27 citations · 45 across the 17 of their papers we have counts for
21 papers
Second-Order Flows for Approaching Stationary Points via the SAV-E Approach
Haifan Chen, Wei Liu, Ziqing Xie +1
Second-order flows represent an emerging computational framework for approaching stationary points of variational energies, characterized by damped hyperbolic partial differential…
Charged Deformation of a Hairy Black Brane: Perturbative Solution and Thermodynamics
Sangheon Yun
We study electrically charged black branes in four-dimensional Einstein-Maxwell-scalar theory with Maxwell coupling , whose potential has an AdS fixed point…
ClimTip-GML: A global bias-corrected and downscaled dataset for assessing impacts of climate tipping events
Philipp Hess, Sebastian Bathiany, Lucas Ferreira Correa +3
Assessing the impacts of future climate scenarios including tipping events of major Earth system components such as the Amazon rainforest (ARF) or the Atlantic meridional overturni…
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…
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…
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…
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…
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…
Anticipating AMOC transitions via deep learning
Wenjie Zhang, Yu Huang, Sebastian Bathiany +4
Key components of the Earth system can undergo abrupt and potentially irreversible transitions when the magnitude or rate of external forcing exceeds critical thresholds. In this s…
Decadal sink-source shifts of forest aboveground carbon since 1988
Zhen Qian, Sebastian Bathiany, Teng Liu +3
Forest ecosystems are vital to the global carbon cycle, yet their long-term aboveground carbon (AGC) dynamics remain uncertain. Here, we integrate multi-source satellite observatio…
The influence of data gaps and outliers on resilience indicators
Teng Liu, Andreas Morr, Sebastian Bathiany +5
The resilience, or stability, of major Earth system components is increasingly threatened by anthropogenic pressures, demanding reliable early warning signals for abrupt and irreve…
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…
Reconciled warning signals in observations and models imply approaching AMOC tipping point
Yechul Shin, Ji-Hoon Oh, Sebastian Bathiany +8
Paleoclimate proxy records and models suggest that the Atlantic Meridional Overturning Circulation (AMOC) can transition abruptly between a strong and a weak state. Empirical warni…
Assessment of Abrupt Shifts in CMIP6 Models using Edge Detection
Sjoerd Terpstra, Swinda K. J. Falkena, Robbin Bastiaansen +3
Past research has shown that multiple climate subsystems might undergo abrupt shifts, such as the Arctic Winter sea ice or the Amazon rainforest, but there are large uncertainties…
Deep Learning for predicting rate-induced tipping
Yu Huang, Sebastian Bathiany, Peter Ashwin +1
Nonlinear dynamical systems exposed to changing forcing can exhibit catastrophic transitions between alternative and often markedly different states. The phenomenon of critical slo…
Targeted Calibration to Adjust Stability Biases in Complex Dynamical System Models
Daniel Pals, Sebastian Bathiany, Richard Wood +2
Models of complex dynamical systems like the Earth's climate often involve large numbers of uncertain parameters. Comprehensive exploration of the parameter space is typically proh…
Conditional diffusion models for downscaling and bias correction of Earth system model precipitation
Michael Aich, Philipp Hess, Baoxiang Pan +3
Climate change exacerbates extreme weather events like heavy rainfall and flooding. As these events cause severe socioeconomic damage, accurate high-resolution simulation of precip…
Spatial correlation increase in single-sensor satellite data reveals loss of Amazon rainforest resilience
Lana L. Blaschke, Da Nian, Bathiany +4
The Amazon rainforest (ARF) is threatened by deforestation and climate change, which could trigger a regime shift to a savanna-like state. Previous work suggesting declining resili…
Uncertainties too large to predict tipping times of major Earth system components from historical data
Maya Ben-Yami, Andreas Morr, Sebastian Bathiany +1
One way to warn of forthcoming critical transitions in Earth system components is using observations to detect declining system stability. It has also been suggested to extrapolate…
Uncertainties in critical slowing down indicators of observation-based fingerprints of the Atlantic Overturning Circulation
Maya Ben-Yami, Vanessa Skiba, Sebastian Bathiany +1
Observations are increasingly used to detect critical slowing down (CSD) to measure stability changes in key Earth system components. However, most datasets have non-stationary mis…
Differentiable Programming for Earth System Modeling
Maximilian Gelbrecht, Alistair White, Sebastian Bathiany +1
Earth System Models (ESMs) are the primary tools for investigating future Earth system states at time scales from decades to centuries, especially in response to anthropogenic gree…