Improving rainfall forecasting using deep learning data fusing model approach for observed and climate change data

Improving rainfall forecasting using deep learning data fusing model approach for observed and climate change data

Abstract Accurate rainfall forecasting is vital for managing water resources, preventing floods, supporting agricultural activities, and enhancing disaster preparedness. Traditional forecasting methods, such as linear regression, autoregressive models, and time-series analysis, are limited in their...

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Bibliographic Details
Main Authors: Farhan Amir Fardush Sham, Ahmed El-Shafie, Wan Zurina Binti Wan Jaafar, S. Adarsh, Mohsen Sherif, Ali Najah Ahmed
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Rainfall forecasting
Machine learning
Climate change
Model prediction
Deep learning
Online Access:https://doi.org/10.1038/s41598-025-13567-2
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https://doi.org/10.1038/s41598-025-13567-2

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