Turbulence spectra and turbulence scales were measured with the AMK-03 acoustic meteorological station and DJI Phantom 4 Pro unmanned aerial vehicle (UAV). The measurements were carried out in the Geophysical Observatory of the Institute of Monitoring of Climatic and Ecological Systems SB RAS, which is located at a territory with complex orography. The turbulence spectra obtained with the AMK-03 and DJI Phantom 4 Pro generally coincide with some discrepancies observed in the high-frequency spectral range starting from Hz. The lateral and longitudinal turbulence spectra in the inertial range obey the “5/3” law, and their ratio corresponds to the Kolmogorov—Obukhov isotropic turbulence. The obtained experimental spectra were approximated by the least square fit method with the von Karman mathematical model. The turbulence scales calculated from the AMK-03 and DJI Phantom 4 Pro findings coincide, and the condition describing the relation between the longitudinal and lateral scales in the isotropic atmosphere is fulfilled.
The paper shows the possibility of using small UAVs with a rotary wing to monitor the state of atmospheric turbulence at different altitudes. The measurements were carried out at the Basic Experimental Observatory (BEC) of the V.E. Zuev Institute of Atmospheric Optics SB RAS. The turbulence spectra at 4, 10, and 27 m, as well as turbulence scale profiles obtained with three DJI Mavic Mini and one DJI Mavic Air quadcopters are reported. The turbulence spectra measured at different altitudes and turbulence scale profiles are compared with the data obtained from three AMK-03 automated meteorological systems installed at the 4-m and 30-m meteorological towers. It has been found that the turbulence spectra obtained with the AMK-03 and quadcopters are generally in a good agreement with some differences observed in the high-frequency spectral region nearby Hz. During the experiment, Kolmogorov turbulence was observed in the atmosphere in a wide frequency range at all altitudes. This type of turbulence was confirmed by both the AMK-03 and quadcopter data. When determining the longitudinal and lateral turbulence scales at altitudes of 4, 10, and 27 m, the least square fit method was used with the von Karman model as the regression curve. The turbulence scales calculated from AMK-03 and quadcopter data are shown to agree well. The condition describing the relation between the longitudinal and lateral scales in an isotropic atmosphere is true to sufficient accuracy.
It is shown theoretically and experimentally that the value of integrated water vapor content in the atmosphere measured by ground-based radiometric facilities in real time can be used, along with the temperature profile, as a predictor of aircraft icing in clouds. The quantitative criterion of occurrence of the conditions leading to aircraft icing is found, and the method for determining these conditions by ground-based remote microwave sensing of the atmosphere in real time is formulated.
The turbulent power spectra of Euler angles are studied. The results of their comparison with the spectra of turbulent fluctuations of wind velocity components in the atmosphere are present. Equations are derived for estimating the horizontal wind components as a function of the means and fluctuation components of Euler angles. Time series of turbulent fluctuations in pitch, roll, and yaw angles, as well as time series of turbulent fluctuations of wind velocity components are obtained during an experiment, which was carried out at Geophysical Observatory of IMCES SB RAS in Tomsk Akademgorodok (Russia). The time series of Euler angles and wind speeds were recorded with a frequency of 10 Hz. The automated weather station data witness anisotropy of turbulent flow speed fluctuations during the measurements in the atmosphere: the spectra of fluctuations of the horizontal components coincide, but differ from the spectrum of vertical fluctuations. The fluctuations of the Euler angles show similar behavior: the spectra of fluctuations of pitch and roll angles coincide, but differ from the spectrum of fluctuations of the yaw angle. The spectra of fluctuations of pitch and roll angles and the spectra of fluctuations of the horizontal wind velocity components generally coincide, though differences are observed in the high-frequency region of the spectrum. In contrast to fluctuations of pitch and roll angles, the spectrum of fluctuations of the yaw angle coincides with the spectrum of the vertical wind velocity component in the high-frequency region.
The problem of ideal hover of an unmanned aerial vehicle in a turbulent atmosphere is considered, and the equations for estimation of turbulent fluctuations of the longitudinal and transverse components of horizontal winds are derived independently of the unmanned aerial vehicle orientation and wind direction. Experiments were carried out on the territory of the Geophysical observatory of Institute of Monitoring of Climatic and Ecological Systems, Siberian Branch, Russian Academy of Sciences. It is situated in Tomsk Akademgorodok, on the territory with complex orography, in a parkland zone with buildings of research institutes and motorways. A DJI Phantom 4 Pro unmanned aerial vehicle flew up to an altitude of 30.7 m and approached an automated weather station, mounted at a mast near the Observatory. Time series of turbulent fluctuations of the longitudinal and transverse components of the horizontal wind were received with the use of the automated weather station, and time series of turbulent fluctuations of estimates of these components, from data of unmanned aerial vehicle in the hovering mode. According to the automated weather station, anisotropic fluctuations of the turbulent flow velocity were observed during the atmospheric measurements: the spectra of fluctuations of the horizontal components coincide, but differ from the spectrum of vertical fluctuations. The spectra of fluctuations of the longitudinal and transverse components of the horizontal wind velocity were comparatively analyzed. The general coincidence of these spectra with the spectra of fluctuations of estimates of the components is shown, with, however, significant differences in the high-frequency spectral region.
Dynamics and statistics of the total content of supercooled water were studied using real-time radiometry methods in the period from November 2016 to January 2017, when aircraft icing was observed at the Tomsk airport. The histogram of the total water content is single-modal and shifted to the left; and the temperature histogram is bimodal. The minimum and maximum values of the total water content are 0 kg/m2 and 1.5 kg/m2 , respectively; and the minimum and maximum temperatures are – 19° C and 0° C. The bimodality of the temperature histogram represents two combined processes that occur during the supercooled water droplets formation in the considered period. The first process is connected with the change of the season of the year, the second - with the arrival of warm and moist air masses to the cold territory.
The impact of Atlantic multidecadal variability (AMV) on anomalous regional temperature regimes formation in the Northern Eurasia during the year is investigated. We study the influence of AMO on the formation of the anomalous regional regimes of near-surface temperature for different seasons. To estimate AMV contribution, we analyzed numerical simulations with the atmospheric general circulation model (ECHAM5) coupled to the thermodynamic model of the upper mixed ocean layer using anomalous ocean heat convergence fluxes associated with the AMV. The results of the model experiment showed that AMV-related anomalous heat fluxes have a significant impact not only on changes in mean temperature, but also they can lead to an increase in the occurrence of regimes with anomalously low and high near-surface temperature deviations. It is found that anomalous heat fluxes may lead to an increase by more than two times of the probability of anomalously low temperatures in winter and spring with increasing mean temperature. An increase by 2-3 times of anomalously hot summer temperatures and anomalously low near-surface autumn temperatures in the Northern Eurasia is also observed.
It is shown that the maximum frequency distribution of icing pireps at the Novosibirsk International Airport in January 2015 was accounted for the height layer from 0 to 1 km. With the increasing height aircraft icing is less common and, starting at 5 km, it is not recorded. Maximum frequency distribution for the Tomsk International Airport in winter 2014 – 2015 was also recorded at these altitudes, but it is not so pronounced, and from 4 km icing has not been reported. Altitude dependencies of frequency distribution for Novosibirsk and Tomsk airports are significantly different from that in the continental United States [1] and from the results published in [2].
Remote sensing technique of detection of potential aircraft icing areas based on temperature profile measurements, using meteorological temperature profiler, and the data of the Airfield Measuring and Information System (AMIS-RF), was proposed, theoretically described and experimentally validated during the field project in 2012 - 2013 in the Tomsk Bogashevo Airport. Spatial areas of potential aircraft icing were determined using the RAP algorithm and Godske formula. The equations for the reconstruction of profiles of relative humidity and dew point using data from AMIS-RF are given. Actual data on the aircraft icing for the Tomsk Bogashevo Airport on 11 October 2012 and 17 March 2013 are presented in this paper. The RAP algorithm and Godske formula show similar results for the location of spatial areas of potential icing. Though, the results obtained using the RAP algorithm are closer to the actual data on the icing known from aircraft crew reports.
Data on temperature inversions in the vicinity of Tomsk on the basis of MTP-5PE profiler data carried out at the IMCES SB RAS were summarized. It is shown that during persistent long-lived powerful anticyclones there is high recurrence of temperature inversions - they occur every day, or 90% of the time. A few characteristics of inversions observed in the region of the Bogashevo airport are presented.
In this paper the numerical simulation results of the Doppler lidar measurements for high horizontal spatial resolution
corresponding grid cell sizes of 1×1 km and 3×3 km are presented. It is shown that the variances, which characterize the
measurement uncertainty of components of mean wind velocity, depend strongly on state of the atmospheric turbulence
and the number and sizes of grid cell. Also the variances are the complex functions of the signal-to-noise ratio, VAD
sector scan angle, elevation angle, and direction sensing. The measurement uncertainty of component of mean wind
velocity U decreases with increasing cell number in the direction sensing of East and for horizontal spatial resolution of
1×1 km. But the measurement uncertainty increases with increasing cell number for resolution equal to 3×3 km. The
variance for the component U is a maximum and the component V has a minimum uncertainty of measurement in the
directions of North and South. The variance for the component U is a minimum and the component V has a maximum
measurement uncertainty in the directions of East and West. The variance for the components U and V have the same
values in the directions of North-East, North-West, South-East, and South-West.
In this paper the numerical simulation results of mean wind velocity vector and its measurement error for VAD
technique using Weather Research and Forecasting Model (WRF) and Yamada-Mellor models are presented. The
numerical model takes into account the non-Gaussian and nonstationary characteristics of the Doppler lidar signal. The
numerical simulation results were compared with CASES-99 experimental data from balloon sonde (GLASS) and the
Doppler Lidar. It shows that results of numerical simulation by WRF and Yamada-Mellor models agree well with
experimental data for potential temperature. Yamada-Mellor model describes the nocturnal low-level jet only up to
100 m and above the fit is fairly bad. But WRF model allows us to have a good comparison for all levels. In case of the
strong turbulence the value of measurement error can greatly surpass the value 0.5 m/s; therefore it does not satisfy
World Meteorological Organization (WMO) requirements for wind. For the high spatial resolution we cannot get the
required accuracy.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.