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.
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