Probabilistic perspectives on climate dynamics

有一句经典的格言描述了天气和气候之间的区别：“气候是你所期望的，而天气是你所得到的。”这个概念基本上是概率的：天气每天的演变被看作是一个湍流系统的特定路径，而气候是所有这些可能的天气路径的概率分布。理解和预测气候系统不仅需要研究平均状态，还需要研究平均状态的可变性强度、可变性的不对称性、极端事件的性质等等。我们感兴趣的基本目标是气候系统的概率分布。本研究发展了气候系统的概率观点，重点关注以下几个广泛目标：(1)描述重要气候变量的概率分布特征；(2)开发基于物理的模式来理解这些分布的起源；(3)评估小尺度（在空间和时间上）“天气”变率对大尺度“气候”系统动力学的影响。需要提出的具体问题包括：“观测到的大尺度大气变化形式的物理起源是什么？”、“日常天气在海洋生态系统从大气中去除二氧化碳方面发挥了什么作用？”、“我们如何更好地描述气候变量之间的关系？”以及“我们如何更好地在气候模式中表现热带对流过程？”这些问题对于改进业务天气和气候模型具有重要意义，并将汇集数学家和气候科学家来解决对加拿大和更广泛的全球社会具有根本重要性的问题。

A classic aphorism  characterising the difference between weather and climate states that "climate is what you expect, but weather is what you get".  This conception is fundamentally probabilistic: the evolution of weather from day to day is seen as the particular path of a turbulent system, while the climate is the probability distribution of all these possible weather paths. Understanding and predicting the climate system involves studying not just the average state, but the strength of variability about the average, asymmetries in this variability, the nature of extreme events, and so forth.  The fundamental object of interest is the probability distribution of the climate system.This research develops probabilistic perspectives on the climate system, focusing on the broad goals of (1)  characterising the  probability distributions of important climate variables, (2)  developing physically-based models to understand the origin of these distributions, and (3) assessing the influence of small-scale (in space and time) "weather" variability on the dynamics  of the large-scale "climate" system. Particular questions to be asked include: "what is the physical origin of observed large-scale forms of atmospheric variability?", "what role does day-to-day weather play in the removal of carbon dioxide from the atmosphere by ocean ecosystems?", "how can we better characterise relationships between climate variables?", and "how can we better represent tropical convective processes in climate models?".  These problems are of significance for the improvement of operational weather and climate models, and will bring together mathematicians and climate scientists to address issues of fundamental importance to Canada and to the broader global community.