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URSI-99 Poster on Phase Structure Function

Structure Functions of Temporal Phase Variations in Vertical Sounding as a Diagnostic Tool for Ionospheric Small-Scale Irregularities

N.A. Zabotin, Rostov State University, Rostov-on-Don, 344090 Russia

J. W. Wright, 1915 Spruce Avenue, Longmont, Colorado, 80501 USA

ABSTRACT

We present a new method of the ionospheric irregularity investigation based on using of temporal structure function of the phase of the vertical sounding signal. Modern digital ionosondes (e.g. the dynasonde) measure the echo phase with very high resolution and precision at closely spaced antennas, frequencies and times. A ‘stringing’ procedure gives continuous and unambiguous phase variation data for time intervals of any desired length. Quasi-periods of tens of seconds up through several minutes are caused by large scale movements of the ionospheric plasma, while short variations are due to interaction of sounding signal with small-scale irregularities. That is why statistical properties of short phase variations are interconnected with statistical characteristics of the ionospheric small-scale irregularities.

The most convenient tool for statistical description of small-scale structures in both temporal (phase variations) and spatial (electron density irregularities) domains is the structure function (SF). Theoretical relation between structure functions of the phase variations and the irregularities can be obtained in the framework of a simple model of frozen irregularity horizontal drift. This relation allows one to solve both direct and inverse problems.

We show that some modification of this approach (which we call rudimentary structure function, or RSF concept) can be applied to analysis of dynasonde recordings obtained in its standard B- and K-modes. Our results suggest a significant diagnostic potential of the RSF method.

What is the ‘structure function’?

SF is one of common statistical characteristics of any random function (random field). It is defined as the mean square of difference of the function values taken at two different points. When random function is statistically homogeneous, SF depends only on vector connecting those two points. Thus it can be defined for temporal phase variations as and for spatial electron density irregularities as where averaging over realization ensemble is supposed. In the case of field aligned irregularities the function depends only on the absolute value of the transverse component of vector (that is on ). Unlike the correlation function or dispersion, large scale variations () do not influence SF. Moreover, structure function is the only natural mathematical analog for the inexact physical definition 'variation (disturbance) at a certain scale length' with relation to random functions.

How is phase SF connected with irregularity SF?

The following consideration is somewhat simplified but simplifications are not of principle character. Let us consider the layer of isotropic plasma with small-scale stationary random irregularities infinitely stretched along the slanting 'magnetic' lines. We shall assume that no multibeam interference exists. But horizontal drift of the layer and the 'frozen' irregularity field with velocity will be taken into account (See Fig. 1). Hence, the ray path of the sounding signal for two different times passes through different irregularities. This is considered the primary reason of the short period phase variations observed at the fixed point on the ground surface.

Let be the reflection level, is the level of the ionospheric layer beginning, , is regular part of the layer profile (), is irregular part of connected with electron density irregularity field by the relation . Random phase variation due to irregularities is given by well known expression with sufficiently broad applicability field:

.

Using definition of structure function, one can obtain for the case of vertical sounding of the linear plasma layer () the following relation:

where

=

and representation has been used.

The above expression can be generalized for the case when reflection occurs along oblique ray path with polar angle and azimuth angle :

where .

What are SF features predicted by the theory?

The irregularity structure function can be easily calculated if the irregularity spatial spectrum is known. For example, if the spatial spectrum has the following, quite typical for the ionospheric conditions form:

,

where and are components of vector orthogonal and parallel to the geomagnetic field vector and delta-function allows for infinite stretching of the irregularities, the corresponding structure function is

.

Here is the Gamma-function, is the Macdonald function and the normalizing constant should be determined from the condition ( has the meaning of averaged distortion value in the scale length ).

Theoretical dependence of the phase structure function on some parameters has been illustrated in Fig. 2a. Parameters = 5 MHz and = 50 km were used here. The magnetic field inclination angle was set equal to 0.2 rad what simulates situation in TromcЬ. For the irregularity spatial spectrum parameters at the scale length km, and = 10 km were used. The drift velocity direction was determined by angle =0.5 rad. The polar angle of the reflected signal was set equal to 0.2 rad, that is the case of was chosen. It was done to demonstrate dependence of the effect on relative orientation of the ray and of the magnetic field line passing through the sounder location. Thus dependence of the structure function on two parameters is shown: on the azimuth angle and drift velocity . Color in the figure marks different values of and line thickness corresponds to the drift velocity value .

One can see that the SF amplitude depends on the ray orientation and on the . It is evident also that it must depend on the . The SF amplitude is especially large when ray direction is close to the magnetic line direction. It is of importance that SF slope is practically independent on , and . At the same time, the SF slope depends on the spectrum index (see Fig. 2b). Therefore, the SF slope can serve as good indicator of the irregularity spectrum index .

How is the phase SF measured?

Generally speaking, phase of a wave is determined ambiguously with an accuracy to integer number of . But, if the phase is measured frequently enough (as with modern digital ionosondes under vertical sounding), special procedure called stringing allows one to obtain continuous series of the phase values determined unambiguously even if they differ more than by .

Long-period (tens of seconds) variations of the phase are caused by large-scale movements of the ionospheric plasma. But we are interested now in small-scale structures. That is why strung phase data must be detrended before calculation of the SF. Both preliminary stages of the data processing (stringing and detrending) are illustrated in Fig. 3 in terms of the TromsЬ dynasonde recording 26 Oct 1985 starting at 1130UT. This recording uses only minimal options of the system: 4-pulse sets at 50 pulses/sec, plus a .04 sec pause between sets; single fixed frequency, a time series of 1000 pulse sets in 160 seconds; sampling 50 complex amplitudes at 10 msec intervals between TOAs of 228.29 and 301.74 km.

Resulting phase structure functions for this recording are presented in Fig. 4. There are two large groups of the SFs, which have been marked by colors. Lilac, red and green constitute the first group. Lilac and red curves are from the wings of the TOA interval, where signal/noise ratio is small. Green ones are from the TOA bands where glint interference takes place. Both cases are not described by the theory which does not take into account multibeam interference effects. Another group (black and blue curves) are from the TOA bands where single glint dominates by amplitude and therefore multibeam interference is not essential. As one can expect, features of the SFs belonging to the second group are in full agreement with the theory stated above. The SF shape in the band of large lags can be elaborated by filtering of long-periodic harmonics from the strung detrended phase data (see Fig. 5). This operation allows one to estimate the dispersion of phase variations caused by small-scale irregularities (it is about 1 rad2 in the presented case). Filtering does not influence the SF behavior in the small-lag band and its most remarkable property — log-log-linear character. This property implies possibility of realization of the rudimentary structure function concept that significantly extends the SF method applicability.

What is rudimentary structure function?

The starting band of the full-scale structure function in the log-log coordinates is well approximated by the following linear dependence:

log(/rad2) = +·log(/sec) .

Structure indices and that have been introduced here depend upon all parameters which SF itself depends on. Their merit is possibility of their determination using only few smallest lags of the full-scale SF. It allows one to use for the purpose of the irregularity diagnostics large volume of the information obtained in standard B and K dynasonde modes.

Almost all dynasonde ionograms today are made using B-mode. In a typical B-mode ionogram, one uses a variant of the following time/frequency pattern of pulse sets. 'x' is one pulse set:

Radio frequencyxxxxxxxxxxxxxxxxxxxx xxetc.
^
xxxxxxxxxxxxxxxxxxxxxxxx
|
xxxxxxxxxxxxxxxxxxxxxxx
|
xxxxxxxxxxxxxxxxxxxxxx
|
xxxxxxxxxxxxxxxxxxxxx
|
xxxxxxxxxxxx
|
xxxxxxxxxxx
|
xxxxxxxxxx
| x
xxxxxxxx
+--------------------------------------------> time

In this example, we have a "B-mode ionogram of 3 ramps of 4 frequencies per block". Simple ionograms (I-mode) can be described as 1 ramp of (say) 1000 frequencies, or 1000 ramps of 1 frequency per block. K-mode could be described as (say) a B-mode of 1000 ramps of (say) 4 frequencies, but this would not be the most flexible way to achieve K-mode.

This is design of a single 8-pulse pulse set:

Pulse xxxxxxxxxx#1 #2 #3 #4 #5 #6 #7 #8 xxxUnits
____________________________________________________________
Time
xxxxxxxxxx-7x -5 -3x -1x 1x 3x 5x 7xxxx0.005 sec
Frequency
xxxxxx1 x-3x 3x -1x -1x 3 -3x 1 xxx1 KHz
Ant,Receiver1
xxxe xN xS xe xxe xS xN xe
Ant,Receiver2
xxxW xs xsx E xxE xs xs xW

Pulse set supplies four lags for the structure function: 0.01, 0.03, 0.05, and 0.07 sec. Obviously, ramp repetitions of pulse sets introduces another series of temporal lags. The relation of these lags to the shorter lags in the constituent pulse sets depends on the number of pulses/set and the number of frequencies per ramp.

Rudimentary structure function (RSF) is the structure function that contains only few initial lags sufficient to determine structure indices and by fitting.

In case of dynasonde B-mode sufficient statistics of the realizations of the phase differences needed to calculate RSF is achieved by using of counts relating to different frequencies. Statistical homogeneity of the realization ensemble is provided in this case by introducing the factor f -4 compensating for the frequency dependence of the .

How does the RSF method works?

We cite here for illustration the results of processing of data of two dynasonde campaigns. The first one — 'UKDYNA' — lasted 30 hours and used only B-mode. The time series of the structure indices for this campaign is shown in Fig. 6. Analogous time series for another campaign are shown in Fig. 7. Their number is twice as much than in the previous case because distinctive feature of this campaign is using of two dynasonde modes, B and K, interlacing. Its duration is also different, about 72 hours.

Besides the structure indices, owing to standard POLAN, UNIPHASE and VFITr algorithms, we have time series for the whole set of other parameters: echolocations, drift velocity, ionospheric layer thickness etc. All these parameters serve as input information for special algorithm of the inverse problem solving based on the above theoretical expressions for the phase structure function . The only additional simplification we make on this stage is assumption that value is equal to 7.5 km. But SF weakly depends on the . Output information for the inverse problem algorithm is two parameters of the irregularity spectrum model cited above: spectrum index and irregularity level in the scale length 1 km.

Time series for the irregularity spectrum parameters are shown in Figs. 8 and 9 for two dynasonde campaigns correspondingly. Lack of some data points is caused mainly by two reasons: by absence of the F layer reflections due to the ES and by occurrence of the >2 cases. Such cases are not described by the present variant of the theory. They are more characteristic of F layer reflections and are probably caused by multibeam interference. Despite this shortcoming, the method gives extensive and unique information about the temporal dynamics of the small-scale irregularity spatial spectrum. Note clear diurnal variation of the spectrum parameters during the UKDYNA campaign which is in qualitative agreement with the results of other, more rough, methods.

CONCLUSION

Our results suggest a significant diagnostic potential of the phase SF/RSF method with relation to small-scale ionospheric irregularities.

 

 

 

 

 

 

 

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