Paper
11 October 2024 Analysis of the nonlinear behaviour of rainfall over Kerala
Parvathy M., Parvathi Ashok, Dhanya Madhu
Author Affiliations +
Proceedings Volume 13276, Second International Conference on Current Trends in Physics and Photonics (ICCTPP 2024); 132760S (2024) https://doi.org/10.1117/12.3044611
Event: 2nd International Conference on Current Trends in Physics and Photonics (ICCTPP 2024), 2024, Pune, India
Abstract
In the current era of climate change, variability in rainfall patterns is an important research topic. This is significant in the context of extreme weather events and disasters, as well as in the context of the availability of usable water for communities. The current study presents an investigation into the nonlinear characteristics of rainfall over Kerala, India. The majority of rainfall received over Kerala is during the summer monsoon season (from June to September). However, a good amount of rainfall is obtained during the winter monsoon which is from October to December, as well as during the pre-monsoon season. Here the technique of correlation dimension is utilized to study nonlinear systems exhibiting intricate interdependencies over time. By calculating a value known as correlation dimension, if it is increasing with a parameter called embedding dimension, it would reveal the occurrence of complexity and unpredictability in the rainfall patterns. Otherwise, if correlation dimension stabilizes beyond a certain point, it would suggest that the rainfall dynamics settle into a more stable and potentially predictable pattern. The findings of this analysis revealed that if the embedding dimension increases, the correlation dimension also increases, indicating the existence of complexity and unpredictability in the rainfall pattern.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Parvathy M., Parvathi Ashok, and Dhanya Madhu "Analysis of the nonlinear behaviour of rainfall over Kerala", Proc. SPIE 13276, Second International Conference on Current Trends in Physics and Photonics (ICCTPP 2024), 132760S (11 October 2024); https://doi.org/10.1117/12.3044611
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Rain

Complex systems

Phase reconstruction

Stochastic processes

Reconstruction algorithms

Autocorrelation

Dynamical systems

RELATED CONTENT


Back to Top