摘要

The El Nino-Southern Oscillation (ENSO) is the most important driver of natural climate variability and is characterized by anomalies in the sea surface temperatures (SST) over the tropical Pacific ocean. It has three phases: neutral, a warming phase or El Nino, and a cooling phase called La Nina. In this research, we modeled the climate under the three phases as a network and characterized its properties. We utilized the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) daily surface temperature reanalysis data from January 1950 to December 2016. A network associated to a month was created using the temperature spanning from the previous month to the succeeding month, for a total of three months worth of data for each network. Each site of the included data was a potential node in the network and the existence of links were determined by the strength of their relationship, which was based on mutual information. Interestingly, we found that climate networks exhibit small-world properties and these are found to be more prominent from October to April, coinciding with observations that El Nino occurrences peak from December to March. During these months, the temperature of a relatively large part of the Pacific ocean and its surrounding areas increase and the anomaly values become synchronized. This synchronization in the temperature anomalies forms links around the Pacific, increasing the clustering in the region and in effect, that of the entire network.

  • 出版日期2018-4