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English(EN) Evaluating Skill and Stability of ArchesWeather and ArchesWeatherGen under Multi-Decadal Climate Simulations

AI模型ArchesWeather和ArchesWeatherGen在气候模拟中表现出稳定性

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员评估了ArchesWeather和ArchesWeatherGen这两个最初为天气预报设计的机器学习模型，在长期气候模拟中的能力。当使用月度海面温度和海冰覆盖数据进行调整，作为强制大气模型运行时，这两个模型都展示了稳定的气候模拟和年度周期。它们成功捕捉了气候变量的漂移，重现了ERA5气候学，并准确地表示了大规模环流和年际变率。 AI

影响 展示了最初用于天气的机器学习模型在气候模拟研究中做出贡献的潜力。

排序理由 这是一篇评估现有机器学习模型在新应用（气候模拟）中的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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AI模型ArchesWeather和ArchesWeatherGen在气候模拟中表现出稳定性

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这是一篇评估现有机器学习模型在新应用（气候模拟）中的研究论文。[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) · Renu Singh, Robert Brunstein, Antonia Jost, Thomas Rackow, Claire Monteleoni, Yana Hasson, Christian Lessig, Guillaume Couairon ·

    评估ArchesWeather和ArchesWeatherGen在多年气候模拟中的技能和稳定性

    arXiv:2605.29976v1 Announce Type: cross Abstract: We evaluate the climate simulation capabilities of ArchesWeather and ArchesWeatherGen, two machine learning models originally trained for weather forecasting and evaluated up to a 10-day lead time. ArchesWeather is a deterministic…

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