Computational tools in meteorology

Enrolment in the programme. Completed course Introduction to physics of the atmosphere.

Basics of using the Linux and Latex operating systems. File and data compression. Use and conversion of typical formats of vector and raster images, animations and video files. Creating animations and video files from a sequence of images. Using Gimp, Inkscape, Imagemagick and ffmpeg. Use of relational databases and SQL language. Use of text, binary and netCDF files in meteorology. Basics of using ncdump, ncview and NCL programming language for reading text and netcdf files and visualizing meteorological data. Basics of using the Python programming language: examples of using SQL databases and reading and writing text and netcdf files with meteorological data, visualization of time series and multidimensional fields, and examples of meteorological data analysis. Basics of using the R programming language: examples of using SQL databases and reading and writing text and netcdf files with meteorological data, visualization of time series and multidimensional fields, and examples of meteorological data analysis.

1. Unix Power Tools. Jerry Peek, Shelley Powers, Tim O'Reilly, Mike Loukides, O'Reilly Media.
2. Ne najkrajši uvod v Latex. Tobias Oetiker Hubert Partl, Irene Hyna in Elisabeth Schlegl (prevod Bor Plestenjak). http://www-lp.fmf.uni-lj.si/plestenjak/vaje/latex/lshort.pdf
3. The LaTeX Companion. Frank Mittelbach , Michel Goossens , Johannes Braams , David Carlisle , Chris Rowley , Addison-Wesley Professional.
4. Getting Started with MATLAB: A Quick Introduction for Scientists and Engineers Paperback. Rudra Pratap. Oxford University Press.
5. Sams Teach Yourself C in 21 Days. Bradley L. Jones , Peter Aitken. Sams Publishing.
6. Fortran 90/95 Explained. Michael Metcalf , John K. Reid. Oxford University Press, USA.

Ability to read, write, analyse and visualize meteorological data and model output fields using standard software tools.

Knowledge and understanding: Use of computer with analysis of meteorological datasets.

Application:

The acquired knowledge serves allows meteorologists to perform analysis of datasets using the standard software tools.

Reflection:

Use of different software tools for analysis for meteorological datasets.

Transferable skills:

Presentation and analysis of time series of meteorological data and model output.

tutorials, work at home

completed exercises, properly prepared written reports
grades: passed/failed (in agreement with the Statutes of the University of Ljubljana)

1. SKOK, Gregor, BACMEISTER, Julio T., TRIBBIA, Joe. Analysis of tropical cyclone precipitation using an object-based algorithm. Journal of climate, ISSN 0894-8755, 2013, vol. 26, iss. 8, str. 2563-2579.
2. ŽAGAR, Nedjeljka, HONZAK, Luka, ŽABKAR, Rahela, SKOK, Gregor, RAKOVEC, Jože, CEGLAR, Andrej. Uncertainties in a regional climate model in the midlatitudes due to the nesting technique and the domain size. Journal of geophysical research, Atmospheres, ISSN 21698996, 2013, vol. 118, iss. 12, str. 6189-6199
3. SKOK, Gregor, TRIBBIA, Joe, RAKOVEC, Jože. Object-based analysis and verification of WRF model precipitation in the low- and Midlatitude Pacific Ocean. Monthly weather review, ISSN 0027-0644, 2010, vol. 138, no. 12, str. 4561-4575
4. SKOK, Gregor, VRHOVEC, Tomaž. Considerations for interpolating rain gauge precipitation onto a regular grid. Meteorologische Zeitschrift, ISSN 0941-2948, 2006, 15, str. 545-557.
5. VRHOVEC, Tomaž, RAKOVEC, Jože, GABERŠEK, Saša, SKOK, Gregor, ŽABKAR, Rahela, GREGORIC, Gregor. Relief shapes and percipitation on the south side of the Alps, Part 2. Heavy-rain cases during MAP and sensitivity to topography modifications. Meteorologische Zeitschrift, ISSN 0941-2948, 2004, 13, str. 201-208.