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The Shift of Precipitation Maxima on the Annual Maximum Series using Regional Climate Model Precipitation Data.

机译：使用区域气候模式降水数据，年度最大值序列上的最大降水量偏移。

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摘要

Ten regional climate models (RCMs) and atmosphere-ocean generalized model parings from the North America Regional Climate Change Assessment Program were used to estimate the shift of extreme precipitation due to climate change using present-day and future-day climate scenarios. RCMs emulate winter storms and one-day duration events at the sub-regional level. Annual maximum series were derived for each model pairing, each modeling period; and for annual and winter seasons. The reliability ensemble average (REA) method was used to qualify each RCM annual maximum series to reproduce historical records and approximate average predictions, because there are no future records. These series determined (a) shifts in extreme precipitation frequencies and magnitudes, and (b) shifts in parameters during modeling periods. The REA method demonstrated that the winter season had lower REA factors than the annual season. For the winter season the RCM pairing of the Hadley regional Model 3 and the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model had the lowest REA factors. However, in replicating present-day climate, the pairing of the Abdus Salam International Center for Theoretical Physics' Regional Climate Model Version 3 with the Geophysical Fluid-Dynamics Laboratory atmospheric-land generalized model was superior. Shifts of extreme precipitation in the 24-hour event were measured using precipitation magnitude for each frequency in the annual maximum series, and the difference frequency curve in the generalized extreme-value-function parameters. The average trend of all RCM pairings implied no significant shift in the winter annual maximum series, however the REA-selected models showed an increase in annual-season precipitation extremes: 0.37 inches for the 100-year return period and for the winter season suggested approximately 0.57 inches for the same return period. Shifts of extreme precipitation were estimated using predictions 70 years into the future based on RCMs. Although these models do not provide climate information for the intervening 70 year period, the models provide an assertion on the behavior of future climate. The shift in extreme precipitation may be significant in the frequency distribution function, and will vary depending on each model-pairing condition. The proposed methodology addresses the many uncertainties associated with the current methodologies dealing with extreme precipitation.
机译：来自北美区域气候变化评估计划的十个区域气候模型（RCM）和大气-海洋通用模型配对被用于使用当前和未来气候情景来估计由于气候变化导致的极端降水的变化。 RCM在次区域级别上模拟冬季风暴和一日持续时间事件。为每个模型配对，每个建模周期得出年度最大序列；以及年度和冬季。由于没有将来的记录，因此使用可靠性集成平均（REA）方法对每个RCM年度最大序列进行资格评定，以重现历史记录和近似平均预测。这些序列确定了（a）极端降水频率和幅度的变化，以及（b）建模期间参数的变化。 REA方法表明，冬季的REA因子低于年度。在冬季，Hadley区域模型3和地球物理流体动力学实验室大气-土地广义模型的RCM配对具有最低的REA因子。但是，在复制当今气候的过程中，阿卜杜勒斯萨拉姆国际理论物理中心的区域气候模型第3版与地球物理流体动力学实验室大气-陆域广义模型的配对更为出色。使用年度最大值序列中每个频率的降水量以及广义极值函数参数中的频率差异曲线，测量24小时事件中极端降水的变化。所有RCM配对的平均趋势都表明冬季年度最大序列没有明显变化，但是REA选择的模型显示了极端季节降水极端值的增加：100年回归期为0.37英寸，冬季表明大约为相同的退货期限为0.57英寸。极端降水的变化是根据基于RCM的未来70年的预测进行估算的。尽管这些模型没有提供这70年间的气候信息，但是这些模型对未来气候的行为提供了断言。极端降水的变化在频率分布函数中可能很重要，并且会根据每个模型配对条件而变化。所提出的方法论解决了与当前有关极端降水的方法论相关的许多不确定性。

著录项

  • 作者

    Riano, Alejandro.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Engineering Civil.;Water Resource Management.;Hydrology.
  • 学位 M.S.
  • 年度 2013
  • 页码 240 p.
  • 总页数 240
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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