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System and Method for Identifying Patterns in and/or Predicting Extreme Climate Events

机译:用于识别和/或预测极端气候事件的模式的系统和方法

摘要

A method and system are provided for medium-range probabilistic prediction of extreme temperature events. Extreme temperatures are measured according to how local temperature thresholds are exceeded on daily timescales to generate a local “Magnitude Index” (MI). A regional MI reflecting the historic temperature intensity, duration and spatial extent of extreme temperature events over all locations within the region is then computed. The regional MI is used to create a synoptic catalog for each of one or more pre-defined weather variables by testing the significance of leading modes in historic atmospheric variability across specified periods of time. Current or recent weather conditions are compared against the synoptic catalog to generate probabilistic predictions of extreme temperature events based the presence of synoptic precursors identified in historic patterns.
机译:提供了一种用于极端温度事件的中程概率预测的方法和系统。根据如何在每日时间尺度上超出本地温度阈值以生成本地“幅值指数”(MI),来测量极端温度。然后计算反映历史温度强度,持续时间和该区域所有位置上极端温度事件的空间范围的区域MI。通过测试特定时间段内历史大气变化的主导模式的重要性,区域MI用于为一个或多个预定义的天气变量中的每一个创建一个天气目录。将当前或最近的天气状况与天气摘要进行比较,以基于历史模式中识别出的天气先兆的存在来生成极端温度事件的概率预测。

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