Home – Home – Jornals – Atmospheric and Oceanic Optics 2024 number 2

Weather conditions are a natural limitation of the use of remote lidar sensing methods of the atmosphere, while the direct method based on an aerological aerosol backscattersonde has no such limitations, and these methods are close in physical principles of measurement. The creation of an all-weather stratospheric aerosol monitoring system can be based on the combination of direct and remote observation methods; however, their consistency should be experimentally confirmed. The results of a lidar-aerological experiment on atmospheric sounding at altitudes of 7-50 and 0-30 km using a ground-based lidar and an aerosol backscattersonde (AZOR), respectively, are presented. The experiment was conducted in Tomsk on March 15-16, 2023. Vertical profiles of backscattering coefficients of radiation from sources with close wavelengths were measured: ground-based 532 nm (in lidar) and balloon-based 528 nm (in AZOR). The obtained consistency of lidar and balloon measurements indicates the possibility of using AZOR as a mobile tool to complement lidar measurements in the case of clouds. The combination of direct and remote sensing of the atmosphere with the aim of improving the quality of measurements in studies of the aerosol composition of the atmosphere is discussed. The possibility of extending two wave (355 and 532 nm) lidar observations by direct measurements of AZOR with an additional set of wavelengths (470, 528, 850, and 940 nm) is shown.

The paper presents an algorithm based on a convolutional neural network with a modified U-Net architecture for detecting cloud formations in satellite images. Multispectral satellite images obtained from the MSU-GS instrument installed at Arktika-M No 1 satellite are used as input data. The accuracy of the algorithm was evaluated using machine learning metrics and comparing the results with reference masks compiled by manual decryption of the satellite images by an experienced decoder specialist. In addition, a comparison with similar products based on data of the SEVIRI and VIIRS instruments was conducted. For areas illuminated by the sun, the cloud mask obtained by the proposed algorithm has an accuracy of 92% compared to the reference mask, and for areas not illuminated by the sun, the accuracy is 89%.

To improve the accuracy of weather and climate forecasts, a deeper understanding of atmospheric processes and phenomena, which are determined, among other things, by high-level clouds (HLCs), is required. The experimental results on polarization laser sensing of high-level clouds are presented. The data of systematic (from December 2009 to present) lidar measurements performed with the high-altitude matrix polarization lidar developed at the Tomsk State University are combined. Optical (backscattering phase matrix, optical depth, and scattering ratio) and geometric (lower and upper boundary altitudes and vertical thickness) characteristics of clouds are determined from the lidar measurements. The dataset is supplemented with corresponding vertical profiles of meteorological quantities (temperature, relative and specific humidity, and wind direction and speed) obtained from radiosonde observations and ERA5 reanalysis. The frequency of lidar detection of HLCs and those of them which are characterized by the preferred horizontal orientation of non-spherical ice particles is estimated. The results were combined into a database and used to create a software product based on neural networks to retrieve the dependencies between the atmospheric meteorological parameters and HLC optical characteristics. The database can be used for various training options in solving problems of atmospheric optics including independent ones.

We present the results of trajectory analysis of multi-year measurements of organic (OC) and elemental (EC) carbon in aerosols sampled on quartz filters from a height of 300 m at ZOTTO station. The EC and OC concentrations were determined by the thermo-optical method. The obtained time series were supplemented with the HYSPLIT backward trajectories. As a result the CWT and PSCF functions were calculated on a grid of 150 ´ 250 cells covering the geographical area 30 ´ 20° with the center in Zotino. These functions characterize the intensity of potential sources of carbon-containing aerosols for a given cell. The results allow us to identify the areas with the strongest organic and elemental carbon emissions and to estimate the seasonal variability of these emissions. In particular, in summer, the main sources of OC and EC are located to the east of Zotino, in the Podkamennaya Tunguska River region, and are most likely associated with forest fires. During the cold seasons, the sources of aerosol carbon dominate in the southwestern part of the geographical area under study, where large cities are located and the bulk of the population is concentrated. It is shown that regression analysis of CWT functions of organic and elemental carbon allows one in some cases to determine the dominant type of sources of carbonaceous aerosols. Our results can be used for estimation of aerosol radiative forcing in Siberia.

Using data from experimental studies in a desertified area and in a wind channel, patterns of vertical distribution of saltating particles in a wind-sand flux have been established, which are necessary for understanding the dynamic and electrical processes in a wind-sand flux. Investigation of the influence of wind velocity in the surface air layer on the vertical distribution of saltating particles in a windsand flux in a desertified area has been carried out. A piecewise exponential approximation of vertical particle concentration profiles with a wind speed-independent height scale and a logarithmic concentration gradient in the lower saltation layer is proposed. Using measurements in the wind channel of saltation particle flux profiles, the dependences of the thickness of the lower saltation layer and the height scale for the mass flux of particles in the lower saltation layer on the size of the saltation particles in the range from 100 to 800 mm are obtained. It is shown that the results of determining the parameters of the windsand flux in the desertified area and in the wind channel are consistent with each other. Our results can be used for modeling the dynamics of wind-sand flux.

Based on simulations performed with the CHIMERE chemistry transport model and WRF meteorological model, we analyzed the processes responsible for the formation of the semi-direct radiative effect (SDRE) of smoke from Siberian fires over snow-ice surfaces in the Arctic. Within the framework of the analysis, time and space averaged changes in the radiative fluxes, cloud parameters in different cloud layers, and some meteorological characteristics associated with cloud formation processes due to the radiative impact of Siberian biomass burning aerosol (SBBA) have been considered. The results show that the scattering of the solar radiation by SBBA particles increases the static stability of the atmosphere at altitudes of 2-4 km and suppresses vertical turbulent motions, which decreases the rate of water condensation, the optical thickness of clouds, and the ratio of the mixture of condensed water in the mid-level and partially low-level clouds. The decrease in the optical thickness of the clouds, in turn, causes the appearance of a positive SDRE of SBBA at the top and bottom of the atmosphere. Absorption of radiation by SBBA particles does not play a fundamental role in these processes, although it causes addition changes in the meteorological characteristics.

The purpose of the present investigation is to evaluate the effect of tropical oscillations on the polar stratosphere. The influence of the quasi-biennial oscillation (QBO) of the zonal wind in the equatorial stratosphere and the El Niño Southern Oscillation (ENSO) on the dynamic state of the stratosphere in winter and the evolvement of sudden stratospheric warming (SSW) is studied. A number of numerical experiments were carried out using the nonlinear general circulation model of the middle and upper atmosphere (MUAM) for the winter conditions of the Northern Hemisphere (January-February). They made it possible to estimate the sensitivity of the fields of zonal wind, temperature, and geopotential to taking into account certain ENSO and QBO phases in the model. Depending on the combination of phases, the statistics of observed SSWs and their evolution differ. For example, the largest number of SSWs is observed under the combination of El Niño and the easterly QBO phase, while major SSWs are not reproduced by the model under the combination of La Niña and the westerly QBO phase. For combinations of El Niño/easterly QBO, El Niño/westerly QBO, La Niña/easterly QBO, the fields of hydrodynamic parameters were averaged to investigate the characteristic features of the model “climatic" SSWs. It is shown that the largest temperature increase in the stratosphere and cooling in the mesosphere are modeled under El Niño conditions and the eastern phase of QBO, but the wind weakening is maxumal during El Niño and the western phase of QBO. The largest amplitudes of planetary waves are modeled during the QBO eastern phase regardless of the ENSO phase. The results can be used in climate forecasting on time scales from one month to decades.

The paper is devoted to thermodynamic and chemical processes inside the stratospheric polar vortex, leading to a decrease in ozone content in this region. The winter-spring seasons in the Arctic with the strongest stratospheric vortices and, as a result, the greatest ozone losses are considered. To study the ozone variations and ozone-active components averaged over the vortex, we used an ensemble of backward trajectories inside the vortex and M2-SCREAM stratospheric reanalysis data, which includes some chemical components that affect the ozone concentration. It is shown that the record ozone depletion in the winter of 2020 was due to not only the long-lived stable stratospheric polar vortex, but also the earlier transformation of chlorine reservoirs into the active form and stronger denitrification and dehydration of air masses. The proposed approach can be used to analyze processes in the polar stratosphere over the past winters, as well as to validate chemical-climate models.

Problem of developing algorithm based upon neutral networks and machine learning to find clouds on hyperspectral images are under consideration. It is required that the network is not a "black box," but allows an analysis of the reasons for decision making and classification results. Presented hybrid model includes decision tree trained to overcast recognition (model 1) on pre-selected features of an image in combination with convolutional neural network (model 2). Model 2 uses the result of model 1 and brightness in a selected band of an image. Model 1 finds cloud cores, and model 2 finds cloud edges. Results of testing the hybrid model on data of HYPERION sensor are presented. Data obtained over three surface types (ocean, plant, and urban region) are considered. Overall accuracy, as well as commission and omission errors are assessed. It is shown that the hybrid model can find 85% cloud pixels, only if the neural network is trained on an image where the contrast attains a maximum in the same spectral band. The results of this work can be applied to solve the general problem of analyzing and processing multispectral satellite images and further in environmental science and monitoring of changes in vegetation, ocean and glaciers.

To estimate the relative contribution of the main chemical and physical processes to the observed variability of climate and atmospheric gas composition in 1980-2020, numerical experiments were conducted with the chemical and climatic model (CMC) SOCOLv3. The following factors of changes in ozone content and atmospheric temperature were studied: changes in the content of ozone-depleting substances; changes in greenhouse gas concentrations, ocean surface temperature and sea ice area; variations in solar activity, and changes in atmospheric aerosol content. To estimate the relative role of these factors, calculations were carried out on scenarios taking into account each factor separately and all factors together. According to the results of numerical experiments, the relative contribution of various factors to changes in the temperature of the troposphere and the lower stratosphere, as well as the ozone content was revealed for the period from 1980 to 2020. The model results have been compared with the satellite SBUV data.

The paper solves the problem of deriving the relationship between the variability of statistical characteristics of atmospheric parameters measured by GNSS receivers and the characteristics of convective processes according to the monitoring data near the Kazan city for 2013-2021. The results of GNSS monitoring are compared with the convective indices for the observation period. To assess convective processes, we used physical and statistical parameters of instability calculated from ERA5 reanalysis: Upward Vertical Velocity, Vortex Generation Parameter, and WMAXSHEAR. Statistical characteristics of the zenith tropospheric delay’s horizontal gradient significantly change under conditions of deep convection. The results of the work can be used to develop a methodology for sub-satellite monitoring of convective processes in the tasks of operational forecasting of severe weather phenomena.

Possibilities of astronomical millimeter and submillimeter observations strongly depend on the precipitable water vapor (PWV), which determines the radiation absorption. The precise determination of PWV within large regions is one of key astroclimate problems. In this work, we refine estimates of PWV content for different sites based on processing ERA5 reanalysis and radiosounding data and test the previously proposed technique for correcting PWV values taking into account the characteristic water vapor vertical scale and relative altitude difference of grid nodes. In addition, the spatial distribution of the nighttime atmospheric optical thickness at a wavelength of 3 mm averaged over December - February 2013-2022 was derived for the first time for Russia and the adjacent territory. Our results can serve the basis for selecting an astronomic site for a new large millimeter telescope within the Eurasian Sub-Millimeter and Millimeter Telescope Project.

High-precision satellite laser ranging (SLR) is actively used all over the world to solve a variety of tasks, primarily in geodesy and navigation. However, the disadvantage of laser systems is the dependence of the effectiveness of their use on weather conditions, in particular, on the presence of clouds. However, in separate experiments conducted at the JSC “Precision Systems and Instruments" (JSC “PSI"), it was possible to receive laser pulses on board a spacecraft in cloudy conditions. The purpose of the work is to evaluate the possibility of functioning of the metrological laser system (MLS) developed at JSC “PSI" in the presence of certain types and forms of clouds that allow the reception and determination of the parameters of laser pulses. Mathematical models of the atmosphere for a laser radiation wavelength of 0.532 microns have been developed, including optical characteristics of the crystalline medium for aggregate structures of ice particles. Calculations of the transfer of optical radiation of subnanosecond laser pulses from ground stations to high-orbit and low-orbit spacecrafts in the presence of upper- and middle-level crystalline clouds have been performed. The amplitude-time characteristics of optical signals on board the spacecrafts are calculated. It is shown that the principles of one-sided SLR can be implemented in the presence of cirrus, cirrus-layered, and cirrus-cumulus clouds in the sky, as well as altostratus clouds with established limitations on the optical thickness. The results confirm the possibility of increasing the technological performance of high-precision SLR systems, in particular, MLS, since the repeatability of the cloud forms under study over the territory of the Russian Federation is about 20%.