1. komponenta

Lecture type	Total
Lectures	30
Exercises	15

* Load is given in academic hour (1 academic hour = 45 minutes)

Subjective way of weather forecasting. Objective methods of weather forecasting: deterministic, stochastic and deterministic-stochastic approach. The governing equations of the atmosphere in different co-ordinate systems (generalised, spherical, tangential and map projections). Review of numerical methods for solving the governing equations: method of final differences and function expansion into series (spectral and final elements). Non-linear numerical nonstability and filtering (low-pass and bandpass filters). Initialisation of numerical models: equilibrium equations, normal modes, 4-dimensional variational analysis. Boundary conditions. Barotropic limited area model in conic map projection. Six-layer hemispheric forecasting model with primitive equations. Global spectral model of the European Centre for Medium Range Weather Forecasts (ECMWF). Introducing with the regional models ALADIN (Aire Limitee Adaptation et Development International) and HIRLAM (High Resolution Limited Area Modelling). Stochastic (regression) approach to the weather forecasting. Analogy method. Deterministic-stochastic approach: atmospheric predictability, ensemble forecasts. Subjective interpretation of the prognostic model outputs. Regression way of interpretation (Method output Statistic, perfect Prognosis). Adaptive deterministic models (e.g. adaptation of air flow to the orography). Forecasts for special applications. Verification of the forecasts.

LEARNING OUTCOMES:
It is expected that after completion of this course, the students should know how to:
Explain the meaning of individual terms in hydrodynamic equations with respect to coordinate systems,
Numerically solve the system of differential equations,
Compare and contrast the meaning of the output of numerical models and the meaning of the analytical material,
Make the subjective and the objective weather forecast,
Distinguish between special and standard weather forecasts.

1. Haltiner, G.J. and R.T. Williams, 1980: Numerical weather prediction. John Wiley & Sons, New York. 477 pp.
2. Kalney, E., 2003: Atmospheric modeling, data assimilation and predictability. Cambridge University Press, Cambridge. 341 pp.
3. Mesinger, F. and A. Arakawa, 1976: Numerical models in atmospheric models. Volume I. GARP Publication Series No. 17, WMO, Geneve. 135 pp.
4. Pielke R.A. and R.P. Pearce, 1994: Mesoscale modeling of the atmosphere. American Meteorological Society, Boston. 167 pp.
5. Radinović, Đ., 1979: Prognoza vremena. Univerzitet u Beogradu. Beograd. 266 str.
6. Zdunkowski, W. and A. Bott, 2003: Dynamics of the atmosphere - A course in theoretical meteorology. Cambridge University Press, Cambridge, 719 pp.
7. Haltiner, G.J., 1971: Numerical weather prediction. John Wiley & Sons, New York,
   317 pp.
8. Houghton, D.D, 1985: Handbook of applied meteorology. John Wiley & Sons, New York, 1461 pp.
9. Petterssen, S., 1956: Weather analysis and forecasting (Vol. I and II). McGraw- Hill, New York, 428 (266) pp.
10. Richardson, L.F., 1922: Weather prediction by numerical process. Cambridge University Press, London, 236 pp.
11. Riley, M.P., Hobson, M.P. and S.J. Bence, 1998: Mathematical methods for physics and enginering. Cambridge University Press, Cambridge, 1008 pp.
12. Zverev, A.S., 1977: Sinoptičeskaja meteorologia. Gidrometeoizdat, Leningrad, 710 pp.

Mandatory course - Regular study - Meteorology and Physical Oceanography