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Spatial and temporal variability of extreme weather in the United States.

机译:美国极端天气的时空变化。

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摘要

As the global climate is influenced by increased warming, the frequency of climate extremes will likely become more variable. The United States Historical Climate Network (USHCN) station data from 1900-2011 is used to quantify trends in daily extreme heat events, daily extreme cold events, and extreme daily precipitation within the contiguous United States. Climate data was spatially aggregated into respective Koeppen-Geiger climate zones where the 3 main zones are; arid, warm temperate and snow. Results show a gain or loss of 20 extreme temperature events and a gain or loss of 4 extreme precipitation events. The arid zone exhibited a loss of extreme minimum temperature a gain of extreme maximum temperature and a mixed result for extreme precipitation. The warm temperate zone indicated that the eastern region follows the exact same temperature trends as the arid zone but exhibits an overall loss of extreme precipitation. The western portion of the warm temperate zone exhibits a loss in extreme temperature events, a gain in extreme minimum temperature events and a gain in extreme precipitation. The trends in the snow zone reveal a mixed signal for extreme maximum temperature, a decline in extreme minimum temperature and a gain in extreme precipitation. Paired t-test results indicate statistically significant shifts in the magnitude of extreme weather events in each of the 3 main climate zones (arid, warm temperate and snow). This spatiotemporal analysis highlights how daily trends in extreme heat, extreme cold, and extreme precipitation have changed in the last 100 years in the context of specific climate zones. In order to understand the impact regional climate has on extreme events, trends in teleconnection patterns were examined in conjunction to daily weather. Teleconnection patterns that directly impact US weather are El Niño Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The use of wavelet analysis, including the continuous wavelet transform, the wavelet cross wavelet transform and the wavelet transform coherence provide insight into the timescales of influence from ENSO and PDO on extreme weather events. The power spectra results from each wavelet analysis have been averaged across Koeppen-Geiger zone. Results indicate that extreme precipitation events have significantly different power spectras than normal events across all timescales. Specific patterns at the annual scale and shorter are found the arid zone for extreme maximum temperature, where results for minimum temperature trends vary.
机译:随着全球气候受变暖影响,极端气候的发生频率可能​​会变得更加可变。 1900-2011年的美国历史气候网络(USHCN)站数据用于量化连续美国内每日极端高温事件,每日极端寒冷事件和极端每日降水的趋势。气候数据在空间上汇总到了Koeppen-Geiger气候区,其中3个主要区域位于其中。干旱,温暖带气候和大雪。结果表明,获得或损失了20个极端温度事件,而获得或损失了4个极端降水事件。干旱区表现出极端最低温度的损失,极端最高温度的增加以及极端降水的混合结果。温暖的温带地区表明东部地区与干旱地区遵循完全相同的温度趋势,但总体表现出极端降水的损失。温带地区的西部在极端温度事件中表现出损失,在极端最低温度事件中表现出增加,并且在极端降水中表现出增加。降雪区的趋势显示出极端最高温度,极端最低温度下降和极端降水增加的混合信号。配对的t检验结果表明,在3个主要气候区(干旱,温暖的温带和降雪)中,每个极端天气事件的大小在统计上都有显着变化。时空分析强调了过去100年来,在特定气候区的背景下,极端高温,极端寒冷和极端降水的每日趋势如何变化。为了了解区域气候对极端事件的影响,结合每日天气检查了远程连接模式的趋势。直接影响美国天气的遥相关模式是厄尔尼诺南方涛动(ENSO)和太平洋十年涛动(PDO)。小波分析的使用,包括连续小波变换,小波交叉小波变换和小波变换相干性,可洞察ENSO和PDO对极端天气事件影响的时间尺度。每个小波分析的功率谱结果已在Koeppen-Geiger区平均。结果表明,在所有时间范围内,极端降水事件的功率谱均与正常事件显着不同。在最高温度的干旱区发现了年尺度或更短的特定模式,而最低温度趋势的结果则有所不同。

著录项

  • 作者

    Wilson, Cassandra Jo.;

  • 作者单位

    University of Kansas.;

  • 授予单位 University of Kansas.;
  • 学科 Geography.;Atmospheric Sciences.;Meteorology.;Climate Change.
  • 学位 M.S.
  • 年度 2013
  • 页码 97 p.
  • 总页数 97
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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