Sonone Rupali, Gupte Neelima
Department of Physics, Indian Institute of Technology Madras, Chennai 600036, India.
Chaos. 2024 Jul 1;34(7). doi: 10.1063/5.0203082.
Climate networks based on surface air temperature data are analyzed to identify distinct signatures of tropical cyclones, which appear in the Indian Ocean. These networks, which are percolating networks, show an abrupt phase transition in the order parameter and the susceptibility during cyclonic events. The behavior seen is compared for the months October-November 2016, when three successive cyclones, viz., cyclone Kyant, cyclone Nada, and cyclone Vardah, were seen, and compared with a year where a single cyclone, cyclone Ockhi, was seen in December 2017. All these cyclones were seen in the Bay of Bengal. The microtransitions, i.e., the locations of jumps in the order parameter, for these two cases show distinct patterns. The signatures of the cyclones can be seen in other quantities like the node degrees and their geographic distributions and other network characterizers. We also compare these with a cyclone, cyclone Ashoba (2015), seen in the Arabian Sea where cyclones are rarer. The networks also show the signatures of precursor behavior, which has implications for further analysis.
基于地表气温数据的气候网络被分析,以识别出出现在印度洋的热带气旋的独特特征。这些网络是渗流网络,在气旋事件期间,序参量和磁化率会出现突然的相变。对2016年10月至11月期间的情况进行了比较,当时出现了三个连续的气旋,即气旋“坚特”、气旋“纳达”和气旋“瓦德赫”,并与2017年12月出现单个气旋“奥奇”的年份进行了比较。所有这些气旋都出现在孟加拉湾。这两种情况下的微观转变,即序参量中的跳跃位置,呈现出不同的模式。气旋的特征可以在其他量中看到,如节点度及其地理分布以及其他网络特征量。我们还将这些与在阿拉伯海出现的气旋“阿绍巴”(2015年)进行比较,阿拉伯海的气旋较为罕见。这些网络还显示出先兆行为的特征,这对进一步分析具有启示意义。