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/m<sup>2</sup> and 1.5 kg/m<sup>2</sup> , 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  and from the results published in .
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