Cloud and Precipitation Microphysics Principles and Parameterizations [Paperback]

This book provides a background to the fundamental principles of parameterization physics for accurate numerical predictions of cloud and precipitation.This book explains how the parameterization or mathematical representation of complex physics is developed and used for accurate numerical predictions of cloud and precipitation. It presents full derivations of these parameterizations, and, supported by online model codes, allows researchers and students to build parameterization packages at varying levels of complexity.This book explains how the parameterization or mathematical representation of complex physics is developed and used for accurate numerical predictions of cloud and precipitation. It presents full derivations of these parameterizations, and, supported by online model codes, allows researchers and students to build parameterization packages at varying levels of complexity.This book focuses specifically on bin and bulk parameterizations for the prediction of cloud and precipitation at various scales - the cloud scale, mesoscale, synoptic scale, and the global climate scale. It provides a background to the fundamental principles of parameterization physics, including processes involved in the production of clouds, ice particles, liquid water, snow aggregate, graupel and hail. It presents full derivations of the parameterizations, allowing readers to build parameterization packages, with varying levels of complexity based on information in the book. Architectures for a range of dynamical models are given, in which parameterizations form a significant tool for investigating large non-linear numerical systems. Model codes are available online at www.cambridge.org/9780521883382. Written for researchers and advanced students of cloud and precipitation microphysics, this book is also a valuable reference for all atmospheric scientists involved in models of numerical weather prediction.1. Introduction; 2. Foundations of microphysical parameterizations; 3. Cloud lc