The determination of climatic norms of wind regime parameters in the lower thermosphere requires some questions of a methodical and scientific character to be settled. Among those of methodical character is: how to properly construct climatic circulation models using limited experimental data obtained by various methods during different time periods and in different geographical regions. The most important questions of a scientific character are: what main dynamic structures characterize the wind regime and how are these structures related to various atmospheric parameters and to the dynamic structures in the overlying and underlying atmospheric layers. These questions are considered and discussed

Portnyagin, Yu. I.

English

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THE CLIMATIC WIND REGIME IN THE LOWER THERMOSPHERE 
FROM METEOR RADAR OBSERVATIONS 
Yu. I. Portnyagin 
Institute of Experimental Meteorology 
Obninsk, Kaluga Region, USSR 
The determination of climatic norms of wind regime parameters in the 
lower thermosphere requires some questions of a methodical and scientific 
character to be settled. Among those of a methodical character one can 
single out the following questions: how to properly construct climatic 
circulation models using limited experimental data obtained by various 
methods during different time periods and in different geographical 
regions. The most important questions of a scientific character are the 
following: what main dynamic structures characterize the wind regime and 
how are these structures related to various atmospheric parameters and to 
the dynamic structures in the overlying and underlying atmospheric layers. 
Let us consider these questions: 
1. Representativeness of sampling used for mean monthly value 
determination 
Wind velocity measurements in the lower thermosphere as a rule are not 
carried out continuously. As a result, for the mean monthly value 
determination, some sample of the total wind field on consecutive days in 
the month, or on several days uniformly distributed throughout the month 
(e.g., on Wednesdays during meteorological rocket launchings), is used. 
Continuous meteor radar measurements carried out in Obninsk and at 
Molodezhnaya station (Antarctica) during several years produced data from 
which one can estimate the degree of difference between such samples and 
the true mean. Let us consider as an example some results of various mean 
monthly value estimates based on continuous measurements from Molodezhnaya 
station (Antarctica). Similar estimates are obtained also for data from 
continuous measurements in Obninsk. 
The results presented in Figures 1 and 2 show that if it is not 
possible to measure continuously it is necessary to carry out measurements 
on separate days uniformly distributed throughout the month. The estimates 
of mean monthly values obtained from such measurement data are close to the 
true monthly means. 
2.  The influence of interannual variability of estimates of monthly 
means. 
Dispersion estimates of monthly mean velocity values caused by the 
interannual variability of mean monthly wind velocities is important in the 
construction of a mean perennial circulation model. 
The knowledge of these dispersions makes possible an evaluation of the 
accuracy of mean monthly values pertinent to the model because it allows 
https://ntrs.nasa.gov/search.jsp?R=19880005124 2020-03-20T08:57:18+00:00Z
32 
(1, rns-' 
40 I 
I 
Pobruary 1977 
+ t  0 + 1 4  A 
1 + 1 + 
t 
' 5 I5 25 5 I5 25 
Unrclr 1917 July 1976 
Fig. 1 Mean monthly velocity values of zonal vo and meridional uo wind: 
$I - selected mean five day values; 1: - value averaged over 4 days 
equally distributed during the month; 4 - values averaged over 8 
days equally distributed during the month; $I - t.rue mean monthly 
values. 
- #  
11, 111s 
10 :F 
Pob- 1977 
0 
9 
i B dB 
I 
): 1~ 
5 15 25 5 i 5  25 
Lhrch 1977 July 1976 
Fig. 2 Mean monthly amplitude values of zonal component v2 and 
meridional component u2 of a semidiurnal tide (symbols the 
same as in Fig. 1). 
33 
one to determine the confidence intervals inherent in the smoothing of 
model values in space and, hence, enables the drawing of realistically 
smoothed isolines of wind velocity. 
Figures 3 and 4 are presented as examples of the internannual 
variation in mean monthly velocity values. These figures show year-to-year 
variations of mean monthly velocity for January and July from perennial 
measurement data from Che Obninsk, Heiss Island and Molodezhnaya stations. 
It is seen from these figures that in some cases the interannual 
variations of mean monthly values may cause wind velocity variations not 
only in value but also in sign. So, in January of different years on Heiss 
Island and in Obninsk the meridional wind can be northerly as well as 
southerly with mean perennial values for January close to zero (Figure 4). 
Such behavior of the meridional wind can be explained by the fact that the 
center of the winter cyclone, characteristic of the Northern Hemisphere 
circulation in January, may not be centered on the pole, but undergo 
periodic displacements from the pole. This would indicate that the 
resulting meridional wind has ageostrophic as well as geostrophic 
components. Similarly, the meridional wind in Antarctica may vary in sign 
in July. The zonal wind, while more stable in sign (Figure 3 ) ,  may in some 
years vary in direction (e.g., in January at Molodezhnaya station). As 
seen from Figures 3 and 4 ,  oscillations with periods of 3-5 years occur in 
the interannual variations of mean monthly values (according to our data, 
this conclusion is also valid for other months of the year). So, the most 
exact evaluation of mean perennial wind velocity values can be obtained by 
averaging observations over periods exceeding five years. Unfortunately, 
such long-term series of observations exist at a comparatively small number 
of geographic locations. 
To quantitatively estimate the dispersions connected with interannual 
variability and the corresponding least square deviations, we used a data 
series obtained during many years at sites located at the high, moderate 
and subtropical latitudes of both hemispheres: on Heiss Island 
(1965-1981), in Obninsk (1964-1981). in Atlanta (1974-1978), Adelaide 
(1966-1972), and at Molodezhnaya station, Antarctica (1968-1981). Figures 
5 - 7  show the values of root mean-square deviations a (dispersion D.) of 
the mean monthly values from mean perennial velocities for all montfis of 
the year; these deviations were estimated from measurements made at the 
above stations. It is seen from the figures that minimum a and u. values 
(i.e. , for meridional and zonal components respectively) are obs&ved in 
Obninsk, which is located at a moderate latitude of the Northern 
Hemisphere. The a. values on Heiss Island are somewhat higher. The 
maximum u values of about 15-20 m/s are observed at subtropical latitudes 
(Atlanta and Adelaide) during some months of the year. A definite seasonal 
a dependence was not established. Moreover, even at one site but at 
different height levels (measurements in Atlanta and Adelaide were carried 
out by facilities which measure height variations) the character of the 
seasonal course of a However, 
results presented in Figures 5-7 give a rather clear presentation of the 
order of ai for different latitudes and allow one to estimate the 
root-mean-square errors of wind velocity values for different seasons of 
the year. 
i 
U V 
i 
i 
i 
does not always coincide (Figures 6 and 7 ) .  i 
It should be noted that dispersion estimates connected with the 
interannual variability are maxima, as scatter in the mean monthly values 
34 
20 
iQ 
0 
40 
50 
20 
i o  
0 
- i o  
" 
Fig. 3 Interannual variability of mean 
monthly zonal wind velocities for 
January and July from measurement 
data for many years on Heiss Island, 
in Obninsk and Molodezhnaya station. 
a) Heiss Island, b) Obninsk, c) 
Molodezhnaya station; 1 January, 
2 July. 
f0 - 
1 1 1 1 1 1 1 1 1 1 1 1 1  I I I I I I  
f9& 66 6( 10 72 74 76 78 80 
Fig. 4 Interannual variability of mean 
monthly meridional wind veloci- 
ties for January and July from 
data of persistent measurements 
on Heiss Island, in Obninsk and 
at Molodezhnaya station. a) Heiss 
Island, b) Obninsk, c) Molodez- 
hnaya station; 1 January, 2 July. 
35 
0 " " ' " "  I . " '  
Fig. 5 Seasonal variations of root-mean-square deviations 
of mean monthly values of wind velocities from 
mean perennial for 95 km obtained during observa- 
tions in Obninsk (1964-1981), at Molodezhnaya 
station (1968-19811, Heiss Island (1965-1981). 
a) meridional component, b) zonal component; 
I-Obninsk, 2-Molodezhnaya station, 3-Heiss Island. 
6f ms-' 
..  
Fig. 6 Seasonal variations of root-mean-square deviations 
from observations in Atlanta (1974-1977) at 80, 92, 
100 km. a) meridional component, b) zonal component; 
1, 2, 3 - 80, 92, 100 km, respectively. 
36 
Fig. 7 Seasonal variations of root-mean-square 
deviations from observation data (1966- 
1972) at 80, 95, 100 km. a) meridional 
component, b) zonal component; 1, 2, 3 - 
80, 95, 100 km, respectively. 
37 
was not excluded since continuous measurements from 1974 to 1983 were 
carried out only in Obninsk. 
Figure 8 presents graphs of the mean perennial seasonal course of 
zonal and meridional prevailing wind velocities obtained by averaging the 
corresponding mean monthly values for the period from 1964 to 1981 from 
observation data in Obninsk, for 1965-1981 from data for Heiss Island and 
for 1968-1981 from data obtained at Molodezhnaya station. It is seen from 
this figure that the amplitude of a seasonal variation of prevailing wind 
velocities exceeds the errors associated with the mean perennial wind 
velocity values; the main features of the seasonal variation at each 
observation site are highly regular from year to year. At the same time, 
at different latitudes the seasonal variation of wind velocity has its own 
typical peculiarities. Differences in the seasonal variations of wind 
velocity are especially significant when comparing northern and southern 
hemisphere sites (it must be kept in mind that there is a shift of seasons 
equal to six months between hemispheres). These results show that when 
constructing a mean perennial circulation model for the meteor zone one can 
use data for different sites averaged over some years even though at these 
sites measurements were not continuous and the years over which the data 
were averaged do not necessarily coincide completely. 
3 .  Longitudinal variability of wind regime parameters. 
As is seen from the analysis, the dependence of mean monthly wind 
velocity values on longitude at moderate latitudes of the northern 
hemisphere is comparatively insignificant. Such a conclusion is confirmed 
by comparing the seasonal variation of zonal and meriodional wind 
velocities at sites located at similar latitudes, but significantly 
different longitudes. 
Figure 9 presents the mean monthly values of zonal and meridional wind 
velocities for sites located in two narrow latitudinal zones of the 
northern hemisphere 52-57"N and 45-50"N. (Stations in latitudinal zone 
52-58"N are Jodrell Bank (2"E), Kuhlungsborne-Collm (12"E), Obninsk (38"E), 
Kazan (49"E), Tomsk (85"E), Badary (102"E) and Saskatoon (107"W); in the 
latitudinal zone 45-50°N, Budrio (12"E), Kiev (31"E), Kharkov (36/E), 
Volgograd (44"E) and Khabarovsk (135"E). It is seen from Figure 9 that 
difference in longitude between the sites does not significantly increase 
the dispersion of mean monthly values in comparison with dispersion of 
these u values specified by their interannual variability (dispersion of 
x wind ve3ocity values resulting from their lon6itudinal variability u according to our estimates, is characterized by ux m/s, uu - 5 m/s). From 
this, we conclude that at moderate latitudes of the northern hemisphere the 
mean meridional wind is mainly of a geostrophic character. This is 
confirmed by comparison of the seasonal variation of wind velocities at 
high, subtropical and tropical latitudes of the northern hemisphere. (High 
latitudes: Heiss Island (80.5"N, 58"E), Kiruna (68"N, 10"E), College 
(65"N, 148"W); subtropical latitudes: Dushanbe (38"N, 69"E), Palo Alto 
(37"N, 122"W), Atlanta (34"N, 84"W), Kyoto (35"N, 136"E) ; tropical 
latitudes: Kingston (18"N, 77"W), Punta Borinken (18"N, 67"W), Waltair 
(18"N, 83"E)).  So, it can be supposed that the dependence of the seasonal 
variation in wind velocity in the meteor zone on longitude is insignificant 
at all latitudes. Thus, when developing atmospheric circulation models, it 
is possible as a first approximation to use mean zonal winds in which only 
seasonal and latitudinal dependencies are taken into account. 
x 
38 
1111111111111 
Fig. 8 Mean perennial seasonal course of meridional u2 
and zonal v2 prevailing wind velocities from 
measurement data in Obninsk (1964-1982). on Heiss 
Island (1965-1982) and at Molodezhnaya station 
(1968-1982). a) Heiss Island, b) Obninsk, 
c )  Molodezhnaya station. 
39 
- f0 'O? -  - 
I l i  111 If v il \ill Vlll I X  x XI 1 1 4 1  ' 
Fig. 9 Seasonal course of zonal vo and meridional u, 
prevailing wind velocity components at 95 km, 
averaged over different longitudes for two 
latitudinal belts: 52"-57" N (a,c) and 45"-50" N 
(b,d). 
40 
4. Regularities of zonal circulation in the region of the mesopause-lower 
thermosphere. 
In constructing our model of zonal circulation in the mesopause-lower 
thermosphere, we used results obtained at 27 sites by meteor radars, and at 
six sites by the partial reflection method. Wind variations in both height 
and time have been measured at the following sites: Kiruna, 68"N; 
Saskatoon, 52"N; Garchy, 48"N; Atlanta, 35"N, Punta Borinken 18"N; 
Townsville, 18"s; Adelaide, 35"s; Birdlings Flat (Christchurch), 44"s). 
The analysis of results from all sites permits the construction of 
height-latitude cross sections of the mean zonal wind field for all seasons 
of the year. Over the 70-80 km height range, the radar wind results have 
been coupled with height-latitude sections constructed from meteorological 
rocket sounding data, with due regard given to the measurement errors 
associated with each technique. The experimental data used for 
construction of these sections at sites located at different longitudes are 
in good agreement with each other, and after smoothing and spatial 
interpolation, latitude-height cross sections of model mean values of zonal 
wind velocity for each month of the year were obtained. 
These sections are presented in Figures 10-13. Let us consider, for 
example, sections of the zonal wind field for January and July (Figures 10 
and 12). Dominant dynamical structures are clearly seen in these sections; 
for example, a region of easterly circulation in the northern hemisphere in 
July and in the southern hemisphere in January which is connected with the 
summer strato-mesopheric anticyclone; a region of westerly circulation in 
the northern hemisphere in January and in the southern hemisphere in July 
caused by penetration of the winter stratomesopheric cyclone into the 
meteor zone; a westerly circulation structure which is specific to the 
lower thermosphere for the summer hemisphere covering in height most of the 
meteor zone; and a region of low latitude easterly circulation and related 
to it the region of easterly circulation in the lower thermosphere of the 
winter hemisphere. Analysis of these cross sections shows that the global 
zonal circulation in the mesopause-lower thermosphere region is greatly 
influenced by dynamical processes in not only the strato-mesophere, but 
also the thermosphere. It follows from Figures 11-13 that in both the 
southern and northern hemispheres, along with general regularities of 
global zonal circulation, there are great differences between the spatial 
location of mean circulation structures and the intensity of air mass 
movements in these structures. 
Lastly, one can conclude that available experimental data on wind 
velocities in the mesopause-lower thermosphere can be analyzed to determine 
climatic regime parameters and to construct mean perennial circulation 
models. However, for further advances in detailed modeling, it will be 
necessary to increase the present station network, particularly in low 
latitudes, and to carry out long-term continuous measurements. A timely 
solution to this problem will require the combined efforts of scientists 
from many countries. 
41 
x k r n  
110 
102 
94 
86 
78 
70 
90” 60 JO 0 30 60 90’s 
Fig. 10 Height-latitude structure of the zonal wind field (m/s), 
December-February. a) December, b) January, c )  February; 
positive value - western wind. 
42 
x krn 
Fig. 1 1  Height-latitude structure of the zonal  wind field ( m / s ) ,  
March-May. a) March, b) April, c) May. 
4 3  
110 
to2 
94 
86 
78 
z km 
- 
- 
- 
- 
- 
/IO 
102 
94 - 
8 6 -  
78 - 
- a  
- 
110 
102 
94 
86 
78 
70 
30 60 90's 90% 60 30 0 
Fig. 12 Height-latitude structure of the zonal wind field (m/s), 
June-August. a) June, b) July, c) August. 
4 4  
86 
78 
70 
Fig. 13 Height-latitude structure of the zonal wind field ( m / s ) ,  
September-November. a) September, b) October, c) November. 


The climatic wind regime in the lower thermosphere from meteor radar observations

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