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Emission of oxides of nitrogen from lightning
Brodnianska, Leontína ; Huszár, Peter (advisor) ; Žák, Michal (referee)
Title: Emission of oxides of nitrogen from lightning Author: Leontína Brodnianska Department: Department of atmospheric physics Supervisor: Doc. Mgr. Peter Huszár, Ph.D., Department of atmospheric physics Abstract: This thesis investigates lightning activity and its role in the production of nitrogen oxide (NOx) emissions using a numerical modelling approach. Lightning is a significant source of NO in the troposphere, contributing approximately 10 % to global annual NO emissions. Through a combination of observational data and model simulations, the spatial and temporal variations of convective available potential energy (CAPE), lightning density and lightning NO emissions (LNO) are investigated. The model simulations also capture the mean-vertical profile over the measured period of LNO emissions for our selected sub-regions of the whole domain, where each region has a different climate, different convective characteristic hence different distribution of emissions. Comparisons between observations and model inputs and outputs reveal different patterns in lightning density, CAPE, and NOx emissions, highlighting the importance of more accurate representation of convective dynamics in atmospheric models. The findings emphasize the need for improved lightning parameterization methods in atmospheric models....
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A Tool for Collaborative Support in Pre-Project Phase
Žák, Michal ; Rychlý, Marek (referee) ; Květoňová, Šárka (advisor)
The aim of this thesis is to design and realize an application for the management of project opportunities for the specific needs of IBM Czech Republic. The work presents the basic methods and approaches for particular time and financial planning. The application is developed in C++ using the Qt framework from Nokia. The tool uses the SQLite relational database.
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Study of relationship between temperature measurement in standard level and herb layer according to meteorological conditions
Klimeš, Vojtěch ; Žák, Michal (advisor) ; Mikšovský, Jiří (referee)
The forest microclimate is different from the conditions measured at mete- orological stations. Conditions in the herbaceous layer are influenced by both the surrounding vegetation and macroclimatic factors. In this thesis, we in- vestigate the relationship between the temperature difference at 2 m and near the ground surface in a forest and meteorological conditions. Microclimatic data are measured using temperature sensors in the national parks Šumava and Bavarian Forest. We build on studies investigating the influence of vege- tation on temperatures in forest stands to complete the picture of how forest microclimate functions. This knowledge is crucial for understanding the im- pact of climate change and for further research using advanced modelling and generalisation to other habitats. For selected meteorological conditions measured at the stations, a statistically significant relationship was found for the temperature difference, which is strongest for snow depth and weakest for precipitation.
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Validation of snow cover forecast by numerical weather prediction model ALADIN
Ševčík, Jáchym ; Žák, Michal (advisor) ; Karlický, Jan (referee)
This thesis deals with forecast of snow cover made by the numerical weather predic- tion model ALADIN and with snow cover measurements. First, it describes the model parametrization of snow-related variables. This is followed by a description of the mete- orological stations network and of the snow measurements methodology. The main focus of the thesis lies on the validation of snow depth and snow water equivalent forecasts. This is done by comparison of measurements from the winter season 2021/2022 against corresponding ALADIN forecasts with forecast ranges of 6 and 30 hours. The comparison is first made with regard to the overall tendency and the magnitude of the model error. Secondly, it deals with model frequency of snow cover misses or false alarms. Finally, the thesis touches upon the validation of snow density forecast. 1
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Climate classifications for the Czech Republic territory
Pešková, Andrea ; Žák, Michal (advisor) ; Belda, Michal (referee)
This bachelor's thesis discusses climate classification of the Czech Republic territory, providing an overview of the existing climate classifications used for the area. The concept of satellite data processing is presented, as an alternative approach to climate classification. Based on satellite data of net radiation, inco- ming solar radiation and fractional cloud cover, new climate classifications for the Czech Republic are created using a hierarchical clustering method. The results show that in all cases, the identified climate units primarily reflect the terrain and increasing continentality of climate in the southwest direction.
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Validation of the cloud and precipitation microphysics scheme in the numerical weather prediction model ALADIN
Němec, David ; Žák, Michal (advisor) ; Huszár, Peter (referee)
This thesis aims to validate the microphysics scheme in the numerical weather predic- tion model ALADIN. The first part is focused on the parameterization of hydrometeors and microphysical processes in various microphysics schemes used in current numeri- cal weather prediction models. The microphysics scheme used in ALADIN is discussed in detail, together with its parameterizations associated with the microphysics scheme. The main part of the thesis deals with an improved parameterization of graupel and improvements in the microphysical processes of all precipitating hydrometeors in the microphysics scheme in ALADIN. Alternative approaches to the parameterization of au- toconversion and evaporation are tested. Results are validated using various objective statistical methods and compared with precipitation estimates based on a combination of data from gauges and radars. 1
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Overview and using of statistical methods for short-term forecasts and nowcasting evaluation
Pitaš, Ondřej ; Žák, Michal (advisor) ; Šaur, David (referee)
Evaluating the success of the weather forecast is a fundamental factor in improving their quality. It is necessary to use statistical methods for this evaluation. However, the existence of a large number of statistical methods complicates their choice and com- paring the results of different studies. To bridge this knowledge problem, we dealt with statistical methods suitable for evaluating accuracy of short-range weather forecasts of deterministic variables. Thesis is dedicated to utilization of statistical methods for veri- fying radar echo nowcasting and for forecasts of numerical weather prediction models. In addition, it also deals with the use of statistical methods for defining loss functions and their use for learning the radar echo nowcasting model. Learned nowcasting models were verified. Numerical weather prediction models ICON and WRF were included to the work. Forecasts were verified with data from synoptic stations and ERA5 reanalysis in the do- main of the Czech Republic. The forecasts of the radar echo of the nowcasting models pySTEPS, rainymotion and MWNet v1.0 were verified with radar images in the domain of the Czech Republic. In most cases, the statistical methods agreed on the results of the evaluation of the weather forecast by the numerical weather prediction models. The differences...
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Use of lightning data for nowcasting.
Arnoštová, Michaela ; Žák, Michal (advisor) ; Bednář, Jan (referee)
Advances in lightning detection systems and convective storm analysis techniques are im- proving our understanding of their correlation. This has been the focus of many studies in re- cent decades, and it has been shown that a sudden increase in lightning, the so-called lightning jump, often precedes the occurrence of severe weather. Based on these findings, 2σ algorithm was developed to assess the occurrence of severe weather, which this thesis builds on. The aim of this thesis was first to perform data analysis of lightning data in convective storms and then, based on the obtained results and by setting an appropriate configuration, to increase not only the success rate of the 2σ algorithm, but also to design its extension part determining the specific type of severe weather that can occur in the storm. For this purpose, 72 convective storms over central Europe were studied from 4 categories - storms without severe weather, storms with hail, with severe wind or with tornadoes. Trends in the density, height and current amplitude of each type of lightning before the onset of specific severe weather were investi- gated, and it turned out that some of these parameters show different behaviour in different storm categories. Therefore, based on the data analysis of these lightning activity parameters, an...
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