AI in 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.

News

Regierungswechsel in Brasilien: Was das für den Amazonas bedeutet

Policy Brief: Key findings and recommendations from three H2020 Projects on Tipping Points

Climate simulation more realistic with Artificial Intelligence

Seasonal prediction of Indian Summer Monsoon onset with Neural Networks

Bericht indigener Völker: Amazonas-Regenwald am Kipppunkt

PIK Press release: Amazon rainforest is losing resiliance: new evidence from satellite data analysis

Guardian Article to: Climate crisis: Amazon rainforest tipping point is looming, data shows

The Washington Post: Satellite images show the Amazon rainforest is hurtling towards a "tipping point"

Guardian article on our study suggesting that the Altantic Meridional Overturning Circulation has been losing stability