MESOSCALE METEOROLOGY
Synthesizes the fundamentals of atmospheric dynamics, thermodynamics and microphysics to explain the theory behind the structure, evolution and prediction of microscale, mesoscale and cloud scale weather. Learn the dynamics, and thermodynamics of mesoscale, fogs, cumulus, and severe storms (including tornadoes), mountain meteorology and convective tropical weather systems (including hurricanes and typhoons) and application of multi-scale numerical methods and models for analysis and prediction.
Prerequisites & course information
Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Spring 2026 Learning Outcomes: 1. Synthesize fundamentals of atmospheric dynamics and thermodynamics to develop a state-of-the-art understanding of the theory behind how weather systems are formed, maintained, and evolve. Audience: Graduate 2. Apply adjustment theory to understanding of multiscale weather structures. Audience: Graduate 3. Analyze raw data and numerical prediction products directly available in real time or archived on the Internet to predict mesoscale and cloud scale weather. Audience: Graduate 4. Apply unconventional state-of the art observation tools, including ground- based, surface-based and mobile Radar, Lidar, aircraft, and satellite observational systems to diagnose and predict weather systems. Audience: Graduate 5. Identify clues regarding the substructure of weather, that conventional observations have neither the temporal or special resolution to resolve. Audience: Graduate 6. Recognize how data assimilation methods help build the unresolved structures into an analysis through marriage of numerical models, conventional and unconventional data. Audience: Graduate 7. Communicate diagnosis of current weather and forecasts of future weather to both scientific and broad audiences. Audience: Graduate Learning Outcomes: 1. Synthesize fundamentals of atmospheric dynamics and thermodynamics to develop a state-of-the-art understanding of the theory behind how weather systems are formed, maintained, and evolve. Audience: Graduate 2. Apply adjustment theory to understanding of multiscale weather structures. Audience: Graduate 3. Analyze raw data and numerical prediction products directly available in real time or archived on the Internet to predict mesoscale and cloud scale weather. Audience: Graduate 4. Apply unconventional state-of the art observation tools, including ground- based, surface-based and mobile Radar, Lidar, aircraft, and satellite observational systems to diagnose and predict weather systems. Audience: Graduate 5. Identify clues regarding the substructure of weather, that conventional observations have neither the temporal or special resolution to resolve. Audience: Graduate 6. Recognize how data assimilation methods help build the unresolved structures into an analysis through marriage of numerical models, conventional and unconventional data. Audience: Graduate 7. Communicate diagnosis of current weather and forecasts of future weather to both scientific and broad audiences. Audience: Graduate
Sources
- Course catalogue ↗2026-2027