Spatial extreme value analysis to project extremes of large-scale indicators for severe weather
Spatial extreme value analysis to project extremes of large-scale indicators for severe weather
复制标题
空间极值分析预测恶劣天气大尺度指标的极值
作者：
E. Gilleland;B. Brown;C. Ammann
同时发现上升气流的最大潜在风速（Wmax）和0-6 km风切变（Shear）的高值代表了恶劣天气的有利环境，这为研究未来气候中的恶劣天气提供了一种方法。在这里，我们采用了一个模型的产品，这些变量（WmSh）从美国国家大气研究中心/美国国家环境预测中心重新分析在北美的条件下，他们有极端的能量在空间领域，以项目的主导空间格局WmSh。该方法是基于Hynnan和Tawn的条件极值模型。结果表明，这种技术估计的空间行为WmSh以及，这使得探索可能的变化，随着时间的推移的模式。虽然该模型能够实现用于推断模式中的不确定性的方法，但是使用当前可用的推断方法进行这样的分析是困难的。还探讨了一种变化的方法来研究如何使用这种类型的模型来定性地了解WmSh的空间格局对应于极端的河流流量事件。对田纳西州西北部三条河流的河流流量进行了案例研究，发现墨西哥湾的WmSh平流盛行，而在其他地方，WmSh在这种极端事件中通常很低。© 2013作者。出版社：JohnWiley & Sons，Ltd.
Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events. © 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd.