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Impacts of climate changes on the spatiotemporal distribution of precipitation in the western United States.

机译:气候变化对美国西部降水时空分布的影响。

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Precipitation in the Intermountain West is characterized by its great variability in both spatial and temporal distributions. Moreover, the spatiotemporal distribution of the precipitation is changing due to the climate changes. In this dissertation, three studies are conducted to investigate the multi-scale temporal variability of precipitation, the performance of current climate models on this variability, the influence of large-scale ocean oscillations on heavy precipitation, and the impact of human induced global warming on storm properties.;The first study is to examine the performance of current climate models on the simulation of the multi-scale temporal variability determined from the observed station precipitation data. The results show that the studied Global Circulation Models/Regional Climate Models (GCMs/RCMs) tend to simulate longer storm duration and lower storm intensity as compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The results also show that these GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with the multi-scale temporal precipitation variability.;The second study investigates the integrated effect of large-scale ocean oscillations including ENSO, PDO, Atlantic Multi-decadal Oscillation (AMO), and North Atlantic Oscillation (NAO) on the multi-scale temporal variability and spatial distribution of heavy precipitation expressed as total precipitation when daily precipitation is larger than 95th percentile (R95) in the western United States using Empirical Orthogonal Function (EOF) analysis. The analysis has shown that the leading modes of R95 variability and the connections between local R95 and Sea Surface Temperature (SST) over Western United States are seasonally dependent. The first EOF mode of summer R95 is associated with AMO. The first two EOF modes of winter R95 are related to an integrated effects of ENSO, PDO, and NAO which explain nearly half (49%) of the spatial and temporal variance in R95 in this region. Additionally, the coupled effects of these three oceanic-atmospheric oscillations on winter R95 are evaluated by investigating the ENSO-R95 responses modulated by a combination of different PDO and NAO phases. The results have implications for predicting the seasonal precipitation extremes for next few decades over the western United States, which may be useful to forecasters and water managers.;In the third study, the potential changes of storm properties including storm duration, inter-storm period, average storm intensity, and within-storm pattern from 10 North American Regional Climate Change Assessment Program (NARCCAP) RCMs with both historical simulations (1968--2000) and future simulations (2038--2070) are evaluated. Results illustrate that NARCCAP RCMs are consistent with observed precipitation in the seasonal variation of storm duration and inter-storm period. The ability to simulate the seasonal trend of average storm intensity varies among locations. Within-storm patterns from RCMs exhibit greater variability than from observed records. Comparisons between historic and future simulations of storm properties indicate that most regions of United States will experience future precipitation projections with shorter storm duration, longer inter-storm period, larger average storm intensity, and unchanged within-storm patterns.;The western United States is undergoing rapidly changing social dynamics, pressure from an expanding population and a greater risk of water shortage and flooding. Gaining better knowledge of how climate changes will impact on the spatiotemporal distribution of precipitation will help us on hydrologic modeling and assessment of uncertainty of water sustainability in this region.
机译:西部山间地区的降水以其时空分布的巨大变化为特征。此外,由于气候变化,降水的时空分布正在改变。本文进行了三项研究,以研究降水的多尺度时间变化,当前气候模式对这种变化的影响,大规模海洋振荡对强降水的影响以及人为引起的全球变暖对降水的影响。第一项研究是从模拟的观测站降水数据确定的多尺度时间变化的模拟上,检查当前气候模型的性能。结果表明,与从观测到的记录相比,研究的全球环流模型/区域气候模型(GCMs / RCMs)倾向于模拟更长的风暴持续时间和更低的风暴强度。大多数GCM / RCM无法产生与夏季风相关的局部对流热传输所引起的高强度夏季风暴。 GCM / RCM模拟的降水时间序列中同时存在年际带和年代际带。但是,这些变化与诸如El Nino / La Nina南方涛动(ENSO)和太平洋年代际涛动(PDO)之类的大规模海洋振荡的模式并不相符。结果还表明,这些GCM / RCM可以通过对数据进行偏差校正和缩小来获取长期的月平均值,但无法模拟包括洪水产生极端事件在内的多尺度降水变化,这表明它们不足以进行关于与多尺度时间降水变化密切相关的洪水和干旱;第二项研究调查了包括ENSO,PDO,大西洋多年代际涛动(AMO)和北大西洋涛动(NAO)在内的大规模海洋振荡的综合影响)使用经验正交函数(EOF)分析,在美国西部日降水量大于95%(R95)时,重降水的多尺度时间变化和空间分布表示为总降水。分析表明,R95变异性的主导模式以及美国西部局部R95与海表温度(SST)之间的联系与季节有关。夏季R95的第一个EOF模式与AMO相关。 R95冬季的前两种EOF模式与ENSO,PDO和NAO的综合效应有关,这解释了该地区R95时空变化的近一半(49%)。此外,通过研究由不同PDO和NAO相组合调制的ENSO-R95响应,评估了这三个海洋-大气振荡对冬季R95的耦合效应。这些结果对于预测美国西部未来几十年的季节性极端降水具有重要意义,这可能对预报员和水管理人员很有用。在第三项研究中,风暴性质的潜在变化包括风暴持续时间,暴风雨间期利用历史模拟(1968--2000)和未来模拟(2038--2070)对北美10个区域气候变化评估计划(NARCCAP)RCM的平均风暴强度和风暴内模式进行了评估。结果表明,NARCCAP RCM与风暴持续时间和风暴间隔期间的季节变化中观测到的降水一致。模拟平均风暴强度的季节性趋势的能力因位置而异。与观察到的记录相比,RCM的风暴内模式具有更大的变异性。历史和未来风暴特征模拟之间的比较表明,美国大部分地区将经历未来的降水预测,风暴持续时间更短,风暴间时间更长,平均风暴强度更大,风暴内模式没有变化。经历着迅速变化的社会动态,不断增长的人口压力以及水资源短缺和洪水的更大风险。更好地了解气候变化将如何影响降水的时空分布,将有助于我们进行水文模拟和评估该地区水可持续性的不确定性。

著录项

  • 作者

    Jiang, Peng.;

  • 作者单位

    University of Nevada, Las Vegas.;

  • 授予单位 University of Nevada, Las Vegas.;
  • 学科 Hydrology.;Climate Change.;Engineering Civil.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 144 p.
  • 总页数 144
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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