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20222026
most citedDifferentiable Programming for Earth System Modeling

27 citations · 45 across the 17 of their papers we have counts for

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7 papers · 1 filter

math.NA2026

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…

hep-th2026

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…

physics.ao-ph2026

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…

physics.ao-ph2026

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…

physics.geo-ph2026

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…

math.DS2026

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…

physics.geo-ph2026★ 1 cited

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…