An overview of complexity studies on Earth systems
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摘要: 本文旨在全面回顾统计物理学、复杂系统科学(如临界现象、网络理论、渗流、临界点分析和熵)以及机器学习等方法在复杂地球系统研究和应用方面的最新进展.这些方法的整合,为理解地球系统的动力学,提供了新的见解和视角.通过运用这些方法,可以更好地建模、分析地球系统中的相互关系和非线性效应,揭示系统的复杂行为和临界性质.Abstract: This review aims to comprehensively recapitulate the latest scientific advancements in methods from statistical physics, complex systems science (such as critical phenomena, network theory, percolation, critical point analysis, and entropy), and machine learning in the research and application of complex Earth systems. The integration of these methods provides new insights and perspectives for understanding the dynamics of Earth systems. By applying these methods, we can better model and analyze the interrelationships and nonlinear effects in Earth systems, revealing the system’s complexity and critical properties.
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Key words:
- statistical physics /
- complex Earth systems /
- complex networks /
- climate change
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表 1 地球气候系统中的一些基本的主要临界要素[36]
编号 临界要素 具体表现 1 格陵兰冰盖(Greenland ice sheet) 冰损失加剧(Ice loss accelerating) 2 北极海冰(Arctic sea ice) 海冰区域面积减少(reduction in area) 3 北方森林(boreal forest) 火灾和害虫变化(fire and pests changing) 4 亚马逊雨林(Amazon rainforest) 频繁的旱灾(frequent droughts) 5 大西洋环流(Atlantic circulation) 自1950年代以来减缓(in slowdown since 1950s) 6 西伯利亚冻土(Permafrost) 永久冻土解冻(thawing) 7 澳大利亚珊瑚礁(Coral reefs) 大面积死亡白化(large-scale die-offs) 8 南极洲东部的威尔克斯盆地
(Wilkes Basin, East Antarctica)冰损失加剧(ice loss accelerating) 9 南极洲西部的冰盖
(West Antarctic ice sheet)冰损失加剧(ice loss accelerating) -
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