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全球气候变化中的物理问题

Physical problems in the global climate change

  • 摘要: 全球气候变化是一个复杂的科学问题,它涉及到气候系统或地球系统的变化,不但需要考虑它们所包含的这些系统内各部分本身的变化,以及它们之间复杂的相互作用,而且还需考虑物理与地球生物化学等许多过程.文章主要讨论全球气候变化中的物理问题,主要有三个方面:(1)辐射传输和全球辐射平衡:不论是由于自然的原因或人类活动(如太阳活动与火山爆发以及温室气体排放增加导致的温室效应加强)一旦破坏全球的辐射平衡,则会引起气候变化,这是气候变化的主要原因与驱动力;(2)大气波动和气候变化的内部变率:除上述外强迫的作用外,气候变化还可由气候系统内部的变率引起,这包括大气内部变率和耦合气候变率.它们主要是通过产生各种大气的波动而实现的.其中最重要的是罗斯贝(Rossby)波.它们的传播和不稳定发展是造成气候变化的另一个原因;(3)气候系统的混沌性质和可预报性:数值预报模式的预报结果对初始场很敏感,即初始场的微小误差可导致完全不同的预报结果,同时模式中物理过程描述的真实程度也影响预报的结果.大气的这种混沌性质限制了天气的可预报性在2周以内.但气候预测由于明显受外强迫的作用,可使大气的混沌时效延长到月、季、年、几十年甚至上百年.为了减少由初始场误差和模式不完善而造成的预报误差,目前气候预报是采用多初值和多模式的集合预报方法,因而气候预测实际上是一种概率预报.

     

    Abstract: Global climate change is a complicated scientific problem that involves changes in the climate system or the Earth’s system. It is necessary to consider changes of each system component and their complex interactions, as well as multiple physical and geobiochemical processes. This paper will focus on the fundermental physical problems in the following three aspects. (1) Radiative transfer and global radiation balance. Global climate changes will occur once the global radiation balance is destroyed, either due to natural causes (solar activity and eruption of vocanoes), or due to human activities, such as an increase in emission of greenhouse gases which leads to enhanced greenhouse effects. These are the main drivers responsible for global climate changes. (2) Atmospheric waves and internal climate variability. Besides the above-mentioned external forcings, climate change can also be caused by internal climate variability, including atmospheric internal variability and coupling of the climate variability. These mainly exert their effects through various kinds of atmospheric waves. Among them, the Rossby wave is a most important mode. Their propagation and unstable development is a cause leading to climate change. (3) The chaotic nature and predictability of the climate system. The prediction of future climate change based on a climate model is very sensitive to initial values, i.e., small errors of initial fields can lead to completely different results. At the same time, the fidelity of climate modes can also cause significant prediction errors.This chaotic nature of the atmosphere limits weather prediction to a range of two weeks. However, due to significant weakening of the chaotic nature under external forcings, climate prediction may extend up to a month, a season, a year, or even multi-decades and multi-centuries. In order to narrow down predictive uncertainty caused by initial errors and incompleteness of the physical model, climate prediction now uses ensemble prediction techniques, thus leading to probabilistic predictions.

     

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