Infopaket

Numerical Methods of Weather Forecast

ОК 3.

Обов’язкова дисципліна для ОП

Second

2023/2024

1 Semester

4

PLO 01.Analyze patterns of of occurrence and development of processes and phenomena in the atmosphere in their interaction with other geospheres. PLO02. Apply their knowledge to identify and solve problematic issues and make informed decisions in meteorology. PLO07. To know modern methods of of meteorological research and be able to to apply them in production and scientific research activities. PLO 12. Model atmospheric processes and phenomena, applying cartographic and mathematical methods and geoinformation technologies. PLO13. Identify and classify known and and record new phenomena and processes in the atmosphere, their properties and their inherent features.

Full-time form

1. Successful mastering of compulsory basic disciplines studied at the department of meteorology and climatology - Mathematics, physics, information technology, physics of the atmosphere. 2. Knowledge of theoretical foundations of physics, mathematics, methods of analysis of meteorological processes and fields, ability to establish causal relationships between phenomena and processes occurring in the atmosphere, information about which comes from different sources. 3. Possession of methods of synthesis and analysis of information.

The main issues are presented that concerning hydrodynamic modeling of atmospheric processes of different scales and weather forecasting. The course consists of two content modules. The first is devoted to methods of processing of meteorological information for numerical models, an overview of the basic equations of hydrothermodynamics in different coordinate systems, and the formulation of the general problem of the forecast, the second presents methods for solving weather equations, in particular the basics of the finite difference method for solving weather equations, the solution of finite difference equations by the method of time steps, etc. Information on spectral models and the basics of long-term hydrodynamic and statistical forecast with a month-season lead time.

1. Прусов В.А., Сніжко С.І. Математичне моделювання атмосферних процесів. – Київ.: Ніка-Центр, 2005.– 496 с. 2. Прусов В.А., Сніжко С.І. Динамічна метеорологія. – Київ.: ВПЦ «Київський університет», 2009.– 383 с. 3. Хоменко Г.В., Хохлов В.М. Гідродинамічні методи прогнозу погоди: Підручник. – Одеса: Екологія, 2008. – 340 с. 4. Ківганов А.Ф. Хвильові процеси в атмосфері. – Одеса: АО БАХВА, 2001. – 180 с. 7. Ківганов А.Ф., Хоменко Г.В., Хохлов В.М. Бонадренко В.М. Гідродинамічні моделі прогнозу погоди і сіткові методи їх реалізації. – Одеса: ТЭС, 2002. – 179 с. 8. Neural Network Load Forecasting with Weather Ensemble Predictions. James W. Taylor and Roberto Buizza IEEE Trans. on Power Systems, 2002, Vol. 17, P. 626- 632.

Lectures, practical

The final assessment in the form of a test: the maximum number of points on the test is 40 points, the minimum number of points that are added to the semester - 24 points (60% of the maximum number of points allocated for the test). Students who have scored at least 36 points during the semester (60% of the maximum number of points allocated for semester control) are allowed to take the test in the discipline. For students who have scored during the semester a total of less points than the critical-calculated minimum - 36 points to pass the test must repeat the current control of knowledge (for example, in the form of testing) in the prescribed manner. In the case of absence of a student for valid reasons, working out and retaking of control works are carried out in accordance with the "Regulations on the procedure for assessing students' knowledge in the credit-modular system of educational process organization" of October 1, 2010.

Ukrainian