印度各气候区气象数据的递归分析
Recurrence analysis of meteorological data from climate zones in India
AI总结：
该研究利用1948—2022年温湿度数据和滑动窗口递归分析，揭示印度不同气候区动力学复杂性的时空转变及其与ENSO和印度夏季风的关联。
摘要：
我们提出了一项关于印度各地（包括喜马拉雅地区、沿海地区、印度中部和东北部）气候动力学背后时空模式的研究。我们试图利用1948—2022年的温度和相对湿度数据，捕捉这些地点动力学复杂性的变化。通过在数据集上采用滑动窗口分析，从重构的相空间动力学中估计基于递归的度量，我们研究了不同空间位置的气候变率。该研究揭示了印度各地潜在动力学复杂性的变化及其异质性。我们发现，几乎所有地点的温度数据都在1972—1979年前后显示出向更不规则、更具随机性动力学的转变，并在2000年以后转回更规则的动力学。这些模式与已报道的、和强及中等强度ENSO事件相关的气候及印度夏季风转变相互关联，并证实了其相关的区域变率。
英文摘要：
We present a study on the spatio-temporal pattern underlying the climate dynamics in various locations spread over India, including the Himalayan region, coastal region, central and northeastern parts of India. We try to capture the variations in the complexity of their dynamics derived from temperature and relative humidity data from 1948-2022. By estimating the recurrence-based measures from the reconstructed phase space dynamics using a sliding window analysis on the data sets, we study the climate variability in different spatial locations. The study brings out the variations in the complexity of the underlying dynamics as well as their heterogeneity across the locations in India. We find almost all locations indicate shifts to more irregular and stochastic dynamics for temperature data around 1972-79 and shifts back to more regular dynamics beyond 2000. These patterns correlate with reported shifts in the climate and Indian Summer Monsoon related to strong and moderate ENSO events and confirm their associated regional variability.
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