Extratropical Persistent Anomalies on a Warmer Earth: Connections to Extratropical Storms and Storm Tracks

这是对大气环流中持续性异常(PA)的研究，定义为大气流动的不寻常状态，在超过几天的时间内保持大致固定。当天气系统在给定位置的正常向东推进被破坏时，这里所述的PAS发生在中纬度地区。它们通常与急流的分裂或经向移动有关，大致上是大气阻塞的同义词，尽管阻塞有更严格的定义。人们对PA的兴趣很大程度上是因为它们与冷空气爆发、干旱、暴雨和热浪等高影响天气事件有关。该项目试图了解决定持续性异常(PA)的频率、强度和持续时间的基本动力学，以及由于温室气体增加而可能导致的PA行为的变化。PA在空间尺度上比统称为天气系统的天气锋和气旋更宽。对阻塞的研究表明，天气系统在阻塞的开始和维持中起着很大的作用，这一发现也适用于PAS。PIS假设，PAS的启动和维持依赖于天气系统内部发生的较小规模的过程，包括将含雨云(发生凝结加热的地方)组织成中尺度特征(例如雨带和锋线)。这一假说的部分原因是研究表明，即使在低分辨率的模式中，与网格间距相比，具有更高分辨率的全球天气和气候模式在模拟块方面做得更好，尽管块的大小很大。PI提出更高的分辨率是更好的，因为它允许更准确地表示发生凝结加热的小得多的中尺度特征。凝结加热的更好表现导致了更强大的系统，这可以更有效地将低涡度空气从热带急流移动到高纬度，这是PA形成所需的。这一假设的一个含义是，更有利于高强度天气系统的模式或气候状态将产生更强的PAS。这一论点表明，随着气候变暖，气候变暖，气候变化可能会变得更强或更突出，因为温暖空气中更高的水分含量允许更强烈的降雨和凝结加热。该项目通过识别一组案例并使用全球大气模式(天气研究和预测模型，或跨尺度预测模型，如果可用)对这些案例进行后播模拟，研究了当今气候中的气候变化。将确定产生这些情况的最佳模拟的模式配置，并将执行一些诊断以确定导致PA启动和持续的关键因素。为了评估这些特征在PA形成中的作用，利用一种技术进行了额外的实验，其中修改了模拟的初始大气状态以删除特定的天气特征。通过重复后播来研究气候变化对PAS的影响，但修改背景状态以接近气候模式模拟的温室效应。长期的模式积分被用来从统计意义上考虑PA的行为，简单的单层模型被用来进一步研究PA的基本动力学。鉴于PA与影响人类活动的高影响天气事件的密切联系，PA的行为是一个具有实用和科学意义的话题。这项工作解决了与提高天气模型预测与PA相关的极端天气的能力以及气候模型预测PA行为未来变化的能力直接相关的问题。此外，该项目通过两门强调合作研究的新课程为本科生提供研究机会，一门是数据分析，另一门是数值模拟。在该项目的每个夏天，还会为本科生实习提供支持，并在为少数族裔服务的机构发布招聘广告。此外，该项目将雇用和培训两名研究生和一名博士后研究员，从而在这一研究领域提供未来的劳动力发展。

This is a study of persistent anomalies (PAs) in atmospheric circulation, defined as unusual states of the atmospheric flow that remain approximately fixed over periods longer than a few days. PAs addressed here occur in middle latitudes when the normal eastward progression of weather systems over a given location is disrupted. They are generally associated with splitting or meridional shifting of jet streams and are loosely synonymous with atmospheric blocking, although blocking has a more restrictive definition. Interest in PAs comes largely from their association with high-impact weather events including cold air outbreaks, droughts, pluvials, and heat waves. The project seeks to understand the fundamental dynamics which determine the frequency, intensity, and duration of persistent anomalies (PAs), as well as the changes in PA behavior that are likely to occur as a result of warming due to greenhouse gas increases.PAs are broader in spatial scale than the weather fronts and cyclones that are collectively referred to as synoptic systems. Studies of blocking show that synoptic systems play a large role in the onset and maintenance of blocks, a finding that holds true for PAs as well. The PIs hypothesize that the initiation and maintenance of PAs depends on smaller-scale processes that occur inside the synoptic systems, including the organization of rain-bearing clouds (where condensational heating occurs) into mesoscale features (rain bands and squall lines, for example). The hypothesis is motivated in part by studies showing that global weather and climate models with higher resolution do a better job in simulating blocks, despite the large size of blocks compared to grid spacing even in low resolution models. The PIs propose that higher resolution is better because it allows a more accurate representation of the much smaller mesoscale features where the condensational heating takes place. Better representation of condensational heating leads to more vigorous systems, which can more effectively move low vorticity air across the jet stream from the tropics to high latitudes as required for PA formation. One implication of this hypothesis is that models or climate states which are more conducive to high intensity synoptic systems will produce more strong PAs. This argument suggests that PAs could become stronger or more prominent as climate warms, as the greater moisture content of warmer air allows for more intense rainfall and condensational heating.The project examines PAs in present-day climate by identifying a set of cases and performing "hindcast" simulations of those cases using a global atmospheric model (the Weather Research and Forecasting model, or the Model for Prediction Across Scales if it becomes available). Model configurations which produce the best simulations of these cases will be identified, and a number of diagnostics will be performed to identify the key ingredients which lead to PA initiation and persistence. Additional experiments are performed using a technique in which the initial atmospheric state for the simulation is modified to remove particular synoptic features, in order to assess the role of these features in PA formation. The impact of climate change on PAs is studied by repeating the hindcasts but with the background state modified to approximate the effects of greenhouse warming as simulated by climate models. Long model integrations are used to consider PA behavior in a statistical sense, and simple single-layer models are used to further examine the basic dynamics of PAs.The behavior of PAs is a topic of practical as well as scientific interest, given the close association of PAs with high-impact weather events that affect human activities. The work addresses questions which are directly relevant to improving the ability of weather models to forecast PA-related extreme weather, and the ability of climate models to anticipate future changes in PA behavior. In addition, the project provides undergraduate research opportunities through two new courses emphasizing collaborative research, one on data analysis and the other on numerical simulations. An undergraduate internship is also supported in each summer of the project, and the position is advertised at minority-serving institutions. In addition, the project will employ and train two graduate students and a postdoctoral fellow, thereby providing future workforce development in this area of research.