Estimation of Turbulence Parameters Using ARIES ST Radar and GPS Radiosonde Measurements: First Results From the Central Himalayan Region

Abstract

Turbulence in the atmosphere plays a vital role in controlling the surface, lower and upper tropospheric dynamics. Here, we have utilized a newly installed Aryabhatta Research Institute of Observational Sciences (ARIES) Stratosphere Troposphere (ST) radar at the high‐altitude subtropical site in the central Himalayan region (Nainital, 29.4°N, 79.5°E, 1793 m above mean sea level) for the first ever estimation of turbulence parameters from this unique location. We have used radar observations made in years 2017 and 2019 with simultaneous and colocated global positioning system (GPS) radiosonde observations. In this context, turbulence parameters like turbulent kinetic energy dissipation rate, and eddy diffusion coefficient due to thermal and momentum fluctuations, have been determined by using (i) wind variance, (ii) Doppler spectral width, and (iii) backscatter signal power methods as well as synergistic radiosonde measurements using Thorpe length scale method. The kinetic energy dissipation rate and eddy diffusivity coefficients were found to be as high as 10−2 m2/s3 and 102.6 m2/s, respectively. Statistical distribution of turbulence parameters derived from radar and radiosonde was found to agree reasonably well in terms of measures of central tendency. The refractive index structure constant (Cn2) shows a decreasing tendency with height, and it is found to vary as large as 10−14 to as small as 10−19 m−2/3. Range and temporal variation of signal‐to‐noise ratio (SNR) indicated the existence of a stable layer around 8 km height. It is also evident from the present study that the turbulence parameters at this central Himalayan region of complex terrain are higher by 1 order of magnitude than those reported from the southern part of India.

Turbulence Parameters in the Troposphere—Lower Stratosphere Observed by Beijing MST Radar

“…Previous studies have shown that the turbulence parameters calculated using MST radar data are in good agreement with the calculated results using radiosonde data [11][12][13]. Kantha and Hocking [13] and Li et al [14] compared the ε calculated by radar data and radiosonde data. They used the radar datasets of Harrow VHF (very high frequency) radar (42.04 • N, 82.89 • W) and MAARSY (Middle Atmosphere Alomar Radar System) radar (69.03 • N, 16.04 • E), respectively.…”

“…This paper gives the statistical results of turbulence parameters, but how the turbulence parameters change during synoptic processes needs to be further investigated. For example, the correlation analysis in this paper shows that the turbulence parameters above 15 km may be mainly affected by the turbulence intensity; the results of Khoma et al [15] show that the seasonal characteristics of turbulence parameters are related to gravity waves in the Antarctic stratosphere; and Li et al [14] calculated ε under different Ri, and the results showed that the median values of ε when Ri < 1 is 3.2 times that of when Ri > 1. From October to the following May, in the height layer of 1 km above and below the tropopause, there is no apparent seasonal difference in the monthly average profile of ε. Additionally, log(ε) increases sharply with a rate of 0.25 m 2 s −3 km −1 , derived by linear regression.…”

“…Table 1 shows statistical results of turbulence parameters derived from MST and ST radars in the troposphere-lower stratosphere in different latitudes (a total of 10 radars), revealing that there are specific differences in the statistical results of turbulence parameters across different studies. Jaiswal et al [14] pointed out that the turbulence parameters of the central Himalayas with its complex topography are an order of magnitude higher than those of southern India. To date, relevant research on using MST radar data to analyze the interannual, seasonal, and diurnal variation characteristics of turbulence parameters at different heights has been limited to just a few regions.…”

Validation and traceability of multi-parameter miniaturized radiosondes for environmental observations

“…The same power spectra analysis of the vertical velocity can be used to identify a cut off point of Brunt-Vaisala frequency, while vertical temperature profile (Fig. 10e) can used to derive a complete profile of the Brunt-Vaisala frequency along the altitude [20,21].…”

Turbulence Kinetic Energy dissipation rate: Assessment of radar models from comparisons between 1.3 GHz WPR and DataHawk UAV measurements

“…VHF Stratosphere-Troposphere radars and UHF wind profilers are commonly used to estimate turbulence kinetic energy (TKE) dissipation rate ε from Doppler spectral width (hereafter, noted 2σ 𝑜𝑏𝑠 ) in the atmosphere (e.g., Hocking, 1983Hocking, , 1985Hocking, , 1986Hocking, , 1999Fukao et al, 1994;Cohn, 1995, Kurosaki et al, 1996Bertin et al, 1997, Delage et al, 1997Naström and Eaton, 35 1997, Dole et al, 2001, Jacoby-Kaoly et al, 2002, Satheesan and Murthy, 2002Naström and Eaton, 2005;Wilson et al, 2005, Kalapureddy et al, 2007Singh et al, 2008;Dehghan and Hocking, 2011;Kantha and Hocking, 2011;Dehghan et al, 2014;Wilson et al, 2014;Hocking et al, 2016;Li et al, 2016;Kohma et al, 2019;Jaiswal et al, 2020;Chen et al, 2022). Several models have been proposed to relate 2σ 𝑜𝑏𝑠 to ε.…”