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280352 VU Climate Data Analysis (2025S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 03.02.2025 08:00 bis Mo 24.02.2025 23:59
- Abmeldung bis Mo 31.03.2025 23:59
Details
max. 20 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
UZA II: 2G542
- N Donnerstag 06.03. 13:15 - 15:15 Ort in u:find Details
- Donnerstag 06.03. 15:30 - 16:30 Ort in u:find Details
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- Donnerstag 20.03. 13:15 - 15:15 Ort in u:find Details
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- Donnerstag 27.03. 13:15 - 15:15 Ort in u:find Details
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- Donnerstag 03.04. 13:15 - 15:15 Ort in u:find Details
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- Donnerstag 10.04. 13:15 - 15:15 Ort in u:find Details
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- Donnerstag 08.05. 13:15 - 15:15 Ort in u:find Details
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- Donnerstag 22.05. 13:15 - 15:15 Ort in u:find Details
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- Donnerstag 05.06. 13:15 - 15:15 Ort in u:find Details
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- Donnerstag 12.06. 13:15 - 15:15 Ort in u:find Details
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- Donnerstag 26.06. 13:15 - 15:15 Ort in u:find Details
- Donnerstag 26.06. 15:30 - 16:30 Ort in u:find Details
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Ipython exercise sheets will be distributed. Students must return 80% of problems. They must explain their solutions before their colleagues for at least 2 problems.
Grading: 30% written solutions, 25% explanation, 45% oral exam at the end of semester
Grading: 30% written solutions, 25% explanation, 45% oral exam at the end of semester
Mindestanforderungen und Beurteilungsmaßstab
Overall they must 50% of the maximum achievable points, summed over all three grading criteria
Prüfungsstoff
For the oral exam, the content of the distributed slides should be known by the students.
During the exam, they will also solve a simple problem with climate data in an ipython notebook to demonstrate their proficiency in data analysis.
A submitted solution of a problem in the exercises will be counted if at least one subproblem has been successfully solved.
In the oral presentation in the exercises they must demonstrate that they really have understood the solution and should be able to answer questions regarding the solution.
During the exam, they will also solve a simple problem with climate data in an ipython notebook to demonstrate their proficiency in data analysis.
A submitted solution of a problem in the exercises will be counted if at least one subproblem has been successfully solved.
In the oral presentation in the exercises they must demonstrate that they really have understood the solution and should be able to answer questions regarding the solution.
Literatur
Mudelsee: Climate Data Analysis
Storch+Zwiers: Statistical Analysis in climate research
Storch+Zwiers: Statistical Analysis in climate research
Zuordnung im Vorlesungsverzeichnis
WM-AdvCli
Letzte Änderung: Mo 20.01.2025 09:46
They assess uncertainties of climate model ensembles and they will use advanced time series analysis methods (Singular spectrum analysis)