On the use of generalized linear models for interpreting climate variability

Many topical questions in climate research can be reduced to either of two related problems: understanding how various different components of the climate system affect each other, and quantifying changes in the system. This article aims to justify the addition of generalized linear models to the climatologist's toolkit, by demonstrating that they offer an intuitive and flexible approach to such problems. In particular, we provide some suggestions as to how 'typical' climatological data structures may be represented within the GLM framework. Recurring themes include methods for space-time data and the need to cope with large datasets. The ideas are illustrated using a dataset of monthly U.S. temperatures. Copyright (c) 2005 John Wiley & Sons, Ltd.