Exploring the Influence of Sea Surface Temperature Extremes on Precipitation Extremes Across India's Climate Zones: A Complex Network Approach

ABSTRACT The present study investigates the impact of Sea Surface Temperature (SST) extremes on precipitation extremes in India's six homogeneous climate regions from 1981 to 2020. A wavelet‐based complex network analysis was used to explore the connections between precipitation extremes and SST extremes. The Maximum Overlap Discrete Wavelet Transform (MODWT) technique was employed for time series decomposition to identify these links across different temporal scales. Spearman correlation was then used to determine the relationships between SST extremes and precipitation extremes at the grid level. Complex networks were then constructed for each of India's climate regions, focusing on both positive and negative correlations with various global sea regions. Results reveal that precipitation extremes at shorter time scales are predominantly driven by proximal oceanic regions such as the Bay of Bengal (BOB), Arabian Sea (ARS), and Eastern Indian Ocean (EIO), reflecting strong monsoon–SST coupling through moisture convergence and synoptic convection processes. As the time scale increases, remote SST influences from the Atlantic (NAO, EAO), Pacific (EPO, NPO, SPO), and Southern Hemisphere oceans (SIO, SAO, SOO) become increasingly dominant, highlighting the role of atmospheric teleconnections, jet stream modulation, and cross‐equatorial moisture transport. Interannual scales show the widest and most diverse SST control, whilst decadal‐scale influence is generally weak and region‐specific. The regional analysis demonstrates distinct propagation pathways of SST influence, with West Central India showing consistent multiscale sensitivity, Central Northeast and Northeast India transitioning from local to global control, and South Peninsular India retaining strong regional dominance. These insights underscore the necessity of integrating both regional and global SST indices into forecasting frameworks for improved prediction and climate adaptation strategies in India.

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Publication Details

Journal
International Journal of Climatology
Published
2025-11-02
DOI
https://doi.org/10.1002/joc.70172
Primary Topic
Climate variability and models
Type
article
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article

Exploring the Influence of Sea Surface Temperature Extremes on Precipitation Extremes Across India's Climate Zones: A Complex Network Approach

Litan Kumar Ray, V. M. Reddy
International Journal of Climatology
Climate variability and models
article

Exploring the Influence of Sea Surface Temperature Extremes on Precipitation Extremes Across India's Climate Zones: A Complex Network Approach

Litan Kumar Ray, V. M. Reddy
article en

Abstract

ABSTRACT The present study investigates the impact of Sea Surface Temperature (SST) extremes on precipitation extremes in India's six homogeneous climate regions from 1981 to 2020. A wavelet‐based complex network analysis was used to explore the connections between precipitation extremes and SST extremes. The Maximum Overlap Discrete Wavelet Transform (MODWT) technique was employed for time series decomposition to identify these links across different temporal scales. Spearman correlation was then used to determine the relationships between SST extremes and precipitation extremes at the grid level. Complex networks were then constructed for each of India's climate regions, focusing on both positive and negative correlations with various global sea regions. Results reveal that precipitation extremes at shorter time scales are predominantly driven by proximal oceanic regions such as the Bay of Bengal (BOB), Arabian Sea (ARS), and Eastern Indian Ocean (EIO), reflecting strong monsoon–SST coupling through moisture convergence and synoptic convection processes. As the time scale increases, remote SST influences from the Atlantic (NAO, EAO), Pacific (EPO, NPO, SPO), and Southern Hemisphere oceans (SIO, SAO, SOO) become increasingly dominant, highlighting the role of atmospheric teleconnections, jet stream modulation, and cross‐equatorial moisture transport. Interannual scales show the widest and most diverse SST control, whilst decadal‐scale influence is generally weak and region‐specific. The regional analysis demonstrates distinct propagation pathways of SST influence, with West Central India showing consistent multiscale sensitivity, Central Northeast and Northeast India transitioning from local to global control, and South Peninsular India retaining strong regional dominance. These insights underscore the necessity of integrating both regional and global SST indices into forecasting frameworks for improved prediction and climate adaptation strategies in India.

International Journal of ClimatologyVol. 46(1)
National Institute of Technology Warangal (IN), Indian Institute of Technology Hyderabad (IN)
Openalex Percentile: Top 70%
Climate variability and models
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