Raghuvanshi et al. (2026) Network Divergence Reveals Predictable Pathways of Extreme Rainfall in Central India

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Geophysical Research Letters
• Year: 2026
• Date: 2026-04-23
• Authors: Akash Singh Raghuvanshi, Ankit Agarwal
• DOI: 10.1029/2026gl121973

Research Groups

Not specified in the provided text.

Short Summary

The study introduces a network-based framework using nonlinear synchronization to predict extreme rainfall in Central India, successfully forecasting over 60% of events exceeding the 95th percentile.

Objective

• To develop a physically grounded, computationally efficient, and operationally actionable framework for the prediction of extreme rainfall events in Central India.

Study Configuration

• Spatial Scale: Central India and the East Coast (including the Bay of Bengal).
• Temporal Scale: Not explicitly specified (focused on monsoon precipitation events).

Methodology and Data

• Models used: Network divergence on directed networks derived from the nonlinear synchronization of extreme events.
• Data sources: High-resolution rainfall data.

Main Results

• Successfully predicted >60% of extreme rainfall events exceeding the 95th percentile in Central India.
• Identified two primary predictive conditions: preceding extreme rainfall over the east coast accompanied by a low-pressure anomaly, and moisture convergence over Central India.
• Determined that the primary drivers are vertically integrated moisture convergence and low-pressure systems propagating west-northwestward from the Bay of Bengal.

Contributions

• Offers a mechanistically interpretable and observationally driven alternative to traditional numerical weather prediction (NWP) models.
• Demonstrates a computationally efficient approach for early warning systems of climate extremes.

Funding

Not specified in the provided text.

Citation

@article{Raghuvanshi2026Network,
  author = {Raghuvanshi, Akash Singh and Agarwal, Ankit},
  title = {Network Divergence Reveals Predictable Pathways of Extreme Rainfall in Central India},
  journal = {Geophysical Research Letters},
  year = {2026},
  doi = {10.1029/2026gl121973},
  url = {https://doi.org/10.1029/2026gl121973}
}