solar wind parameters and geomagnetic indices from 173 identified high speed solar wind streams from 1995 to 2006; data from the OMNI2 data set. The black line is the median value with the red lines giving the upper and lower quartiles. The time of epoch is taken to be the westward to eastward change in the solar wind speed. On average the streams produce both moderate auroral activity (indicated by AE) and small ring current enhancements (indicated by SYM-H). Only a few events produce a classical storm with a large ring current. footprints are provided to give an indication of where the precipitating electrons originate in the magnetosphere. 3. Data Selection [13] The HSSs used in this paper were determined from the time-shifted OMNI data set [King and Papitashvili, 2005] (http://omniweb.gsfc.nasa.gov/ow_min.html) from between 1995 and 2006 (inclusive); all solar wind times are those determined to be at the bow shock. Primary event selection criteria were (1) an increase in the X(GSE) component of the solar wind speed of at least 50 km/s within one day, (2) a west east deflection in the solar wind direction following a local peak in the interplanetary magnetic field strength and solar wind density (indicative of a stream interface in a CIR), (3) sustained solar wind speed above 500 km/s for one day following the W E deflection. [14] These criteria provide a means of basic data reduction but on their own do not guarantee the selection of only HSSs; ICME may also fit the above criteria thus it is essential to use further filtering. We cross-checked the list of events produced by the above criteria with the comprehensive list of ICME by Richardson and Cane (http://www.ssg. sr.unh.edu/mag/ace/acelists/icmetable.html). This is an updated and revised version of the list that originally appeared in Cane and Richardson [2003] and incorporates composition and charge state data [Richardson and Cane, 2004] and is not restricted to events with magnetic clouds. The parameters considered include the typical solar wind features (changes in speed, magnetic field strength and density), periods of abnormal solar wind charge/composition states and evidence of bi-directional suprathermal electron strahls. All supposed HSS events that overlap with identified ICME have been removed; we make no consideration for 3of13

Figure 2. The distribution of high speed solar wind streams used in this study. (a) The occurrence of streams as a function of month of the year. Peaks are identified in spring and autumn; however streams that overlap with CME, PCA and closely spaced streams have been removed. In general there is a good distribution across seasons. (b) breakup of this distribution by the peak solar wind speed following the zero epoch. (c) Sums Figure 2b across the months to show that the occurrence of streams peaks between 650 700 km/s. whether an ICME identification is considered weak and so err on the side of caution in our event selection. [15] To ensure our ground-based observations were not contaminated by solar proton events [e.g., Kavanagh et al., 2004b] we removed all instances where the >10 MeV proton flux measured by the SEM instrument on the GOES satellites crossed the 10 pfu threshold. This removed all instances of Polar Cap Absorption (PCA), which is caused by quasi uniform precipitation of 10s 100s MeV protons over the polar cap and auroral zones. Although these events are infrequent if left in the data set the signature of these events would dominate the background CNA. These events are often associated with ICME; however they can occur several days before an ICME reaches Earth and the generating ICME may never pass over the Earth. [16] From the remainder of the events, only those with no other stream onsets two days before and five days after were selected. The solar wind data from the remaining events were then checked by eye and cross-checked against observations of coronal holes and the NOAA Space Weather reports (http://www.swpc.noaa.gov/ftpmenu/warehouse. html). This left a total of 173 events between 1995 and 2006 that we could be confident were purely isolated HSSs. [17] Given the levels of solar wind speed during the long solar minimum circa 2007, it is worth noting that CIR may be followed by solar wind elevated above the background but which do not meet the third criterion. Although of interest and worthy of research these cannot be truly classed as high speed and as such we have not included them in this study. [18] Figure 1 shows an epoch analysis of the OMNI2 data for these events; the zero epoch is the stream interface, determined from the W E deflection of the solar wind following a peak in the magnetic fields strength and solar wind density. We plot the data from 3 days before to six days after the zero epoch. For each panel the black line indicates the median value while the red lines provide the interquartile range. The top two panels show the solar wind speed in the V x Earthward (Figure 1a) and V y eastward (Figure 1b) directions (GSE coordinates); note that the median V x does not quite return to pre-hss levels before the end of the analysis period. The next two panels show the solar wind proton density (Figure 1c) and the IMF field strength (Figure 1d). Both of these show the expected increase before the zero epoch as the fast wind flows into the slow, resulting in magnetic and density pile-up. Figure 1e presents the IMF B Z ; this is essentially flat with slightly more variability around the zero epoch. Given the expected Alfvénic structure for each HSS event [Tsurutani et al., 2006] it is not surprising that the median value tends to zero. The final two panels are the geomagnetic indices AE (Figure 1f) and sym- H (Figure 1g). The quick look AE index (provided to OMNI by Kyoto WDC) indicates appreciable substorm activity following the zero epoch with a large range of intensity. The peak is 13 h after the zero epoch and it is worth noting that activity rises during the preceding CIR. The same is true for the sym-h. This index is often considered to be a proxy for the high resolution D st, responding to changes in the ring current. The selected HSSs do not produce very much classical storm activity, the minimum in the median value only reaches 20 nt with the lower quartile 35 nt. [19] Figure 2 shows how the HSSs are distributed as a function of time of year (Figure 2a) and of peak speed (Figure 2c). Peaks in HSSs occurrence do occur in Spring 4of13

Figure 3. (top) The diurnal variation of cosmic noise absorption using data from the central beam of IRIS at 1 min resolution, from 1995 to 2006. Periods of polar cap absorption have been removed leaving electron precipitation as the dominant source of CNA. (bottom) The result of binning the data by the instantaneous solar wind velocity (V X GSE) (50 km/s bins). There is clearly a dependence on solar wind speed with enhancements in CNA between 20 16 MLT. The deep minimum always remains in this statistical pattern. and Autumn with winter being slightly higher than summer; however it is not clear how significant this is, especially since these events have been pre-filtered to remove overlap with CME, PCA and closely spaced (<5 days) streams. It does mean that any analysis of the seasonal effects from this set of HSS should perhaps be treated carefully and normalized for occurrence. 55% of the HSS are between 600 and 750 km/s with only 23% at higher speeds. There is no obvious seasonal pattern of solar wind speed though there is a grouping of 700 800 km/s events in early autumn. Overall, there is no seasonal bias on solar wind speed in this data set. 4. Riometer Observations [20] Kavanagh et al. [2004a] demonstrated that CNA has a strong dependence on solar wind speed that varies in local time; CNA has a peak in the morning sector (10 MLT), a smaller peak close to midnight (23 MLT) and a strong minimum in the afternoon (17 MLT). Figure 3 shows how the absorption varies with respect to solar wind speed using all non-pca data from 1995 to 2006. Figure 3 (top) shows the median CNA diurnal variation from the central narrow beam of IRIS with the upper and lower quartiles of the data. This pattern can be explained in terms of the substorm process; electrons injected from the plasma sheet are subject to gradient curvature drift and are transported dawnward. The anisotropic distribution gives rise to whistler mode chorus waves which in turn scatter electrons into the loss cone as they drift. On the dusk-side there is a minimum in CNA that is attributed to electron fluxes being below the Kennel- Petschek stable trapping limit, it is certainly true that this region is generally devoid of whistler mode chorus waves [e.g., Meredith et al., 2001]. Figure 3 (bottom) shows the results of binning the data with respect to the instantaneous solar wind velocity (GSE V x ) (from OMNI). Higher solar wind velocity lead to statistical increases in the midnight to noon CNA, an increase from 450 500 km/s to 550 600 km/s increases the median CNA by a factor of 2. However, the deep minimum between 16 and 21 MLT is a consistent feature of the daily absorption regardless of the increase in solar wind velocity. [21] Figures 4a and 4b show an epoch analysis of the riometer data using the stream interface as the zero epoch as in Figure 1. The x-axes show the time from epoch (in 15 min steps), the y-axes show the MLT variation (in 1 h bins); the local time effect is very strong such that simply binning the data in time from epoch would mask features in the CNA. The upper plot shows the data from the latitudinal chain of NORSTAR riometers (Dawson, Fort Simpson, Fort Smith, Rabbit Lake and Gillam); the lower plot is from the central beam of IRIS. To help interpret the data Figures 4c and 4d show the median solar wind density and solar wind speed as a function of epoch time. There is a clearly defined, persistent, MLT variation that matches the statistical pattern shown in Figure 3; i.e., a peak in the morning sector followed by a deep minimum and a rise over the night side. It 5of13

CNA increases slightly prior to the zero epoch, some 12 h after the zero epoch the CNA begins to peak and it remains high until the second day after which levels start to decline. By day 5 the CNA is still moderately elevated above the quiet period two days before the onset. As noted by Turner et al. [2006] energy input to the magnetosphere during long lasting HSSs may rival or exceed the energy input during short duration CMEs. Figure 4. Epoch analysis of CNA from the NORSTAR latitudinal chain (Gillam, etc.) at (a) 30 MHz compared with the same from the central beam of IRIS at (b) 38.2 MHz. The data have been sorted into bins of size 1 h of MLT by 20 min of epoch time. The MLT variation is consistent with Figure 3; the slight difference in timing of the peak can be attributed to the difference in L-shell (0.5 Re difference). Although the CNA increases following the zero epoch (and before due to solar wind pressure effects), there is a delay of 12 h before starting to peak. The median (c) solar wind density and (d) speed are presented to provide context. appears that substorm activity is strongly related to the precipitation changes detected throughout the HSS. Differences between the NORSTAR and IRIS analyses are likely due to the slightly different L-shells of the observations (0.6 Re separation) and the lower amount of data that has gone into the IRIS plot. The general features are the same though, the 5. Results 5.1. Overall Variation: MLT Effects and Duration [22] The basic observations show that HSSs have a significant effect on the precipitation of >30 kev electrons by enhancing the precipitation in the morning sector in the days following the onset of the HSS. This enhancement peaks 12 h after the zero epoch, in line with the time of peak median AE (a magnetic substorm index) shown in Figure 1. Given that the CNA response appears linked to substorm activity and the subsequent gradient curvature drift, one might expect a delay in the local time response corresponding to the time it takes for the electrons to drift toward noon. Unfortunately such an effect is difficult to extract from the data due to the nature of the observations; there is a delay but it could well be due to the UT-MLT relationship of the observations. We draw no further conclusions in this respect but plan to investigate this in detail in future studies. [23] Figure 5 shows the results of performing the same epoch analysis with larger bins: 1 day of epoch time and 1 h of MLT. Choosing these bin sizes reduces the fine scale detail (limiting timing information) but reduces the noise making it easier to determine trends in the median data. The choice of MLT bin size should not be so large that it smoothes over times of very different precipitation characteristics (given the sensitivity of CNA to MLT); however, Kavanagh et al. [2004a] and Senior et al. [2007] show that one hour of MLT is reasonable. Binning the data in this way gives the impression that the peak is one day after the zero epoch rather than beginning midway through the first day. Figures 5c and 5d show the factor by which the CNA is increased over the level on the quiet day two days before the zero epoch. The pre-storm level due to the CIR is clear with an increase of around a factor of 2 following HSS-arrival. The morning sector peak for NORSTAR (IRIS) is a factor of 3.5 5.5 (2.8 3.5) times greater than the pre-hss level, whereas over the night the difference is a factor of 4 5 (2.8 3.2). The exact relationship between CNA and the electron-flux and energy is highly dependent on the shape of the precipitating electron spectrum. However, given that the absorption is proportional to the height integrated electron density in the D-layer where attachment dominates it is also proportional to the square root of the electron flux. Therefore changes of factor 3.5 in CNA is equivalent to a factor increase of 12 in the >30 kev flux. Thus the values we observed with the riometers are in broad agreement with the factor 10 increase reported by Meredith et al. [2011] using the NOAA POES data to study precipitation during 42 HSS induced storms. Of course CNA is also dependent on the energy as well as the flux and so to more accurately compare direct flux measurements with riometers observations an estimate of any change in the electron precipitation fluxspectrum would be required. 6of13

Figure 5. (a, b) Similar to Figure 4 but with 1 day epoch and 1 hr MLT bins. The delay to the peak in CNA is clear with the peak appearing to be one full day after the zero epoch at this resolution. (c, d) The increase factor when compared with the CNA two days before the zero epoch. The morning sector peak for NORSTAR (IRIS) is a factor of 3.5 5.5 (2.8 3.5) times greater than pre-hss level, whereas over the night the difference is a factor of 4 5(2.8 3.2). An interesting effect is that that both systems show an increase in CNA in the period of the statistically deep minimum (15 20 MLT) following the onset of the HSS. [24] This comparison also highlights an interesting feature of the afternoon minimum. Contrary to what the statistical analyses in Figure 3 indicate, there is a definite and sustained increase in CNA between 15 and 20 MLT immediately following the zero epoch. It is stronger in the lower frequency NORSTAR riometers (Figure 5c) at 2 2.5 the pre-hss level and less than 1.5 the pre-hss level in the IRIS data (Figure 5d). We will examine this feature further, below. [25] Figure 6 shows the zero epoch analysis of the median absorption in a different format. Figure 6 (top) shows the median absorption from the central beam of IRIS with the associated upper and lower quartiles (dotted red lines). The data are shown in magnetic local time within each day from the zero epoch. The increase following the arrival of the HSS is clear as is the change in the minimum around 18 MLT. CNA is much higher on days 0 and 1 and returns to background levels on day 4. [26] Figure 6 (bottom) shows the occurrence of absorption at three distinct local times for five of the days: (i) magnetic midnight; (ii) the morning peak around 10 MLT; (iii) the afternoon minimum around 18 MLT. At midnight and 10 MLT there is a marked change in the occurrence distribution following the arrival of a HSS; the occurrence of much higher CNA levels is clear. The occurrence difference at 18 MLT is less pronounced even though the median level (and interquartile range) shows a small uplift of 0.02 db in the median CNA following the HSS arrival as revealed in Figure 5. The overall occurrence pattern for each day is very similar, particularly below 0.5 db. The occurrence of CNA on Days 2 and 1 drop to zero at 0.8 db whereas day 1 and day 2 show low occurrence of CNA up to 1.2 db. Combined with the observed change in the median CNA and the interquartile range this is suggestive of a small average difference in this time sector after the arrival of the stream. To test this we performed a two sample Kolmogorov- Smirnov test on the underlying CNA data; the result was a rejection of the null hypothesis that the post-epoch (day +1) and pre-epoch (day 2) distributions are from the same underlying population at the 1% level. Thus the difference in median CNA and the occurrence, although small, is statistically significant. Given the shape of the occurrence and the change in the median value this might suggest that there is, for some (but not all) HSSs, some process (or processes) increasing precipitation into that MLT sector following the arrival of HSSs that is not usually present. A likely candidate is the precipitation of gradient-curvature drifting electrons extended to later local times or that substorm related spike events are occurring earlier than expected (P. Wild, private communication, 2011). Further analysis of this effect is warranted but beyond the scope of this study. This is in general agreement with the data presented by Meredith et al. [2011] (see their Figure 6) who observed an increase in the >30 kev electrons at that local time. Another possibility is that the data may include examples of relativistic precipitation events (>300 kev); CNA events have previously been observed in imaging riometer data in that MLT sector 7of13

Figure 6. (top) An epoch analysis of the CNA response at IRIS to HSSs presented as a time series in MLT (Figure 5d unwrapped ). The black line is the median value from the central beam; the dotted red lines show the interquartile range. (bottom) Three panels comparing the distribution of CNA for selected days for 20 min around (i) midnight, (ii) 10 MLT the morning peak and (iii) 18 MLT - the afternoon minimum. There are clear differences in the CNA distributions at those times with occurrence of higher absorption increased post epoch, including a small but appreciable difference at 18 MLT, which sees an uplift in the top panel. which have been attributed to such energy level events [Ranta et al., 1997]. Recent work by Wild et al. [2010] used tomographic reconstruction and height triangulation to confirm that at least some of the types of events identified by Ranta et al. [1997] are likely due to relativistic energy electrons. Whether events such as these are increased during high speed streams is yet to be definitively established. 5.2. Influence of the Interplanetary Magnetic Field [27] Although Kavanagh et al. [2004a] confirmed the strong dependence of CNA on solar wind speed (as shown in updated form in Figure 2), they also showed that the direction of the interplanetary magnetic field was important. Given the dependence of CNA on substorm activity [e.g., Aminaei et al., 2006; Kavanagh et al., 2002; Hargreaves et al., 1997] this is not surprising. The IMF B Z component plays an important role in determining the effectiveness of HSSs on electron precipitation and a southward orientated field is the key factor in building energy for substorm release [Wild et al., 2009; Morley and Freeman, 2007]. [28] Figure 7 illustrates one aspect of the effect of B Z by comparing the MLT and magnetic latitude variation of CNA (from the NORSTAR riometers) as a function of day from epoch and whether the daily median IMF B Z on the day prior to the HSS epoch is negative or positive (Figures 7a 7c). Figure 7a shows the median MLT-latitude variation for all events; Figure 7b is for negative median IMF B Z, and Figure 7c is for positive IMF B Z. The panels below show the zero epoch analysis of the IMF B Z (Figure 7d), solar wind speed (Figure 7e) and AE index (Figure 7f) for all (red), positive median-imf B Z (blue) and negative median-imf B Z (green). Note that if the median daily IMF B Z is mostly negative prior to the zero epoch then it tends to be biased negative throughout. The solar wind speed is not dependent on the binning by B Z such that any differences in CNA cannot be attributed to the solar wind speed. The plot of the median AE index shows that negative IMF B Z produces moderately more active conditions on average. The latitudinal structure of CNA during HSSs reveals a broad peak across the auroral zone. In terms of magnetic local time the morning peaks tends to flatten at lower latitudes/l-shells with a growth in relative importance of the night side peak compared to the morning peak. The CNA also remains at higher levels to a later MLT at lower latitudes; the afternoon minimum remains but is on average, sharper and shorter. The onset of CNA in the evening remains at a consistent MLT. The expansion of the morning sector is likely related to the drift-paths in the inner magnetosphere; less of the particles are lost to the magnetopause than at higher latitudes. The CNA shows a notable difference for each day of 8of13

Figure 7. Magnetic latitude versus MLT versus mean CNA from NORSTAR for (a) all events, (b) events with average IMF B Z negative for epoch 2 and (c) events with average IMF B Z positive for epoch 2. There is a clear difference between Figures 7c and 7b with enhanced CNA at lower latitudes with the negative case for the first two days after onset. Also shown are (d) IMF Bz, (e) solar wind velocity, and (f) AE index for (red) all events, (green) events corresponding to Figure 7b and (blue) events corresponding to Figure 7c. the epoch analysis at all but the highest latitudes. There is good agreement with the results of Meredith et al. [2011], who observed low >30 kev electron fluxes pre-storm onset, peaking at greater than L = 5 (MLAT 63.5 ). Following storm onset there is an increase in the >30 kev electron flux across 21 13 MLT similar to the enhancement in CNA seen by the riometers. The CNA enhancement is greatest above 61 which is at L 4.4, close to Meredith et al. [2011] limit of L = 4.5 and the latitudinal extent is also greatest pre-noon with little precipitation/cna around dusk at all latitudes. Comparing the middle and bottom panels the CNA is more enhanced for events where the pre-epoch IMF is mostly southward, and that enhancement continues throughout the duration, probably due to the tendency for the IMF to remain biased toward negative (positive) if the prior-epoch daily median IMF B Z is negative (positive). The overall structure of the CNA as a function of latitude and MLT remains the same though lower latitudes observe a larger increase for 9of13

Figure 8. Epoch analysis of events split by season. In each panel the median values are shown for events 40 days around the spring equinox (blue), autumn equinox (green), summer solstice (red) and winter solstice (cyan). The median values are all events are presented in purple for comparison. Parameters presented are (a) CNA, (b) solar wind speed, (c) IMF BZ, (d) AE index, and (e) SYM-H index. negative events; enhanced coupling does not affect where the CNA occurs in MLT. The average difference between the B Z positive (Figure 7c) and B Z negative (Figure 7b) events peaks on day 0; it remains elevated before decaying after day 2. The pre-midnight average CNA is not enhanced by much between the two types of event whereas the morning sector shows more variation but peaks at 0.4 db higher on day 0. This is an increase by almost a factor of 2 between the positive and negative events, located at 69 N. At the lowest latitudes the average CNA difference is between 0.1 and 0.2 db. Clearly the IMF plays an important role in determining the level of electron precipitation during HSSs. [29] Given the generally observed tendency for geomagnetic activity to peak around the equinoxes one might expect that the HSSs that produce more precipitation would congregate about these times, yet there is no seasonal bias in these data. The spread of events across the year for negative and positive leading IMF are similar for both high median CNA and lower median CNA producing HSSs. This does not rule out a seasonal effect, rather it indicates that HSSs that produce larger CNA (indicating enhanced precipitation) occur independently of the season. 5.3. Seasonal Variation in the Observations [30] We investigate whether a seasonal effect is present in the CNA data by splitting the events by HSS arrival time as a function of day around the equinoxes and solstices and binning appropriately. Figure 8 shows the result of this exercise providing the median values for CAN (Figure 8a), solar wind speed (Figure 8b), IMF B Z (Figure 8c), AE index (Figure 8d), and SYM-H index (Figure 8e) for spring (blue), autumn (green), summer (red), winter (cyan) and all events (purple). The temporal resolution of the data has been reduced to hourly averages. Figure 2 showed a very slight equinoctial preference for occurrence of streams in our selection; however it also indicated that there was no bias in the solar wind speed, which is one of the dominant factors in determining the level of CNA. [31] In Figure 8a the CNA shows a marked seasonal difference; equinoxes show much higher median CNA in the morning sector whereas the solstices, particularly summer are depressed. Nighttime median values for each season are similar. [32] The solar wind speed (Figure 8b) indicates that there is no obvious biasing of events by speed with the median 10 of 13

Figure 9. Epoch analysis of the total flux of 32 kev electrons at geosynchronous orbit, measured by the LANL MPA instrument. The y axis is the local time, the x axis is the time from epoch and the color scale gives the average flux. (a d) The results for each season (as indicated above each plot), (e) the result for HSS where data were available. values for all cases being similar in agreement with the count provided in Figure 2. Although the median B Z (Figure 8c) shows no major difference between season, the trend-lines around which the data varies reveals that there is a seasonal variation. Taking the mean values of B Z for the 3 days after the zero epoch for each event we produced distributions for each season; the equinox distributions were skewed more negative than the solstices with median values of 0.63 (spring), 0.75 (autumn), 0.17 (summer), 0.13 (winter). This ranking matches the median CNA in Figure 8a giving credence to a seasonal effect. [33] In terms of the AE (Figure 8d) and SYM-H (Figure 8e) indices, overall there is little difference, certainly in peak values and decay times. The equinoxes do favor slightly higher median values than the solstices for SYM-H and this is reflected in the interquartile range with a small shift along the negative axis. However, there is not the large difference one might expect given the variation in CNA and it is unclear why the nighttime median CNA values cluster together splitting only in the daytime. [34] Figure 9 shows an epoch analysis of the total flux of 32 kev electrons measured at geostationary orbit by the MPA instrument on the Los Alamos National Laboratory (LANL) satellite [McComas et al., 1993]. Figures 9a 9d show the data split by season (as indicated above each plot), Figure 9e shows all of the data together. The data is presented in the same format as in Figure 4, with local time on the y axis and time from epoch on the x axis; the color scale represents the average flux. This is part of the source population of the precipitating electrons that produce the CNA and there is very little difference between the seasons. The equinoxes do show a higher flux level than summer but the difference is not large enough to explain the observed difference in the CNA level at any local time. Consequently it is unlikely that seasonal differences in the source population can explain the differences observed in the average seasonal CNA and another explanation must be sought. [35] One possibility is the effect that solar radio emission (SRE) has on CNA. A riometer is essentially a sensitive radio receiver and on those occasions when the Sun is emitting at the riometer frequency it can affect the received signal suppressing absorption and at extremes causing negative values of CNA. This effect will be largest in the summer months as the gain of the riometer beam in the direction of the Sun is much higher, for longer. To test this effect we looked at times when there was radio emission that could contaminate the IRIS riometer data. Observations of emission were provided by NOAA from Upice, in the Czech Republic, which measures at 33 MHz (http://www.ngdc. noaa.gov/stp/solar/solarradio.html#bursts). Given the separation of the riometer from the observing station and the difference in frequencies it is possible that not all events were identified; out of 1384 days (173 HSS events) only 274 contained emission. Binning the CNA by season and by whether SRE was occurring allowed us to examine the effect on the daily median values. The same pattern (reduced CNA in the summer daytime) that was shown in Figure 8 was found when there was no SRE identified; this suggests that it is unlikely that SRE is playing a role in the seasonal variation presented in Figure 8. Thus although it appears that season plays a role in the average level of CNA it is not clear what the mechanism is. The small change in the coupling efficiency between the solar wind and magnetosphere, indicated by the mean B Z level for each season does not seem enough to drive the difference when one considers the lack of variation in the AE and SYM-H indices and the electron source population. Also it is unclear why differences in the CNA are limited only to daylight hours. Further analysis of the effect of SRE on riometer data is warranted, using measurements of SRE that are perhaps better situated and closer in frequency to the riometer station. 6. Discussion [36] We have completed an epoch analysis of the effect of high speed solar wind streams on the precipitation of >30 kev electrons using 173 high speed streams. The interaction of a high speed solar wind stream with geospace increases the average energetic electron precipitation (>30 kev) across both L-shell and MLT. Precipitation begins as the CIR interacts with the magnetosphere (including potentially through pressure enhancements) during the day prior to HSS arrival. The MLT variation through the events is (overall) consistent with the established diurnal variation which is explained in terms of the substorm 11 of 13

injection and subsequent drift of electrons combined with scattering into the loss cone via whistler mode chorus waves. The location of the peak in CNA as a function of L-Shell and local time is consistent with other studies [e.g., Meredith et al., 2011]. Following onset the CNA level increases by a small but statistically significant margin during the afternoon minimum, contrary to the results of simple statistical studies. This could be partly due to the expansion in MLT of the precipitation of >30 kev electrons (as indicated by Meredith et al. [2011, Figure 6]). This is also the time when relativistic electrons are predicted to precipitate due to interaction with EMIC waves [e.g., Summers et al., 1998] and when Ranta et al. [1997] speculated that isolated CNA spikes in IRIS were due to electrons with energies in excess of 100 s of kev. [37] The riometer observations allow us to probe the response at a higher time resolution than satellites can offer; this reveals a definite ramp up of precipitation which peaks about 12 h after the HSS arrives; we interpret this as the build-up of energy in the magnetosphere due to intermittent reconnection on the dayside with the Alfvénic structures in the IMF. Whether there is a similar delay in terms of the MLT response is uncertain. [38] The effectiveness of the HSS in terms of precipitation is strongly controlled by the IMF; Events where the average IMF B Z on the preceding quiet day (over a day before the zero epoch) is negative tend to have increased precipitation throughout. If the IMF-B Z is predominantly negative before the onset, it tends to remain that way throughout the event, thus energy coupling is prolonged/enhanced. The opposite is also true - that if the IMF-B Z is predominantly positive before the onset it tends to remain that way throughout the event. Thus energy coupling is curtailed/suppressed. 7. Summary and Conclusions [39] 1. The MLT variations of precipitation can be broadly explained in terms of substorm injections and gradient curvature drift. The location of the peak precipitation (in terms of CNA) in L-shell and local time is consistent with the results obtained by Meredith et al. [2011] using polar orbiting satellite data. [40] 2. Following the arrival of the HSS there is an enhancement in the CNA levels across all local times, including the statistical deep minimum in the afternoondusk sector. CNA levels remain elevated above pre-hss arrival times for about four days. [41] 3. The average level of precipitation following a highspeed stream arrival is highly dependent on the average state of the IMF B Z component on the day prior to the stream arrival. An average negative IMF B Z will produce higher CNA across all L-shells and MLT up to 100% higher than an average positive IMF B Z. [42] 4. There is a seasonal variation in the level of CNA that cannot be simply attributed to increased solar wind - magnetosphere coupling around the equinoxes compared to the solstices. Epoch analyses of geomagnetic indices (AE and SYM-H) reveal no corresponding significant seasonal differences and an analysis of the lower energy portion of the source population (32 kev) suggests that this is not the source of the observed differences. The CNA result might be a combination of changes in the mesospheric chemistry and the prevalence of solar radio emission contamination in the summer; however preliminary analysis tends to rule out the latter as playing a substantial role. [43] Acknowledgments. We acknowledge the support of the European Community - Research Infrastructure Action under the FP6 Structuring the European Research Area Programme, LAPBIAT (RITA-CT-2006-025969). A.J.K. was supported by the Science and Technology Facilities Council (grant ST/G002401/1). The Imaging Riometer for Ionospheric Studies (IRIS) is operated by the Space Plasma Environment and Radio Science (SPEARS) group, Department of Physics, Lancaster University (UK), in collaboration with the Sodankylä Geophysical Observatory. Operational support for NORSTAR (formally the CANOPUS riometers array) was provided by the Canadian Space Agency. We acknowledge the NORSTAR team for providing the riometers data used in this study and Don Wallis, who was principally responsible for the scientific operation of the CANOPUS riometer array. Thanks to Michelle Thomsen, Mike Henderson, and the LANL MPA team for the geosynchronous satellite data. [44] Philippa Browning thanks the reviewers for their assistance in evaluating this paper. References Alfonsi, L., et al. (2008), Probing the high latitude ionosphere from groundbased observations: The state of current knowledge and capabilities during IPY (2007 2009), J. Atmos. Sol. Terr. Phys., 70, 2293 2308, doi:10.1016/j.jastp.2008.06.013. Aminaei, A., F. Honary, A. J. Kavanagh, E. Spanswick, and A. Viljanen (2006), Characteristics of night-time absorption spike events, Ann. Geophys., 24(7), 1887 1904, doi:10.5194/angeo-24-1887-2006. Baker, D. N., E. W. Hones, R. D. Belian, P. R. Higbie, R. P. Lepping, and P. Stauning (1982), Multiple-spacecraft and correlated riometer study of magnetospheric substorm phenomena, J. Geophys. Res., 87, 6121 6136, doi:10.1029/ja087ia08p06121. Borovsky, J. E., and M. H. Denton (2006), Differences between CMEdriven storms and CIR driven storms, J. Geophys. Res., 111, A07S08, doi:10.1029/2005ja011447. Borovsky, J. E., and M. H. Denton (2010), On the heating of the outer radiation belt to produce high fluxes of relativistic electrons: Measured heating rates at geosynchronous orbit for high speed stream driven storms, J. Geophys. Res., 115, A12206, doi:10.1029/2010ja015342. Borovsky, J. E., and J. T. Steinberg (2006), The calm before the storm in CIR/magnetosphere interactions: Occurrence statistics, solar wind statistics, and magnetospheric preconditioning, J. Geophys. Res., 111, A07S10, doi:10.1029/2005ja011397. Browne, S., J. K. Hargreaves, and B. Honary (1995), An imaging riometer for ionospheric studies, Electr. Comm. Eng. J., 7, 209 217, doi:10.1049/ ecej:19950505. Cane, H. V., and I. G. Richardson (2003), Interplanetary coronal mass ejections in the near-earth solar wind during 1996 2002, J. Geophys. Res., 108(A4), 1156, doi:10.1029/2002ja009817. Clilverd, M. A., A. Seppälä, C. J. Rodger, P. T. Verronen, and N. R. Thomson (2006), Ionospheric evidence of thermosphere-to-stratosphere descent of polar NO X, Geophys. Res. Lett., 33, L19811, doi:10.1029/ 2006GL026727. Clilverd, M. A., A. Seppälä, C. J. Rodger, N. R. Thomson, J. Lichtenberger, and P. Steinbach (2007), Temporal variability of the descent of highaltitude NOx inferred from ionospheric data, J. Geophys. Res., 112, A09307, doi:10.1029/2006ja012085. Denton, M. H., J. E. Borovsky, R. M. Skoug, M. F. Thomsen, B. Lavraud, M. G. Henderson, R. L. McPherron, J. C. Zhang, and M. W. Liemohn (2006), Geomagnetic storms driven by ICME and CIR dominated solar wind, J. Geophys. Res., 111, A07S07, doi:10.1029/2005ja011436. Denton, M. H., J. E. Borovsky, R. B. Horne, R. L. McPherson, S. K. Morley, and B. T. Tsurutani (2008), High-speed solar wind streams: A call for key research, Eos Trans. AGU, 89(7), 62, doi:10.1029/ 2008EO070002. Detrick, D. L., and T. J. Rosenberg (1990), A phased-array radiowave imager for studies of cosmic noise absorption, Radio Sci., 25, 325 338, doi:10.1029/rs025i004p00325. Hargreaves, J. K., S. Browne, H. Ranta, T. J. Rosenberg, and D. L. Detrick (1997), A study of substorm-associated spike events in auroral absorption using imaging riometers at South Pole and Kilpisjärvi, J. Atmos. Terr. Phys., 59(8), 853 872, doi:10.1016/s1364-6826(96)00061-2. Honary, F., S. R. Marple, K. Barratt, P. Chapman, M. Grill, and E. Nielsen (2011), Digital beam-forming imaging riometers systems, Rev. Sci. Instrum., 82, 031301, doi:10.1063/1.3567309. Kavanagh, A. J., and M. H. Denton (2007), High-speed solar-wind streams and geospace interactions, Astron. Geophys., 48, 6.24 6.26. 12 of 13

Kavanagh, A. J., F. Honary, I. W. McCrea, E. Donovan, E. E. Woodfield, J. Manninen, and P. C. Anderson (2002), Substorm related changes in precipitation in the dayside auroral zone: A multi-instrument case study, Ann. Geophys., 20(9), 1321 1334, doi:10.5194/angeo-20-1321-2002. Kavanagh, A. J., M. Kosch, F. Honary, A. Senior, S. R. Marple, E. E. Woodfield, and I. W. McCrea (2004a), The statistical dependence of auroral absorption on geomagnetic and solar wind parameters, Ann. Geophys., 22, 877 887, doi:10.5194/angeo-22-877-2004. Kavanagh, A. J., S. R. Marple, F. Honary, I. W. McCrea, and A. Senior (2004b), On solar protons and polar cap absorption: Constraints on an empirical relationship, Ann. Geophys., 22, 1133 1147, doi:10.5194/ angeo-22-1133-2004. King, J. H., and N. E. Papitashvili (2005), Solar wind spatial scales in and comparisons of hourly Wind and ACE plasma and magnetic field data, J. Geophys. Res., 110, A02104, doi:10.1029/2004ja010649. Little, C. G., and H. Leinbach (1959) The riometer: A device for the continuous measurements of ionospheric absorption, Proc. IRE, 37, 315 320. Longden, N., M. H. Denton, and F. Honary (2008), Particle precipitation during ICME driven and CIR driven geomagnetic storms, J. Geophys. Res., 113, A06205, doi:10.1029/2007ja012752. McComas, D. J., S. J. Bame, B. L. Barraclough, J. R. Donart, R. C. Elphic, J. T. Gosling, M. B. Moldwin, K. R. Moore, and M. F. Thomsen (1993), Magnetospheric plasma analyzer: Initial three-spacecraft observations from geosynchronous orbit, J. Geophys. Res., 98(A8), 13,453 13,465, doi:10.1029/93ja00726. McPherron, R. L., and J. Weygand (2006), The solar wind and geomagnetic activity and function of time relative to corotating interaction regions, in Recurrent Magnetic Storms: Corotating Solar Wind Streams, Geophys. Monogr. Ser, vol. 167, edited by B. Tsurutani et al., pp. 125 137, AGU, Washington, D. C., doi:10.1029/167gm12. Meredith, N. P., R. B. Horne, and R. R. Anderson (2001), Substorm dependence of chorus amplitudes: Implications for the acceleration of electrons to relativistic energies, J. Geophys. Res., 106(A6), 13,165 13,178, doi:10.1029/2000ja900156. Meredith, N. P., R. B. Horne, M. M. Lam, M. H. Denton, J. E. Borovsky, and J. C. Green (2011), Energetic electron precipitation during highspeed solar wind stream driven storms, J. Geophys. Res., 116, A05223, doi:10.1029/2010ja016293. Morley, S. K., and M. P. Freeman (2007), On the association between northward turnings of the interplanetary magnetic field and substorm onsets, Geophys. Res. Lett., 34, L08104, doi:10.1029/2006gl028891. Randall, C. E., et al. (2005), Stratospheric effects of energetic particle precipitation in 2003 2004, Geophys. Res. Lett., 32, L05802, doi:10.1029/ 2004GL022003. Ranta, H., A. Ranta, J. Hargreaves, and S. Browne (1997), Localized absorption events in the afternoon sector, J. Atmos. Sol. Terr. Phys., 59(8), 891 902, doi:10.1016/s1364-6826(96)00063-6. Richardson, I. G., and H. V. Cane (2004), Identification of interplanetary coronal mass ejections at 1 AU using multiple solar wind plasma composition anomalies, J. Geophys. Res., 109, A09104, doi:10.1029/ 2004JA010598. Senior, A., A. J. Kavanagh, M. J. Kosch, and F. Honary (2007), Statistical relationships between cosmic radio noise absorption and ionospheric electrical conductances in the auroral zone, J. Geophys. Res., 112, A11301, doi:10.1029/2007ja012519. Seppälä, A., C. E. Randall, M. A. Clilverd, E. Rozanov, V. L. Harvey, and C. J. Rodger (2009), Geomagnetic activity and polar surface air temperature variability, J. Geophys. Res., 114, A10312, doi:10.1029/ 2008JA014029. Summers, D., R. Thorne, and F. Xiao (1998), Relativistic theory of waveparticle resonant diffusion with application to electron acceleration in the magnetosphere, J. Geophys. Res., 103(A9), 20,487 20,500, doi:10.1029/98ja01740. Tsurutani, B. T., R. L. McPherron, W. D. Gonzalez, G. Lu, N. Gopalswamy, and F. L. Guarnieri (2006), Magnetic storms caused by corotating solar wind streams, in Recurrent Magnetic Storms: Corotating Solar Wind Streams, Geophys. Monogr. Ser, vol. 167, edited by B. Tsurutani, et al., pp. 1 17, AGU, Washington, D. C., doi:10.1029/167gm03. Turner, N. E., E. J. Mitchell, D. J. Knipp, and B. A. Emery (2006), Energetics of magnetic storms driven by corotating interaction regions: A study of geoeffectiveness, in Recurrent Magnetic Storms: Corotating Solar Wind Streams, Geophys. Monogr. Ser, vol. 167, edited by B. Tsurutani, et al., pp. 113 124, AGU, Washington, D. C., doi:10.1029/167gm11. Wild, J. A., E. E. Woodfield, and S. K. Morley (2009), On the triggering of auroral substorms by northward turnings of the Interplanetary Magnetic Field, Ann. Geophys., 27(9), 3559 3570, doi:10.5194/angeo-27-3559- 2009. Wild, P., F. Honary, A. J. Kavanagh, and A. Senior (2010), Triangulating the height of cosmic noise absorption: A method for estimating the characteristic energy of precipitating electrons, J. Geophys. Res., 115, A12326, doi:10.1029/2010ja015766. 13 of 13