AGS-PRF Coupling Between Regional Climate Feedbacks and Large-Scale Circulation in a Hierarchy of Models

温室气体浓度增加引起的气候变化通常被称为全球变暖，气候对温室气体浓度增加的敏感性是通过给定温室气体浓度均匀增加时全球平均温度的增加来衡量的。然而，决定气候敏感性的反馈过程表现出很大的地理依赖性，例如，与冰和雪有关的反照率反馈主要限于较冷的高纬度地区，而云和水汽反馈在亚热带地区最强。气候对统一外力的反应也表现出强烈的地理依赖性，对人类和自然系统产生重要影响。但响应的空间模式与反馈的空间模式不匹配，因为大气和海洋环流有效地重新分配了区域反馈引入系统的过剩能量。此外，在气候变化模拟中发现大气环流的强劲变化，推测是由反馈和外部强迫引起的，但它们反过来可能对反馈产生实质性影响。该奖项支持PI进行博士后研究，以了解区域气候反馈、能量传输、大气稳定性和环流动力学在确定气候系统对外部强迫的区域响应方面的相互作用。这项工作的具体重点是热带和亚热带的气候反馈和气候变化，以及它们如何与哈德利环流强度的变化有关，哈德利环流是指空气在多雨的热带辐合带上升和在干燥的亚热带地区下降的翻转环流。PI和她的同事们已经开发出一个诊断方程，其中哈德利单元强度的微小变化可以分解为上述所有因素的贡献。诊断分析应用于为气候模式比较项目第5版(CMIP5)存档的一组气候模拟，其中气候反馈可以被量化。一个需要解决的问题是，为什么模型模拟往往显示随着气候变暖，Hadley模拟的强度下降，另一个问题是，Hadley单元响应的模型之间的差异是否与反馈和其他因素的差异有关。这一分析将得到不同复杂阶段的模型层次实验的补充，以检查哈德利细胞变化与反馈和能量传输之间的因果关系。鉴于气候变化对热带和亚热带地区的重大社会和生态影响，这项工作具有重要的更广泛的影响。这项工作的结果对于理解未来气候变化的模型模拟的行为，特别是对于理解和减少气候模型预测的不确定性，以及决定模拟的哪些方面可能被证明是最可靠的，可能是有价值的。此外，该项目有一个教育部分，其中PI将开发教育材料，为本科生提供严格的气候反馈分析基础。这些材料包括使用用Python编写的简单能量平衡模型的动手练习，该模型将在网上提供。

Climate change due to increased greenhouse gas concentration is generally referred to as global warming, and the sensitivity of climate to greenhouse gas increases is measured by the increase in global mean temperature for a given uniform increase in greenhouse gas concentrations. Yet the feedback processes which determine climate sensitivity show substantial geographical dependencies, for example the albedo feedbacks associated with ice and snow are largely confined to colder high latitude regions, while cloud and water vapor feedbacks are strongest in the subtropics. The response of climate to uniform external forcing also shows strong geographical dependence, with important consequences for human and natural systems. But the spatial pattern of the response does not match the spatial pattern of the feedbacks, as atmospheric and oceanic circulation are effective in redistributing the excess energy introduced to the system by the regional feedbacks. Moreover, robust changes in atmospheric circulation are found in climate change simulations, presumably caused by the feedbacks and external forcing, but they may in turn have substantial effects on the feedbacks.This award supports the PI to conduct postdoctoral research to understand the interplay of regional climate feedbacks, energy transport, and atmospheric stability and circulation dynamics in determining the regional response of the climate system to external forcing. The specific focus of the work is on climate feedbacks and climate change in the tropics and subtropics and how they relate to changes in the strength of the Hadley cell, the overturning circulation in which air rises in the rainy intertropical convergence zone and subsides in the dry subtropics. The PI and her colleagues have developed a diagnostic equation in which fractional changes in the strength of the Hadley cell can be decomposed into contributions from all of the factors mentioned above. The diagnostic analysis is applied to a set of climate simulations archived for the Climate Model Intercomparison Project version 5 (CMIP5) for which the climate feedbacks can be quantified. One question to be addressed is why model simulations tend to show a decrease in the strength of the Hadley simulation as climate warms, and another is whether model-to-model differences in the Hadley cell response can be related to differences in feedbacks and other factors. This analysis will be supplemented by experiments with a hierarchy of models at various stages of complexity, to examine causal relationships between changes in the Hadley cell and the feedbacks and energy transports.The work has important broader impacts given the substantial social and ecological impacts of climate change in the tropics and subtropics. The results of this work may be valuable for understanding the behavior of model simulations of future climate change, in particular for understanding and reducing uncertainty in climate model projections, and for deciding which aspects of simulations are likely to prove most reliable. In addition, the project has an educational component in which the PI will develop educational materials to provide undergraduate students with a rigorous foundation in climate feedback analysis. The materials include hands-on exercises using a simple energy balance model written in Python, which will be made available online.