Improved Understanding of the Response of Mean and Extreme Precipitation to Climate Change

这项工作的目标是了解决定全球气温上升如何影响降水的基本机制，包括降水空间分布的变化和最极端降水事件强度的变化。气候系统对温室气体增加的响应的模型模拟表明，由于全球变暖，降水发生了实质性变化，但模型对这些变化的细节存在分歧，其机制也没有得到很好的理解。一种经常被引用来解释这种变化的机制是基于这样一个事实，即空气中的水分含量通常随着变暖而增加，因此在水分已经汇聚并在当今气候中造成降水的地区，水分汇聚和随后的降雨量增加(在已经干燥的地区，同样预计会出现干燥)。但PI之前的工作表明，这种“变得更湿”的论点不能充分解释陆地上的降水量变化，而陆地上的降雨量变化对社会影响最大。通过简化大气环流模式的试验和气候模式国际比较项目第五版(CMIP5)的模拟分析，通过考虑陆地表面变暖和相对湿度变化的空间差异所起的作用，本项工作试图更好地理解陆地上的降水响应。另一种观点认为，当热带海洋的局部海面温度(SST)超过热带SST的总体变暖时，降水将增加，因为较暖的SST会导致上层大气比邻近地区更不稳定。但是这种“变暖变湿”的观点忽略了近地表风的汇聚、水蒸气和云层的辐射效应以及干燥的静态稳定性的变化所带来的潜在贡献。这些影响将通过一个诊断模式和第二个模式一起检验，在诊断模式中，降水与响应低层辐合的浅垂直模有关，第二个模式捕捉深部对流对相对海温变化的依赖。极端降水事件强度变化的研究使用理想配置的云系解析模式(CRM，特别是大气模拟系统)，以弥补气候模式在描述极端降水方面的局限性。一些模拟是使用次静力定标进行的，其中人为地修改了垂直动量方程，以缩小发生对流降水的小尺度与天气图上发现的典型天气系统和高、低气压中心的大得多的尺度之间的尺度差距。这种方法使得将两种刻度合并在一起的实验成为可能，否则计算成本太高。另一个要讨论的话题是气候变暖对极端降雪事件的影响。PI之前的工作为极端降雪设定了一个最佳温度，这是因为极端降雨量随着温度的升高而增加，而降雪量在接近冰点的范围内急剧下降。这里的工作使用观测降雪数据和模型输出来测试这一理论，并探索其对气候变暖的影响。由于平均降水量的变化和极端降水事件的严重性的潜在影响，该工作具有更广泛的影响。平均降雨量对农业和水资源及其管理很重要，而极端降雨量往往对社会造成破坏，极端降雪事件与城市环境中的一些成本有关。该项目还支持和培训一名研究生，从而促进这一研究领域的劳动力发展。该项目还为一名本科生提供暑期支持。

The goal of this work is to understand the basic mechanisms which determine how increases in global temperature affect precipitation, including both changes in the spatial distribution of precipitation and changes in the intensity of the most extreme precipitation events. Model simulations of the response of the climate system to greenhouse gas increases show substantial changes in precipitation as a consequence of global warming, but models disagree on the details of these changes and the mechanisms for them are not well understood. One mechanism commonly invoked to explain the changes is predicated on the fact that the moisture content of air typically increases with warming, so moisture convergence and subsequent precipitation increase in regions where moisture is already converging and causing precipitation in the present-day climate (drying is likewise expected in regions which are already dry). But previous work by the PI shows that this "wet get wetter" argument does not adequately account for precipitation changes over land, where they have the greatest societal impacts. Work pursued here seeks to better understand the precipitation response over land by considering the roles played by spatial differences in land surface warming and relative humidity change, through experiments with a simplified atmospheric general circulation model and analysis of simulations from the Climate Model Intercomparison Project version 5 (CMIP5) . Another argument holds that precipitation will increase over the tropical oceans where local sea surface temperature (SST) exceeds the overall warming of tropical SSTs, as the warmer SSTs cause the overlying atmosphere to be less stable than in neighboring regions. But this "warmer gets wetter" argument neglects potential contributions from near-surface wind convergence, the radiative effects of water vapor and clouds, and changes in dry static stability. These effects will be examined together using a diagnostic model in which precipitation is related to a shallow vertical mode which responds to low-level convergence, and a second mode which captures the dependence of deep convection on relative SST change.Research on changes in the intensity of extreme precipitation events uses a cloud-system resolving model (CRM, specifically the System for Atmospheric Modeling) in idealized configurations to make up for the limitations of climate models in representing extreme precipitation. Some simulations are performed using hypohydrostatic scaling, in which the vertical momentum equation is artificially modified to reduce the scale gap between the small scales on which convective precipitation occurs and the much larger scales of typical of the weather systems and high and low pressure centers found on weather maps. This approach enables experiments incorporating both scales which would otherwise be too computationally expensive. A further topic to be addressed is the effect of warming on extreme snowfall events. The PI's previous work posits an optimal temperature for snowfall extremes which occurs because precipitation extremes increase with temperature whereas the fraction of precipitation that falls as snow decreases sharply in a range near the freezing point. Work conducted here uses observed snowfall data and model outputs to test this theory and explore its implications for a warming climate.The work has broader impacts due to the potential impacts of changes in mean precipitation and the severity of extreme precipitation events. Mean precipitation is important for agriculture and for water resources and their management, while extreme precipitation is often disruptive to society, and extreme snowfall events are associated with a number of costs in urban environments. The project also supports and train a graduate student, thus contributing to workforce development in this research area. The project also provides summer support for an undergraduate student.