非马科夫式能源平衡模型在气候中的挑战
Nicholas W Watkins1,2, Raphael Calel1,3, Sandra C Chapman2,4,5
1Grantham Research Institute on Climate Change and the Environment, The London School of Economics and Political Science, Houghton Street, London WC2A 2AE, United Kingdom.
Chaos (Woodbury, N.Y.)
|July 30, 2024
概括
克劳斯·哈塞尔曼 (Klaus Hasselmann) 的气候建模范式是一项获得诺贝尔奖的创新,它将天气波动与气候变化联系起来. 新的方法,比如一般化的朗格文方程,建立在改善气候模型的基础上.
科学领域:
- 复杂性科学 复杂性科学
- 气候建模气候模型
- 统计力学 统计力学
背景情况:
- 对克劳斯·哈塞尔曼 (Klaus Hasselmann) 1976年提出的范式进行回顾,这是在气候科学领域获得诺贝尔奖的创新.
- 哈塞尔曼的工作引入了早期能源平衡模型 (EBM) 的变性,并将天气与气候联系起来.
- 该范式利用布朗运动将快速的天气波动与缓慢的气候变化联系起来.
研究的目的:
- 探索哈塞尔曼范式在当代气候科学中的演变和应用.
- 在莫里-兹万齐格通用朗格温方程 (GLE) 框架内研究哈塞尔曼型模型的集成.
- 提出一个简单的随机EBM,对全球温度异常具有记忆,由莫里-库博过度减压的GLE告知.
主要方法:
- 对哈塞尔曼范式及其概念基础的审查.
- 分析最近的发展,包括莫里-兹万齐格GLE和带内存的随机EBM.
- 应用莫里-库博过度减压的GLE来制定一个随机的EBM,并对全球温度异常进行记忆.
主要成果:
- 哈塞尔曼的范式提供了天气和气候变化之间的基本联系.
- 莫里-兹万齐格 GLE 框架为哈塞尔曼型模型提供了一个严格的数学层次结构.
- 为全球温度异常提出了一个简单的带记忆的随机EBM,它是从Mori-Kubo GLE中衍生出来的.
结论:
- 哈塞尔曼的范式仍然非常相关,为气候变化和反机制提供了洞察力.
- 像GLE这样的先进框架为气候建模提供了更全面的方法.
- 拟议的带内存的随机EBM为了解和建模全球温度动态提供了一个有希望的途径.
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