Next-Gen Weather Forecasting: Deep Learning and Data Analysis

This book delivers an end-to-end, science-driven methodology for next-generation weather forecasting by integrating deep learning methods with physically based climate models. This book proposes a hybrid model incorporating multimodal data fusion, temporal sequence learning, and physics-constrained neural networks to improve forecast accuracy and credibility by a substantial margin.Using ground station, satellite, global reanalysis system, and IoT-based data, the framework resolves the spatial and temporal disconnects plaguing traditional prediction systems.

Autorentext
Saptarshi Mondal, B.Tech CSE (AIML) 3rd year student at Adamas University, has published a Springer paper on AI for disabled assistance. Rupsha Roy, B.Sc (Hons) Agriculture 3rd year student at Adamas University, focuses on climate-resilient farming. Both collaborate on AI-driven weather forecasting research.