Artificial Intelligence in the Anthropocene

Future Lab on Machine Learning and data-driven methods in Climate and Earth system science

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 data-driven approaches.

Key research questions

How can techniques from Complexity Science and Machine Learning complement physical process-based approaches to

  • quantify the likelihood of abrupt transitions and extreme events in a warming Earth system?
  • improve predictions of extreme weather events on time scales of days to weeks?
  • assess the ecological impacts of a warming climate and changing extreme event characteristics?


We mainly employ methods from Complexity Science and Machine Learning such as

  • Complex Networks / Graphs for exploring dependencies in large datasets of climatic and ecosystem observables, to develop first hypotheses on underlying coupling mechanisms, and as a tool to coarse grain the data to extract the most relevant information
  • Bayesian inference for systematic calibration of physics-based low-order models that capture the key dynamics of the natural systems under study
  • Artificial Neural Networks to model (emergent) processes that are challenging to tackle with more traditional, primitive differential-equation-based approaches


We currently focus on the following areas of applications within the Earth system:

  • Abrupt climate transitions that have occurred in the Earth's long-term past, as evidenced in paleoclimate proxy records
  • Extreme events such as heat waves, droughts, and floods
  • Impacts of a warming climate and changing extreme-event characteristics on ecosystems, currently with a focus on boreal forests


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

Associated projects

  • EU Horizon 2020 project 'Tipping Points in the Earth System' (TiPES)
  • Freigeist Research group 'Predicting abrupt transitions and extremes in the Earth system' (FU Berlin, funded by the Volkswagen Foundation)
  • BMBF project ClimXtreme - Subproject B3.2: Spatial synchronization patterns of heavy precipitation events in Europe (SynXtreme)
  • EU Horizon 2020 International Training Network (ITN) 'CriticalEarth' (FU Berlin)

News & Media

Brandenburg Postdoc Award 2019

Press release on our recent paper on Amazon resilience

Press release on our recent paper on extreme rainfall teleconnections

Nature Physics highlighted our recent paper on extreme rainfall teleconnections

Radio interview on the hydrological impacts of global warming (OE1 - german)

Radio interview on consequences of the Amazon forest fires (Deutschlandfunk - german)

Radio interview on the Amazon as a tipping element (Deutschlandfunk Kultur - german)

Selected publications

  • 2020

F. Hassanibesheli, N. Boers, J. Kurths: Reconstructing Complex System Dynamics from Time Series: A Method Comparison, New Journal of Physics (2020)

C. Ciemer, L. Rehm, J. Kurths, R. V. Donner, R. Winkelmann, N. Boers: An early-warning indicator for Amazon droughts exclusively based on tropical Atlantic sea surface temperatures, Environmental Research Letters (2020)

D.-D. Rousseau, P. Antoine, N. Boers, F. Lagroix, M. Ghil, J. Lomax, M. Fuchs, M. Debret, C. Hatté, O. Moine, C. Gauthier, D. Jordanova, N. Jordanova: Dansgaard–Oeschger-like events of the penultimate climate cycle: the loess point of view, Climate of the Past (2020)

F. Wolf, J. Bauer, N. Boers, R.V. Donner: Event synchrony measures for functional climate network analysis: A case study on South American rainfall dynamics, Chaos (2020)

  • 2019

C. Ciemer, N. Boers, M. Hirota, J. Kurths, F. Mueller-Hansen, R. Oliveira, R. Winkelmann: Tropical vegetation in regions with higher rainfall variability is more resilient to climate change, Nature Geoscience (2019)

N. Boers, B. Goswami*, A. Rheinwalt*, B. Bookhagen, B. Hoskins, J. Kurths: The global pattern of extreme rainfall teleconnections revealed by complex networks, Nature (2019)

  • 2018

M. Gelbrecht, N. Boers, J. Kurths: Phase Coherence between Precipitation in South America and Rossby Waves, Science Advances (2018)

N. Boers, M. Ghil, D. Rousseau: Interactions between ocean circulation and sea ice explain Dansgaard-Oeschger events, Proceedings of the National Academy of Sciences (2018)

N. Boers: Early-warning signals for Dansgaard-Oeschger events in a high-resolution ice core record, Nature Communications (2018)

B. Goswami, N. Boers*, A. Rheinwalt*, N. Marwan, J. Heitzig, S.F.M. Breitenbach, J. Kurths: Abrupt transitions in time series with uncertainties, Nature Communications (2018)

C. Ciemer, N. Boers, H.M.J. Barbosa, J. Kurths, A. Rammig: Temporal Evolution of the spatial covariability of rainfall in South America, Climate Dynamics (2018)

  • 2017

N. Boers, M. Chekroun, H. Liu, D. Kondrashov, D.-D. Rousseau, A. Svensson, M. Bigler, M. Ghil: Inverse stochastic-dynamic models for high-resolution Greenland ice-core records, Earth System Dynamics (2017)

N. Boers, B. Goswami, M. Ghil: A complete representation of uncertainties in layer-counted paleoclimatic archives, Climate of the Past 13, 1169–1180 (2017)

D.-D. Rousseau, A. Svensson, M. Bigler, A. Sima, J.P. Steffensen, N. Boers: Eurasian contribution to the last glacial dust cycle: how are loess sequences built?, Climate of the Past (2017)

D.-D. Rousseau, N. Boers, A. Sima, A. Svensson, M. Bigler, F. Lagroix, S. Taylor, S. Antoine: (MIS3 & 2) millennial oscillations in Greenland dust and Eurasian aeolian records–A paleosol perspective, Quaternary Science Reviews (2017)

M. Gelbrecht, N. Boers, J. Kurths: A complex network representation of wind flows, Chaos (2017)

N. Boers, N. Marwan, H.M.J. Barbosa, J. Kurths: A deforestation-induced tipping point for the South American monsoon system, Scientific Reports (2017)

  • 2016

D.Traxl*, N. Boers*, A. Rheinwalt, B. Goswami, J. Kurths: The size distribution of spatiotemporal extreme rainfall clusters around the globe, Geophysical Research Letters (2016)

D.Traxl, N. Boers, J. Kurths: Deep Graphs - a general framework to represent and analyze heterogeneous complex systems across scales, Chaos 26, 06530 (2016)

N. Boers, B. Bookhagen, N. Marwan, J. Kurths: Spatiotemporal Characteristics and Synchronization of Extreme Rainfall in South America with Focus on the Andes Mountain Range, Climate Dynamics (2016)

A. Rheinwalt, N. Boers, N. Marwan, J. Kurths, P. Hoffmann, F. Gerstengarbe, P. Werner: Non-Linear Time Series Analysis of Precipitation Events Using Regional Climate Networks for the Region of Germany, Climate Dynamics 46, 1065–1074 (2016)

N. Boers, P. Pickl: On Mean Field Limits for Dynamical Systems, Journal of Statistical Physics (2016)

  • 2015

N. Boers, H. Barbosa, B. Bookhagen, J. Marengo, N. Marwan, and J. Kurths: Propagation of Strong Rainfall Events from Southeastern South America to the Central Andes, Journal of Climate (2015)

N. Boers, B. Bookhagen, J. Marengo, N. Marwan, J. v. Storch, J. Kurths: Extreme rainfall of the South American monsoon system: A dataset comparison using complex networks, Journal of Climate (2015)

N. Boers, R. Donner, B. Bookhagen, J. Kurths: Complex network analysis helps to identify impacts of the El Niño Southern Oscillation on moisture divergence in South America, Climate Dynamics (2015)

N. Boers, A. Rheinwalt, B. Bookhagen, N. Marwan, J. Kurths: A complex network approach to investigate the spatiotemporal co-variability of extreme rainfall, in: Machine Learning and Data Mining Approaches to Climate Science: Proceedings of the Fourth International Workshop on Climate Informatics, Springer (2015)

A. Rheinwalt, N. Boers, B. Goswami, J. Heitzig, N. Marwan, R. Krishnan, J. Kurths: Teleconnections in Climate Networks: A Network-of-Networks Approach to Investigate the Influence of Sea Surface Temperature Variability on Monsoon Systems, in: Machine Learning and Data Mining Approaches to Climate Science: Proceedings of the Fourth International Workshop on Climate Informatics, Springer (2015)

  • 2014

N. Boers, B. Bookhagen, H.M.J. Barbosa, N. Marwan, J. Kurths, J. Marengo: Prediction of Extreme Floods in the Eastern Central Andes based on a Complex Networks Approach, Nature Communications (2014)

D. Traxl, N. Boers, J. Kurths: General scaling of maximum degree of synchronization in noisy complex networks, New Journal of Physics (2014)

N. Boers, A. Rheinwalt, B. Bookhagen, H.M.J. Barbosa, N. Marwan, J. Marengo, J. Kurths: The South American Rainfall Dipole: A Complex Network Analysis of Extreme Events, Geophysical Research Letters (2014)

  • 2013

N. Boers, B. Bookhagen, N. Marwan, J. Kurths, J. Marengo: Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System, Geophysical Research Letters (2013)

*Equal author contribution.