Keywords
1. Meteorology 2. Data Science 3. Weather Forecasting 4. Climate Analysis 5. Numerical Weather Prediction (NWP) 6. Remote Sensing 7. Satellite Data 8. Atmospheric Physics 9. Machine Learning in Meteorology 10. Statistical Weather Analysis 11. Weather Data Visualization 12. Climate Modeling 13. Data Quality Control 14. Big Data in Weather 15. Predictive Analytics 16. Weather Intelligence 17. Environmental Data Analytics 18. Severe Weather Prediction 19. Renewable Energy Forecasting 20. Urban ClimatologyAnalytics in Meteorology: Data Transformation for Weather Intelligence
authored by: BV Ramana Rao, Surender Singh & V Uma Maheswara RaoLength: 152 mm | Breadth: 22.26 mm | Height: 229 mm | Imprint: NIPA | Weight: 782 GMS
Analytics in Meteorology: Data Transformation for Weather Intelligence bridges the gap between atmospheric science and modern data analytics. In an era of rapid climate change and data abundance, the book shows how to transform vast meteorological datasets—from satellites, ground stations, drones, and citizen science—into actionable insights. Covering atmospheric physics, data acquisition, quality control, statistical analysis, machine learning, visualization, and numerical weather prediction, it offers a unified framework for understanding and forecasting weather and climate. Designed for meteorologists, data scientists, researchers, students, and policymakers, this book equips readers to improve forecast accuracy, strengthen climate assessments, and support informed decision-making. Combining theory, tools, and real-world applications, it provides the essential foundation for harnessing “Weather Intelligence” to meet today’s environmental challenges.
1. Introduction to Meteorology and Data Science
2. Atmospheric Physics and Measurement Principles
3. In Situ Observations
4. Remote Sensing from Ground-based Platforms
5. Satellite Remote Sensing
6. Data Formats, Storage, and Access
7. Meteorological Data Quality Control and Preprocessing
8. Statistical Methods in Meteorological Analysis
9. Advanced Analysis Techniques
10. Visualization of Meteorological Data
11. Numerical Weather Prediction (NWP)
12. Climate Data and Analysis
13. Specialized Applications and Future Trends
14. Challenges, Ethics, and the Future of Meteorological Data Science