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Nikolina Ban: Katalogdaten im Frühjahrssemester 2019

NameFrau Dr. Nikolina Ban
Adresse
Professur f. Hydrologie&Klimat.
ETH Zürich, CHN L 18
Universitätstrasse 16
8092 Zürich
SWITZERLAND
E-Mailnikolina.ban@env.ethz.ch
DepartementUmweltsystemwissenschaften
BeziehungDozentin

NummerTitelECTSUmfangDozierende
701-1216-00LNumerical Modelling of Weather and Climate Information 4 KP3GC. Schär, N. Ban
KurzbeschreibungThe course provides an introduction to weather and climate models. It discusses how these models are built addressing both the dynamical core and the physical parameterizations, and it provides an overview of how these models are used in numerical weather prediction and climate research. As a tutorial, students conduct a term project and build a simple atmospheric model using the language PYTHON.
LernzielAt the end of this course, students understand how weather and climate models are formulated from the governing physical principles, and how they are used for climate and weather prediction purposes.
InhaltThe course provides an introduction into the following themes: numerical methods (finite differences and spectral methods); adiabatic formulation of atmospheric models (vertical coordinates, hydrostatic approximation); parameterization of physical processes (e.g. clouds, convection, boundary layer, radiation); atmospheric data assimilation and weather prediction; predictability (chaos-theory, ensemble methods); climate models (coupled atmospheric, oceanic and biogeochemical models); climate prediction. Hands-on experience with simple models will be acquired in the tutorials.
SkriptSlides and lecture notes will be made available at
http://www.iac.ethz.ch/edu/courses/master/modules/numerical-modelling-of-weather-and-climate.html
LiteraturList of literature will be provided.
Voraussetzungen / BesonderesPrerequisites: to follow this course, you need some basic background in atmospheric science, numerical methods (e.g., "Numerische Methoden in der Umweltphysik", 701-0461-00L) as well as experience in programming. Previous experience with PYTHON is useful but not required.