Journal Printed
oj Afmosphuic and Terrewiul m Great Britam.
Physics, Vol
4X, Nos 9-10,
pp. 817-826.
MU-916Yr86S3.00+ Pergamon Journals
1986.
.I0 Ltd.
Seasonal and tidal variations of neutral temperatures and densities in the high latitude lower thermosphere measured by EISCAT S. KIRKW~~D EISCAT, Ramljordmoen, N-9027 Ramtjordbotn,
Norway
(Receivedfor publication 1 May 1986)
Abstract-Measurements of ion temperature, ion-neutral collision frequency and ion drift in the E-region from the period December 1984 to November 1985 are used to derive neutral temperatures, densities and meridional winds in the altitude intervals 92-120 km, 92-105 km and 92-120 km, respectively. Altitude profiles of temperature and density and their seasonal variations are compared with the CIRA 1972 and MSIS 1983 models and the effects of geomagnetic activity are demonstrated. Semi-diurnal tidal variations in all three parameters are derived and the comparison with lower latitude measurements is discussed.
INTRODUCTION Incoherent scatter measurements of temperature and density in the lower thermosphere have made a major contribution to our understanding of that part of the Earth’s atmosphere. The altitude interval 9&120 km is relatively difficult to measure by other techniques, ‘being above the altitude reached by most sounding rockets but below that covered by most satellites. Measurements of the lower thermosphere by the Millstone Hill, Saint Santin and Arecibo incoherent scatter radars (e.g. SALAH and EVANS, 1973; SALAH and WAND, 1974 ; WAND, 1983a,b ; BERNARD, 1974 ; HARPER and WAND, 1978; HARPER, 1981) have played an important part in the development of thermospheric models (e.g. ALCAYDB, 1981; HEDIN et al., 1977; HEDIN, 1977, 1983) and models of tidal structure (e.g. FORBES, 1982a,b). The EISCAT measurements so far available cover a much shorter time interval (one year) than those from the other radars and so cannot yet provide comparable constraints on the theoretical models. They are, however, from a much higher latitude (70”N), where conditions are not well known, so that even preliminary results can provide worthwhile new information. An important item of interest at these high latitudes is energy input to the thermosphere during magnetically active conditions and before we can study this we need a better understanding of the ‘normal’ quiet conditions and of other sources of variations, such as tides.
EXPERIMENTAL TECHNIQUE AND DATA ANALYSIS The EISCAT incoherent scatter radars have been described by FOLKESTADet al. (1983) and the common
operating modes have been described conveniently by BARON and PERSIAN (1985). The measurements described here were made with the UHF radar, which has been making regular E-region measurements since the beginning of 1984 (in Common Program CP-1). E-region measurements are made using the multipulse technique (FARLEY, 1972) to measure the plasma autocorrelation function and hence derive ion and electron temperatures, electron densities, ion drift and ionneutral collision frequencies. During most of 1984 the experimental scheme used was a 5 x 15 ps multipulse, essentially as described by KOFMAN and LATHUILLERE (1985), but with the addition of a true zero-lag of the autocorrelation function measured by transmitting a single 15 ps pulse at a different frequency. As discussed by those authors, this scheme provides useable measurements only when E-region densities are enhanced above quiet levels by particle precipitation, i.e. only during active conditions which occur predominantly in the 12 h centred on local magnetic midnight. At the end of 1984 a new experimental scheme was implemented which allowed useable measurements to be made at lower electron densities, including those normally present during quiet, day-time conditions, thus providing a more uniform coverage more suitable for studying seasonal and tidal effects. The pulse schemes used are illustrated by Fig. 1. The long pulses are used for F-region measurements and the short pulse sequences for the E-region measurements described here. The 3 x 20 ps and 4 x 20 ~LSmultipulses and the single 20 ps pulse are used to measure different elements of the autocorrelation function, as illustrated by Fig. 2. This is found, with the particular technical constraints of the EISCAT UHF system, to give better results than a simple multipulse sequence. A factor of
817
818
S.
KIRKWWD
FO I F5 F3 Fl F4 F2 I
I
/
I
0
200
400
600
I
800
I
I
1000
2ooops
1. Sequence of radar pulses transmitted,
repeated every 9 ms. Fn denotes the transmission frequency, 929.5tO.S n MHz.
2.5 improvement in signal-to-noise ratio compared to measured as far as the first zero-crossing from about the scheme described by KOF’MAN and LATHUILLERE 95 km upwards and as far as the second zero-crossing
(1985) is achieved, corresponding to a 2.5 times reduction in the electron density required for useable measurements. E-region measurements are made at altitudes from 84 km to 168 km, at 2.9 km intervals, with approximately 3 km altitude resolution (i.e. 50% of the signal comes from a 3 km altitude interval centred on the nominal altitude). The lower limit is determined by the need to avoid excessive ground clutter and the upper limit by the space available to store the results. As can be seen in Fig. 2, autocorrelation functions are
from about 104 km upwards, although these limits can vary somewhat depending on the ionospheric conditions. The inclusion of a true zero-lag provides useable measurements even at the highest altitudes, where the first zero-crossing approaches 40 ps. Measurements below 90 km do not extend to the longest lags, because of ground clutter contamination and are intended for Doppler shift estimation only, as the measured autocorrelation function is too short to provide reliable estimates of other parameters. Fitting of ionospheric parameters to the measured autocorrelation functions is performed by routines developed by G. Lejeune (LEJEUNE,1979). The application of these routines in determining temperatures and ion-neutral collision frequencies has been discussed by LATHUILLEREet al. (1983), KOFMANand LATHUILLERE(1985) and FLA et al. (1985). As discussed by those authors, it is not usually possible to determine collision frequency and both ion and electron temperatures simultaneously. In this work, therefore, electron and ion temperature were assumed equal in the 90-105 km altitude interval, where this is usually expected to be valid, so that collision frequencies could be determined, and a model of collision frequency was assumed for altitudes above 105 km, where collisions have a much smaller effect on the 160 km 130 km form of the autocorrelation function and differences between ion and electron temperatures might be expected and are of interest. Large differences between electron and ion temperatures have occasionally been observed at low altitudes (WICKWAR et al., 1981 ; I I I L 1 I I 1 1 3oop 200 0 100 200 300 0 100 SCHLEGELand ST.-MAURICE, 1981) and in such conthe collision frequencies determined as Fig. 2. Example autocorrelation functions measured 23 IS-- ditions described above will be wrong. However, the presence 2320 UT on 5 November 1985 at the altitudes shown. The open square shows the zero-lag measured by the single 20 ps of such anomalous heating should be evident in the pulse at frequency F2, the crosses show the Iag estimates temperatures determined above 105 km, and, in fact, measured by the 4 pulse sequence at F3 and the open circles no significant indications of such events were found show those measured by the 3 pulse sequence at Fl The solid in the data used here. The use of an inappropriate line is the theoretical autocorrelation function chosen as the collision frequency model above 105 km could also best fit to the measurements.
Neutral temperatures and densities in the iower the~asphere Table I. Dates and times of measurements
Date 12/13 Dec. 1984 28129 Jan. 1985 14/15 Feb. 1985 16/17 Apr. 1985 I4,/1.5May 1985 21/22 May 1985 E/26 Jun. 1985 06jO7 Aug. 1985 13114Aug. 1985 03/04 Sep. 1985 lo/l1 Sep. 1985 29/30 Oct. 1985 05/06 Nov. 1985 12/13 Nov. 1985
Per cent data useable (104 km)
Time (UT) 120&1200 1200-1200 12o(t1200 110&l 100 080~8~ 1200-1200 1200-1200 080~800 1200-1200 L200--1200 1800-1800 0900-0900 090&0900 23OC-2300
53 72 78 53 85 94 96 64 99 44 84 18 II 42
Sodankyla 3h K indices 3212 6676 2456 3103 1114 1434 I154 0002 3376 0101 6532 3221 2246 2211
4523 7.511 5211 2010 1331 3101 4223 0100 3432 0201 1211 0000 7332 5375
lead to erroneous results, and this is discussed in more detail below. The dates and times for which data are available are shown in Table 1, together with an indication of the magnetic activity given by the Sodankyll (northern Finland) 3 h K indices. A period of 24 h was used in each case, chosen to be the 24 h with most uniform coverage in those cases when more than 24 h data were available, and the completeness of coverage is indicated by the percentage of useable data at 104 km altitude. ‘Useable’ here is taken as an uncertainty of
819
25% or less in the fitted ion temperature (with 5 min integration) and is found to correspond to an electron density of 5 x 10” me3 or higher at 104 km for typical operations with 1.2 MW transmitted power. As can be seen from Table 1, coverage is best near midsummer and during magnetically disturbed periods.
NEUTRALDENSITY
VARIATIONS
The relationship between ion-neutral collision frequency and neutral density and composition has been discussed by BANKSand KOCKART~(1973) and the use of this relationship in connection with incoherent scatter measurements by LATHUILLEREet al. (1983). Since the ion-neutral collision frequency is sensitive to both density and composition (particularly the proportion of atomic oxygen) of the neutral atmosphere, and both these parameters vary from one atmospheric model to another, a comparison with models is best made by computing collision frequencies for the models and comparing directly with the measurements, rather than trying to convert the measurements to densities. Such comparisons are made here with the CIRA (1972) and MSIS (HEDIN, 1983) models. A scale of neutral density, assuming 0% atomic oxygen, is included on the figures as a rough guide only. An example of collision frequency measurements over a 24 hperiod is shown in Fig. 3. Mean-over-day profiles for different seasons and interpolated values at fixed altitudes over the year are shown in Figs, 4 and 5, respectively. Only measurements with less than
4 3.5
4 z I
3.5
t
2 $
4 3.5
4 3.5
I
I
I8
24
I 06
12
UT
Fig. 3. Ion-neutral collision frequency estimates for the 24 h 1200-1200 UT on 21/22 May 1985 at the altitudes shown. The error bars are the uncertainties estimated by the fitting routines. The curves show the variation over the day (mean, diurnal and semi-diurnal component) fitted by Fourier analysis.
820
S. KIRKWOOD
alt (km) 105
100
95
lo4 coil freq(Hz) (a)
alt. (km) 105
100
lo4 toll. freq(Hz)
IO3 fb)
I
ait (km)
, ,1!1111
I
,I
early summer/autumn
lo3
10' co~~.freq.(Hz) (c)
Fig. 4. Altitude profiles of ion-neutral collision frequency, averaged over 24 h, for each day shown. The solid lines show the models described in the text. The small open circles and the dashed line show values computed from the CIRA 1972 (70”N) and MSIS 1983 (70”N, 20”E, Ap = 10, F10.7= 70) models, respectively. The CIRA and MSIS model profiles shown are for (a) mid-summer, (b) mid-winter and (c) September equinox. 50% uncertainty were included in the averaging and only those where the fitting routines were able to determine a collision frequency which was significantly better than the starting model in the
iteration. Quite often, in the iterative fitting procedure, no better fit than the starting model is found, either because the model is correct or because the measured autocorrelation function is too noisy. Since it is not.generally possible to distinguish between these two classes of result, and including a wrong model can be shown to bias the results, only genuinely fitted results can be used in the averaging. Only those averages where at least 36 estimates (corresponding to 3 h of data) spread over at least 12 h of the day are available are included, in order to avoid possible bias due to semi-diurnal tides (see below). As Figs. 4 and 5 show, there is very little seasonal variation, apparently less than predicted by at least the CIRA model, and the measurements show consistently higher collision frequencies than either model. There is a tendency to lower collision frequencies in mid-summer than mid-winter between 95 and 100 km, in agreement with the models, however. There is also consistency with the temperature profiles (see below). In winter the collision frequency (neutral density) scale height is about 6 km between 92 and 105 km altitude, corresponding to the almost constant temperatures in that height interval. In summer the scale height increases steadily from about 5 km at 92 km altitude to about 8 km at 105 km altitude, in agreement with the steadily increasing temperatures. In terms of assessing the quality of the models, the agreement between model and experiment should probably be considered good. The differences correspond to an offset in altitude profiles of only l-2 km in the presence of a scale height of 5-8 km and a measurement resolution of 3 km. However, in terms of assessing how good the models are for use in deriving accurate temperature estimates from incoherent scatter data, the measurements indicate a significant error. The use of an incorrect collision frequency model in deriving ion temperatures (when collision frequency is not fitted) can introduce large errors. In the collision dominated region (below about 90 km in this case) the width of the incoherent scatter spectrum depends on the ratio of temperature to collision frequency (TANEBAUM, 1968 ; TEPLEY and MATTHEWS, 1978 ; FUKUYAMA and KOFMAN, 1980), i.e. a 50% too low collision frequency model will result in a 50% too low temperature estimate. At slightly higher altitudes, as the collision frequency becomes smaller, the effect is less severe. The effect of a change in collision frequency model on the temperature estimates has been tested by comparing results where a model was assumed with those where collision frequency was fitted, and is illustrated by Fig. 6. This shows that a 30-50% underestimate of collision frequency, as would
Neutral temperatures and densities in the lower thermosphere I
3.1041
J
I
t
I
/
I
I
I
1
I
I
821
i
FMAMJJASON
time
of
year
Fig. 5. Seasonal variation of ion-neutral collision frequency compared with CIRA 1972 and MSIS 1983 models, as in Fig. 4. The error bars represent the standard deviation from the mean and therefore represent both tidal and statistical fluctuations.
occur if we used the CIRA 1972 or MSIS 1983 models, would result in significant (10-20*/L) underestimates of ion tem~rature at 95 km, but reducing to an insignificant level (l-2%) at 105 km. Thus the assumption of model values for collision frequency above 105 km should not lead to any significant errors in ion temperature determination. The seasonal variation is not yet well determined by the EISCAT measurements, so it seems inadvisable
to try to derive an improved model with seasonal variation. As a first step, a simple two-season model can be fitted. Only the mid-summer months June and 105 1.0
-
1,
100 ,
95
t I{ / , ,//
90 alt
(km)
August seem to show significantly different results from the rest of the year, so a ‘summer’ model referring only to these two months and a ‘winter’ model referring to the rest of the year seem appropriate. It is clear from Fig. 4 that the scale height increases with altitude and the simplest form which can be assumed for this increase is a linear one. Following BANKS and KOCKARTS (1973), if we assume a linear increase in atmosphere pressure scale height with altitude (corresponding to a linear increase in tem~rature), we can write a simple expression for neutral number density and hence ion-neutral collision frequency (assuming constant composition) in the vicinity of some reference altitude
I
’
vin = v0 exp -(I +~)(z-zc)/(Ho+0.5~(z-zo)),
0.0 lo3
IO4
Vi, Is-‘)
Fig. 6. Errors in estimates of ion temperature
(TJ resulting from an error in assumed ion-neutral collision frequency (v,.). Each point represents a 24 h average at a particular height and is derived by comparing T, estimates where v,, was determined simultaneously (assumed correct) with r, estimates where a model value of v,, was assumed. The solid line is intended to represent the maximum expected error.
where B is the scale height gradient dH/dz, vi,, is the ion-neutral collision frequency at height z and Ho,v, are the scale height and collision frequency, respectively, at reference height Q. In fitting models of this form to the measurements, Ho and j3 have been derived from a least squares fit to the temperature profiles (see below) and v,, from a subsequent fit to the collision frequency profiles. The resultant ‘winter’ model has fi = 0.13, Ho = 6.05 km and v0 = 4.5 x lo3 Hz (with reference height 100 km), and the ‘summer’ model /I = 0.24, H0 = 6.63 km, v0 = 3.8 x lo3 Hz. These models are shown by the solid lines in Fig. 4, where the ‘winter’ model is shown on both Figs. 4b and 4c. They give a reasonable fit to the measurements and are much closer than either the CIRA or MSIS models.
822
S. KIFCKWGOD
SEASONALVARIATIONSOF NEUTRALTEMPERATURE An example of temperature measurements over 24 h is shown in Fig. 7. Mean-over-day profiles are shown in Fig. 8 and the seasonal variation is shown by interpolated values at fixed altitudes in Fig. 9. Comparison is made with the CIRA (1972) and MSIS (HEDIN, 1983) models, where the computations for the MSIS model were made for solar minimum (FlO, = 70) and quiet magnetic conditions (Ap = 10). Only data with less than 25% uncertainty in the ion temperature estimate are included in the averages. Below 105 km altitude only those estimates where the ion-neutral collision frequency was also determined are included. As indicated by Fig., 6, a wrong model of collision frequency at those altitudes would give biased temperature estimates. The model used in the data analysis (when collision frequency was not successfully fitted) was based on the CIRA model atmosphere and was evidently incorrect. Further, periods of suspected Joule heating have been excluded, so that ion temperatures can be assumed equal to neutral temperatures. Again, only those averages which represent at least 3 h of data spread over at least 12 h are included, in order to avoid possible bias due to semi-diurnal tides. The agreement with the CIRA 1972 model is rather
poor. The asymmetry between the equinoxes and the high summer temperatures in the model are not supported by the measurements. This is perhaps not surprising, as the model was based on only a very small number of temperature measurements at high latitudes. Clearly, the MSIS model fits the measurements much better, but with some interesting discrepancies. The most notable differences from the MSIS model are at the highest altitude shown, 120 km, and are clearly correlated with magnetic activity, as indicated by the sum of the Sodankyla 3 h K indices for the period of measurement. The best illustration of the temperature enhancement due to magnetic activity is a comparison of the profiles from 6/7 August, 13/14 August and 3/4 September. The first and last of these days were magnetically quiet and the temperature profiles are very similar. The middle day, however, was active, in fact coming at the end of a major global storm, and the temperatures are considerably higher. The temperature enhancement amounts to about 10K at 104 km altitude, increasing to about 60K at 120 km. This is very close to the temperature increase predicted by the MSIS model (HEDIN, 1983) for an Ap of 60 (as observed for that day). Further differences are the consistently lower temperatures in winter, generally about 20K lower than the model at altitudes below 110 km and about 40K lower than the model near the equinoxes between 105
350 ;i
250
c 300
250
, 50
I.111 )!I
1, ’
‘0
‘-
h
,I
12
I 18
I 24 UT
Fig. 7. As Fig. 3, but for temperature.
I 06
12
Neutral temperatures and densities in the lower thermosphere ait
I
(km) ' 120 -
I
I .A
.
86
.I
summer
l
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+
0 0 A ' .
. ..Kx%'. ,a rm: ye';
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823
n
14115May 21/22May 25/26June 617Aug. 13114Aug. 3/4Sepf
I
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f
200
300
400
I Temp.(K)
(a) alt (km) 120
/
’
I
,
/ t’xa , r.da 0 l
.,a *
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.
’
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winter 0 291300ct. 0 516 Nov. * 12113Nov l l n
90
’ 100
l40
0
ISd
I
200
300
JFMAMJJASOND Time of year
12if3Dec. 28/29Jan. 14115Feb
Fig. 9. As Fig. 5, but for temperature, plus an indication of the geomagnetic activity (uppermost data) represented by the sum of the Sodankyla K indices for each period of measurements.
/ 400 Temp.(K)
th~~ospheric temperatures, but there are indications that the amplitude of the semi-annual variation is much larger than that modelled and that the winter temperatures are rather lower than the model values.
tb) alt ikmlI 120
0
SEMI-DIURNAL
,.
TIDES
I
110
*
0 *.
l
o
, I’
spring/autum~
,’
l16/17Aprll
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~IOlll Sept
0 .Z,'
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The semi-diurnal tide is expected to be the dominant tidal model in the height interval 90-120 km (FORBES,
00,:
,, t
I)
D
c8 90
I
100
I
I
/
200
300
400 Temp
-I
(K
Cc)
Fig. 8. As
Fig.4, but
for temperature.
and 115 km altitudes. More measurements will be needed, particularly close to the equinoxes, to properly separate seasonal and magnetic activity-related effects. For the present, it seems that the MSIS (1983) model gives a fairly good representation of the lower
1982a,b). Slightly smaller amplitude diurnal tides may be present, but will not be easily resolvable with the present data set. The semi-diurnal tide is most clearly seen in measurements of ion velocity parallel to the magnetic field (Fig. IO), which represents, in this case, the component in that direction of the meridional neutral wind (assuming vertical tidal motion is much less than horizontal, as indicated by FORBES, 1982b). The tide can also be seen in collision frequency (neutral density) and temperature me~urements (Figs. 3 and 7, respectively), but less clearly. as the coverage of the day is less complete and the data noisier. In order to examine the amplitude and phase profiles of these tidal variations, the most complete data sets have been selected and the tidal components
824
S. KIRKWOOD
50 -50 50 a 3 -50 i s 50 -50 1= 50 -50 50 -50
12
18
06
24 UT
Fig.10.As Fig. 3, but for ion drift parallel
alt (km 120
to the magnetic
12
field (inclination
76.5’).
alt (km) 120
110
1oc
100
90
90
120
120
110
110
too
100
I
$?J dens
I
I
10 20 30K 40 80 120mis 10 20 30 %
I
0
I
6
I
12
I
18
1 24lJT
I
I
I
I
Teiop, 10 20 30K wIndO 40 50 120mls dens0 10 20 30%
I
0
I
6
I
12
I
18
(b) (a) Fig. 11. Amplitude and phase (time of rn~irn~ amplit~dc) profiles for the semi-diu~al tides in neutral density (crosses), temperature (open circles) and southward wind (solid circles). Results are shown for the 4 days with most complete coverage of a 24 h period.
“I
24UT
825
Neutral temperatures and densities in the lower thermosphere
determined by Fourier transform. Results are shown in Fig. 11. If we consider the amplitude profiles, the meridional wind results are the clearest, with a distinct maximum in the southward wind of 70-140 m s- ’ at about 105 km on three of the four days shown. The rather different behaviour on the fourth day (13/14 August), where the strongest winds occur below 100 km, may be an effect of the unusually high level of magnetic activity at that time. The amplitude profiles of the temperature tides are noisier, but do generally indicate maximum amplitudes of about 1S-30K somewhere between 112 km altitude and the highest altitude shown. The collision frequency measurements do not cover a sufficient altitude interval for any maximum to be determined. The phase behaviour is similar for both temperature and southward wind variations, with peak temperatures generally reached 2-4 h after the maximum southward wind. The neutral density variations are approximately in phase with the southward wind. For comparison with earlier tidal measurements from the Millstone Hill (WAND, 1983b) and Saint Santin (BERNARD, 1974) radars, averages over the available measurements have been made (excluding the anomalous winds of 13/14 August) (Fig. 12). These show that the amplitude and phase variations of both the temperature and meridional wind are similar to those reported for the other mid-latitude radars. The amplitude of the tide in the meridional wind is rather larger and in the temperatures rather smaller at
EISCAT, in qualitative agreement with the theoretical predictions of FORBES(1982b) for higher latitude.
CONCLUSIONS The EISCAT incoherent scatter radar has provided measurements of neutral densities, temperatures and meridional winds in the lower thermosphere at 70”N latitude for all times of the day and all seasons of the year. Comparison of the seasonal variation of daily mean temperatures and densities with the CIRA 1972 and MSIS 1983 atmospheric models has shown that neutral density is fairly well modelled. The models, however, are not sufficiently accurate that they can be used in incoherent scatter temperature determination. The MSIS temperature model is found to be reasonably accurate, both in modelling the seasonal variation and the effects of geomagnetic activity. There is, however, some evidence that the semi-annual temperature variation between 105 and 1I5 km is larger than that modelled, with the lowest temperatures occurring near the equinoxes, and that temperatures below 110 km are rather lower than the model values
alt
0
(km1I 120
10 20 30K
’
0
6
12
T’T ’
18
: . LT
18
+LT
I
110
100
90 120
110
100
90
i 0
I
I
I
40 80 120mis
I
t
/
0
6
12
Fig. 12.Comparison of the semi-diurnal tides in temperature and southward wind measured at EISCAT (circles, mean over available measurements) with those observed at Saint Santin (squares) (BERNARD,1974) and Millstone Hiil (triangles) (WAND, 1983).
during winter. The CIRA temperature model is found to be substantially in error. Semi-diurnal tidal variations in temperature, density and southward wind have been demonstrated and are found to show phase and amplitude behaviour very similar to those observed at Saint Santin and Millstone Hill. An exception is the amplitude of the tide in the southward wind, which is found to be much higher at EISCAT. ~ckn~w~~dgements-Thanks are particularly due to W. KOFMAN,for many fruitful discussions, to R. GRAS and G. LEJEUNEfor providing software, to the Sodankyll Geophysical Observatory. for their prompt provision of magnetic indices, and to the Director and staff of EISCAT for the many hours of successfut operations. The EISCAT Scientific Association is supported by the Centre National de la Recherche Scientifique of France. Suomen Akatemia of Finland, Max-Planck-Gesellschaft of the Federal Republic of Germany, Norges Almenvitenskaplige Forskningsrad of Norway, Naturvitenskapliga Forskningsradet of Sweden and the Science and Engineering Research Council of the United Kingdom.
826
S. tiKwo0~ REFERENCES
ALCAYD~:D. BANKSP. M. and KOCKARTSG. BARONM. and PERSSON K. BERNR. CIRA
1981 1973 1985 1974 1972
FARLEYD. FLA T., KIRKW~~D S. and SCHLEGEL K. FOLKESTAD K., HAGFORST. and WESTLUNDS. FORBESJ. FORBESJ. FUKUYAMAK. and KOFMANW. HARPERR. M. HARPERR. M. and WAND R. H. HEDINA. E. HEDINA. E. HEDINA. E., REBERC. A., NEWTONG. P., SPENCER N. W., BRINTONH. C., MAYR H. G. and POTTERW. E. KOFMANW. and LATHUILLERE C. LATHUILLERE C., WICKWARV. B. and KOFMANW. LEJEUNE G. SALAHJ. E. and EVANSJ. V. SALAHJ. E. and WAND R. H. SCHLEGEL K. and ST.-MAURICEJ. P. TANEBAUMB. S. TEPLEYC. A. and MATHEWSJ. D. WAND R. H. WAND R. H. WICKWAR V. B., LATHUILLERE C., KOFMANW. and LEJEUNE G.
1972 1985 1983 1982a 1982b 1980 1981 1978 1977 1983 1977
Annls GPophys. 31,515. Aeronomy. Academic Press, New York. EISCAT Technical Note 85/43. Kiruna. Sweden. J. atmos. terr. Phys. 36, 1105. COSPAR International Reference Atmosphere. Akademie-Verlag, Berlin. Radio Sci. 7, 661. Radio Sci. 20, 785. Radio Sci. 18, 867. J. geophys. Res. 81, 5222. J. geophys. Res. 87,524l. J. Geomagn. Geoelect. 32, 67. J. atmos. terr. Phys. 43,255. J. atmos. terr. Phys. 40, 887. J. geophys. Res. 82,2139. J. geophys. Res. 88, 10170. J. geophys. Res. 82, 2148.
1985 1983 1979 1973 1974 1981 1968 1978 1983a 1983b 1981
J. geophys. Res. 90,352O. J. geophys. Res. 88, 10137. EISCAT Technical Note 79/18 Kiruna. Sweden. Space Res. 13,267. J. geophys. Res. 79,4295. J. geophys. Res. 86, 1447. Phys. Rev. 171,215. J. geophys. Res. 83, 3299. J. geophys. Res. 88,720 1. J. geophys. Res. 88,721O. J. geophys. Res. 86,472 1.