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Copula-Based Hazard Risk Assessment of Winter Extreme Cold Events in Beijing

机译:基于Copula的北京冬季严寒事件危险性评估

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Extreme cold events (ECEs) have occurred more frequently over the last few winters in China, associated with large losses of human life and increasing costs. Here, copulas are used to establish a bivariate copula distribution model for ECE variables of duration and intensity, based on observed daily surface air temperatures in winter from 1978 to 2015 at 20 meteorological stations in Beijing. We demonstrate that durations of ECEs follow Weibull distributions, while their intensities fit a generalized extreme value distribution at most stations. The Gumbel–Hougaard copula best described the relationship between duration and intensity of ECEs at most stations. The joint and conditional return periods based on the bivariate copula described both ECE frequency and the corresponding hazard risk. A high risk was calculated for northern and western areas of Beijing, while a lower risk was calculated for urban and southeastern areas. Although the risk of a low temperature event of greater than 3 days with intensity in the range from ?12 °C to ?15 °C decreased, the risk of extreme low temperature events with durations greater than 2 days and intensity lower than ?15 °C increased over the last 18 years. These probabilistic properties provide useful information for both climate change and hazard risk assessments.
机译:在过去的冬季中,极端寒冷事件(ECE)的发生频率更高,这与人类生命的重大损失和成本增加有关。在这里,根据1978年至2015年冬季在北京20个气象站观测到的冬季地面日气温,使用copulas建立持续时间和强度的ECE变量的双变量copula分布模型。我们证明,ECE的持续时间服从Weibull分布,而其强度适合大多数站点的广义极值分布。 Gumbel-Hougaard copula最能描述大多数站点的ECE持续时间和强度之间的关系。基于双变量copula的联合和有条件返回期描述了ECE频率和相应的危险风险。北京北部和西部地区的风险较高,而城市和东南部地区的风险较低。尽管强度在?12°C至?15°C之间的情况下,发生低温事件超过3天的风险降低了,但持续时间超过2天且强度低于?15°的极端低温事件的风险降低了在过去的18年中,C的增加。这些概率特性为气候变化和灾害风险评估提供了有用的信息。

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