复杂网络方法在东亚地区夏季极端降水研究中的应用

Application of complex network method to summer extreme rainfall in East Asia

  • 摘要: 利用1971-2007年东亚地区夏季(6-8月)逐日格点降水资料,借助事件同步法建立格点之间的非线性相关,构建了极端降水复杂网络,从复杂网络的角度研究了东亚地区极端降水的区域性特征,并利用复杂网络中的关联强度和关联方向信息,从极端降水时、空记忆性的角度构建了预测模型。复杂网络结构特征量表明:北部陆地地区的夏季极端降水空间同步性好,而沿海地区的夏季极端降水空间同步性差。不同地区的格点与周围格点的关联空间范围不一样,沿海地区格点之间远距离连接少,关联空间范围小,北部陆地地区格点之间远距离连接多,关联空间范围较大。极端降水预测模拟结果显示沿海地区的预测准确率一般高于北部陆地地区,其原因是该地区极端降水强度大、降水密集度高且空间格点的平均连接距离小、直接关联性强。研究表明,从时、空记忆的角度构建的预测模型对东亚地区的极端降水具有一定的预测能力,在极端降水研究中存在一定的潜在应用价值。

     

    Abstract: Based on daily rainfall data over East Asia for the period of 1971 to 2007, nonlinear correlations between different grid points are calculated by event synchronization method, and an extreme rainfall network over East Asia is built. By using complex network method, regional characteristics of extreme rainfall over East Asia are analyzed and a dynamics prediction model is constructed. Spatial distribution of degree shows that spatial synchronization is better in northern inland region than in coastal region. It is found that grid points in different regions have different spatial correlation extents, and the northern inland has larger spatial correlation extent than the coastal region. Furthermore, the results show that the prediction accuracy is higher in coastal region than in northern inland region. This is partly because of the short average link distance among grid points, and partly because of the extreme precipitation intensity. The prediction model constructed from the perspective of space and time continuity has the ability to predict extreme rainfall in East Asia on a certain level, and it has some potential application values in the research of extreme rainfall.

     

/

返回文章
返回