...
首页> 外文期刊>Journal of hydrometeorology >Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes
【24h】

Characterizing and Modeling Temporal and Spatial Trends in Rainfall Extremes

机译:表征和模拟降雨极端时空趋势

获取原文
获取原文并翻译 | 示例
           

摘要

A hierarchical spatial model for daily rainfall extremes that characterizes their temporal variation due to interannual climatic forcing as well as their spatial pattern is proposed. The model treats the parameters of at-site probability distributions for rainfall extremes as "data'' that are likely to be spatially correlated and driven by atmospheric forcing. The method is applied to daily rainfall extremes for summer and winter half years over the Swan-Avon River basin in Western Australia. Two techniques for the characterization of at-site extremes-peaks-over-threshold (POT) analysis and the generalized extreme value (GEV) distribution-and three climatic drivers-the El Nino-Southern Oscillation as measured by the Southern Oscillation index (SOI), the Southern Hemisphere annular mode as measured by an Antarctic Oscillation index (AOI), and solar irradiance (SI)-were considered. The POT analysis of at-site extremes revealed that at-site thresholds lacked spatial coherence, making it difficult to determine a smooth spatial surface for the threshold parameter. In contrast, the GEV-based analysis indicated smooth spatial patterns in daily rainfall extremes that are consistent with the predominant orientation of storm tracks over the study area and the presence of a coastal escarpment near the western edge of the basin. It also indicated a linkage between temporal trends in daily rainfall extremes and those of the SOI and AOI. By applying the spatial models to winter and summer extreme rainfalls separately, an apparent increasing trend in return levels of summer rainfall to the northwest and decreasing trends in return levels of winter rainfall to the southwest of the region are found.
机译:提出了一种日降雨极端值的分层空间模型,该模型描述了由于年际气候强迫引起的时间变化及其空间格局。该模型将降雨极端事件的现场概率分布参数视为可能与空间相关并受大气强迫驱动的“数据”,该方法适用于天鹅湖夏季和冬季半年的每日降雨极端事件。西澳大利亚州的雅芳河流域。两种用于表征现场极值-极值-峰值(POT)分析和广义极值(GEV)分布的技术,以及三种气候驱动因素-厄尔尼诺-南方涛动通过南极涛动指数(SOI),南极涛动指数(AOI)和太阳辐照度(SI)对南半球环形模式进行了研究,对现场极端情况的POT分析表明,缺乏现场阈值空间相干性,难以确定阈值参数的平滑空间表面;相比之下,基于GEV的分析表明,在每日降雨量极端值为与研究区域内风暴径的主要方向以及盆地西缘附近的沿海陡坡的存在保持一致。这也表明每日极端降雨的时间趋势与SOI和AOI的时间趋势之间存在联系。通过分别将空间模型应用于冬季和夏季极端降雨,发现西北地区夏季降雨返回水平有明显的上升趋势,而该地区西南地区冬季降水返回水平有下降的趋势。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号