SubjectsSubjects(version: 867)
Course, academic year 2019/2020
Meteorological data analysis and interpretation - NAFY046
Title: Analýza a interpretace meteorologických dat
Guaranteed by: Department of Condensed Matter Physics (32-KFKL)
Faculty: Faculty of Mathematics and Physics
Actual: from 2016 to 2019
Semester: summer
E-Credits: 6
Hours per week, examination: summer s.:2/2 C+Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Note: enabled for web enrollment
Guarantor: Mgr. Michal Žák, Ph.D.
Annotation -
Last update: T_KMOP (18.05.2011)
: Students will gain knowledge about principles of meteorological data analysis and about possibilities of their interpretation that are used in weather services.
Course completion requirements - Czech
Last update: Mgr. Michal Žák, Ph.D. (14.02.2019)

Klasifikovaný zápočet je získán za účast (alespoň 60 %). Vzhledem k podmínce účasti se zápočet opakovat nedá.

Literature -
Last update: Mgr. Michal Žák, Ph.D. (01.09.2011)

Daley R.: Atmospheric data analysis. Cambridge University Press, 1993

Kalnay E.: Atmospheric modeling, data assimilation and predictability. Cambridge University Press, 2002

Lorenc A.: Analysis methods for numerical weather prediction. Quart. J. Roy. Meteor. Soc. 112, 1177-1194, 1988

Sancier, W.: Principles of Meteorological Analysis, Univ. Press, Chicago, 1955

Wickham, P.G.: The Practice of Weather forecasting, London 1970

Requirements to the exam - Czech
Last update: Mgr. Michal Žák, Ph.D. (14.02.2019)

Hodnocena je znalost schopnosti analýzy povětrnostní mapy při finální prezentaci na jedné ze závěrečných hodin.

Syllabus -
Last update: T_KMOP (18.05.2011)

Practical lessons will focus on basic principles of analysis of meteorological fields, analysis of atmospheric fronts and other special atmospheric features based on modern conceptual models and aeorological diagrams and vertical cross-sections of atmosphere. Using of satellite data in meteorology and climatology and of different data sources and data quality.

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