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Network analysis of hurricanes affecting the United States.

机译：网络分析影响美国的飓风。

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摘要

Hurricanes affecting the United States cause severe damage and kill people. The risk of future hurricane activity along the coast is the subject of much scientific and public interest. While considerable work had been done to understand the occurrence of hurricanes along the coast, much less has been done to examine the inter-relationships among the hurricanes. This dissertation concerns the relationships of hurricanes affecting the United States using methods of network analysis. Network analysis has been used in a variety of fields to study relational data, but has yet to be used in the study of hurricane climatology. The present work is largely expository introducing network analysis and showing how it can be applied to possibly better understanding regional hurricane activity as well as hurricane activity overtime.;The research is divided into two cases. The first case consists of networks developed based on the relationships of spatial locations of landfalls and the second part consists of networks developed based on the relationships of the temporal occurrence of landfalls. In the first case, the network links coastal locations (termed nodes) with particular hurricanes (termed links). The topology of the network is examined using local and global metrics. Results show that certain regions of the coast (like Louisiana) have high hurricane occurrence rates, but not necessarily high values of network connectivity. Low values of connectivity indicate that hurricanes affecting Louisiana tend not to affect other regions. Regions with the highest values of connectivity include southwest Florida, northwest Florida, and North Carolina. Virginia which has a relatively low occurrence rate is well-positioned in the network having a relatively high value of betweenness. In the second case, the year-to-year variation in U.S. hurricane activity is examined by extending the ideas and concepts of network analysis for time series data. The "visibility" network link years experiencing a hurricane landfall with other hurricane landfall years "visible" to each other through time. The topology of the visibility network is examined using local and global metrics. Results show that overall the visibility network has few years with many lines of visibility, therefore, many linkages to other years. Years with high hurricane count have more visibility in the network than those years that have less storms. Among years with high counts the years that are surrounded (before and after) with years of low counts will have greater visibility. The years 1886, 1893, 1955 and 2004 are highly visible in the network of U.S. hurricanes. A year is more central if it is a link in more visibility chains between other years in the network.;Six conditional networks are constructed for the spatial and temporal networks based on years of below and above average values of important climate variables. Significant differences in the connectivity of the network are noted for different phases of the El Nino-Southern Oscillation. During El Nino years, when the equatorial waters of the eastern Pacific are warm, there tends to be shearing winds and subsidence over large portions of the North Atlantic where hurricanes form. These conditions lead to fewer hurricanes affecting the United States. More work is needed to better understand the details of how climate influences the network of landfalls.;The scientific merit of the research is a better understanding of the relationships in the regional risk of hurricane activity. The broader impacts are an introduction of network analysis to hurricane climatology.
机译：影响美国的飓风造成了严重破坏，并造成了人员死亡。沿海地区未来飓风活动的风险是许多科学和公共利益的主题。尽管已经做了很多工作来了解沿海地区飓风的发生，但是研究飓风之间的相互关系却做得很少。本文利用网络分析方法研究了飓风对美国的影响。网络分析已用于许多领域来研究关系数据，但尚未用于飓风气候学研究。目前的工作主要是说明性的，介绍了网络分析，并展示了如何将其应用到可能更好地了解区域飓风活动以及加班的飓风活动中的方法。该研究分为两个案例。第一种情况由基于登陆的空间位置关系开发的网络组成，第二部分由基于登陆的时间发生关系开发的网络组成。在第一种情况下，网络将沿海位置（称为节点）与特定的飓风（称为链接）链接在一起。使用本地和全局指标检查网络的拓扑。结果表明，沿海某些地区（如路易斯安那州）的飓风发生率很高，但网络连接性不一定很高。较低的连通性值表明，影响路易斯安那的飓风趋向于不影响其他地区。连通性值最高的区域包括佛罗里达西南部，佛罗里达西北部和北卡罗来纳州。发生率相对较低的弗吉尼亚州在网络之间具有相对较高的价值定位，位置相对较高。在第二种情况下，通过扩展用于时间序列数据的网络分析的思想和概念，研究了美国飓风活动的逐年变化。 “可见性”网络将经历飓风登陆的年份与其他“飓风登陆年”在时间上彼此可见。使用本地和全局指标检查可见性网络的拓扑。结果表明，可见性网络总体上具有几年可见性，并且具有许多可见性，因此与其他年份之间存在许多联系。与飓风较少的年份相比，飓风数量较高的年份在网络中的可见度更高。在计数较高的年份中，计数较低的年份（之前和之后）包围的年份将具有更大的可见性。 1886年，1893年，1955年和2004年在美国飓风网络中非常明显。如果一年是网络中其他年份之间更多可见性链中的链接，则年份会更重要。基于重要气候变量的平均值低于和高于平均值的年份，为时空网络构建六个条件网络。对于厄尔尼诺-南方涛动的不同阶段，网络的连通性存在显着差异。在厄尔尼诺现象期间，东太平洋的赤道水很暖，在飓风形成的北大西洋大部分地区，往往会有剪切风和沉降。这些情况导致较少的飓风影响美国。需要做更多的工作来更好地了解气候如何影响着陆网络的细节。研究的科学价值是更好地了解飓风活动区域风险中的关系。广泛的影响是将网络分析引入飓风气候学。

著录项

  • 作者

    Fogarty, Emily A.;

  • 作者单位

    The Florida State University.;

  • 授予单位 The Florida State University.;
  • 学科 Physical Geography.;Atmospheric Sciences.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 79 p.
  • 总页数 79
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然地理学;
  • 关键词

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