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  • View in gallery

    Rocketsondes experiments in 1967–2004 for (left) months and (right) seasons.

  • View in gallery

    (left) Zonal and (right) meridional winds of rocketsondes in 1967–2004.

  • View in gallery

    Distribution of wind speed frequency at 26, 28, 30, 35, 40, and 50 km.

  • View in gallery

    Distribution figure of normal distribution testing.

  • View in gallery

    Frequency of the wind speed in a logarithmic coordinate.

  • View in gallery

    Distribution figure of lognormal distribution testing.

  • View in gallery

    Monthly average zonal winds at the heights of 28, 38, and 48 km. The circle denotes observation data. The black line denotes the fitted curve. (bottom) Number of rocketsondes in 12 months during 1967–2004.

  • View in gallery

    Seasonal profiles of zonal winds and meridional winds for DJF, MAM, JJA, and SON. The blue circle denotes wind speeds. The red line denotes wind speed average. Two dashed red lines denote the std dev for the mean wind. The black line denotes the average wind of HWM07. Negative (positive) U means easterly (westerly) wind direction.

  • View in gallery

    Scatters of (left) zonal and (right) meridional winds for rockets and HWM07. Negative (positive) U means easterly (westerly) wind direction.

  • View in gallery

    Differences between the rocketsondes and HWM07 for (left) zonal and (right) meridional winds in DJF, MAM, JJA, and SON.

  • View in gallery

    Scatter of (left) zonal and (right) meridional winds for rocketsondes and the reanalysis.

  • View in gallery

    Differences between the rocketsondes and the reanalysis for (left) zonal and (right) meridional winds. The horizontal bar denotes the double std dev of the mean value.

  • View in gallery

    Zonal wind profiles (red lines) and HWM07 simulations (blue lines) when no major SSWs occur.

  • View in gallery

    Zonal wind profiles (red lines) and HWM07 simulations (blue lines) when major SSWs occur.

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Characteristics of Stratospheric Winds over Jiuquan (41.1°N, 100.2°E) Using Rocketsonde Data in 1967–2004

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  • 1 College of Meteorology and Oceanology, People’s Liberation Army University of Science and Technology, and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China
  • | 2 College of Meteorology and Oceanology, People's Liberation Army University of Science and Technology, Nanjing, China
  • | 3 College of Meteorology and Oceanology, People's Liberation Army University of Science and Technology, and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China
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Abstract

Stratospheric winds play a significant role in middle atmosphere dynamics, model research, and carrier rocket experiments. For the first time, 65 sets of rocket sounding experiments conducted at Jiuquan (41.1°N, 100.2°E), China, from 1967 to 2004 are presented to study horizontal wind fields in the stratosphere. At a fixed height, wind speed obeys the lognormal distribution. Seasonal mean winds are westerly in winter and easterly in summer. In spring and autumn, zonal wind directions change from the upper to the lower stratosphere. The monthly zonal mean winds have an annual cycle period with large amplitudes at high altitudes. The correlation coefficients for zonal winds between observations and the Horizontal Wind Model (HWM) with all datasets are 0.7. The MERRA reanalysis is in good agreement with rocketsonde data according to the zonal winds comparison with a coefficient of 0.98. The sudden stratospheric warming is an important contribution to biases in the HWM, because it changes the zonal wind direction in the midlatitudes. Both the model and the reanalysis show dramatic meridional wind differences with the observation data.

Publisher’s Note: This article was revised on 3 April 2017 to correct the name and contact information for the corresponding author.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: J. W. Li, 15651009118@sina.cn; 19994035@sina.com

Abstract

Stratospheric winds play a significant role in middle atmosphere dynamics, model research, and carrier rocket experiments. For the first time, 65 sets of rocket sounding experiments conducted at Jiuquan (41.1°N, 100.2°E), China, from 1967 to 2004 are presented to study horizontal wind fields in the stratosphere. At a fixed height, wind speed obeys the lognormal distribution. Seasonal mean winds are westerly in winter and easterly in summer. In spring and autumn, zonal wind directions change from the upper to the lower stratosphere. The monthly zonal mean winds have an annual cycle period with large amplitudes at high altitudes. The correlation coefficients for zonal winds between observations and the Horizontal Wind Model (HWM) with all datasets are 0.7. The MERRA reanalysis is in good agreement with rocketsonde data according to the zonal winds comparison with a coefficient of 0.98. The sudden stratospheric warming is an important contribution to biases in the HWM, because it changes the zonal wind direction in the midlatitudes. Both the model and the reanalysis show dramatic meridional wind differences with the observation data.

Publisher’s Note: This article was revised on 3 April 2017 to correct the name and contact information for the corresponding author.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: J. W. Li, 15651009118@sina.cn; 19994035@sina.com
Keywords: Stratosphere; Wind

1. Introduction

The stratospheric wind is an important factor in gas, energy, and momentum transportations, which influences the atmospheric dynamics (Baumgaertner 2007; Hildebrand et al. 2012; Shepherd 2007). It is also critical for the safety of rocket launches, falling points prediction of spacecraft recovery, and the design of stratospheric airships (Schmidt et al. 2006; Polmar 2001). Studies on stratospheric winds are based on various measurements. The meteorological parameters of atmosphere below 30 km can be obtained by radiosonde balloons and at 80 km there are satellite data. As to the middle atmosphere, the medium-frequency (MF) radar and meteor radar are two fundamental devices that can observe the mesospheric winds continuously (Chen et al. 2012; Fritts et al. 2010). In addition, some new instruments are developed to detect the middle atmospheric winds, especially in the stratosphere. The Stratospheric Wind Interferometer for Transport Studies (SWIFT) instrument is able to measure the stratospheric winds and ozone (Shepherd et al. 2001). The Rayleigh lidar technique could cover the height range of 20–85 km (Hildebrand et al. 2012). The horizontal winds between 30 and 79 km could be detected by the ground-based microwave Doppler spectroradiometer (Rüfenacht et al. 2012, 2014). The above-mentioned techniques contribute to studies on the stratosphere and mesosphere.

Comparatively speaking, the meteorological rocket is an effective method for detecting the stratosphere and mesosphere. Because of the high cost, rocket experiments are rare and valuable. But, because of the need for research, many rocket sounding programs have been performed around the world; we mention some of them here. Early records of 53 rocket soundings in 1960–65 were summarized by Nordberg et al. (1965). Most of them were launched at Wallops Island, Virginia (38°N), and Fort Churchill, Manitoba, Canada (59°N). The rest were conducted on Ascension Island (8°S) and in Kronogard, Sweden (66°N). They provided a valuable picture of temperature and wind in the stratosphere and mesosphere. In 1990, a Dynamics Adapted Network for the Atmosphere (DYANA) campaign was performed at Uchinoura, Japan (31°N, 131°E), using rocketsonde and middle and upper atmosphere (MU) radar to collect temperature and wind profiles in the height range of 20–90 km (Tsuda et al. 1992). The Meridian Space Weather Monitoring Project launched its first rocket at Hainan, China (19°N), in 2010, which was a part of space environment detection program along the longitude of 120°E (Jiang et al. 2011). It observes temperature and wind from the ground to the stratopause.

Since the 1960s, a rocketsonde program developed at the Jiuquan Satellite Launch Center (41.1°N, 100.2°E) has had the purpose of serving Chinese aerospace technology development. This program mainly uses two-stage solid rocketsondes and a small solid rocketsonde.

We describe the details of the rocketsondes and model in section 2. Section 3 describes the observed wind characteristics and studies the distribution of wind speed. In section 4, we analyze the monthly and seasonal variations of stratospheric winds. Validations of Horizontal Wind Model 2007 (HWM07) and Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis are performed in section 5. Changes in zonal winds due to sudden stratospheric warming (SSW) are discussed in section 6. Section 7 provides a summary.

2. Rocketsonde data collection

The detection of upper atmosphere by rocketsondes in China began in the late 1950s in order to meet the needs of weapons and space technology development. For decades, a series of rocketsondes, including T-7, HP-2, HP-6, and 761, were developed using liquid rockets, solid rockets, and small solid rockets. The detection method is detailed by Fan et al. (2013). A large amount of available observation data were obtained and provide the preliminary wind distribution at heights of 20–50 km. There are 65 profiles of stratospheric wind data detected by rocketsondes from 1967 to 2004, which cover heights from 26 to 50 km. The precision of rocketsondes is less than 3 m s−1 for wind speed bias and less than 10° for wind direction bias. The vertical resolution is 1 km. For the first time, the data are presented publicly to research the stratospheric wind at the Jiuquan Satellite Launch Center. Chinese rocketsondes sounding data are reliable and can be used (Jiang et al. 2011), and the datasets can be obtained from the authors upon request.

Table 1 lists the dates of the rocketsondes experiments in 1967–2004. Most of the rockets were launched at the beginning of the 1970s and 1980s. According to the stipulation in our launch plan, all of them were launched at 0600–0800 local time (LT). There is a large time series gap in the 1990s. Figure 1 shows rockets in each month and season. The number of rockets is most in May (13 times) and July (12 times). There is no observation in September and October. In December, only two experiments were conducted in 1972. In other months, the number of rockets range from 4 to 8.

Table 1.

Dates of rocketsonde experiments from 1967 to 2004.

Table 1.
Fig. 1.
Fig. 1.

Rocketsondes experiments in 1967–2004 for (left) months and (right) seasons.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

The year is divided into four seasons, namely, December–February (DJF), March–May (MAM), June–August (JJA) and September–November (SON). The accumulated number of rocketsondes in Fig. 1 exhibits that JJA and MAM have the most observations. There are 15 profiles in winter. Data in autumn (SON) include observations only in November, which should be kept in mind in the following analysis.

Figure 2 shows zonal and meridional wind profiles of total rocketsondes. Some profiles have gaps for missing data. Zonal winds in the upper stratosphere have larger variations than in the lower stratosphere. The meridional wind seems to changes little with height. The westerly winds could reach up to 100 m s−1 at the stratopause, which are much stronger than easterly winds. The Jiuquan station is located at midlatitude, where jet streams often occur in upper stratosphere.

Fig. 2.
Fig. 2.

(left) Zonal and (right) meridional winds of rocketsondes in 1967–2004.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

HWM07 (Drob et al. 2008) is the well-known version of the Horizontal Wind Model series. The model provides horizontal wind fields from the ground to the exosphere based on more than 50 years of observations from ground-based and space-based equipment. It is a statistical model that provides the average state of wind fields and cannot resolve random or stochastic variations. This model has been widely used in middle atmosphere research. Many researchers compare their results with HWM (Jiang et al. 2011; Sutton et al. 2007). We run the model to get horizontal winds at heights of 26–50 km on rocket takeoff days. To compare the wind data of HWM and rocketsondes, the model date and local time we choose are same with the rocket takeoff days and local time.

3. Analysis methods and wind speed distribution

A comprehensive wind profile is used to be the flying data designed for NASA in the United States. For example, the integrated wind profile is used by the Kennedy Space Center (28.5°N, 80.6°W), Florida, and the relationship between the average wind and heights is linear in the height range of 20–50 km. The wind speed at the same height is also complex, which changes with the temperature, location, and time.

a. Analysis method

Figure 3 shows the frequency of wind speed distribution at 26, 28, 30, 35, 40, and 50 km, based on the rocketsonde data. Most of the wind speeds are less than 20 m s−1. The frequencies of wind speed indicate that it obeys the lognormal distribution instead of the normal distribution at the same height in many cases. Here wind speed at the height of 35 km is used to explain the data processing for the lognormal distribution. First, speed values of all observations at the same height are arranged in an ascending order. Second, the sorted data are evenly divided into consequent speed sections with an interval of 3 m s−1 as shown in Table 2. Finally, we get cumulative frequency for count numbers in each speed section. The cumulative frequency for wind speed at other heights is calculated in the same way.

Fig. 3.
Fig. 3.

Distribution of wind speed frequency at 26, 28, 30, 35, 40, and 50 km.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

Table 2.

Wind speed partition table of rocketsondes at 35 km.

Table 2.

As the distribution regularity of wind speed is unknown, it is necessary to use the statistical nonparametric testing method to test the overall distribution of wind speed. The wind speed is set as the abscissa and the frequency is set as the ordinate when calculating wind speed, and the cubic spline method is used to roughly draw the curve and determine the initial distribution of wind speed.

b. Normal distribution testing

We mark the accumulated frequency of each section and the corresponding median on the normal probability paper to determine whether the distribution is on a line. If it is a line, then it satisfies the criterion and the wind distribution is normal distribution; otherwise, it is not normal distribution. The testing results by normal probability paper are shown in Fig. 4. It can be found that the distribution does not obey the linear distribution, so the wind speed distribution at the same height does not obey the normal distribution.

Fig. 4.
Fig. 4.

Distribution figure of normal distribution testing.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

c. Lognormal distribution testing

Figure 5 use a base 10 logarithmic scale for the x axis and a linear scale for the y axis. The probability of logarithmic wind speed frequency approaches normal distribution. We mark the related data on the lognormal distribution paper and determine whether it satisfies the linear distribution. If it obeys linear distribution, then it proves that the wind speed of the same height obeys the lognormal distribution.

Fig. 5.
Fig. 5.

Frequency of the wind speed in a logarithmic coordinate.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

As seen in Fig. 6, the distribution regularity of wind speed can be described by the lognormal distribution in most cases and that the distribution can be described as follows:
e1
where is the wind speed distribution density, is the wind speed scalar, and and are constants. The values of and are different at different heights and the corresponding values are listed in Table 3.
Fig. 6.
Fig. 6.

Distribution figure of lognormal distribution testing.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

Table 3.

The values of σ and μ.

Table 3.

4. Wind variations

a. Monthly zonal winds

According to Fig. 1, rocketsondes used in our paper nearly cover every month in a year except for September and October. Most of rockets were launched in May and July. This enables us to study the monthly variations of zonal winds. We choose the heights of 28, 38, and 48 km to represent three layers of the stratosphere, respectively. The monthly mean winds show a clear annual variation that blows to the west in summer and to the east in winter. Therefore, we use a cosine curve to fit mean winds with a fixed period of 12 months. The expression is given by
e2
where is time, is phase, is the amplitude and is the monthly average zonal winds, and is a regulatory factor of amplitude. We define
e3
where Q is used to adjust the amplitude of ; thus, in the fitting curve, the westerly zonal wind in winter is stronger than the easterly zonal wind in summer. The value of Q changes with t, the multiplication factor 0.2 is used to narrow the value range of Q, and the amplitude offset +1 is used to ensure the value of Q to be positive. The phase lag −2 is based on our rocketsonde wind data, since the monthly zonal wind distribution for 12 months is given in Fig. 7. We determine the three fit constants by testing and comparing many times.
Fig. 7.
Fig. 7.

Monthly average zonal winds at the heights of 28, 38, and 48 km. The circle denotes observation data. The black line denotes the fitted curve. (bottom) Number of rocketsondes in 12 months during 1967–2004.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

The fitted monthly mean winds are denoted by black lines in Fig. 7. The coefficients of Eq. (2) and its goodness-of-fit statistics are listed in Table 4. The R2 values of the three fitted models range between 0.6 and 0.7, suggesting that monthly zonal winds are well captured by cosine curves with the annual cycle. But in winter the fitting result is not good, which may be due to the zonal winds being fluctuant in winter. The root-mean-square error (rmse) increases with height. The amplitudes of zonal winds increase with altitude from 21 m s−1 at 28 km to 36 m s−1 at 48 km. The zonal wind direction reverses in spring and autumn and starts from the upper stratosphere.

Table 4.

Results of fitted curves and goodness-of-fit statistics.

Table 4.

b. Seasonal variations

In general, stratospheric winds are westerly in winter and easterly in summer. Because of uneven solar radiation, in winter upper airflow from the low latitudes to the midlatitudes occurs and becomes westerly wind in the midlatitudes with the influence of Coriolis force. The same theory is used for summer, so stratospheric winds are westerly in winter and easterly in summer. Therefore, we divided the rocketsonde observations into four seasons and then averaged them. In Fig. 8, the red line denotes mean wind profiles and the two dashed red lines denote the standard deviation (std dev) of the mean wind profiles; we also provide mean wind profiles simulated with the HWM07 model as a reference (black dashed lines).

Fig. 8.
Fig. 8.

Seasonal profiles of zonal winds and meridional winds for DJF, MAM, JJA, and SON. The blue circle denotes wind speeds. The red line denotes wind speed average. Two dashed red lines denote the std dev for the mean wind. The black line denotes the average wind of HWM07. Negative (positive) U means easterly (westerly) wind direction.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

In winter, the mean zonal wind is eastward from 26 to 50 km with a minimum of ~5 m s−1 at 41 km and a maximum of ~31 m s−1 at 50 km. The model is in agreement with the observed mean zonal winds in the lower stratosphere and the smaller speeds in the upper stratosphere. Moreover, the difference lies mostly within one standard deviation. Zonal wind scatters also show some negative points, which even exceed 40 m s−1 in some cases. The prominent easterly winds in the winter in the midlatitudes may be caused by the SSW, which could turn the easterly winds around. For mean meridional winds, observations are always southward and large in the lower stratosphere. While simulated mean meridional winds are less than ~5 m s−1, they are quite different from rocketsondes in the lower stratosphere.

The average winds in MAM are much smaller than that in the winter, which are less than 10 m s−1 for zonal winds and 4 m s−1 for meridional winds. The HWM07 wind speed is quite small (not more than ~5 m s−1), which agrees with the observation data. The standard deviation of zonal winds is about 10–15 m s−1 in the stratosphere, which is a large variation for spring winds. The large variation may be related to the measurements scattered in time and date. Moreover, the tides and planetary waves may also have some contribution.

In the summer, easterly mean winds dominate the stratosphere, increasing with altitude from about 12 m s−1 at 26 km to 34 m s−1 at the stratopause. The zonal wind scatters are between −20 and about −50 m s−1. Its standard deviation is the smallest one in the four seasons. HWM07 shows a less than 1 m s−1 speed for meridional winds in the stratosphere. Observed mean meridional winds in JJA are small (less than 5 m s−1 in speed). They are in good agreement.

The wind in SON in our paper consists of only rocketsondes measurements in November. The mean zonal wind is ~15 m s−1 at 26 km and increases rapidly to more than 70 m s−1 at 50 km. It displays a marked difference compared with the model, which shows a westerly wind of ~17 m s−1 in the lower and middle stratosphere and increases to ~36 km at the stratopause. As for the mean meridional wind direction, the model is poleward in the entire height range, whereas the observed mean meridional wind is southward below ~42 km and turns to northward above. Although large zonal winds could reach to 100 m s−1 near the stratopause, there is a case agreeing with the model results. We are not sure whether the westerly jet stream is a common phenomenon or occasional events according to only five cases. These cases may not represent the general zonal wind fields.

5. Comparisons

a. HWM07

Comparisons between rocketsondes and HWM07 are exhibited in Fig. 9. The correlation coefficient for zonal winds is 0.7, suggesting high correlations between observations and simulations. The rocket-minus-model bias is 1.8 m s−1 and the root-mean-square (rms) value is 18.9 m s−1. For meridional winds, there is a coefficient of −0.4 between the rockets and the model. The flat shape of wind scatters shows a large spread for the observed winds, which are poorly demonstrated by HWM07. The difference is −0.7 m s−1 and the rms is 12.0 m s−1. The dramatic variations of meridional winds draw our attention when the model provides small results.

Fig. 9.
Fig. 9.

Scatters of (left) zonal and (right) meridional winds for rockets and HWM07. Negative (positive) U means easterly (westerly) wind direction.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

Considering the wind direction differs in winter and summer, we get mean winds for four seasons. Figure 10 shows the observations-minus-simulations differences in DJF, MAM, JJA, and SON. In general, differences are large in the upper stratosphere for zonal winds and in the lower stratosphere for the meridional winds. Zonal mean winds in SON have the largest biases, especially in the stratopause. The SON have data only in November 2004, and the wind is extreme large. We are not sure whether the wind in November could maintain such a high speed. Large biases also exist in DJF for zonal winds and meridional winds because of the dramatic variations. Zonal winds in JJA and SON are overestimated by the model, although the biases are small.

Fig. 10.
Fig. 10.

Differences between the rocketsondes and HWM07 for (left) zonal and (right) meridional winds in DJF, MAM, JJA, and SON.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

Below 100 km, the databases of HWM07 consist of observations from rockets, radiosondes, and falling spheres (Drob DP et al. 2008). Besides, the National Centers for Environmental Prediction (NCEP) data are used for the heights of 0–35 km (Wu et al. 1987). However, observations from the Chinese region covering the subtropics and midlatitudes are hardly included in the model. Hence, biases between the model and rocketsondes are large for most of the time, especially in winter.

b. Modern-Era Retrospective Analysis for Research and Applications

The MERRA reanalysis was developed by the Global Modeling and Assimilation Office (GMAO) of NASA. It is produced by the Goddard Earth Observing System Model, version 5 (GEOS-5), assimilation system. The reanalysis begins from 1979. The horizontal resolution of daily MERRA reanalysis is 0.5° latitude × ⅔° longitude. There are 72 levels up to 0.01 hPa (Rienecker et al. 2011) and four time values on one day. We chose 15 rocketsonde profiles: 7, 8, 10, and 12 July 1981; 12, 14–16 July 1985; 15 August 1998; 26 April 1999; and 8, 15–17, and 19 November 2004. Rocketsondes on some of these days have no data above 40 km. So, the reanalysis is interpolated onto a vertical grid with an interval of 1 km in the height range of 26–40 km. The coordinate of 41.0°N, 100.0°E in the MERRA grid is selected to match the rocketsonde launching site. Values at 0600 and 1200 UTC are averaged for the rocketsonde takeoffs that occurred almost in daylight.

Figure 11 shows the wind relation between MERRA and the rocketsondes. For zonal winds, the correlation coefficient of 0.9877 suggests that the observation data and the reanalysis agree well with each other. The mean bias (rocket minus MERRA) is 0.62 m s−1 and the rms is 4.47 m s−1. Zonal winds of rocketsondes are stronger than that of MERRA. Large biases accompany high speed winds. For meridional winds, the correlation between measurements and the reanalysis is not poor, because our rocketsonde measurements are from one location, while MERRA is a global model. But from the figure, the mean bias is −0.43 m s−1 and the rms is 16.97 m s−1. For MERRA, the meridional wind speed is small. However, the observed meridional wind speed is large. The reanalysis seems to underestimate the speed of meridional winds.

Fig. 11.
Fig. 11.

Scatter of (left) zonal and (right) meridional winds for rocketsondes and the reanalysis.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

Figure 12 gives the differences between the observation data and the reanalysis. The top height is 40 km because of data missing in the measurements. The standard deviation is denoted by a bar. The differences for zonal winds are less than 3 m s−1 and for meridional winds they are less than 10 m s−1. Besides, biases between the reanalysis and the rocketsondes are characterized by the alternating positive and negative variations with height, whereas the model overestimates zonal winds and does not change with height. HWM07 cannot simulate interannual variations of horizontal winds, which may introduce prominent biases compared with MERRA.

Fig. 12.
Fig. 12.

Differences between the rocketsondes and the reanalysis for (left) zonal and (right) meridional winds. The horizontal bar denotes the double std dev of the mean value.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

6. Zonal wind variations due to the SSW

We have noticed that there are large biases for zonal winds between the rocketsondes and HWM07 in DJF. The SSW in winter is a significant phenomenon that can change temperature gradients and wind fields in the North Hemisphere’s stratosphere (Gao et al. 2011). SSW is mainly caused by large planetary waves propagated from the troposphere into the stratosphere. The mean temperature of the stratosphere increases and an induced meridional circulation slows the westerly winds. A major warming is defined if at 10 mb or below the zonal mean temperature increases poleward from 60° latitude and the zonal mean wind reverses. If the wind does not reverse, it is a minor warming. In a major warming event, the westerly wind even changes to easterly, which cannot be produced by the empirical model and introduces dramatic biases for the HWM07 prediction.

There are 15 sets of experiments in DJF, during which major SSWs occur in 1967, 1970, and 1972 as listed in Table 5 (Andrews et al. 1987). In 1971 and 1973, there is no major SSW. These experiments provide us a chance to study zonal wind variations associated with SSWs at the midlatitudes.

Table 5.

Occurrences of major SSWs during the period of rocket sounding projects.

Table 5.

Before investigating zonal winds during SSW occurrences, we should have knowledge of background wind fields in general situations. We present zonal wind profiles in DJF in Fig. 13. Apart from 3 and 10 January 1973, winds on other days were all eastward. In January, westerly winds decreased with height and increased again above ~35 km to maximum near the stratopause. The inflection point in the rocket sounding profiles is lower by more than 5 km than that in the model simulations. HWM07 zonal winds are small (about 20 m s−1) at the stratopause compared with measured winds. The cases are not enough to draw a universal conclusion on zonal winds in winter, but they remind us that the HWM07 results at the Jiuquan Satellite Launch Center in winter seem problematic.

Fig. 13.
Fig. 13.

Zonal wind profiles (red lines) and HWM07 simulations (blue lines) when no major SSWs occur.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

Figure 14 shows four cases during the occurrence of major warmings. On 19 January 1967, easterly winds were found in the overall stratosphere with a maximum of 18 m s−1 at 40 km. This is a significant feature of a major SSW. On 23 January, the zonal winds seemed to recover from the warming event and become westerly with large fluctuations. The wind in the upper stratosphere was still slowed down by the event. On 27 January, zonal winds were westerly below 35 km and easterly above it. The maximum easterly wind was of 21 m s−1 at 42 km. On 3 February 1970, there was a major SSW, but when it was over, the winds became strongly westerly with a minimum of 15 m s−1 at 34 km and a maximum of 63 m s−1 at 46 km. These cases reveal that a major SSW severely changes the zonal wind direction. At the same time, HWM07 results are smooth and not affected by the warming events.

Fig. 14.
Fig. 14.

Zonal wind profiles (red lines) and HWM07 simulations (blue lines) when major SSWs occur.

Citation: Journal of Atmospheric and Oceanic Technology 34, 3; 10.1175/JTECH-D-16-0014.1

7. Conclusions

Rocketsondes are a significant tool for detecting the stratosphere wind with many advantages that cannot be replaced by other instruments. They can provide wind observations for establishing the middle atmosphere wind forecast model and make it possible to detect real-time variation of upper-atmosphere wind (Sica et al. 2008; Zhang et al. 2011). The paper uses 65 instances of rocketsondes sounding wind data from 1967 to 2004 to analyze characteristics of stratosphere wind and makes comparisons with HWM07 and the MERRA reanalysis. The results indicate that the horizontal wind speed at the same heights obeys the lognormal distribution.

Observations are spread across each month in a year except in September and October. We use an adapted cosine curve to fit the monthly mean zonal winds. The period is set to 12 months. The R2 goodness-of-fit statistics are 0.6–0.7 for cases at 28, 38, and 48 km. Amplitudes of annual variations for zonal winds increase with height.

We also discuss the seasonal variations of horizontal wind fields. The mean zonal wind in DJF is westerly with a minimum speed at ~41 km and a maximum speed of ~31 m s−1 at 50 km. Mean winds in MAM have slowed down and zonal winds have become easterly in the upper stratosphere. In summer, zonal winds in the stratosphere have changed directions from westerly to easterly completely. The mean zonal wind is 12 m s−1 at 26 km and increases to 34 m s−1 at 50 km. Observation data in SON represent the mean wind only in November, which has turned to westerlies.

In section 5, all data are used to compare with HWM07 and 15 sets of observations are compared with the MERRA reanalysis. The correlation coefficient for zonal winds between the rocketsonde and MERRA is 0.9877, which is better than 0.7 between the observation data and the model. Although the number of samples is different, the reanalysis overwhelms HWM07 in the stratosphere. As to meridional winds, both HWM07 and MERRA have a weak relation with rocketsondes data.

Finally, we study the SSW impact on winter zonal winds. During the rocket sounding program, there are three occurrences of major warming in 1967, 1970, and 1972. Without SSWs, zonal winds in winter are westerly with a minimum lower than the model predicted and maximum at the stratopause. When SSWs break out, even westerly winds can change to easterly winds. The largest easterly wind was about 21 m s−1 on 27 January 1970.

Acknowledgments

The work was partly supported by the National Natural Science Foundation of China (Grants 41105013 and 41375028); the National Natural Science Foundation of Jiangsu, China (Grant BK2011122); and the Jiangsu Key Laboratory of Meteorological Observation and Information Processing (China) Scientific Research Fund (Grant KDXS1205).

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