Comparison Study of Wind Profile and Tropopause Height Estimated by Wuhan Atmosphere Radio Exploration radar and GPS Radiosonde

Haiyin Qing1, Chen Zhou1, Zhengyu Zhao1, Binbin Ni1, Wenxun Zhang1, Gang Chen1, Yujia Zhu1, and Hua Li1

1School of Electronic Information, Wuhan University, 129 Luoyu Road, Wuhan, 430072, China, E-mail:qinghaiyin123@whu.edu.cn

Abstract

The Wuhan atmosphere radio exploration (WARE) radar is one of the significant facilities of the Meridian Space Weather Monitoring Project of China and dedicated to real-time atmospheric observations. We compare the Wuhan MST radar wind data (3-25 km) with the simultaneous radiosonde data and the temperature data computed from NRLMSISE00 models. Our results show good agreement between the wind field data from Wuhan MST radar and from the GPS radiosonde. The tropopause heights determined by the three methods are close to each other. In terms of the structure constant of atmospheric refractive index Wuhan MST radar gives a height of 15-16.5 km, the GPS radiosonde temperature profile reads that of 16.5-17 km, and NRLMSISE00 modeling computes a value of 16.2 km. Current work indicates that the WAER radar is operative and its data are reliable.

1. Introduction

The Wuhan atmosphere radio exploration (WARE) radar is located in Chongyang County, Hubei Province (geographic coordinates 114°8�8”E, 29°31�58”N; geomagnetic latitude 19.56°; altitude above sea level 62 m) [1, 2]. MST radar is a high-resolution type of atmospheric detecting radar, and it is one of the few large ground-based radio detection equipments in the world and which typically has multiple detection modes with detection altitudes ranging from 3-25 km to 60-110 km, and uses a working time as short as 5 minutes for detecting the complete three-dimensional wind profile. This is tens of times faster than the detection cycles of conventional GPS radiosondes. Therefore, MST radar serves as a powerful technique for studying atmospheric dynamics with intermediate and small time scales. While it has been a common practice to use GPS radiosondes to observe wind fields below 25 km, MST radars have become increasingly familiar to the atmospheric science community as new and valuable wind-field detecting facilities. By comparing MST radar data with those from a GPS radiosonde, we can test the detecting capacity of the radar. Meanwhile, by comparing the detection mechanisms of the two techniques, we can verify our understanding of some common atmospheric phenomena. Figure 1 shows the power spectral density with 5 beams.

Figure 1. Power spectral density with 5 beams: (a) east, (b) west, (c) south, (d) north, (e) zenith

2. Experimental Data and Treatment

During September 10-12 of 2011, Wuhan University organized a GPS radiosonde observational test with 10 radiosondes sequentially launched from the site of the WAER radar to collect wind field and temperature data.

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Meanwhile, the WAER radar operated at appropriate modes corresponding to the radiosonde flight levels and acquired relevant data for comparison. The final effective height of the GPS radiosondes was approximately 25 km, close to the detection height of the intermediate mode of the WAER radar. We calculated all radial velocities in terms of the power density diagram, then we obtained the meridional wind, zonal wind, horizontal wind velocities, and wind directions. The final wind field data from the WAER radar are the values averaged over the entire observation period. GPS radiosondes acquired wind field data directly from each level. Considering the large amount of data because of their high range resolution, we collected one dataset every 20 data points along the height, showing in Figure 2 and 3.

Figure 2. Comparative result of the zonal wind speed. The black lines are the WAER radar data and the blue lines are the

GPS radiosonde data: (a) 2011-09-10, 10:54, (b) 2011-09-10, 17:15, (c) 2011-09-11, 16:52, (d) 2011-09-12, 06:46, (e) 2011-09-12, 09:21

Figure 3. The same as in Fig. 2, but for the meriditional wind speed

There are different definitions for tropopause height. In this work, we choose the international standard version, which means the height at which the temperature structure of low atmosphere loses its saturated adiabatic lapse rate [3, 4]. Certainly tropopause heights determined by different observing tools may differ in their numerical values as a result of differences in instrument mechanism or measurement parameters. For example, Röttger defined the tropopause by radar detection as “radar tropopause”[5]. Radar detection of the tropopause primarily relies on vertical echo waves or Cn

2 calculated from these echoes, since atmospheric turbulence attenuates with height and Cn

2 decreases exponentially with height. As height increases, atmospheric water vapor content quickly drops. Consequently, the dependence of Cn

2 on both temperature and humidity gradually changes to depend only on temperature. The tropopause is the transitional layer from turbulence to advection, and also the transition region for temperature stratification. Below the troposphere, the temperature decreases with height; whereas it increases with height above. Under the synactic effects of turbulence and temperature stratification, a maximum Cn

2 occurs near the tropopause. To expand the range for comparison, we intended to gather the temperature data from the GPS radiosondes and expected a minimum reading near the tropopause along the temperature profile. Unfortunately, part of the data was missing. We defined the temperature as a function of height and fit a fourth order polynomial to yield a satisfactory result. As pointed out in literature [6], the structure constant of atmospheric refractory index that is derived from the WAER radar echoes has an evident maximum at the tropopause. In addition, this work used the NRLMSISE00 model to calculate the related temperatures [7]. Finally a comparative interpretation of the tropopause was provided in terms of the structure constant (Cn

2 ) profile of atmospheric refractive index from the MST radar data, the observed temperature profile from the GPS radiosondes, and the calculated temperature profile from NRLMSISE00 modeling, showing in Figure 4.

Figure 4. The same as in Fig. 2, but for the tropopause's height. The redlines are the temperature calculated from NRLMSISE00 model; the green lines are the WAER radar data and the blue lines are the GPS radiosonde data.

3. Results and Comparative Analysis

By comparing the zonal winds from Fig. 2 and the meridional winds from Fig. 3, we find good agreement between the data from the WAER radar and the data from the GPS radiosondes, with anomalous jumps in the data at only a few points. The WAER radar and GPS radiosondes are the current detection methods for wind fields within 3-25 km, so they obtain real-time atmospheric data; therefore, their data are more realistic. The slight numerical discrepancy between them arises mainly from the difference in their measuring techniques. The WAER radar calculates motion velocities of turbulences of certain scales in terms of backscattered echoes of Bragg scattering, whereas GPS radiosondes measure their velocities in terms of their position differences between any two instants of time. Therefore, there must be some minor differences in the magnitude but consistency in the trend between the results from the two methods.

As shown in Fig. 4, the tropopause height can be clearly identified from the ten sets of comparative data. The tropopause height determined by the WAER radar observations of refractivity structure constant ranges within 15-16.5 km, that by the GPS radiosondes ranges within 16.5-17 km, and that by NRLMSISE00 modeling is 16.2 km. Studies on latitude dependence of the tropopause indicate that tropopause height decreases with latitude, reaching nearly 20 km in the equatorial area, and dropping to around 10 km in the polar regions and the tropopause height has seasonal variations as well [8]. Mega et al. and Yamamoto et al. used the AER radar to study the tropopause in the equatorial area, in which they obtained a tropical tropopause layer ranging within 16.1-16.4 km during December 12-14 of the same year [9,10]. They investigated the turbulence evolution in terms of Kelvin-Helmholtz instability of the tropical tropopause.The three different approaches in our work led to an essentially consistent result for the tropopause height, which agrees with the results by other studies of the tropopause [11]. Generally speaking, because the tropopause is a relatively stable atmospheric stratification, its height barely exhibits a sharp jump over a short interval, with the exception of sporadic diminishing and expansion to multiple stratifications.

4. Conclusion

The WAER radar has been demonstrated to be a powerful tool for the three-dimensional detection of atmospheric wind fields. Other applications of the radar include observations of the tropopause, atmospheric angular spectrum, atmosphere gravity wave, meteor tail, clear-air turbulence, etc. The radar can also be used in observing the lower ionosphere. In a word, the WAER radar is capable of providing basic data for (a) studying small-scale atmospheric systems, atmospheric turbulences, and the atmospheric boundary layer; (b) examining the turbulent structure of atmospheric motion; (c) monitoring changes in the atmospheric boundary layer; (d) determining the height of wind shear; (e) improving short-term forecasts; (f) investigating the spatial structure and temporal variation of wind fields in the middle and upper atmosphere in Wuhan area; (g) elucidating some fundamental dynamic processes in the middle and upper atmosphere; (h) clarifying the mechanisms of coupling between the middle and upper atmosphere and the ionosphere and between the ionosphere and the lower atmosphere. Here we focus on the comparison of the wind field data from the WAER radar and from the GPS radiosondes. We find good agreement in the fine structures of the wind

field between the two methods. The results show the reliability of the WAER radar data, accuracy of the wind field algorithms, fulfillment of the technical specifications of the radar, and its appropriateness in serving as a database establishment for China’s space weather exploration.

5. Acknowledgments

We acknowledge the use of data from the Chinese Meridian Project. This work is also supported by the National Natural Science Foundation of China (41204111).

6. References

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