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Teaching and Degree Theses

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Master Module Interdisziplinary Natural Risk Research (Freie Universität Berlin, winter term)

Topics

What are disasters? How predictable are they? Why do we fear the wrong things? How vulnerable are societies and how can they regenerate themselves? How are decisions made under uncertainty? How can effects be modelled quantitatively? How can risks be communicated in an understandable way? What effects do technological warning systems have on the safety culture? How can warnings have a greater effect?

These are some of the questions that we want to address from the perspective of various natural, social and behavioural sciences. In order to investigate these questions, we will get to know concepts and methods and present and discuss possible answers. The exchange between the participating scientific disciplines should promote common understanding and thus strengthen interdisciplinary competence.

Target Group

The module, consisting of lecture, seminar/exercise and project work (6 LP in total) is primarily aimed at students of meteorology, geography, communication science, social and cultural anthropology, computer science and psychology. In the Master's programme Meteorology the module can be credited as a compulsory elective subject. For other courses of study, please contact the responsible examination office.

Lectures Tue 10 am -12 pm (Alter Hörsaal 041, Altbau 3) and seminar/tutorial Thu 10 am -12 pm (PC-Pool Wasserturm, 2nd Floor), Meteo-Campus Carl-Heinrich-Becher Weg 6-10, 12557 Berlin (Steglitz).

For exemplary schedules, please see the German Version of this site.

Please note the access rules https://www.fu-berlin.de/sites/coronavirus/news-start/news/2021-09-28.html . In particular you need to show proof that you have been fully vaccinated, recovered or tested.

This year's topics for project work are (probably):

  • Modelling of vegetation fires
  • Formulation of weather warnings from the perspective of the population
  • Communication of weather/weather events in media and everyday life
  • Decisions in extreme weather

A more detailed description of the individual projects will follow in the coming weeks.

Lecturers

The lecturers come from the Institute of Meteorology, the Working Group on Security Research, the Disaster Research Unit of the Freie Universität Berlin, the Max-Planck-Institute for Human Development and the German Weather Service.

Lecturer Institution
Dr. Nico Becker

Freie Universität Berlin - Institut für Meteorologie

Dr. Nadine Fleischhut

Max-Planck-Institut für Bildungsforschung

Prof. Dr. Lars Gerhold

Forschungsforum Öffentliche Sicherheit

Fachgebiet Interdisziplinäre Sicherheitsforschung

Dr. Martin Göber

Deutscher Wetterdienst/

Freie Universität Berlin - Institut für Meteorologie

Prof. Dr. Henning Rust

Freie Universität Berlin - Institut für Meteorologie

M. Sc. Jasmina Schmidt 

Forschungsforum Öffentliche Sicherheit

Fachgebiet Interdisziplinäre Sicherheitsforschung

Dr. Katja Schulze

Katastrophenforschungsstelle

Prof. Dr. Uwe Ulbrich Freie Universität Berlin - Institut für Meteorologie
Prof. Dr. Martin Voß Katastrophenforschungsstelle
This module is supported by DataCamp - DataCamp creates an intuitive learning environmit including video tutorials for R, Python and SQL. 

Creditability:

  • It is possible to attend only the lecture (= 0LP)
  • It is possible to attend lectures and exercises (= 2LP by arrangement)
  • Successful completion of the module (lecture, exercise and seminar including project work) results in = 6 LP 

and it is still possible to listen to the final presentations of the project groups.

Opportunities to participate:

  • There is a limitation of participants for the project work (15 participants)

Enrollment

If you are interested in enrolling to this module, please send your information (first and last name, course of study, university, university e-mail, matriculation number) to Kevin Cyriac Edampurath (kevin.edampurath@fu-berlin.de).

Comprehensive

    • Felgentreff, C. und Glade, T. (2008). Naturrisiken und Sozialkatastrophen. Berlin, Heidelberg: Springer. (passt jetzt nicht direkt zu qual. Methoden, ist aber generell ganz passend fürs Modul)
    • Harald Karutz, Wolfram Geier, Thomas Mitschke (Ed.), 2017: Bevölkerungsschutz (Notfallvorsorge und Krisenmanagement in Theorie und Praxis), Lehrbuch

Qualitative methods of social research

For the start

    • Bryman, A. (2012): Social research methods. Oxford Univ. Press. (Behandelt auch quantitative Methoden)
    • Flick, U. (2011): Qualitative Sozialforschung. Eine Einführung. Reinbek bei Hamburg: Rowohlt-Taschenbuch-Verlag.

For the deepening

    • Mayring, P. (2015): Qualitative Inhaltsanalyse. Grundlagen und Techniken. Weinheim: Beltz Verlag.
    • Bogner, A., Littig, B. & Menz, W. (2002). Das Experteninterview. VS Verlag für Sozialwissenschaften.
    • O'Reilly, K. (2012). Ethnographic Methods. Taylor and Francis.

Quantitative methods of social research

For the start

    • Döring, N. & Bortz, J. (2016): Forschungsmethoden und Evaluation für Human- und Sozialwissenschaftler. 5. Auflage. Heidelberg: Springer. (Behandelt auch qualitative Methoden)
    • Rasch, B.; Friese, M.; Hofmann, W.; Naumann, E. (2014):  Quantitative Methoden I. Berlin, Heidelberg: Springer-Verlag.
    • Porst, R. (2013). Fragebogen: Ein Arbeitsbuch. Springer-Verlag. 4. Auflage. 

For the deepening

    • Mummendey, H. D. & Grau, I. (2014): Die Fragebogen-Methode: Grundlagen und Anwendung in Persönlichkeits-, Einstellungs- und Selbtskonzeptforschung. 6., korrigierte Auflage. Hogrefe Verlag.
    • Huber. O. (2005): Das psychologische Experiment: Eine Einführung. 4., vollst. überarb. Auflage. Hogrefe AG.

Impact modeling

Citizen Science

Master Module Energy Meteorology (Universität zu Köln, winter term)

The module is offered virtually (digital materials and video conferencing) and can therefore be taken from any location.

Aims of the module and acquired skills

  • Understanding the meteorological requirements for a meaningful generation of electricity from wind and solar power
  • Gaining insight into the operation of an electrical grid with weather-dependent renewable energies
  • Project and seminar give the opportunity to deepen knowledge in one of the three fields “wind power”, “solar power”, or “grid operation”

Contents of the module

  • Physical basics of energy supply
  • Economic and regulatory framework in the energy system
  • On- and off-shore wind parks
  • Photovoltaic and concentrating solar thermal energy systems
  • Site auditing – including complex terrain and cloudy and aerosol-loaded locations for wind and solar technologies
  • Wind and solar forecasting – deterministic and probabilistic approaches
  • Possible impact of climate change

Related Links

Creditability:

In the Master's programme Meteorology the module can be credited as a compulsory elective subject. For other courses of study, please contact the responsible examination office.

Enrollment

Meteorology students in the Master's program outside the University of Cologne can register by mail. Please fill in your personal information under item 1, as well as date and signature under item 4 in the form (no other changes in the form) and send it to the following address:

Dagmar Janzen

Institut für Geophysik und Meteorologie

Universität zu Köln

Pohligstr. 3

50969 Köln

Downloads

The schedule for WiSe 2020/21 (in the lecture-free time) are linked down below.

Related Links

Degree Theses

You have the possibility to write your bachelor and/or master thesis within the WEXICOM project. Your topic and academic background do not have to be within a meteorological framework. We welcome students from all other departments that are interested in research on natural hazards.

A member of our team would supervise you and support you with data, methods and interpretation of your results - even if you are not a student at the Institute of Meteorology of the Freie Universität Berlin! 

Please contact a team member, if you are interested in writing your degree thesis with us.

Degree Year Title (most of them in German)
M.Sc. 2020

Weather Influence on Traffic - How Machine Learning Can Enrich Impact Research

M.Sc. 2020

Entwicklung eines Schätzverfahrens mittels Künstlicher Neuronaler Netze zur Ermittlung der Zwischenschicht zwischen Reifen und Fahrbahn

B.Sc. 2019

Windstauvorhersage für die Deutsche Bucht - Probabilistische Modellierung und Verifikation

B.Sc. 2019

How does the coarseness of a forecast influence perception?

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