Meteorology Expert

---
name: meteorology-expert
version: 1.0.0
description: Expert-level meteorology covering atmospheric dynamics, thermodynamics, synoptic meteorology, mesoscale systems, numerical weather prediction, and climate dynamics.
author: luo-kai
tags: [meteorology, atmosphere, weather, NWP, climate, thermodynamics]
---

# Meteorology Expert

## Before Starting
1. Synoptic, mesoscale, or microscale?
2. Forecasting or research focus?
3. Specific weather phenomenon?

## Core Expertise Areas

### Atmospheric Structure
Troposphere: weather occurs here, temperature decreases with height, 0-12 km.
Stratosphere: temperature increases with height, ozone layer, 12-50 km.
Tropopause: boundary between troposphere and stratosphere.
Standard atmosphere: reference profile of temperature, pressure, density vs altitude.

### Atmospheric Thermodynamics
Dry adiabatic lapse rate: 9.8 K/km for unsaturated air.
Moist adiabatic lapse rate: 4-7 K/km for saturated air.
CAPE: convective available potential energy — thunderstorm intensity indicator.
Skew-T diagram: thermodynamic diagram for atmospheric sounding analysis.
Lifting condensation level: altitude where air parcel reaches saturation.

### Atmospheric Dynamics
Geostrophic wind: balance between pressure gradient and Coriolis force.
Thermal wind: vertical wind shear related to horizontal temperature gradient.
Vorticity: rotation of air parcels, positive cyclonic in Northern Hemisphere.
Jet stream: fast upper-level winds guiding surface weather systems.

### Synoptic Meteorology
Fronts: boundaries between air masses — cold, warm, occluded, stationary.
Cyclones: low pressure systems, convergence at surface, rising air, clouds.
Anticyclones: high pressure, divergence, sinking air, clear skies.
Norwegian cyclone model: development and occlusion of mid-latitude cyclones.

### Numerical Weather Prediction
Primitive equations: Navier-Stokes + thermodynamics + continuity.
Grid models: finite difference or spectral, GFS, ECMWF.
Ensemble forecasting: multiple runs with perturbed initial conditions.
Data assimilation: 4D-Var, EnKF — merge observations into model state.

## Best Practices
- Always consult multiple models when forecasting
- Use ensemble spread as uncertainty indicator
- Understand model limitations and biases
- Combine NWP with climatological knowledge

## Common Pitfalls
| Pitfall | Fix |
|---|---|
| Over-relying on single model | Always compare multiple NWP products |
| Ignoring mesoscale effects | NWP coarse resolution misses local terrain effects |
| CAPE without shear context | High CAPE needs wind shear for severe weather |
| Forgetting Coriolis in dynamics | Essential for large-scale flow patterns |

## Related Skills
- climatology-expert
- oceanography-expert
- physics/fluid-physics-expert