7 papers
Red noise in continuous-time stochastic modelling
Andreas Morr, Dörte Kreher, Niklas Boers
The concept of time-correlated noise is important to applied stochastic modelling. Nevertheless, there is no generally agreed-upon definition of the term red noise in continuous-ti…
Predicting Instabilities in Transient Landforms and Interconnected Ecosystems
Taylor Smith, Andreas Morr, Bodo Bookhagen +1
Many parts of the Earth system are thought to have multiple stable equilibrium states, with the potential for rapid and sometimes catastrophic shifts between them. The most common…
Fast, Scale-Adaptive, and Uncertainty-Aware Downscaling of Earth System Model Fields with Generative Machine Learning
Philipp Hess, Michael Aich, Baoxiang Pan +1
Accurate and high-resolution Earth system model (ESM) simulations are essential to assess the ecological and socio-economic impacts of anthropogenic climate change, but are computa…
Discontinuous stochastic forcing in Greenland ice core data
Keno Riechers, Andreas Morr, Klaus Lehnertz +4
Paleoclimate proxy records from Greenland ice cores, archiving e.g. O as a proxy for surface temperature, show that sudden climatic shifts called Dansgaard-Oeschger events…
When Geoscience Meets Foundation Models: Towards General Geoscience Artificial Intelligence System
Hao Zhang, Jin-Jian Xu, Hong-Wei Cui +4
Artificial intelligence (AI) has significantly advanced Earth sciences, yet its full potential in to comprehensively modeling Earth's complex dynamics remains unrealized. Geoscienc…
Data-driven Global Ocean Modeling for Seasonal to Decadal Prediction
Zijie Guo, Pumeng Lyu, Fenghua Ling +8
Accurate ocean dynamics modeling is crucial for enhancing understanding of ocean circulation, predicting climate variability, and tackling challenges posed by climate change. Despi…