RAPID: Physical Behavior of Precipitation Extremes in CMIP5 GCMs and Observations

这是政府间气候变化专门委员会第五次评估报告（IPCC AR5）中鼓励对气候模式模拟进行诊断分析的致同事信（NSF 11-006）资助的16个快速响应（Rapid）项目之一。在这些项目中进行的研究预计将导致更详细的模式相互比较，更好地理解稳健模式行为，更好地理解和量化未来气候模拟中的不确定性。本项目考察了为AR5准备的当今气候模拟中的极端降水事件。推动这个项目的核心问题是：模型模拟的极端事件在多大程度上是由极端事件实际发生时发生的物理行为造成的？这个问题是通过两个主要活动来解决的：1)在模拟和观测中提取特定的、气候同质区域的极端日降水事件；2)评估极端事件在导致极端事件发生的几天内的环流、温度、湿度和水/能量通量场所描述的行为。自组织图（SOMs）统计分析工具用于提取模拟和观测中伴随极端降水事件的天气条件的空间格局和演变，以便对两者进行一致性比较。该项目的重点区域是北美，那里的观测足够密集，可以进行深入的物理比较。该项目的更广泛影响在于它对IPCC第五次评估报告的支持，该报告旨在向全球决策者提供有关气候变化及其后果的信息。本研究中评估的气候模式将用于评估由于全球变暖导致的极端降水事件的预估变化，这一分析对于确定我们对未来极端事件的模式预估的置信度非常重要。

This is one of 16 Rapid Response (RAPID) projects funded as the result of a Dear Colleague Letter (NSF 11-006) encouraging diagnostic analyses of climate model simulations prepared for the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). Research conducted in these projects is expected to lead to more detailed model intercomparisons, better understanding of robust model behaviors, and better understanding and quantification of uncertainty in future climate simulations.This project examines extreme precipitation events in present-day climate simulations prepared for the AR5. The central question motivating the project is this: to what extent do extreme events simulated by the models result from physical behavior that occurs when extreme events actually happen? This question is addressed through two main activities: 1) extracting extreme daily precipitation events for select, climatologically homogeneous regions in simulations and observations, and 2) evaluating the behavior of the events as depicted in circulation, temperature, humidity and water/energy flux fields on the days leading up to the extreme event. The statistical analysis tool known as Self-organizing maps (SOMs) is used to extract the spatial patterns and evolution of the synoptic conditions that accompany extreme precipitation events in both simulations and observations, so that the two can be compared for consistency. The region of focus for the project is North America, where observations are dense enough to allow in-depth physical comparison. The broader impact of the project lies in its support of the IPCC AR5, which is intended to provide information on climate change and its consequences to decision makers worldwide. The climate models evaluated in this study will be used for assessing projected changes in extreme precipitation events due to global warming, and this analysis is important for determining the level of confidence we can have in model projections of future changes in extremes.