13 papers
Flexible generation of daily Earth system model projections across radiative forcing scenarios
Yu Huang, Sebastian Bathiany, Shangshang Yang +3
Earth system model (ESM) projections of the climate system's response to anthropogenic forcing are central to assess the impacts of climate change and inform adaptation and mitigat…
Generating realistic global precipitation fields from modelled atmospheric circulation
Michael Aich, Sebastian Bathiany, Philipp Hess +2
Improving the representation of precipitation in Earth system models (ESMs) is critical for assessing the impacts of climate change and especially of extreme events like floods and…
Generative deep learning improves reconstruction of global historical climate records
Zhen Qian, Teng Liu, Sebastian Bathiany +7
Accurate assessment of anthropogenic climate change relies on historical instrumental data, yet observations from the early 20th century are sparse, fragmented, and uncertain. Conv…
Extrapolation from historical data cannot reliably predict the time of a potential AMOC collapse
Andreas Morr, Maya Ben-Yami, Brian Groenke +6
Ditlevsen and Ditlevsen [Nature Communications, 2023] (DD23 hereafter) propose a statistical framework to estimate the timing of a potential collapse of the Atlantic Meridional Ove…
NeuralCrop: Combining physics and machine learning for improved crop yield projections
Yunan Lin, Sebastian Bathiany, Maha Badri +6
Global gridded crop models (GGCMs) are crucial to project the impacts of climate change on agricultural productivity and assess associated risks for food security. Despite decades…
Statistical warning indicators for abrupt transitions in dynamical systems with slow periodic forcing
Florian Suerhoff, Andreas Morr, Sebastian Bathiany +2
There is growing interest in anticipating critical transitions in natural systems, often pursued through statistical detection of early warning signals associated with dynamical bi…