论文标题
使用基于潜在高斯的多元二进制响应时间序列的多站点沉淀的建模
Modeling of Multisite Precipitation Occurrences Using Latent Gaussian-based Multivariate Binary Response Time Series
论文作者
论文摘要
开发了一种在多个位置观察到的新的随机模型。建模概念是使用指标函数和多元高斯分布的椭圆形，以表示每日沉淀的关节概率。通过使用此概念，与常用的两态马尔可夫链方法相比，可以大大减少降水发生建模所需的参数数量。随着此参数的减少，在不同位置观察到的每日降水发生过程的时空依赖性的建模不再困难。使用从魁北克省南部十个Raingauges网络获得的降水记录的说明性应用的结果也证明了所提出模型的准确性和可行性。
A new stochastic model for daily precipitation occurrence processes observed at multiple locations is developed. The modeling concept is to use the indicator function and the elliptical shape of multivariate Gaussian distribution to represent the joint probabilities of daily precipitation occurrences. By using this concept, the number of parameters needed for precipitation occurrence modeling can be largely reduced when compared to the commonly used two-state Markov chain approach. With this parameter reduction, the modeling of spatio-temporal dependence of daily precipitation occurrence processes observed at different locations is no longer difficult. Results of an illustrative application using the precipitation record available from a network of ten raingauges in the southern Quebec region, also demonstrate the accuracy and the feasibility of the proposed model.
