Tobias Braun has been working as a doctoral researcher at Potsdam Institute for Climate Impact Research between 2019-2022. Under the purview of the DFG-funded project NEMACS (Nonlinear Empirical Mode Analysis of Complex Systems), he further developed nonlinear time series analysis methods based on recurrence plots and identified significant transitions in palaeoclimate proxy records along with their societal repercussions. He is now affiliated with the Potsdam Institute for Climate Impact Research as a guest researcher.
After finishing his PhD, he pursued a short postdoctoral placement in the ClimXtreme project where he investigated the spatiotemporal characteristics of global atmospheric rivers and their role in triggering heavy precipitation events. He is currently visiting the GFZ-Potsdam under the Helmholtz Visiting Researcher Fellowship (HIDA). Here, he applies his knowledge on recurrence analysis to reveal precursors of debris flow. His current broad and interdisciplinary research interests include complex networks, natural hazards, recurrence analysis and palaeoseasonality. Tobias holds a Master's degree in Physics from the University of Duisburg-Essen.
Contact
14412 Potsdam
ORCID
GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
- 2012-2017: B. Sc. / M. Sc. Physics (University Duisburg-Essen)
- 2019-2022: PhD (University Potsdam)
Research Highlights
- Transfer of muli-scale/self-similarity concepts to recurrence analysis
- Treatment techniques for irregular sampling & dating uncertainties in palaeoclimate proxy records
- Detection of a decline in seasonal predictability that might have contributed to disintegration of Classic Maya societies
- Development of a power spectral estimate for discrete/event-like data
(selected publications, full list on Google Scholar)
- Braun, T. (2023). "Recurrences in past climates: novel concepts & tools for the study of Palaeoseasonality and beyond." Diss. Universität Potsdam, https://doi.org/10.25932/publishup-58690
- Marwan. N. and Braun, T. (2023). "Power spectral estimate for discrete data." Chaos: An Interdisciplinary Journal of Nonlinear Science 33.5.
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Braun, T., et al (2023). "Decline in seasonal predictability potentially destabilized Classic Maya societies." Communications Earth & Environment 4.1: 82.
- Braun, T., Unni, V. R., Sujith, R. I., Kurths, J., & Marwan, N. (2021). "Detection of Dynamical Regime Transitions with Lacunarity as a Multiscale Recurrence Quantification Measure." Nonlinear Dynamics 104.4: 3955-3973.
- DFG: Nonlinear Empirical Mode Analysis of Complex Systems: Development of General Approach and Applications in Climate
- BMBF: Klimawandel und Extremereignisse (climXtreme)
- Nonlinear Data Analysis Concepts (University of Potsdam, Institute of Geoscience, GEW-DAP02, 2020-2022)
- Econophysics (University Duisburg-Essen, Faculty of Physics, 2015-2017)
- 2021-2022: Review Editor in Dynamical Systems: Frontiers in Applied Mathematics and Statistics
