Computational Earth System Sciences

Welcome to the Computational Earth System Sciences research group. We are dedicated to advancing the understanding of the complex dynamics shaping our planet in times of global warming. By combining computational approaches with Earth system science, we explore how critical components of the climate and biosphere may undergo abrupt, potentially irreversible changes.

Our research focuses on modelling:

  • Tipping elements in the climate system and the biosphere

  • Interactions between tipping elements and their potential to trigger cascading transitions

  • Earth system resilience

  • Social and social-ecological transformations

Our research takes an interdisciplinary perspective, combining insights from Earth system science, complex systems theory, network science, and social-ecological research. We use computational tools—from nonlinear dynamics to ensemble modeling and risk assessments—to explore the interplay between (geo-)physical, ecological, and social processes relevant for the stability of our planet.

We actively collaborate across disciplines and welcome students, PhD candidates, and PostDoctoral researchers who are passionate about advancing computational approaches to global sustainability challenges. Join us in exploring the tipping points of the Earth system—and the pathways to Earth resilience. Explore our research, publications and the team below. For current thesis opportunities and teaching activities, please contact Prof. Dr. Nico Wunderling.

Team
  • Jonathan Kroenke (PhD Researcher, Stability of the Amazon rainforest)
  • Niklas Lohmann (Master Student, Causal detection of tipping element interactions)
  • Luan Holte (Master Student, Tipping risks under global warming)
  • Ulrike Mühlhaus (Master Student, Effect of climate sensitivity on tipping risks)
  • Felix de Cecco (Master Student, Socio-climate transformations)
Publications

See publication list here.

Teaching

WS 2025/2026: Course "Computational Earth System Sciences - From Tipping Points to Earth Resilience"

  • Study programs: M.Sc. Physics and M.Sc. Atmospheric & Climate Sciences
  • Room: N160-107, Riedberg Campus - Chemisches Institut
  • Time: Tuesday 14:15-15:45 (Lecture) and 16:00-17:30 (Problem Class); First lecture: 14. October 2025
  • Teaching language: English
  • Link: Lecture Schedule (Vorlesungsverzeichnis): TBA

 

PhD and PostDoc opportunities

Join Our Team

We are always interested in working with motivated and highly qualified PhD candidates and Postdoctoral researchers who are passionate about our research topics.

  • Open Positions:
    New opportunities at PhD and PostDoc level will be available shortly within our group. If you are interested in joining us, please reach out with your CV and a brief statement of your research interests related to our work.
  • Scholarship Options:
    For many (PhD-)scholarship programs, it is possible to combine funding with a part-time position—we actively support this whenever we can.

Feel free to contact us regarding these or other opportunities. We look forward to hearing from you and potentially working together.

Projects for Students

Motivated students from different disciplines are invited to work in the Computational Earth System Sciences group on the topics listed below (or related topics) as part of a Bachelor’s/Master’s thesis or during a longer-term internship. Our group is happy to discuss further ideas and project options. Please contact us.

Worth noting: Our research is computational by nature. While students from all relevant academic fields are welcome, a background in mathematical modeling, quantitative analysis, or computational methods is important for successfully engaging with our topics.

Topics include:

  • Tipping elements in the climate system and the biosphere
  • Interactions between tipping elements
  • Stability of tropical ecosystems (e.g. Amazon rainforest)
  • Earth system resilience
  • Complex social-ecological systems dynamics

Methods include:

  • Earth System Modelling
  • Nonlinear dynamical systems
  • Complex systems and Network theory
  • Computational and Statistical Physics
  • Climate Physics
  • Causal Detection and Machine learning
  • High Performance Computing (e.g. for large scale Monte Carlo sampling or Earth System Modelling efforts)