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Regional climate model evaluations of long-term changes in total precipitation and high precipitation events.

机译:总降水量和高降水量事件长期变化的区域气候模型评估。

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摘要

Extreme events, including precipitation extremes, can have severe impacts on human society and on ecosystems. In the late 20th century, heavy precipitation events tend to occur with increasing frequency or intensity proportion to total rainfall over most land areas in the world. Precipitation, however, is the single most difficult variable to simulate in numerical weather/climate models. There are very limited studies on modeling evaluation of long-term trends in extreme precipitation events over the contiguous U.S.;This study examines the downscaling skills of a state-of-the-art regional climate model, the Climate extension of Weather Research and Forecasting Model (CWRF), in evaluating long-term changes (1982-2008) in total precipitation and high precipitation events (e.g., 75th, 85th, 95th percentiles) over the contiguous U.S. The CWRF, driven by the NCEP-DOE AMIP II Reanalysis (R-2), was simulated for the period 1982-2008 over the contiguous United States. All the 27-yr interannual and interseasonal (half years of warm season: March-August; cold season: September-February) total and high precipitation events were calculated from the observational data and model outputs. The observed and simulated trends for the total and high precipitation events were calculated by using Kendall's tau based slope estimator (Theil-Sen regression), a powerful alternative to the simple least squares linear regression slope. The Mann-Kendall Rank-based nonparametric significance test was applied to evaluate the statistical significance of the trends in the total and high precipitation events. The CWRF not only captured the magnitudes of total and high precipitation evens overall in the contiguous U.S., but simulated their trends well relative to those derived from observations, even in higher-elevated subregions (e.g., the West Coast and some areas of Rocky Mountains), where it is difficult for a model to properly determine precipitation. In general the trends in total and high precipitation events simulated by he model were not as intense as the observed ones. Better agreements between model and observations in both total and high precipitation events and their trends were found in the warm half years (warm seasons: Mar.-Aug.) than in the cold half years (cold seasons: Sep.-Feb.) during 1982-2008. Thus, CWRF shows significant improvements in warm-season convective precipitation relative to many other numerical weather/climate models. It is also noticed that trends in the high precipitation events are highly sensitive to the spatial scale chosen (at least for a case study of the lower-elevated regions from the Midwest (MW) to Illinois (IL), and to central Illinois (CIL) in the contiguous U.S.) from both model and observations.;This is the first study to evaluate a regional climate model's capability in capturing long-term historical trends in precipitation extremes (or high precipitation events) over the contiguous United States. Previously only Kunkel et al. (2002) evaluated a 10-yr (1979-88) heavy precipitation events over the U.S. using the second-generation Regional Climate Model (RegCM2), but did not examine the trends in the heavy precipitation. The findings have important implications on the capabilities of projections of total and extreme precipitation events in the future climate. Our study also provides important information for the capabilities of using this model to assess long-term variations of climatic and hydrologic extremes and hazards (e.g. floods, droughts, etc.) and to support mitigation strategies.
机译:极端事件,包括极端降水,可能对人类社会和生态系统产生严重影响。在20世纪后期,在世界上大多数土地上,强降雨事件的发生频率或强度与总降雨的比例呈上升趋势。但是,降水是在数值天气/气候模型中要模拟的最困难的单个变量。关于美国连续性极端降水事件长期趋势的模型评估的研究非常有限;该研究考察了最新的区域气候模型,天气研究和预报模型的气候扩展的降尺度技巧(CWRF),用于评估美国连续地区总降水量和高降水事件(例如,第75、85、95%百分位数)的长期变化(1982-2008年)由NCEP-DOE AMIP II再分析(R -2),是在美国本土1982-2008年期间进行的模拟。从观测数据和模型输出中计算出所有27年的年际和季节间(暖季的一半年:3月至8月;寒冷的季节:9月至2月)。通过使用基于Kendall基于tau的斜率估算器(Theil-Sen回归),可以计算出总降水量事件和高降水事件的观测趋势和模拟趋势,这是简单最小二乘线性回归斜率的有力替代方案。基于Mann-Kendall秩的非参数显着性检验用于评估总降水事件和高降水事件趋势的统计显着性。 CWRF不仅捕获了连续美国的总降水量和高降水量的均值,而且相对于根据观测得出的趋势,甚至在海拔较高的次区域(例如,西海岸和落基山脉的某些地区),也很好地模拟了它们的趋势。 ,模型很难正确确定降水量。通常,由他的模型模拟的总降水事件和高降水事件的趋势并不像所观察到的那样强烈。在总降水量和高降水事件及其趋势方面,模型和观测值之间的一致性更好,而在温暖的半年(暖季:3月至8月)比寒冷的半年(冷季:9月至2月)好。 1982-2008年。因此,与许多其他数值天气/气候模型相比,CWRF在暖季对流降水方面显示出显着改善。还应注意,高降水事件的趋势对所选的空间尺度高度敏感(至少对于从中西部(MW)到伊利诺伊州(IL)以及伊利诺伊州中部(CIL)的低海拔地区的案例研究),这是第一个评估区域气候模型在捕获连续美国的极端降水(或高降水事件)的长期历史趋势方面的能力的研究。以前只有Kunkel等。 (2002年)使用第二代区域气候模型(RegCM2)评估了美国10年(1979-88年)的强降水事件,但没有研究强降水的趋势。这些发现对未来气候中总降水和极端降水事件的预测能力具有重要意义。我们的研究还为使用此模型评估气候和水文极端事件和灾害(例如洪水,干旱等)的长期变化以及支持缓解策略的能力提供了重要信息。

著录项

  • 作者

    Jia, Wenjing.;

  • 作者单位

    University of Illinois at Urbana-Champaign.;

  • 授予单位 University of Illinois at Urbana-Champaign.;
  • 学科 Atmospheric sciences.;Meteorology.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 195 p.
  • 总页数 195
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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