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English(EN) Rescene: band-limited stochastic forcing turns a frozen neural weather operator into a climate emulator

使用Rescene将冻结的神经天气模型改编用于气候模拟

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了Rescene，这是一种将冻结的神经天气模型改编用于气候模拟的新颖方法。通过添加确定性包装器和频谱整形随机扰动，Rescene使先前不稳定的模型能够进行长达数十年的气候模拟而不会出现漂移。该方法成功恢复了每日变化性并保持了集合校准，证明了在利用预训练模型进行长期气候预测方面取得了重大进展。 AI

影响 利用预训练的神经天气模型实现长期气候模拟，可能加速气候研究。

排序理由 该集群包含一篇学术论文，详细介绍了一种将现有模型改编用于不同科学领域的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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使用Rescene将冻结的神经天气模型改编用于气候模拟

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该集群包含一篇学术论文，详细介绍了一种将现有模型改编用于不同科学领域的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Minjong Cheon ·

    Rescene：限带随机强迫将冻结的神经天气算子转变为气候模拟器

    arXiv:2608.09971v1 Announce Type: cross Abstract: Over the past few years, the rapid development of machine learning (ML) models for weather forecasting has produced deterministic models whose medium-range skill matches or exceeds that of the European Centre for Medium-Range Weat…

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