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

更好地了解平均降水量和极端降水量对气候变化的响应

基本信息

批准号：
1552195
负责人：
Paul O'Gorman
金额：
$ 42.02万
依托单位：
Massachusetts Institute of Technology
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-07-01 至 2020-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1552195&HistoricalAwards=false
关键词：
Improved Understanding Response Mean Extreme

项目摘要

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.

这项工作的目标是了解决定全球气温升高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显示，由于全球变暖，降水量发生了巨大变化，但模型对这些变化的细节存在分歧，而且其机制尚不清楚。通常用来解释这些变化的一种机制是基于这样一个事实，即空气中的水分含量通常会随着变暖而增加，因此在水分已经聚合并在当今气候中导致降水的地区，水分会聚和随后的降水增加（干燥是已经干旱的地区也有同样的预期）。但 PI 之前的工作表明，这种“湿变得更湿”的论点并不能充分解释陆地上的降水变化，而陆地上的降水变化具有最大的社会影响。这里进行的工作旨在通过考虑陆地表面变暖和相对湿度变化的空间差异所发挥的作用，通过简化的大气环流模型的实验和气候模型比对项目第5版的模拟分析，更好地了解陆地上的降水响应（CMIP5）。另一种观点认为，当地海面温度（SST）超过热带海表温度整体变暖的热带海洋降水量将会增加，因为海表温度升高导致上层大气比邻近地区不稳定。但这种“变暖变得更湿”的论点忽略了近地表风辐合、水蒸气和云的辐射效应以及干静态稳定性变化的潜在贡献。这些影响将使用一个诊断模型来一起检查，其中降水与响应低层辐合的浅垂直模式和捕捉深对流对相对海表温度变化的依赖性的第二模式有关。强度变化的研究极端降水事件的研究使用理想化配置的云系统解析模型（CRM，特别是大气模拟系统）来弥补气候模型在表示极端降水方面的局限性。一些模拟是使用次流体静力学尺度进行的，其中垂直动量方程被人为修改，以减少对流降水发生的小尺度与典型天气系统和高低压中心的大尺度之间的尺度差距。天气图。这种方法使得实验能够结合两种尺度，否则计算成本太高。另一个要讨论的话题是变暖对极端降雪事件的影响。 PI之前的工作提出了极端降雪的最佳温度，这是因为极端降水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减少。这里进行的工作使用观测到的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。由于平均降水量变化和极端降水事件严重程度的潜在影响，这项工作具有更广泛的影响。平均降水量对于农业和水资源及其管理非常重要，而极端降水量往往对社会造成破坏，极端降雪事件与城市环境的许多成本相关。该项目还支持和培训一名研究生，从而促进该研究领域的劳动力发展。该项目还为本科生提供暑期支持。