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Related Articles from SNS
A mathematical framework for dynamic emergent constraints in climate science
Announce Type: new Abstract: Emergent constraints in climate science are empirical relations that link the response to a forcing of a physical observable to the properties of other observables, with the aim of reducing climate change projection uncertainties. Here we use recent results in linear response theory to develop a mathematical framework for dynamic emergent constraints, a class of emergent constraints linking the response of different observables to the same forcing. We show how...
ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science Analysis
arXiv:2604.16922v3 Announce Type: replace Abstract: Climate research is pivotal for mitigating global environmental crises, yet the accelerating volume of multi-scale datasets and the complexity of analytical tools have created significant bottlenecks, constraining scientific discovery to fragmented and labor-intensive workflows. While the emergence Large Language Models (LLMs) offers a transformative paradigm to scale scientific expertise, existing explorations remain largely confined to...
The weather and climate science AI revolution isn’t revolutionary
It feels like there's no escaping AI right now, whether you’re trying to type a sentence without being interrupted by a digital “assistant” or struggling to find a new refrigerator that doesn’t require a Wi-Fi connection for some reason. You’d be forgiven for wondering if we’re in the midst of a quantum leap in tech or whether people are just hyping up a heap of slop. So what should we make of the growing use of AI in weather and climate modeling?
The weather and climate science AI revolution isn’t revolutionary
It feels like there's no escaping AI right now, whether you’re trying to type a sentence without being interrupted by a digital “assistant” or struggling to find a new refrigerator that doesn’t require a Wi-Fi connection for some reason. You’d be forgiven for wondering if we’re in the midst of a quantum leap in tech or whether people are just hyping up a heap of slop. So what should we make of the growing use of AI in weather and climate modeling?
Science news this week: Laotian 'death jar,' climate change threatens rice crops, and an asthma drug treats tough cancer
Death jar mystery revealed, rice reaching its "thermal limit," prehistoric art controversy, and the asthma drug that could help fight cancer.
Climate scientists say heatwave misinformation is fuelling online harassment
Misleading claims about Europe's record heatwave in May have followed familiar climate-change denial narratives, as scientists say that misinformation can help fuel online hostility. A May heatwave across Europe has shattered temperature records and sparked a wave of familiar claims online that attempt to throw climate science into disrepute. One post on X, viewed thousands of times, claims that historic heatwaves, such as those in London in the summer of 1976 and in 1921, prove that the...
Aerosols may warm or cool the climate depending on timing, new study finds
Aerosols may warm or cool the climate depending on timing, new study finds Gaby Clark Scientific Editor Andrew Zinin Lead Editor A new study from the Hebrew University of Jerusalem challenges a long-held assumption in climate science by showing that aerosols—tiny particles suspended in the atmosphere—can either warm or cool the climate, depending on the time scale considered. Led by Prof. Guy Dagan of the Fredy and Nadine Herrmann Institute of Earth Sciences, the research reveals that...
Samudra 2: Scaling Ocean Emulators across Resolutions
arXiv:2606.02610v1 Announce Type: cross Abstract: Ocean general circulation models (OGCMs) are essential to climate science but computationally expensive, limiting ensemble size and forcing scenarios. Neural emulators promise orders-of-magnitude speedups, yet existing ocean emulators have not combined fine spatial resolution with multi-year autoregressive rollouts. Samudra, the first autoregressive neural ocean emulator to produce multi-decade global rollouts, is limited to $1^\circ$...
Samudra 2: Scaling Ocean Emulators across Resolutions
arXiv:2606.02610v1 Announce Type: new Abstract: Ocean general circulation models (OGCMs) are essential to climate science but computationally expensive, limiting ensemble size and forcing scenarios. Neural emulators promise orders-of-magnitude speedups, yet existing ocean emulators have not combined fine spatial resolution with multi-year autoregressive rollouts. Samudra, the first autoregressive neural ocean emulator to produce multi-decade global rollouts, is limited to $1^\circ$...