# Contents

## Idea

This page is about meteorology, the study of the atmosphere and short term weather forecasting.

## Details

### Scales

Meteorology is subdivided into specialist field concentrating on phenomena at certain length scales $L$. There are different classifications, a simple one is this:

• microscale: $\lt$ 20 km

• mesoscale: 20 km $\lt$ L $\lt$ 1000 km

• synoptic (large) scale: L $\gt$ 1000 km

### Forecast Validation

Forecast validation is an important topic in meteorology, since a huge part of the subject is concerned with prediction more or less extraordinary weather events. For more details, see

• I. T. Jolliffe and David B. Stephenson: Forecast verification: a practitioner’s guide in atmospheric science (John Wiley and Sons, 2003)

## Computational and Implementation Issues

Computational meteorology relies heavily on Computational fluid dynamics.

### Parameterization

Numerical weather models? are usually grid models?, so that there are usually a lot of important processes that cannot be incorporated into the model directly, because they evolve on a sub-grid scale. Therefore, these processes are approximated by additional parameetrizations, that are influences that act on the model on each grid and depend on a certain set of parameters. For more details, see

• David J. Stensrud: Parameterization schemes: Keys to Understand Numerical Weather Prediction Models (Camebridge 2007)

## References

### Introductory Textbooks

• C.Donald Ahrens: Meteorology Today (Brooks Cole; 9 edition (July 2, 2008)

### Computational Meteorology and Weather Models

• Wilford Zdunkowski and Andreas Bott: Dynamics of the Atmosphere: A Course in Theoretical Meteorology (Cambridge University Press (April 28, 2003)

### Organizations

• UCAR, the University Corporation for Atmospheric Research provides for example software and data, like NetCFD

category: area of research