论文标题
极端热事件特征的长期空间建模
Long-term Spatial Modeling for Characteristics of Extreme Heat Events
论文作者
论文摘要
越来越多的证据表明,全球变暖在更频繁的温暖日子中表现出来,热浪将变得更加频繁。目前,文献中没有同意对热浪的形式定义。为了避免这场辩论,我们考虑了极端的热量事件,在给定的位置,该事件被很好地定义为超过相关局部阈值的连续数天。 EHES的特征是主要感兴趣的,例如发病率和持续时间,以及在EHE期间阈值高于阈值的平均超过和最大值的幅度。 使用在给定区域中18个位置收集的每日最高温度数据的大约60年的时间序列,我们提出了一个时空模型来研究EHES随时间的特征。该模型可以预测该区域内未观察到的位置的EHE特征的行为。具体而言,我们的方法采用了具有局部阈值的EHES的两国时空模型,其中一个状态定义高于阈值的每日最高温度,另一种状态定义了阈值的温度。我们表明,我们的模型能够恢复感兴趣的EHE特征,并胜过相应的自回归模型,该模型忽略了基于样本外预测的阈值。
There is increasing evidence that global warming manifests itself in more frequent warm days and that heat waves will become more frequent. Presently, a formal definition of a heat wave is not agreed upon in the literature. To avoid this debate, we consider extreme heat events, which, at a given location, are well-defined as a run of consecutive days above an associated local threshold. Characteristics of EHEs are of primary interest, such as incidence and duration, as well as the magnitude of the average exceedance and maximum exceedance above the threshold during the EHE. Using approximately 60-year time series of daily maximum temperature data collected at 18 locations in a given region, we propose a spatio-temporal model to study the characteristics of EHEs over time. The model enables prediction of the behavior of EHE characteristics at unobserved locations within the region. Specifically, our approach employs a two-state space-time model for EHEs with local thresholds where one state defines above threshold daily maximum temperatures and the other below threshold temperatures. We show that our model is able to recover the EHE characteristics of interest and outperforms a corresponding autoregressive model that ignores thresholds based on out-of-sample prediction.