Diagnosis of severe squalls based on the data of DMRL-C Doppler weather radars and numerical modeling

The approach to the automated diagnostics of severe squalls (≥ 25 m/s) based on the DMRL-C radar network information and the results of numerical modeling is presented. The discriminant function used for the diagnostics was previously tested during the automated forecast of severe squalls. The predictors are the maximum convective velocity calculated from the DMRL-С data and the Laplacian of surface pressure predicted at the 0,05×0,05° radar data grid points with a temporal resolution of 10 minutes according to the regional model of the Hydrometeorological Center of Russia. The proposed approach was tested during the period from May 1 to July 31, 2020 (more than 13000 observation moments). The presented results will provide additional data on severe squalls and can be used to refine short-term forecasts and storm warnings about such weather events.Keywords: diagnostics, squall, severe weather events, radar data, DMRL-C, simulation results

On the uniform controllability for a family of non-viscous and viscous Burgers-α systems

In this paper we study the global controllability of families of the so called non-viscous and viscous Burgers-α systems by using boundary and space independent distributed controls. In these equations, the usual convective velocity of the Burgers equation is replaced by a regularized velocity, induced by a Helmholtz filtered of characteristic wave-length α. First, we prove a global exact controllability result (uniform with respect to α) for the non-viscous Burgers-α system, using the return method and a fixed-point argument. Then, the global uniform exact controllability to constant states is deduced for the viscous equations. To this purpose, we first prove a local exact controllability property and, then, we establish a global approximate controllability result for smooth initial and target states.

Convective and turbulent motions in non-precipitating Cu. Part 1: Method of separation of convective and turbulent motions

Atmospheric motions in clouds and cloud surrounding have a wide range of scales, from several kilometers to centimeters. These motions have different impacts on cloud dynamics and microphysics. Larger-scale motions (hereafter referred to as convective motions) are responsible for mass transport over distances comparable with cloud scale, while motions of smaller scales (hereafter referred to as turbulent motions) are stochastic and responsible for mixing and cloud dilution. This distinction substantially simplifies the analysis of dynamic and microphysical processes in clouds. The present research is Part 1 of the study aimed at describing the method for separating the motion scale into a convective component and a turbulent component. An idealized flow is constructed, which is a sum of an initially prescribed field of the convective velocity with updrafts in the cloud core and downdrafts outside the core, and a stochastic turbulent velocity field obeying the turbulent properties, including the -5/3 law and the 2/3 structure function law. A wavelet method is developed allowing separation of the velocity field into the convective and turbulent components, with parameter values being in a good agreement with those prescribed initially. The efficiency of the method is demonstrated by an example of a vertical velocity field of a cumulus cloud simulated using SAM with bin-microphysics and resolution of 10 m. It is shown that vertical velocity in clouds indeed can be represented as a sum of convective velocity (forming zone of cloud updrafts and subsiding shell) and a stochastic velocity obeying laws of homogeneous and isotropic turbulence.

The line asymmetry in the spectra of the Sun and solar-type stars

We have analysed the asymmetry of lines Fe I and Fe II in spectra of a solar flux using three FTS atlases and the HARPS atlas and also in spectra of 13 stars using observation data on the HARPS spectrograph. To reduce observation noise individual line bisectors of each star have been averaged. The obtained average bisectors in the stellar spectra are more or less similar to the shape C well known to the Sun. In stars with rotation velocities greater than 5 km/s the shape of the bisectors is more like /. The curvature and span of the bisectors increase with the temperature of the star. Our results confirm the known facts about strong influence of rotation velocity on the span and shape of bisectors. The average convective velocity was determined based on the span of the average bisector, which shows the largest difference between the velocity of cold falling and hot rising convective flows of the matter. It’s equal to -420 m/s for the Sun as a star. In stars, it grows from -150 to -700 m/s with an effective temperature of 4800 to 6200 K, respectively. For stars with greater surface gravity and greater metallicity, the average convective velocity decreases. It also decreases with star age and correlates with the velocity of micro and macroturbulent movements. The results of solar flux analysis showed that absolute wavelength scales in the atlases used coincide with an accuracy of about -10 m/s, except for the FTS-atlas of Hinkle et al., whose scale is shifted and depends on the wavelength. In the range from 450 to 650 nm, the scale shift of this atlas varies from -100 to -330 m/s, respectively, and it equals on average of 240 m/s. The resulting average star bisectors contain information about the fields of convective velocities and may be useful for hydrodynamic modeling of stellar atmospheres in order to study the characteristic features of surface convection.

Diagnosis of squalls in snowstorms based on DMRL-C Doppler weather radar data

The results of studying the diagnosis of squalls in snowstorms based on DMRL-C Doppler weather radar data are presented. The diagnosis of squalls is performed using the algorithm developed in the Hydrometcentre of Russia for diagnosing showers based on the maximum convective velocity calculated from radar data (maximum radar reflectivity in a cloud and the cloud top height). The algorithm implies the determination of the fact of the occurrence of squalls for three speed gradations (15-19 m/s; 20-24 m/s; ≥25 m/s) and the refinement of wind speed during a squall. Keywords: diagnosis, radar data, snowstorm, squall Fig. 6. Ref. 7.

Parameterization of Radiation Fog-Top Height and Methods Evaluation in Tianjin

Different methods have been developed to estimate the fog-top height of radiation fog and evaluated using the measurements obtained from a 255-m meteorological tower located in Tianjin in 2016. Different indicators of turbulence intensity, friction velocity (u*), turbulence kinetic energy (TKE), and variance of vertical velocity (σw2) were used to estimate the fog-top height, respectively. Positive correlations between the fog-top height and u*, TKE, and σw2 were observed, with empirical parameterization schemes H = 583.35 × u * 1.12 , H = 205.4 × ( T K E ) 0.68 , and H = 420.10 × ( σ w 2 ) 0.51 being obtained. Among them, σw2 is the most appropriate indicators of turbulence intensity to estimate the fog-top height. Compared with sensible flux and condensation rate, the new form of convective velocity scale (w*) was the most appropriate indicator of buoyancy induced by radiative cooling, and the relationship H = 328.33 × w * 1.34 was obtained. σw2 and with w*, which represents the intensity of turbulence and buoyancy, were used to estimate the fog-top height. The relationship H = 396.26 × (σw + 0.1 × w*) − 16 was obtained, which can be used to accurately estimate the fog-top height. Moreover, the temperature convergence (TC) method was used to estimate the fog-top height; however, the results strongly rely on the threshold value.