AI in the Anthropocene

Artificial Intelligence in the Anthropocene - Machine Learning and data-driven Modelling in Earth System Science
AI in the Anthropocene

Many phenomena in Earth system dynamics are complex in the sense that they emerge from nonlinear interactions of large numbers of processes across wide ranges of temporal and spatial scales. Modelling such phenomena on the basis of the underlying fundamental physical laws poses serious challenges, in particular in situations of strongly nonlinear behavior that may lead to abrupt state transitions, or if one is interested in the characteristics of extreme events.

In this Future Lab, hosted by PIK’s Research Department 4, we explore mathematical techniques to investigate and model complex Earth system processes with a strong focus on combining process-based with Machine Learning approaches.

Associated Projects

ClimTip - Uncertainty-aware quantification of climate tipping potential and climatic, ecological, and socioeconomic impacts
Funded by EU, Horizon Europe
Coordinator: Niklas Boers

CriticalEarth - Multiscales and Critical Transitions in the Earth System
Funded by EU, H2020
Contact: Niklas Boers

Predicting abrupt transitions and extremes in the Earth system
Funded by Volkswagen Foundation
Contact: Niklas Boers


If you are interested in carrying out a BSc, MSc, or PhD project with us, please to discuss possible topics.