Dangerous Weather Phenomena Research Articles

LEVERAGING DEEP LEARNING FOR IMPROVED CYCLONE FORCASTING

Tropical cyclones (TCs) are frequently rarest but one of the foremost dangerous weather phenomena to arise over tropical oceans, usually creating huge issues with nearly ninety storms globally annually. Early detection and monitoring of TCs are necessary for the early warning of areas in danger. Since these storms originate over the open ocean and frequently out at sea many miles of continental regions, they are detected using remote sensing. In this paper, we propose an automatic method to identify the formation of TCs through satellite images combining a deep learning architecture. The methodology is based on a two-stage deep learning framework: Mask CNN as detector stage—second wind speed filter and lastly Convolutional Neural Network (CNN) for classification. The best possible performance is obtained by hyperparameter optimization using Bayesian Optimization across the pipeline. Results show that the proposed method achieves a precision, specificity, and accuracy of 97.10%, 97.59%, and 86.55% in test images respectively KEYWORDS— Convolutional Neural Networks (CNN), Deep Learning, Cyclone Detection and Tracking, Tropical cyclone Intensity.

A DEEP LEARNING MODEL FOR EFFECTIVE CYCLONE INTENSITY ESTIMATION

Tropical cyclones are extremely dangerous weather phenomena that cause significant damage to human life, property, economy, agriculture, and development. Currently, various methods are being used to estimate cyclone intensity. One such method is the objective deviation angle variance technique, which estimates the intensity of tropical cyclones from satellite infrared imagery by performing statistical analysis of the brightness of those images. The limitation of this method is that it requires images with properly marked cyclone centers. Another method to estimate cyclone intensity involves feature engineering and machine learning, however, which is a manual process. To address the limitations associated with the above conventional methods, a new approach is being proposed that uses a deep learning mechanism to design a CYCLONE NETWORK (CY-Net) model. This model will estimate the cyclone intensity by using INSAT-3D infrared (IR) images. The CY-Net model is developed based on structural, intensification, and landfall features along with biasing parameters such as wind speed, sea level pressure, and sea surface temperature. The INSAT 3D data is given as input to the model for training, testing, and validation. It undergoes convolution along with the Re-lu activation function to generate feature maps, max pooling, sub-convolution, and fully connected layers. The stochastic gradient descent factor is measured to implement the backpropagation. The Stochastic gradient and backpropagation network are implemented to obtain the best filter coefficients. The trained, tested, and validated model is deployed in Python-flask for web application and then hosted using the web servers for web application. This approach uses advanced machine learning techniques to estimate cyclone intensity and has the potential to improve accuracy and reduce manual effort.

THE OBSERVATION NETWORK PERFECTION FOR FLIGHT SAFETY IN THE REPUBLIC OF KAZAKHSTAN

One of the ways of flight safety improvement and quality air traffic services is perfection the material and technical equipment of the country's observation network. This makes it possible to improve the analysis of the state of the “surface background– atmosphere” system, which is necessary, in particular, to identify hazardous and especially dangerous weather phenomena and to predict them. One of the directions for improving the means of monitoring atmospheric processes is the use of remote sensing methods of the atmosphere, which include meteorological radar. Today, meteorological radar networks have been created in all developed countries: in the United States, the NEXRAD network unites about 150 WSR-88D Doppler polarized S-band radars; in Europe, within the framework of the international OPERA project, about 180 radars from various manufacturers working in various observation programs are networked. Some of them are doppler and polarized. In China, Japan, Australia, radars are also integrated into national networks. In the process of analyzing open sources, we determined the main characteristics of meteorological radar networks in several countries of the world and calculated the required number of radars to cover the territory of the Republic of Kazakhstan.

Dangerous Weather Phenomena in Tbilisi and Associated Climate Risks

Dangerous Weather Phenomena in Tbilisi and Associated Climate Risks

Improvement of research methodology mesostructures of atmospheric fronts on the basis of ground­based microwave radiometry

The paper considers the some results of experimental studies of the mesoscale structure of atmospheric fronts using a ground-based microwave water vapor radiometer. A methodology for studying the mesoscale structure of atmospheric fronts is described, which includes two stages: the stage of syn- optic (frontological) analysis and the stage of mesoscale analysis based on measurements of atmospheric moisture and cloud liquid water content using a microwave water vapor radiometer. The application of the methodology is demonstrated by the example of the analysis of the results of observation of the case of the passage of warm and cold fronts through the Leningrad region on September 9—14, 2020. Based on the analysis of the results of previous studies, the features of changes in the characteristics of moisture content during the passage of atmospheric fronts are generalized. The growth of the atmospheric water vapor and cloud liquid water content is delayed relative to the appearance of harbingers of a warm cloud front of the upper tier. The growth of moisture content characteristics has a wave-like character, which can be explained by the manifestation of the strip mesostructure of the front. Estimates of the characteristic scales of spatial heterogeneities in the structure of atmospheric fronts for the area under consideration differ from similar characteristics obtained by P. Hobbs for the northeastern coast of North America. In the course of mesoscale analysis, the type of atmospheric front crossing the observation point can be clarified. The results obtained determine the prospects for improving the methods of diagnostics and current forecasting of dangerous weather phenomena during the passage of atmospheric fronts using ground-based microwave radiometers

Spectral Parameters of Signal in a Meteorological Radar

Specific features of the application of the spectral parameters of the received signal for the recognition of dangerous weather phenomena in a meteorological radar are considered. The advantages and disadvantages of existing methods are outlined. A new recognition method based on the estimation of the base of the input random process is proposed.

Study of Ultra-High Frequency Radiometric Humidity Sounding of the Atmosphere for the Early Warning of Hazardous Weather Phenomena

Ground-based microwave radiometry was used to study the characteristics of the moisture content of the atmosphere during the development of cloud-related hazardous weather phenomena, precipitation, and thunderstorms. On the basis of complex radiophysical studies of the atmosphere, carried out in the Leningrad oblast, the possibility of improving the methods of early warning of dangerous weather phenomena and diagnostics Ground-based microwave radiometry was used to study the characteristics of the moisture content of the atmosphere during the development of cloud-related hazardous weather phenomena, precipitation, and thunderstorms. On the basis of complex radiophysical studies of the atmosphere, carried out in the Leningrad oblast, the possibility of improving the methods of early warning of dangerous weather phenomena and diagnostics of atmospheric fronts with the involvement of operational microwave radiometric information is shown.

Decision criteria for the classification of meteorological phenomena in the weather radar complex of the near-airfield zone

The increasing need to obtain data on the meteorological situation to ensure the safety of aircraft flight actualizes the development of radar systems for remote collection and processing of information, including for solving the problems of classifying dangerous weather phenomena. This determined the primary development of the domestic weather radar complex of the near airfield zone (WR BZ). The article presents the features of the construction of the WR BZ, as well as the main tasks it solves. To classify meteorological phenomena from cloudiness to squall in the weather radar complex of the near airfield zone, it is proposed to take as a basis the criteria tested by weather radar stations of previous generations. These criteria are based on an analysis of the height distribution of reflectivity, taking into account the vertical temperature profile. In addition, a criterion for classifying thunderstorms in the cold period of time has been additionally introduced in the WR BZ. To calibrate the values of the criteria, a mathematical apparatus and special software were developed. To collect statistical data, WR BZ were installed in various climatic regions: the Central and North-Western Federal Districts and the Republic of Crimea. Further, an effective validation of the information received was carried out. At present, WR BZ has passed preliminary, acceptance, certification tests, trial operation, while demonstrating an effective classification of meteorological phenomena, thanks to the correct selection of decision criteria. The article considers the possibility of increasing the reliability and justification of the classification of dangerous meteorological phenomena through the additional use of information on the distribution of altitudes of the specific rate of dissipation of turbulent energy of the atmosphere, as well as an additional set of statistical data in various climatic zones of the European territory of Russia – the Upper Volga Region and the Krasnodar Region.

Климатология туманов в Центральном Предкавказье

Introduction. Fog is one of the dangerous weather phenomena, since it has a negative impact on the operation of all types of transport, worsens the ecological state of the air basin of cities, leads to deterioration in the well-being of people with a number of diseases, etc. Therefore, the study of the fog regime and its dynamics is an important task, especially in the era of rapid and significant climate change. The work is devoted to the study of the regime of fogs in various landscapes of the Central Ciscaucasia. The main characteristics of the fog regime in the current climate are calculated. To determine the change in the fog regime, the new century data are compared with data for two multi-year periods of the 20th century. Particular attention is paid to the modern regime of fogs in the resort of Kislovodsk and in airport areas in Mineralnye Vody and Stavropol. Materials and research methods. The information base for the analysis of the fog regime was the observation data of 16 meteorological stations of the Stavropol Krai for 2001–2020, data from the USSR Climate Reference Book [24] and the monograph “Stavropol Territory: modern climatic conditions” [5]. The studies were carried out by methods of physical-statistical and regression analysis. Research results and their discussion. For all meteorological stations of the Central Ciscaucasia, the averaged main characteristics of the fog regime for the first two full 10 years of the new century are calculated: the annual, seasonal and monthly number of days with fog and their total duration in the indicated periods. The extreme values of the specified characteristics are determined. The analysis of the annual course of the main characteristics of fogs has been carried out. Based on the results of a comparative analysis of the obtained data with data over two long-term periods of the 20th century, the characteristic of the dominant trend in long-term changes in the frequency and duration of fogs is given. Conclusion. It is shown that the distribution of fogs over the territory of the Stavropol Krai has a complex character; there is no clear connection with the landscape structure. For most of the region, there is a certain similarity in the trends in changing the fog regime: decrease in the annual number of days with fog; reduction of the total annual duration of fogs; decrease in the proportion of fogs of the cold period in the annual number of days with fog; reduction in the share of fogs of the cold period in the total annual duration of fogs; decrease in the duration of one fog both on average per year and during the cold period.

Об одной модели снижения рисков от засух в сельском хозяйстве

Introduction. The article analyzes the changes in moisture content of the soil in the south of the European territory of Russia (ETR) associated with climate warming. It is shown that both in the foothill and steppe climatic zones there is a tendency to decrease this parameter, which greatly increases the relevance of developing methods to reduce risks in agriculture associated with droughts. A model based on different vulnerability of agricultural crops to this dangerous weather phenomenon is presented, the results of model calculations for the conditions of the steppe zone of the Kabardino-Balkarian Republic (KBR) are presented. Materials and research methods. When conducting research, the Selyaninov hydrothermal coefficient was used as an indicator characterizing the moisture content of the soil. The values of this coefficient were calculated using data from 13 weather stations on the amount of precipitation and air temperature for 1961-2018. The development of a risk reduction model in this paper is considered within the framework of decision theory. As a target in the problem, you can use a function that describes the gain or loss of agriculture. Using this method of choosing an action to reduce risks avoids the formation of a set of actions from which it is necessary to choose the most appropriate one. Research results and their discussion. The results of the calculations carried out in the work showed that the consequence of climate change in the south of the EPR will be a significant deterioration in the conditions for the production of agricultural products. The consequences of such a trend will be extremely negative for agricultural production in the area. As a result of solving the problem, it is possible to determine the optimal structure of crop production from the point of view of the criterion used, taking into account the probability of droughts. As such a criterion, the maximum expected volume of crop production was used, taking into account the impact of droughts. Conclusions. A method has been proposed to reduce the losses of agriculture from droughts, taking into account their different vulnerability to various crops. The model was written in the framework of linear programming, which makes it possible to determine the optimal structure of agricultural production in terms of the criterion used. The method can be used in regions with different production and economic conditions.

Monitoring of climate change and its impact on grain production in the Saratov region using remote sensing data

The relevance of the topic of the article is due to the increase in the number of adverse climatic phenomena and the strengthening of their influence on the basic branch of agriculture - crop production. The differential manifestation of negative weather factors in the most productive regions leads to fluctuations in yields and agricultural production, disruption of food chains and a decrease in food stocks, thereby jeopardizing sustainable agricultural production and creating risks for ensuring the food security of the Russian Federation. This necessitates the study of regional features of the manifestation of dangerous weather phenomena for the subsequent substantiation of organizational and economic measures to mitigate the consequences and adapt agriculture to global climate change. As an example, we took the Saratov region, as a region with a significant amount of sown (planting) areas and a high share of crop production in the total crop production of the Russian Federation. Using satellite monitoring data, a number of adverse meteorological (weather) phenomena have been established that manifested themselves in the period from 1991 to 2019 in the Saratov region. The tendency to their growth and increase in duration in the territory of the given region is revealed. The dependence of the main indicators of grain production in the Saratov region on the growing influence of negative climatic factors has been studied. The necessity of taking into account the impact of hazardous meteorological (weather) phenomena in the system of strategic priorities, as well as in the preparation of forecasts for the socio-economic development of the region, modeling the impact of negative climatic factors on the structural balance of the agro-industrial complex, is substantiated.

Об особенностях пространственно-временной изменчивости характеристик волн тепла последних трех десятилетий (Араратская долина, Армения)

The aim of this work to study, identify the repeatability and duration of heat waves of the study area. For it were suggested and decided the following tasks: Findings. The study of regularities of variability of the spatial-temporal distribution of characteristics of heat wave in conditions of regional and global changes of climate is current task of modern geographical science. Extremely high temperatures and heat waves of study area excessively conditioned by the influence of secondary thermal depressions from the Arabian Peninsula, a number of cases that last for 2-3 decades are significantly increased. Tropical thermal depression, forming of extreme hot summers and heat waves, have cycles of activation and weakening, periodicity of which is estimated at 20-22 years. Starting from July (sometimes from the second half of June) to the last ten days of August (sometimes to first half of September), weather conditions of Ararat valley are formed under influence of thermal depression. The invasion of southern and south-eastern tropical warm and dry air currents from the Arabian deserts is increasing. As a result in some years the air temperature in Ararat valley is increased to 40-43 °C, and relative humidity is low than 30%. Heat waves are dangerous weather phenomena, is threat for live and activity, are characterized with some negative consequences. They can be accompanied by droughts and dry winds, forest fires, desertification, disruption of the natural ecosystem, economic damage, decreased working capacity, psychological and sociological consequences, even deaths. Temporal tendencies in course of values of the characteristics of heat wave for last 2-3 decades have positive unambiguous character, more frequent heat waves and extremely warm summers. Heat waves of low and medium intensity have a particularly high frequency. The probability of strong waves is less. The study area is distinguished a characteristic regime and an almost uniform spatial distribution of summer extreme high temperatures. They range from 41,5 to 42,6 °C. The entire study area is vulnerable to heat waves. Heat waves can cause dangerous meteorological phenomena such as droughts or dry winds, which cause great damage to various sectors of the economy, especially agriculture. Therefore the results of the work can be used in the field of agriculture, mitigating and reducing the consequences of possible damage caused. They can also be used in agrometeorological forecasts. In the study area, summer conditions become warmer and drier, which should be taken into account when developing strategic programs for the future development of this area.

Climatology of selected dangerous weather phenomena at Cairo and Borg-Alarab airports

Climatology of selected dangerous weather phenomena at Cairo and Borg-Alarab airports

Example of the importance of early warning of extreme weather events in Montenegro in the context of recent climate change

In the last two decades, there has been no year in Montenegro in which some weather extreme has not been registered. The aim of this paper is to highlight the importance of an early announcement of potentially dangerous weather phenomena in the example of one case in Montenegro. The prognostic material including ocassionally storm surges, heavy rainfall and the occurrence of severe local instability in Montenegro on July 28, 2019 was considered. Based on the analysis of the synoptic material, the warning of the expected weather conditions was given two days before. The warnings of the competent institutions should be respected in order to adapt the population to the expected extreme weather situations and thus avoid or mitigate the negative consequences.

Freezing rain phenomena. Case study: Bucharest metropolitan area, January 24-29, 2019.

The paper has a structure with four parts and presents the climatic risk aspects that happened in Romania during the winter of the year 2019, concentrating on Bucharest, where a very rare and dangerous phenomenon occurred, `freezing rain`. The first part contains the theoretical analysis of the subject under discussion (the notion of risk and freezing rain), in the second part we analyzed the synoptic context (the causes that led to the phenomena) and the datacollected, the third part presents the results of the research (the duration of phenomena and the case study in the city), and the last part deals with proposed measures in order to reduce the risk of freezing rain, measures that can apply to any dangerous weather phenomena with freezing deposits. Therefore, the study aims to analyze this risk starting from the theoretical explanation of the synoptic context that generated its production to the quantitative analysis of the phenomena. To achieve this objective, the periods ECMWF models and the synoptic databases were accessed, with the help of which the representation and evolution of the phenomena was managed.

Concept of the Secondary Automated Network for Monitoring Weather Conditions whith Low-power Radars as Sensors

This article is devoted to creation of the secondary network using base stations of mobile telecommunications operators. General advantages of the secondary networks are discussed. Then we suggest to build a novel network of low-cost small base radars (BSR) by adding the low-power radars to the existent selected base stations’ equipment. This gives a possibility to obtain a high-resolution meteorological information in particular about dangerous weather phenomena in real-time and for any region of mobile network coverage. The applications of the proposing network are not limited by meteorology, but includes also some other fields, for example, traffic monitoring, birds and insects’ migration observations, etc.

Синоптические условия формирования снежных гроз на территории Западной Сибири

The article presents the results of work on the study of synoptic conditions for the formation of a dangerous weather phenomenon for the territory of Western Siberia – a thundersnow. The material for the study was the archive of aerosynoptic material from the Khanty-Mansiysk Air Meteorological Center.

Investigations of the Atmospheric Moisture Contents Variations Using Ground-Based Microwave Radiometers

The method of microwave radiometry for investigations of the atmospheric water vapor and integrated cloud liquid water content is considered. Some results of experimental studies of temporal and spatial variations in the integrated water vapor and cloud liquid water contents using ground-based microwave radiometers during different meteorological condition as well as during developments of dangerous weather phenomena are presented. The results of the experiments confirm the prospects of using microwave radiometric information for forecasting of dangerous weather events associated with the development of convective clouds and thunderstorms.

Time distribution of thunderstorms observed at Odesa AMSC at the beginning of the 21st century

The article presents the results of the research of thunderstorm activity at Odesa AMSC for the period of 2000-2019. Under conditions of intense warming, thunderstorm activity responds to the changes of temperature, humidity, radiation regime and atmospheric composition. Modern climate changes that are characterized by rising air temperatures have a decisive influence on the conditions under which dangerous weather phenomena are formed, thus monitoring of the thunderstorms formation in Ukraine is of great importance.
 The research includes the analysis of synoptic conditions of thunderstorm activity formation such as air-mass processes, frontal activity, and studies daily and daytime variability of the number of thunderstorm cases for the given period. The results of everyday meteorological observations of atmospheric phenomena conducted by Odesa AMSC within the period of 2000-2019 were used as input data to determine the characteristics of thunderstorm activity over city of Odesa. In order to identify the presence, time and duration of thunderstorm activity aviation weather diaries AV-6 were also reviewed. Certain synoptic materials were used to analyze the types of phenomena. Such materials include interactive database ARMsyn, surface synoptic charts for the periods of observation before and during the thunderstorms.
 It was established that during the period under study air-mass thunderstorms were formed in 370 cases of thunderstorm activity observed at the given observation post. Frontal thunderstorms occur less often: 241 cases over 20 years. The largest number of such thunderstorms is cold front thunderstorms amounting to 129 cases. 75 of them were identified as occlusion front thunderstorms. The least frequent were warm front thunderstorms – only 37 cases constituting 15% of the total number of frontal formations.
 During the studied period a total number of 620 thunderstorm cases was recorded, 195 of which are dry thunderstorms. Considerable attention is paid to the daily and daytime variability of thunderstorm cases number recorded by Odesa AMSC. With relation to the daily variation, more thunderstorms are observed during daytime amounting to 393 cases, 130 of which are dry thunderstorms. Night thunderstorms amount to 227 cases, 65 of which are dry thunderstorms. With relation to daytime distribution, more thunderstorms were detected in the afternoon.

Doppler weather radar data assimilation at convective-allowing grid spacing for predicting an extreme weather event in Southern India

ABSTRACT Thunderstorms and heavy rainfall are the most devastating and dangerous weather phenomena over the tropical region. Southern Peninsula India in general and regions close to Western Ghats in particular are very prone to such severe weather activity. To improve the short-range forecasting of such extreme weather hazards, tremendous efforts are made to develop Doppler Weather Radar (DWR) network over Indian region for detection and continuous monitoring of weather activities. In this study, the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3D-Var) data assimilation system are used to evaluate the importance of the frequently available DWR observations at convective-allowing grid spacing for predicting an extreme weather event. Various assimilation experiments are performed using background error covariance statistics generated from the National Meteorological Center (NMC) method and Ensemble method, quality control in radial winds, and with/without Digital Filter Initialization (DFI) schemes for DWR data assimilation. Results suggest that with the assimilation of DWR observations, the WRF model is able to predict selected rainfall events with less temporal, spatial and intensity error. Moreover, synoptic conditions are more favourable after DWR assimilation. Due to lack of precise initial conditions, control experiments are not able to capture this extreme weather activity. Results suggest that better skill is seen when the DFI method is used in combination with ensemble background error covariance as compared to other experiments. The maximum rainfall prediction skill is enhanced with DWR data assimilation experiment with DFI method and ensemble background error covariance statistics.