Joint probability analysis for estimation of extremes

2008 ◽  
Vol 46 (sup2) ◽  
pp. 246-256 ◽  
Author(s):  
Peter J. Hawkes
Author(s):  
Shanshan Tao ◽  
Zhifeng Wang ◽  
Ri Zhang ◽  
Sheng Dong

Co-occurrence probability analysis of sea ice between adjacent areas is very helpful for the hazard prevention and protection strategy making of coastal and offshore engineering. Yingkou and Huludao with similar latitudes are located on the opposite sides of Liaodong Bay of China. Their sea ice conditions are both apparent in winter and early spring, so it is useful to study on the co-occurrence situations of sea ice conditions between these two areas. Based on the annual maximum sea ice thickness of Yingkou and Huludao observation stations, the co-occurrence probability analysis of sea ice thickness is conducted. The joint probability distributions of sea ice thickness between these adjacent areas are constructed by using univariate maximum entropy distributions and four bivariate copulas. Both marginal curve fittings are very well, and the model determined by Gumbel-Hougaard copula describes the bivariate sea ice thickness data best. Then different cases of co-occurrence probabilities of sea ice thickness between Yingkou and Huludao are presented, and they can provide references to the hazard protection of the coastal and offshore structures between these two areas.


2013 ◽  
Vol 726-731 ◽  
pp. 833-841 ◽  
Author(s):  
Liang Pang ◽  
Xuan Chen ◽  
Yu Long Li

The sea state of the South China Sea is influenced by tropical cyclone obviously. It is important to carry out the long-term prediction and probability analysis of typhoon wind, wave height and wave period for the coastal and offshore engineering. In this paper the measured wind and wave data during typhoon processes from 1964-1989 are used to predict the long-term extreme sea states by using Grey Markov Chain Model. And the joint probability analysis of extreme wave height with concomitant wave period and wind speed is performed by using Multivariate Compound Extreme Distribution model which involves typhoon occurrence frequency and corresponding joint probability distribution of typhoon induced extreme sea environmental events. The proposed model shows that the mean value of typhoon occurring frequency per year plays the significant role in long term prediction of typhoon induced joint return values of extreme sea events.


2019 ◽  
Vol 98 (3) ◽  
pp. 1051-1089 ◽  
Author(s):  
Panagiota Galiatsatou ◽  
Christos Makris ◽  
Panayotis Prinos ◽  
Dimitrios Kokkinos

2020 ◽  
Vol 215 ◽  
pp. 107879
Author(s):  
Guilin Liu ◽  
Yanhui Yu ◽  
Yi Kou ◽  
Xiaozhen Du ◽  
Longzhi Han ◽  
...  

2020 ◽  
Vol 30 ◽  
pp. 100279 ◽  
Author(s):  
Andreia F.S. Ribeiro ◽  
Ana Russo ◽  
Célia M. Gouveia ◽  
Carlos A.L. Pires

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