814329 Meteorological data analysis and visualization (in Eng.)
- Type
- Lecture and exercise
- Semester hours
- 2
- Lecturer (assistant)
- Organisation
- Offered in
- Wintersemester 2022/23
- Languages of instruction
- Englisch
- Content
-
Over the last decades the global network of ground-based meteorological stations has significantly expanded. At the same time tremendous progress has been made in observations from remote-sensing platforms and the skill and resolution of global and regional weather-forecast and climate models has steadily increased. Observational and model output exists in a variety of data formats and analysis frequently requires experience with numerical programming environments. In this class an overview is given about selected data sets available from in-situ or remote-sensing platforms as well as model archives. Different methodological frameworks and numerical recipes for the analysis of meteorological and climatological data are presented. Theoretical content is supplemented with hands-on experience, with special emphasis on the application of toolboxes available within open-source software. Besides numerical analysis emphasis is given on the effective visualization of meteorological and climatological data to ease interpretation.
- Previous knowledge expected
-
none
- Objective (expected results of study and acquired competences)
-
After participation students will have gained experience in the analysis and visualization of meteorological and climatological data. Students will be able to read and process data of different formats with open-source software (R, Python). Students will have experience in the analysis of station data as well as gridded data sets from climate-models, remote-sensing platforms and reanalyses. Students will be able to apply methods from time series analysis, hypothesis testing and extreme value analysis. Students will be able to produce illustrative 2D and 3D visualizations of meteorological and climate data.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.