Fangfei Lan, Brandi Gamelin, Lin Yan, Jiali Wang, Bei Wang, Hanqi Guo
{"title":"Topological Characterization and Uncertainty Visualization of Atmospheric Rivers","authors":"Fangfei Lan, Brandi Gamelin, Lin Yan, Jiali Wang, Bei Wang, Hanqi Guo","doi":"10.1111/cgf.15084","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Atmospheric rivers (ARs) are long, narrow regions of water vapor in the Earth's atmosphere that transport heat and moisture from the tropics to the mid-latitudes. ARs are often associated with extreme weather events in North America and contribute significantly to water supply and flood risk. However, characterizing ARs has been a major challenge due to the lack of a universal definition and their structural variations. Existing AR detection tools (ARDTs) produce distinct AR boundaries for the same event, making the risk assessment of ARs a difficult task. Understanding these uncertainties is crucial to improving the predictability of AR impacts, including their landfall areas and associated precipitation, which could cause catastrophic flooding and landslides over the coastal regions. In this work, we develop an uncertainty visualization framework that captures boundary and interior uncertainties, i.e., structural variations, of an ensemble of ARs that arise from a set of ARDTs. We first provide a statistical overview of the AR boundaries using the contour boxplots of Whitaker et al. that highlight the structural variations of AR boundaries based on their nesting relationships. We then introduce the topological skeletons of ARs based on Morse complexes that characterize the interior variation of an ensemble of ARs. We propose an uncertainty visualization of these topological skeletons, inspired by MetroSets of Jacobson et al. that emphasizes the agreements and disagreements across the ensemble members. Through case studies and expert feedback, we demonstrate that the two approaches complement each other, and together they could facilitate an effective comparative analysis process and provide a more confident outlook on an AR's shape, area, and onshore impact.</p>\n </div>","PeriodicalId":10687,"journal":{"name":"Computer Graphics Forum","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cgf.15084","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Graphics Forum","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/cgf.15084","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Atmospheric rivers (ARs) are long, narrow regions of water vapor in the Earth's atmosphere that transport heat and moisture from the tropics to the mid-latitudes. ARs are often associated with extreme weather events in North America and contribute significantly to water supply and flood risk. However, characterizing ARs has been a major challenge due to the lack of a universal definition and their structural variations. Existing AR detection tools (ARDTs) produce distinct AR boundaries for the same event, making the risk assessment of ARs a difficult task. Understanding these uncertainties is crucial to improving the predictability of AR impacts, including their landfall areas and associated precipitation, which could cause catastrophic flooding and landslides over the coastal regions. In this work, we develop an uncertainty visualization framework that captures boundary and interior uncertainties, i.e., structural variations, of an ensemble of ARs that arise from a set of ARDTs. We first provide a statistical overview of the AR boundaries using the contour boxplots of Whitaker et al. that highlight the structural variations of AR boundaries based on their nesting relationships. We then introduce the topological skeletons of ARs based on Morse complexes that characterize the interior variation of an ensemble of ARs. We propose an uncertainty visualization of these topological skeletons, inspired by MetroSets of Jacobson et al. that emphasizes the agreements and disagreements across the ensemble members. Through case studies and expert feedback, we demonstrate that the two approaches complement each other, and together they could facilitate an effective comparative analysis process and provide a more confident outlook on an AR's shape, area, and onshore impact.
大气河流(ARs)是地球大气中水汽形成的狭长区域,将热量和湿气从热带地区输送到中纬度地区。大气河流通常与北美洲的极端天气事件有关,对供水和洪水风险有重大影响。然而,由于缺乏统一的定义及其结构上的变化,描述 AR 的特征一直是一项重大挑战。现有的 AR 检测工具(ARDTs)会对同一事件产生不同的 AR 边界,从而使 AR 风险评估成为一项艰巨的任务。了解这些不确定性对提高 AR 影响的可预测性至关重要,包括其登陆区域和相关降水,这可能会在沿海地区造成灾难性的洪水和山体滑坡。在这项工作中,我们开发了一个不确定性可视化框架,它可以捕捉到由一组 ARDTs 产生的 ARs 集合的边界和内部不确定性,即结构变化。首先,我们使用 Whitaker 等人的等高线方框图提供了 AR 边界的统计概览,根据嵌套关系突出显示了 AR 边界的结构变化。然后,我们介绍了基于莫尔斯复合体的 AR 拓扑骨架,它描述了 AR 集合的内部变化特征。受雅各布森等人的 MetroSets 的启发,我们提出了这些拓扑骨架的不确定性可视化方法,它强调了集合成员之间的一致和分歧。通过案例研究和专家反馈,我们证明这两种方法可以相互补充,共同促进有效的比较分析过程,并为 AR 的形状、面积和陆上影响提供更有把握的前景。
期刊介绍:
Computer Graphics Forum is the official journal of Eurographics, published in cooperation with Wiley-Blackwell, and is a unique, international source of information for computer graphics professionals interested in graphics developments worldwide. It is now one of the leading journals for researchers, developers and users of computer graphics in both commercial and academic environments. The journal reports on the latest developments in the field throughout the world and covers all aspects of the theory, practice and application of computer graphics.