Climatology & Meteorology

A comprehensive course covering atmospheric thermodynamics, dynamics, cloud physics, climate systems, and weather forecasting with computational examples

Course Overview

This course provides an in-depth exploration of Earth's atmosphere, weather phenomena, and climate systems. We combine rigorous mathematical treatment with computational methods to understand atmospheric processes from first principles.

Topics span from fundamental thermodynamics and fluid dynamics to modern climate modeling and numerical weather prediction. Extensive Python and Fortran examples illustrate key concepts.

Course Structure

Part I: Atmospheric Thermodynamics

Fundamental thermodynamic principles governing atmospheric behavior, including equation of state, stability, adiabatic processes, and atmospheric moisture.

• Composition & Structure

• Ideal Gas Law & Hydrostatic Balance

• First Law of Thermodynamics

• Adiabatic Processes

• Atmospheric Stability

• Water Vapor & Phase Changes

Part II: Atmospheric Dynamics

Equations of motion, forces acting on atmospheric flow, geostrophic wind, vorticity, and wave phenomena in the atmosphere.

• Equations of Motion

• Coriolis & Pressure Gradient Forces

• Geostrophic Wind

• Thermal Wind

• Vorticity & Circulation

• Atmospheric Waves

Part III: Cloud Physics & Precipitation

Microphysics of cloud formation, droplet growth, ice crystal processes, precipitation mechanisms, and severe weather phenomena.

• Cloud Formation & Classification

• Cloud Microphysics

• Warm Rain Processes

• Ice Crystal Physics

• Precipitation Types

• Thunderstorms & Severe Weather

Part IV: Climate Systems

Global circulation patterns, energy balance, ocean-atmosphere coupling, climate variability, and climate change physics.

• Energy Balance & Radiation

• General Circulation

• Ocean-Atmosphere Interaction

• Climate Oscillations (ENSO, NAO)

• Greenhouse Effect & Forcing

• Climate Modeling

Part V: Weather Analysis & Forecasting

Observational techniques, data assimilation, numerical weather prediction, ensemble forecasting, and modern forecasting methods.

• Weather Observations & Instruments

• Weather Maps & Analysis

• Data Assimilation

• Numerical Weather Prediction

• Ensemble Forecasting

• Forecast Verification

Part VI: Paleoclimatology

Earth's climate history from ice cores, sediments, and other proxies. Understanding past climates to inform future projections.

• Climate Proxies (Ice Cores, Sediments)

• Milankovitch Cycles

• Quaternary Ice Ages

• Deep Time Climate

• Holocene Climate Variability

• Abrupt Climate Changes

Part VII: Extreme Weather Events

Physics and impacts of tropical cyclones, severe storms, heat waves, floods, and droughts.

• Tropical Cyclones & Hurricanes

• Severe Thunderstorms & Tornadoes

• Heat Waves & Heat Stress

• Floods (Flash, River, Coastal)

• Droughts & Water Scarcity

• Extreme Precipitation

Part VIII: Climate Change Science

Observed changes, attribution, projections, impacts, and responses to anthropogenic climate change.

• Observed Climate Changes

• Attribution Science

• Carbon Cycle & Emissions

• Future Projections (SSP Scenarios)

• Climate Impacts & Tipping Points

• Mitigation & Adaptation

Video Lectures

158 Video Lectures from 5 University Series

Curated lecture collections spanning introductory to advanced topics:

Yale GG 140 (36 lectures)

Atmosphere, ocean, climate change — Prof. Ronald Smith

UH ATMO 620 (21 lectures)

Physical meteorology, cloud microphysics — Prof. Giuseppe Torri

NPTEL Monsoon (42 lectures)

Monsoon dynamics, ENSO, prediction — IIT

Dynamic Meteorology (35 lectures)

Forces, scale analysis, vorticity — Prof. Richard Rood

Weather & Climate (24 lectures)

Beginner-friendly intro — Mel Strong

Watch All 158 Lectures →

Computational Resources

Python Programs

Interactive Python examples for atmospheric calculations, data visualization, and analysis:

• Spectral atmospheric model
• Atmospheric stability analysis (CAPE/CIN)
• Skew-T log-p thermodynamic diagrams

View Python Programs →

Fortran Numerical Models

High-performance Fortran codes for numerical weather prediction:

• 3D primitive equations model (WRF-style)
• 2D shallow water equations solver
• Operational-scale NWP implementations

View Fortran Models →

Prerequisites

Mathematics

• Vector calculus (div, grad, curl)
• Partial differential equations
• Numerical methods
• Statistical analysis

Physics

• Classical thermodynamics
• Fluid mechanics
• Radiation physics
• Basic electromagnetism

Learning Outcomes

Upon completing this course, you will be able to:

✓ Apply thermodynamic principles to analyze atmospheric stability and processes
✓ Understand and derive the equations governing atmospheric motion
✓ Explain cloud formation, precipitation mechanisms, and severe weather
✓ Analyze global climate patterns and climate change physics
✓ Interpret weather maps and understand forecasting methods
✓ Implement numerical models for atmospheric simulation
✓ Process and analyze meteorological data using computational tools