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首页> 外文期刊>Journal of Climate >Track-pattern-based model for seasonal prediction of tropical cyclone activity in the western North Pacific.
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Track-pattern-based model for seasonal prediction of tropical cyclone activity in the western North Pacific.

机译：基于轨迹模式的北太平洋西部热带气旋活动季节预测模型。

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Skillful predictions of the seasonal tropical cyclone (TC) activity are important in mitigating the potential destruction from the TC approach/landfall in many coastal regions. In this study, a novel approach for the prediction of the seasonal TC activity over the western North Pacific is developed to provide useful probabilistic information on the seasonal characteristics of the TC tracks and vulnerable areas. The developed model, which is termed the "track-pattern-based model," is characterized by two features: (1) a hybrid statistical-dynamical prediction of the seasonal activity of seven track patterns obtained by fuzzy c-means clustering of historical TC tracks and (2) a technique that enables researchers to construct a forecasting map of the spatial probability of the seasonal TC track density over the entire basin. The hybrid statistical-dynamical prediction for each pattern is based on the statistical relationship between the seasonal TC frequency of the pattern and the seasonal mean key predictors dynamically forecast by the National Centers for Environmental Prediction Climate Forecast System in May. The leave-one-out cross validation shows good prediction skill, with the correlation coefficients between the hindcasts and the observations ranging from 0.71 to 0.81. Using the predicted frequency and the climatological probability for each pattern, the authors obtain the forecasting map of the seasonal TC track density by combining the TC track densities of the seven patterns. The hindcasts of the basinwide seasonal TC track density exhibit good skill in reproducing the observed pattern. The El Nino-/La Nina-related years, in particular, tend to show a better skill than the neutral years.Digital Object Identifier http://dx.doi.org/10.1175/JCLI-D-11-00236.1
机译：对季节性热带气旋（TC）活动的熟练​​预测对于减轻许多沿海地区TC进近/登陆的潜在破坏非常重要。在这项研究中，开发了一种预测北太平洋西部季节性TC活动的新颖方法，以提供有关TC径迹和脆弱地区的季节性特征的有用的概率信息。所开发的模型称为“基于轨迹模式的模型”，其特征是具有两个特征：（1）对通过模糊 c -平均历史TC径迹的聚类和（2）一种技术，使研究人员能够构建整个盆地季节性TC径迹密度的空间概率预测图。每种模式的混合统计动态预测是基于该模式的季节性TC频率与国家中心的动态预测的季节性均值关键预测变量之间的统计关系。五月份的环境预测气候预报系统。留一法交叉验证显示了良好的预测技能，后验与观测值之间的相关系数在0.71至0.81之间。利用每种模式的预测频率和气候概率，作者通过结合七个模式的TC径迹密度获得了季节性TC径迹密度的预测图。流域范围的季节性TC径迹密度的后兆在再现观测模式方面显示出良好的技巧。与厄尔尼诺/拉尼娜有关的年份尤其比中性年份显示出更好的技能数字对象标识符http://dx.doi.org/10.1175/JCLI-D-11-00236.1

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