Regional Climate Modelling: Probing the strengths and limitations of dynamical downscaling with nested models

经济、环境和卫生的几个部门对变幻莫测的天气、气候变化和预期的变化很敏感。一个技术先进的社会需要利用最好的信息，根据对预期影响的量化评估，设计减少脆弱性的应对战略。这需要通过气候物理研究发布的气候模拟器获得对未来气候的准确预测。因此，气候物理学方面的培训和学术研究是气候影响和适应研究的基础。 拟议研究方案的目的是加深我们对嵌套区域气候模式(RCM)动力缩减尺度的优势和(特别是)局限性的理解。RCM的预测需要由全球气候模型(GCM)的边界条件(BC)驱动。但GCM只提供了不完善的大规模信息。因此，RCM的附加值是解决GCM所缺乏的细小尺度问题。RCM的有限区域意味着细尺度必须完全在区域区域内发展，这意味着分辨率从GCM跳到RCM和RCM区域大小，以允许适当的自旋，同时保持对RCM模拟的控制。经过精心设计的实验，将实现一些理想化的方法，如我几年前设计的、现在被世界各地几个研究中心使用的“老大哥实验”，以及使用更现实和复杂背景的其他实验，以估计区域进程的高分辨率区域管理模拟和预测的信心限度以及潜在和实际的附加值。

Several sectors of economy, environment and health are sensitive to weather vagaries, climate variations and anticipated changes. A technologically advanced society needs to use the best information to design a coping strategy to reduce vulnerability, based on a quantitative assessment of anticipated impacts. This requires accurate projections of future climate that are obtained with climate simulators issued from research in the physics of climate. Training and academic research in the Physics of climate are therefore the very foundation for climate impacts and adaptation studies. The objective of the proposed research programme is to further our understanding of the strengths and (specially) the limitations of dynamical downscaling with nested Regional Climate Models (RCMs). RCMs' projections need to be driven by boundary conditions (BC) from Global Climate Models (GCMs). But GCMs provide only imperfect large-scale information. The added value of RCMs is thus to resolve fine scales that are absent in GCMs. The limited area of an RCM implies that fine scales must develop entirely within the regional domain, with implications on the resolution jump from the GCM to the RCM and RCM domain size to allow proper spin up, while maintaining control of the RCM simulation. Carefully designed experiments, some following idealised approaches such as the "Big-Brother Experiment" I designed a few years ago and which is now used by several research centres around the world, and other experiments using more realistic and complex context, will be realised to estimate the limits of confidence and the potential and real added value of high-resolution RCM simulations and projections on regional processes.