Synopsis: This chapter provides information on the design and implementation of mesoscale numerical models. The governing equations of typical mesoscale models are given, as are their numerical approximations. Physical processes such as those involving cloud and precipitation microphysics are represented as simplified functions of model variables. Schemes for the parameterization of these and other relatively complex processes are provided to show basic formulations. Design and implementation issues, such as the size of the model domain, the use of nested grids, and model initialization, are also discussed.

Introduction

The objective of this chapter is to introduce the reader to the basic design and implementation of mesoscale numerical models. As will be demonstrated in the remaining chapters – and perhaps as the reader has already experienced – such models play dual roles as experimental and weather prediction tools. Indeed, some community models, such as the Weather Research and Forecasting (WRF) model, have a built-in functionality that allows for (1) idealized modeling, which employs simplified initial and boundary conditions (ICs, BCs), and for (2) real-data modeling, which employs observationally derived ICs and BCs such that real events can be simulated or predicted. Our treatment herein assumes a fairly generous definition of a mesoscale model so that both approaches can be discussed.