ERA5
PulseAugur coverage of ERA5 — every cluster mentioning ERA5 across labs, papers, and developer communities, ranked by signal.
2 天有情绪数据
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New benchmark RealBench improves AI weather forecast evaluation
Researchers have introduced RealBench, a new benchmark designed to more accurately evaluate AI weather forecasting models under real-world operational conditions. Unlike previous benchmarks that relied on reanalysis dat…
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新型求解器融合人工智能与物理学实现场重建
研究人员开发了一种新颖的物理信息生成求解器，旨在从有限数据中重建复杂的物理场。该方法将数据驱动学习与基本守恒定律相结合，确保生成的态符合物理原理。该方法使用鞅正则化分数匹配进行稳定的先验学习，并使用物理信息隐式分数采样来指导生成过程，在声学和气象场重建等应用中取得了成功。
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Multi-Scale Wavelet Transformers Enhance Dynamical System Operator Learning
Researchers have developed Multi-Scale Wavelet Transformers (MSWTs) to improve the accuracy of data-driven models for dynamical systems, particularly in areas like weather forecasting. These models, known as neural oper…
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AI models learn tropical cyclone dynamics and aid weather data discovery
Researchers have developed a new 10-term cubic stochastic differential equation model to simulate tropical cyclone intensification, trained on historical intensity data and environmental features. This model successfull…
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Earth System Foundation Model integrates diverse data for climate forecasting
Researchers have developed the Earth System Foundation Model (ESFM), an open-source framework designed to integrate and forecast using diverse Earth system data. ESFM builds upon the Aurora model's architecture and inco…
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AI weather models show promise for extreme event prediction with uncertainty quantification
A new study published on arXiv investigates the effectiveness of AI-based weather models in predicting extreme events by quantifying their uncertainty. Researchers found that while models like FuXi, GraphCast, and SFNO …
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New signature kernel scoring rule enhances weather forecasting accuracy
Researchers have introduced a new metric called the signature kernel scoring rule for probabilistic weather forecasting. This rule reframes weather variables as continuous paths, using iterated integrals to capture temp…
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AI model enhances climate data resolution for renewable energy forecasting
Researchers have developed a super-resolution recurrent diffusion model (SRDM) to enhance the temporal resolution of climate data for more accurate renewable energy generation predictions. This model addresses the limit…