Turbopause  Workshop  

NSF  CEDAR  Workshop  Boulder,  CO  

25  June  2010  

Where  is  the  turbopause?  

Nicolet  Blamont,  1963  Rees,  1972  Roper,  1996  

K  ~  0.81  ε/N2      

FluctuaOons  and  inner  scale  observaOons    Smith,  Thrane,  Lübken  (1997)  

69°  N  

K  ≈  D  

USSA76  ^  Summer  <  Winter  

“Mass  spectrometer”  Turbopause  matching  N2/Ar  raOos  to  Keddy  profile,  only  Kzz  

Danilov;  von  Zahn  et  al  (1990)  

69°  N  

7444 VON ZAHN ET AL.' MASS SPECTROMETRIC STUDIES

(I)e, j is taken proportional to an empirical constant Ke, the eddy coefficient, which is the same for all constituents j and is defined through [e.g., yon Zahn et al., 1983]

(I) e , j Ke = (2)

n{d(nj/n)/dz} where

(I)e,j vertical eddy flux of the constituent j; n total number density = •;jnj;

nj number density of the constituent j; z vertical coordinate.

For argon in the lower thermosphere and under steady state conditions the total diffusive flux is zero; hence

(I)m,Ar = -- (I)e,Ar Under these conditions one obtains

(3)

Ke = (4) n{d(n^r/n)/dz}

Measurements of altitude profiles n^r(Z) and n(z) yield the denominator of this ratio. The numerator, the molecular diffusion flux 0m,^r, can be calculated from the measured parameters (n^r; n) by employing standard kinetic theory of diffusion in gases [e.g., Chapman and Cowling, 1970]. The flux equation becomes particularly simple for the case of a binary gas mixture, say, for argon in "air." Utilizing in addition that the binary thermal diffusion factor for argon in air, OtAr,air , is much smaller than 1, one obtains

{•Ar dnAr mar g 1 d•zz 7} •m,Ar = -- nAr DAr,air • + +- (5) dz kT T

Thus in principle, Ke(Z ) can be calculated from (4). The result is very sensitive to the gradients of the parameters n^r and n, which cannot be measured with the accuracy required for this method. In order to circumvent this problem, we construct instead a model of the Ar distribution in which the altitude profile of K e is varied until a suitable fit to our observations is obtained (see section 8.3). The same model is used to generate 02 and O number densities which are added to the measured N 2 number densities to obtain the total number densities n.

It should be recognized, however, that the usefulness of the eddy coefficients K e derived in this way has certain limitations. Here we shall discuss briefly those of (1) the time scales connected with K e and (2) their "sensitivity" to vertical bulk motions.

2.1. Time Scales for Eddy Mixing According to Mange [1957] the lower thermosphere ad-

justs with a time constant r = Hi 2/D i (or H2/Ke, whichever is smaller) to a new turbulent situation. This argument conveys the impression that these compositional adjust- ments are completed in a considerably shorter time, say, at 150 km, in the lower thermosphere than at the turbopause near 105 km (owing to the much larger D i at 150 km). This is in fact not true for a case in which the turbulent intensity (but not the temperature profile) changes near the turbopause. The composition in the middle thermosphere must respond to changes in atmospheric composition near the turbopause

80 km

120 km

1_.0

m

1/,0 km

•:• 0.5 ¸

tLme

Fig. 1. Computer simulation of the response of the ratio n(Ar)/ n(N2) in the lower thermosphere to a sudden increase in turbulent intensity. Before t - 0 an eddy profile is assumed as given in USSA 1976. At the time t = 0 the eddy coefficient is increased by a factor of tOO, and its profile is shifted 20 km upward. It takes about t0 hours to fully mix the atmosphere up to an altitude of t t0 km.

as long as the latter is changing. Hence a steady state cannot be reached faster at 150 km than near the turbopause.

To obtain a semiquantitative picture of the effects of changing turbulent intensity on the composition of the lower thermosphere, we have studied them with the help of a one-dimensional, photochemical, and time-dependent model of the thermosphere. We adapted a code, originally em- ployed by yon Zahn et al. [1980] for studies of the Venus thermosphere, for terrestrial applications. We studied in particular the effects of sudden changes in the strength of eddy diffusion on the lower thermosphere composition. In an initial model experiment we prescribed solar, thermal, and turbulent conditions as defined in the U.S. Standard Atmo- sphere 1976 (USSA 1976). A steady state was reached after approximately 20 model days, at which time the number densities of the various constituents were within 20% of the USSA 1976 values (we attribute the remaining differences to our photochemistry codes being different from the one used in the USSA 1976). We then increased abruptly the eddy coefficient by a factor of 100 and shifted its profile 20 km upward, which simultaneously raises the turbopause from 105-km to 125-km altitude. Figure 1 shows the response of the ratio of number densities n(Ar)/n(N2) in the lower thermosphere to this sudden change in turbulent conditions, which occurs at time t = 0. It takes about 10 hours to fully mix the atmosphere up to altitudes of 110 km. These compositional changes need another 10 hours or so to propagate upward into the 140-km region where a new steady state is approached after about 20 hours.

In the second model experiment (Figure 2) the initial

VON ZAHN ET AL' MASS SPECTROMETRIC STUDIES 7457

the fact that the flow field in front of the ion source is starting to change from free molecular flow toward continuum flow. In each figure we also show the USSA (1976) profile for comparison. Neglecting consideration of small-scale varia- tions, the n(N2) profiles are little variable between the four experiments but fall somewhat below the USSA (1976) values (Figure 12). Their scale heights are reasonably close to the USSA 1976 scale heights, indicating also temperatures similar to USSA (1976) temperatures (see section 10).

The n(Ar) profiles measured in the experiment BUGATTI 2 and 6 (Figure 13) parallel the USSA (1976) profile. The n(Ar) profile obtained in the BUGATTI 7 experiment, how- ever, shows over the entire altitude range of measurement an Ar scale height which is significantly higher than that of the USSA (1976) profile. A similar n(Ar) profile was also ob- tained from the BUGATTI 3 experiment [Dickinson et al., 1985]. The quality of the Ar density data obtained from the two experiments was, however, quite different. On the one hand, the BUGATTI 3 instrument exhibited two unusual (and unexplained) features: (1) the laboratory calibration curves indicated a nonlinear relationship between the num- ber densities in the ion source and the measured ion current even at low densities where this relationship is normally expected to be a linear one, and (2) during the in-flight calibration procedure, startup and operation of the ion getter pump of the instrument interfered with the measurement of low ion currents. On the other hand, the BUGATTI 7 instrument had quite normal calibration curves (see Figure 10), with the expected linearity at low densities. In addition, its in-flight calibration procedure reproduced the laboratory curves quite well. Hence we will concentrate the following discussion of n(Ar) profiles on the results of the experiments BUGATTI 2, 6, and 7.

120

!10

100

BUGATTI 2

........ BUGATTI 6

----- BUGATTI 7

* + + IJSSA 1976

i i i i i i1[ I i i [ i i

1015 1016 10•?

+

+

i i i i i

orebLent number denstty Ar [m -s] Fig. 13. Ambient number densities of argon n(Ar) measured in

three BUGATTI experiments. The USSA (1976) profile (crosses) is given also for comparison.

D

120

110

100

+ + + USSA 1976

" ' I • ' ' ' I +

,

+ + ,,

+ ,

BU '-,

........ BUGATT ! 6 / . ' +

,, .... BUGAIT I 7 i ++ ,

/ + ' .

+

+

, 90 , , I • , , , I 0.005 0.010

Fig. 14. Density ratios n(Ar)/n(N2) as measured in three BU- GATTI experiments. The star on the abscissa marks the sea level value.

The density ratios n(Ar)/n(N2) are shown in Figure 14. The general decrease of this ratio with altitude is due to molec- ular pressure gradient diffusion. The BUGATTI 2 curve is the most "normal" of the three profiles and falls close to the USSA (1976) profile. A local enhancement of the ratio of approximately 10% is observed near 105-km altitude. Nev- ertheless, at this altitude the measured ratio remains still smaller than the sea level value of 1.20 x 10 -2. The profile of BUGATTI 6 lies significantly above the USSA (1976) profile, indicating a turbopause about 3 km higher than assumed in USSA (1976). Below 96-km altitude, the mea- sured ratio exceeds by a small amount the sea level value. As we do not know of an atmospheric process which could cause an enrichment of the Ar/N 2 ratio above its sea level value we attribute this signal as being due to the instrument errors and is within the absolute error bar of -+7%.

The BUGATTI 7 profile of n(Ar)/n(N2) shows a character quite different from those of BUGATTI 2 and 6. It shows the ratio n(Ar)/n(N2) to be almost independent of altitude up to 112 km. In principle, this behavior could be caused by either strong upward bulk motions or strong vertical turbulent mixing (or a combination of both processes). Strong upward winds would cause the n(Ar)/n(N2) ratio to approach a constant value throughout the lower thermosphere, which would be its sea level value. We observe, however, a mixing ratio which is depleted below the sea level value at altitudes as low as 100 km. To explain this observation we invoke strong mixing with air from much higher altitudes, allowing at the same time for little upward mixing of argon-rich air from below. Schlegel and R6ttger [1987] present wind mea- surements obtained in the altitude region 70 to 110 km by the EISCAT incoherent scatter radar and by a rigid falling sphere launched close in time and location to BUGATTI 7.

VON ZAHN ET AL.' MASS SPECTROMETRIC STUDIES 7461

120

110

100

BUGATTI 6

pressure scale heLght [km]

Fig. 24. Profile of the pressure scale height derived from BU- GATTI 6 data.

procedure to derive the Ke(z) profile smoothes over any small scale variations of K e versus altitude z. Small-scale structure in turbulent intensity is, however, better derived from our K i data.

For the experiments BUGATTI 2 and 6 the chosen profiles Ke(z) yield a quite satisfactory agreement of the measured and modelled Ar profiles. The sensitivity of the least squares fit against variations of Ke(max) is such that the uncertainty in Ke(max) can be taken as a factor of 2. The parameter Ke(max) describing best the results of the experiment BU-

GATTI 2 is virtually identical with the one used in USSA (1976), in case of the experiment BUGATTI 6 it is 3 times as large. Using the definition of K e = D for the altitude Zh of the turbopause, we obtain z h -- 105 and 108 km for the experi- ments BUGATTI 2 and 6, respectively.

If we choose to describe the BUGATTI 7 profile of n(Ar)/n(N 2) as being caused by strong eddy diffusion, its flatness indicates directly that throughout the altitude range of observation the eddy coefficient must have been consid- erably larger than the molecular diffusion coefficient. Under these circumstances the Ar profile shows little dependence on K e, and hence only a lower limit for Ke(max) of 1 x 103 m2/s can be determined from our experiment (see also Figure 26). The altitude Zh of the turbopause would be higher than 115 km.

10.4. Spectral Indices

As is outlined in section 8.3, the power spectrum SP(kz) of the measured density fluctuations and the spectral index s c were calculated for each 1-km altitude bin. Figure 27 shows as example the power spectral density of the N 2 density fluctuations for the altitude range 91.0 _+ 0.5 km, derived from BUGATTI 7 data. Figure 28 shows the profile sr-(z) obtained from the BUGATTI 7 data (solid line). The shaded area indicates the uncertainty of s c. The spectral index varies about -5/3 between 93- and 106-km altitude. At the lowest altitudes a steepening of the power spectrum is indicated, at the highest altitudes a flattening.

BUGATTI 7 took the data shown in Figure 28 on the downleg of the sounding rocket payload M-T5 (see Table 1). During the ascent of this same payload and starting at 62-km altitude a positive ion probe measured the fluctuations of positive ion density [Thrane et al., 1987]. A spectral analysis of the observed ion density fluctuations yields a spectral index profile sr-(z) which is shown as the dashed line in Figure 28. Although the sampling volumes of the two experiments were horizontally displaced, near 95-km altitude by almost 30 km, the general agreement of the independently deter-

120 -

_

110 -

_

number dens Fig. 25. Density profiles measured by BUGATTI 2 (solid lines) and model calculations of argon profiles (dashed lines)

for three assumed profiles of the eddy coefficient Ke(z ). The best fitting K e profile is shown in the inset.

“Radar”  Turbopause  from  MF  echo  fading  Ome  Hall  et  al.,  1998;  2008  

HALL ET AL.: SEASONAL VARIATION OF 2t-IE TURBOPAUSE 28,773

130 120

110

4_17

lOO

9o

.+4

+2

I I I I

4 6 8 10 month (1 = 31s• Jonuory etc)

Figure 7. Value ht as a function of season. Again the month axis annotation indicates month endings. Error bars correspond to the highest and lowest intersections obtained using the errors in s', as illustrated by Figure 6. The pluses indicate monthly averages of ht from Danilov et al. [1979] corresponding to our estimates, but for Heiss Island in the 1970s. The digits to the right of each plus indicate the numbers of soundings used in the averaging.

instrument for monitoring the small-scale dynamics of this part of the atmosphere and furthermore points to a future of investigation into interannual variation.

The features highlighted by the investigation of turbulent intensities are (1) semiannual variation in the upper mesosphere/lower thermosphere and (2) annual variation in the mid-mesosphere. We have seen the clear signature of the semiannual oscillation (SAO) in the total wind, although we did not present data from other heights (turbulence observations being the subject of this study.) The interaction between the horizontal wind and the upwardly propagating gravity wave field is described by Lindzen [1981]. Essentially, the background wind through the troposphere and stratosphere has already determined the gravity wave flux arriving at the heights of our observations. Of course, the mean background wind must be combined with the tidal component to test for gravity wave stability, but nevertheless, we have combined the overall zonal and meridional components from Figures 2 and 3 to produce the total (i.e., absolute value) wind in Figure 5. In the mesosphere, around the reversals in the zonal wind, the gravity wave horizontal phase velocities have a better possibility to exceed the total (Eulerian) parcel velocities (the background wind being near zero), and therefore propagation can continue without convective instability [Fritts, 1984]. Thus s' exhibits a semiannual oscillation (SAO) with minima around the zonal wind reversals or alternatively the corresponding total wind minima.

Inclusion of error estimates in these kinds of measurements is somewhat unusual and our method of using the spectral noise floor seems a more appropriate approach than using the overall standard deviation. When employing daily or even, for example, 6-hourly standard deviations, it is impossible to separate the error from the variability induced by gravity wave, tidal, and planetary wave dynamics.

Subsequently, using the profiles of energy dissipation rate and assuming them to be representative of •, we are able to make

estimates of the turbopause height, extending the work by Hall et a!., [1998b]. If e' is considered an upper limit for s, the derived turbopause heights are then similarly upper limits. Nevertheless, there is an indication of a lowering of the turbopause in the summer months which is in agreement with observations from Heiss Island (80øN) by Danilov et al. [1979] and, at the same time, casting doubt on the semiempirical model of Blum and Schuchard [ 1978].

Acknowledgments. The authors are indebted to the technical staff of the Auroral Observatory, Tromso, for both regular maintenance of and refurbishing work on the MF radar. Thanks go to the reviewers of this paper who suggested important improvements to the original manuscript.

References

Blum, P.W., and K.G.H. Schuchard, The role of eddy turbulence for long period variations of upper atmosphere density, Space Res. XVIIL 18, 191-194, 1978.

Briggs, B.H., The analysis of spaced sensor records by correlation techniques, Handb. MA?, 13, 166-186, 1984.

Danilov, A.D., and U.A. Kalgin, Eddy diffusion studies in the lower thermosphere, Adv. Space Res., 17, (11)17-(11)24, 1996.

Danilov, A.D., U.• Kalgin, and A.• Pokhunkov, Variation of the turbopause level in the polar regions, Space Res. XIX, 83, 173-176, 1979.

Fritts, D.C., Gravity wave saturation in the middle atmosphere: A review of theory and observations, Rev. Geophys., 22, 275-308, 1984.

Hall, C.M., Virtual to true height correction for high latitude MF radar, Ann. Geophys., 16, 277-279, 1998.

Hall, C.M. and U.-P. Hoppe, Characteristic vertical wavenumbers for the polar mesosphere, proc. 13th ESA sympostum., 499-504, 1997.

Hall, C.M., T.A. Blix, E.V. Thrane, and F.-J. Ltibken, Seasonal variation of mesospheric turbulent kinetic energy dissipation rates at 69øN, Proc. ESA Symp., 13, 505-509, 1997.

Hall, C.M., and U.-P. Hoppe, Estimates of turbulent energy dissipation rates from determinations of characteristic vertical wavenumber by EISCAT, Geophys. Res. Lett., in press 1998.

Hall, C.M., C.E. Meek, and A.H. Manson, Turbulent energy dissipation rates from the University of Tromso / University of Saskatchewan MF radar, d. Atmos. Solar-Terr. Phys., 60, 437-440, 1998a.

Hall, C.M., A.H. Manson, and C.E. Meek, Measurements of the arctic turbopause, Ann. Geophys., 16, 342-345, 1998b.

Hocking, W.K., Strengths and limitations of MST radar measurements of middle-atmosphere winds, Ann. Geophys., 1,5, 1111-1122, 1997.

Lindzen, R.S., Turbulence and stress owing to gravity wave and tidal breakdown, d. Geophys. Res., 86, 9707-9714, 1981.

Lfibken, F.-J., Seasonal variation of turbulent energy dissipation rates at high latitudes as determined by in situ measurements of neutral density fluctuations, d. Geophys. Res., 102, 13,441-13,456, 1997.

Manson, A.H., and C.E. Meek, Small-scale features in the middle atmosphere wind field at Saskatoon, Canada (52øN, 107øW): An analysis of MF radar data with rocket comparisons, d. Atmos. Sci., 44, 3661-3672, 1987.

Manson, A.H., and C.E. Meek, Climatologies of mean winds and tides observed by medium frequency radars at Tromso (70øN) and Saskatoon (52øN) during 1987-1989, Can. d. Phys., 69, 966-975, 1991.

Manson, A.H., et al., Comparisons between satellite-derived gradient winds and radar derived winds from the CIRA-86, d. Atmos. Sci., 48, 411-428, 1991.

Schuchard, K.G.H., and P.W. Blum, Global thermospheric models of neutral density, exospheric temperature and turbopause height, Space Res. ,¾1/III, 18, 195-198, 1978.

C. M. Hall, Dept. of Physics, University of Tromso, 9037 Tromso, Norway. (e-mail: chris.hall•phys.uit. no)

• H. Manson and C. E. Meek, Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. (e-mail: manson•dansas.usask. ca; meek•dansas.usask. ca.)

(Received August 16, 1998; accepted August 17, 1998.)

68°  N  

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 103, NO. D22, PAGES 28,769-28,773, NOVEMBER 27, 1998

Seasonal variation of the turbopause' One year of turbulence investigation at 69øN by the joint University of Tromso/University of Saskatchewan MF radar

C. M. Hall

Dept. of Physics, University ofTromso, Tromso, Norway

A. H. Manson and C. E. Meek Institute of Space and Atmospheric Studies, University of Saskatchewan, Saskatoon, Canada

Abstract. Following upgrades to the University of Tromso/University of Saskatchewan MF radar, located in northern Norway at 69øN, 19øE, we have been able to complete a full calendar year of estimates of mesospheric turbulent intensity. The results represent the first such study using continuous measurements from this region, and temporal and height variations are satisfyingly in accordance with expectation. Since in the past there has been a degree of disagreement as to absolute intensities, we briefly compare our results with some from totally independent methods. The resulting dissipation rates, to be regarded as maxima for the turbulent dissipation, are used to identify an upper limit to the turbopause. The Arctic turbopause appears to exhibit an annual variation, being lower in the summer, in agreement with Danilov et al. [ 1979] but refuting Blum and Schuchard [1978].

1. Introduction

The joint University of Tromso/University of Saskatchewan MF radar, located in northern Norway at 69øN, 19øE was, during the winter of 1996/1997, refurbished to some degree. This has meant that the data quality, particularly its reliability, and accessibility for ease of analysis has been greatly improved and which has in turn facilitated the acquisition of a complete calendar year (1997) of estimates of turbulent intensity in the mesosphere. During the autumn of 1997 the transmitter antenna array was refurbished, resulting in a slightly altered beam shape, and subsequently, changes were made to the receiver software and firmware. Nevertheless, as we shall see, the clear seasonal variation apparent in our data is unlikely to be an artefact. Table 1 gives the specification of the radar for the period prior to the modifications; the transmitter antenna beam width being greater later in the last 3 months of the year. The salient points of Table 1, for the purposes of this study, are the final height and time resolutions of 3 km and 5 rain, respectively. Winds are determined by the spaced antenna method elegantly described by Hocking [1997] using the full correlation analysis (FCA) described by Briggs [1984]. Indeed, Hocl•'ng [1997], comparing the various methods of data analysis, suggests that FCA is less prone to beam-broadening effects than the Doppler-broadening method, and so the antenna modifications are less likely to affect our results, thanks to our analysis strategy. The radar operates unattended round the clock so that 288 profiles of signal fading time are available each day. Not each profile is complete, however, because of either poor signal-to-noise ratios (typical at night in winter) or due to total reflection of the signal (during periods of high auroral activity); indeed, we see evidence for lack

Copyright 1998 by the American Geophysical Union.

Paper number 1998JD200002. 0148-0227/98/1998JD200002509.00

of signal in January and December. The signal fading times are converted into estimates of the kinetic energy dissipation rate •' (as distinct from the true turbulent energy dissipation rate •) according to the method described by Hall et al. [ 1998a]. Value •' may be interpreted as an upper limit to • as it may inevitably include some contributions from short-period gravity waves. However, this aspect is addressed to some degree in section 2 where we attempt to estimate errors.

Prior to this work no continuous monitoring of mesospheric turbulence had been performed at this location. Only intermittent in situ and incoherent-scatter-based estimates existed, summarized by Hall et al. [1997] and Hall and Hoppe [1997], respectively; thus these results represent unprecedented observations at 69 ø N. Finally, we use the energy dissipation rates we derive to estimate the turbopause height, following the method by Hall et al. [1998b]. The resulting seasonal variation is characterized by a lower turbopause in summer than in winter. This result is in agreement with Danilov et al. [ 1979].

2. Method

The radar illuminates the mesosphere and power is reflected from scattering structures subsequently forming a diffraction pattern on the ground that moves at twice the speed of the scatterers, as described by Hocl•'ng [1997]. This reflected power is detected by spaced antennae, the individual signals being autocorrelated and cross-correlated using the FCA. The autocorrelations indicate the rate at which the scattering structures are being dissipated, characterized by the "fading time" Subsequently, velocity fluctuations v', appropriate to an observer moving with the background wind, are computed according to Briggs [1984], at a height resolution of 3 km and time resolution of 5 min via

Z•/In 2 v'= (1)

28,769

28,770 HALL ET AL.' SEASONAL VARIATION OF THE TURBOPAUSE

Table 1. MF radar system features.

Parameter Value

Geographic coordinates 69.58øN, 19.22øE Operating frequency 2.8 MHz Pulse repetition frequency 100 Hz Peak transmitter power N20 kW Transmitter antenna b earn width 17 ø Receiver antenna three spaced inverted-V dipales Height resolution 3 km Postintegration time 5 min

where 7, is the radar wavelength. Thereafter, we assume a total velocity fluctuation [Hall et al., 1998a] and use

e' = 0.8v':/r (2) where TB is the Brunt-Vfiisalfi period in seconds. Note that we recognize that the spatial scale inherent in the experiment cannot preclude buoyancy-scale fluctuations, because the outer scale of turbulence LB can be expected to be as little as 200 m in the mesasphere which is why we choose to introduce e' to distinguish our measurement from e. Furthermore, equation (2) implicitly assumes them is no motion of the observer relative to the

standard deviation in 88 km E' 60 ......... ' ......... ' ......... ' .....

5O

40

• 3o

20

lO

100 200 300 day number

i2

10

8

6

(noise floor) error in 88 km(' ......... i ......... i ......... i ......

......... i ......... i ......... i .....

1 oo 200 300 doy number

Figure 1. (top) Daily standard deviations of •' for 88 km as a function of season; (bottom) daily noise-floor-derived errors in g' for 88km as a function of season. A 30-day boxcar smoothing has been apphed to each time series (the spiky nature of the time series end points is a failure of the smoothing).

background wind; we have not attempted to compensate for departures from this.

Errors in FCA analyses from individual soundings are difficult to estimate. To overcome this, we have taken advantage of the large numbers of soundings in our data. For each day we perform a spectral analysis of e' at each height and identify noise floors at the high-frequency ends of the power spectra. To clarify this, we detect the noise floor at high frequencies where it becomes discernible above the diminishing signal; this noise is then assumed to be white noise spanning the entire spectrum. From individual case studies we found this to be typically from periods of 20 min or shorter. We do not include explicit examples of these spectra here; indeed, in the routine analysis of 365 days of data, the noise floor is estimated automatically as the average power between 20-rain periods and the Nyquist frequency. The noise floor from each day is subsequently used to estimate the error in e'. Note that this approach does not use variances and deem them to be experimental errors. Instead, we use the presence of a noise floor in the spectra of the data, where buoyancy subrange power law dependence is expected. The derived errors thus also give an indication of the high-frequency gravity wave contribution in e', i.e., that which differentiates it from e. It is important to note the difference between the mere daily standard deviations and the noise-floor error we employ here. Figure 1 shows the two kinds of errors obtained using our data for 88 km. Recall that the standard deviation that a whole day's data includes changes in the energy dissipation induced by larger-scale dynamics right up to the diurnal tide and to a certain degree, even longer timescales. We see that the standard deviation is considerably larger than the high-frequency noise-floor-derived error. Furthermore the standard deviation exhibits a distinct seasonal variability, perhaps not surprisingly considering the seasonal differences in gravity wave propagation. There is a similar signature in the noise-floor error showing that it still reflects larger-scale dynamics to some extent but not to the same degree as the standard deviation.

3. Basic Results

Using the method referred to above, we have derived an estimate of the energy dissipation rate as a function of both month and height, and this is shown in Figure 2. Because of low photoionization in the mesasphere during January and December, the data quality is fairly poor at the very beginning and end of the plot. Nevertheless, we note the following features: (1) low turbulent levels below 80 km in the summer, giving an annual variation in the mid-mesosphere; (2) low turbulent levels around the equinoxes in the upper mesasphere (winter)/lower thermasphere (summer) giving a semiannual variation. The recent statistics presented by both Hall and Hoppe [ 1997] and Hall et al. [1997] show similar tendencies and give considerable credibility to the estimation of • from MF signal fading times. In the figure, a degree of smoothing has been applied to improve clarity.

In order to relate these results to the horizontal dynamics that determines the stability of the upwardly propagating gravity wave field and hence turbulence production, we show the corresponding zonal (Figure 3) and meridional (Figure 4) winds selected at 90 km. These parameters are also products of the FCA. We see little seasonal variation in the meridional component. The zonal wind's autumn reversal coincides with the demise of the summer turbulent levels. In the spring, however, the upper mesasphere turbulence dies out at the end of February, over a month before the spring wind reversal. To further illustrate this, we have computed the total horizontal wind speed and plotted it on the

upper  limits  for  v’,  ε’  

“Wave”  Turbopause  from  satellite  temperature  variaOons  

Offermann  et  al.  2006;  2009  

(GW, PW, etc.) an exponential growth of ampli-tudes according to Eq. (6) (e.g., Holton andAlexander, 2000):

f ¼ f0 expðZ # Z0Þ=ð2HÞ, (6)

where Z is the height, Z0 a reference height, and Hthe scale height. Such altitude distributions shouldbe seen in our temperature standard deviationswhich are assumed to represent the temperaturewave amplitudes. Four such examples are shown inFig. 10 as dotted (red) lines. They are clearly notcompatible with the linear increase at the loweraltitudes, which is obviously much too flat. At theupper altitudes, however, the s increase is muchmore in line with an exponential increase.

This is an interesting result. We tentativelyinterpret it as a difference in wave damping in thetwo altitude regimes. At the upper altitudes thewaves are large and obviously undergo relativelylittle damping. This is not surprising as thetemperature gradient is strongly positive in thelower thermosphere, and hence this part ofthe atmosphere is convectively very stable (Figs. 2and 3). At the lower altitudes the amplitudes aresmall and the waves are considerably damped inmuch of the altitude regime. The fit lines (blue) inFig. 10 intersect at an altitude of around 95km(diamond). This point is the altitude where thedissipative regime ends, and above which theundamped wave propagation begins. We denote itas the ‘‘wave-turbopause’’ which is meant to indicatethat production of turbulence stops at this altitude

or somewhere near to it. This wave-turbopause isnot the same as the classical mixing turbopause(homopause), nor as the turbopause defined byturbulence dissipation discussed above (Section 1). Itmust, however, be closely related to them.

If temperature changes in the vertical directionare present in the atmosphere, Eq. (6) takesthe form

T 0 ¼ cðT=gÞoB expððZ # Z0Þ=2HÞ. (7)

Here T 0 is the temperature amplitude of the wave, Tthe atmospheric temperature, g the gravity accel-eration, and oB the Brunt–Vaissalla frequency. C isa constant. The influence of vertical temperaturechanges is not important below 90km. They becomevisible above 100 km where the temperature gradi-ent is large (Figs. 2 and 3). This is seen by thedashed green curve in Fig. 10 that starts at theintersection point of the two blue lines (diamond) at95 km and extends upwards. This curve assumesthat everything except T is constant in Eq. (7) at andabove 95 km. It thus shows the isolated influence ofthe temperature increase, which obviously cannotexplain the measured s increase.

The wave-turbopause as defined here by anextrapolation of two curves is, of course, artificialto some extent. A point-like turbopause is asimplistic approach because one cannot assumethe wave damping that exists below to stopsuddenly at a certain altitude. It is also anapproximation because in the altitude regime ofextrapolation (and intersection) the s profilesfrequently are not as smooth as in Fig. 10. Theyrather exhibit pronounced structures as is indicatedin Fig. 9. A more detailed picture of this is given inFig. 11 which shows the vertical s profiles in 10%

latitude steps ð10% binsÞ from 60%S to 60%N togetherwith the corresponding lower and higher altitude fitcurves. The intersection points (turbopause alti-tudes) are shown as full dots. Although an estimateonly of the wave-turbopause, they are seen to be asuitable means to compare different vertical sprofiles to each other and thus compare the waveactivities at the lower and higher altitudes irrespec-tive of the disturbances present at the middlealtitudes ð75295 kmÞ. (The green dashed curvedescribed for Fig. 10 has also been calculated forthe other latitudes. These curves are included inFig. 11).

Limb scanning instruments like CRISTA andSABER have only limited capability to detectwaves with short (vertical/horizontal) wavelengths.

ARTICLE IN PRESS

0 10 20 30 40Standard Deviation [K]

40

50

60

70

80

90

100

110A

ltitu

de [k

m]

Fig. 10. Vertical profile at 401N taken from Fig. 9. For straight,dotted, and dashed lines see text.

D. Offermann et al. / Journal of Atmospheric and Solar-Terrestrial Physics 68 (2006) 1709–17291720

for  40°  N  

Workshop  quesOons  

•  Why  is  the  turbopause  important?  •  Turbulent  diffusion  Kt  vs.  Eddy  diffusion  Ke  •  Turbulent  structure  at  different  scales,  3-­‐D  (isotropic,  Kolmogorov),  2-­‐D  (Kraichnan)  

•  Structure  at  gravity  wave  scales?    Structure  of  turbulence  above  100  km?    

•  What  are  the  implicaOons  for  verOcal  transport  and  horizontal  transport?  “Anomalous”  horizontal  transport  above  100  km?  What  is  its  impact  globally?  

•  How  do  experimental  results  connect  with  models?    And  vice  versa?    

Schedule  •  08:00  Gerald  Lehmacher:  IntroducOon,  turbopause  definiOons,  Turbopause  2009  experiment,  

quesOons,  schedule  •  08:15  Rich  Collins,Brentha  Thurairajah:    Turbopause  2009  experiment,  post-­‐stratwarm  condiOons,  

lidar  results  •  08:30  Tyler  Scoq:  Turbopause  2009  experiment,  TMA  trails  •  08:45  Jim  Hecht:  Media:hecht_turbopause.pdf  TOMEX:  Some  thoughts  10+  years  auer  launch,  new  

results  from  Chile  •  09:00  Miguel  Larsen:  2-­‐D  and  3-­‐D  turbulence,  experimental  challenges  •  09:20  Cora  Randall:  Media:randall_abstract.pdf  Atmospheric  Coupling  via  EnergeOc  ParOcle  

PrecipitaOon  •  09:35  Hanli  Liu:  Large  wind  shears  as  related  to  temperature  structures  near  the  turbopause  region;  

modelling  challenges  •  09:50  Discussion  •  10:00  Break  •  10:30  Jia  Yue:  Media:Yue_turbopause.pdf  On  large  wind  shears  and  fast  meridional  transport  near  

the  turbopause  •  10:45  Liying  Qian:  Media:Qian_liying_abstract.pdf  Impact  of  Eddy  Diffusivity  in  the  Mesopause  

Region  on  Seasonal  VariaOons  in  the  Thermosphere  •  11:00  Discussion  •  12:30  Adjourn  

2009  Turbopause  experiment  

Poker  Flat,  Feb  2009  very  quiet  aurora  

Meteorology:  GOES  11  Infrared  

Background  profiles  

superposiOon  of  2  linear  waves  (12h/30km+8h/10km)  

Richardson  number  

Ri  <  0.25   Ri  <  0.25  

turbulent  electron  density  fluctuaOons  (at  90  km)  

10 1 100 101 102 103

80

100

120

140

160

180

200

Frequency (Hz)

41.078 NT upleg t = 95.9 Z = 88.7 km 37

AC3 1.64 sDC 1.64 sDC 3.28 sDC 6.56 sAC3i 1.64 s

Power (dB)

DC  electron  probe,    Charlie  Croskey  Penn  State  

-­‐5/3  

more  trail  details  

Schedule  •  08:00  Gerald  Lehmacher:  IntroducOon,  turbopause  definiOons,  Turbopause  2009  experiment,  

quesOons,  schedule  •  08:15  Rich  Collins,Brentha  Thurairajah:    Turbopause  2009  experiment,  post-­‐stratwarm  condiOons,  

lidar  results  •  08:30  Tyler  Scoq:  Turbopause  2009  experiment,  TMA  trails  •  08:45  Jim  Hecht:  Media:hecht_turbopause.pdf  TOMEX:  Some  thoughts  10+  years  auer  launch,  new  

results  from  Chile  •  09:00  Miguel  Larsen:  2-­‐D  and  3-­‐D  turbulence,  experimental  challenges  •  09:20  Cora  Randall:  Media:randall_abstract.pdf  Atmospheric  Coupling  via  EnergeOc  ParOcle  

PrecipitaOon  •  09:35  Hanli  Liu:  Large  wind  shears  as  related  to  temperature  structures  near  the  turbopause  region;  

modelling  challenges  •  09:50  Discussion  •  10:00  Break  •  10:30  Jia  Yue:  Media:Yue_turbopause.pdf  On  large  wind  shears  and  fast  meridional  transport  near  

the  turbopause  •  10:45  Liying  Qian:  Media:Qian_liying_abstract.pdf  Impact  of  Eddy  Diffusivity  in  the  Mesopause  

Region  on  Seasonal  VariaOons  in  the  Thermosphere  •  11:00  Discussion  •  12:30  Adjourn