Weather Intelligence and Analytics: Response Management in Agriculture

This book is a practical guide to building and using weather intelligence for resilient, profitable food systems. It begins with meteorological fundamentals tailored to agriculture and allied sectors, explaining how temperature, humidity, radiation, wind, and rainfall drive crop growth, disease risk, and livestock comfort. It then shows how to acquire high-quality data from automatic weather stations, satellites, and farm-scale sensorsand manage it in robust databases for analysis at field to regional scales. Readers learn what classical statistical methods can (and cannot) do in non-stationary, extreme-prone climates, and how AI/ML approaches add value with interpretable, operational models. A dedicated section on IoT and real-time monitoring demonstrates continuous situational awareness for precision agriculture.

The book translates weather signals into concrete decisions for crops and livestock: sowing windows, irrigation and fertigation timing, disease/pest advisories, and heat-stress mitigation. Remote sensing and GIS workflows deliver risk maps and yield outlooks, while decision support and response management frameworks turn forecasts into on-farm actions using risk matrices and cost-loss analysis. Regional applications and sectoral variations illustrate early-warning systems across diverse value chains. The final chapter looks ahead to innovation and policyopen standards, ethical AI, and sustainability incentivesoffering templates that are India-aware yet globally adaptable.