Seasonal Space–Time Models for Climate Systems

A class of seasonal space–time models for general lattice systems is proposed. Covariance properties of spatial first-order models are studied. Estimation approaches in time series analysis are adopted and forecasting techniques using the seasonal space–time models are discussed. The models are applied to 516 consecutive fields of monthly averaged 500 mb geopotential heights over a 10 × 10 lattice in the extra-tropical northern hemisphere for the purpose of understanding the underlying statistical structure. It is found that space–time models with instantaneous spatial component give the best fit compared to other models in terms of maximizing the conditional likelihood function. The models are potentially useful for assessing the consistency of outputs from laboratory-based numerical models with field observations. Forecasting ability of the seasonal space–time models is also investigated. This revised version was published online in June 2006 with corrections to the Cover Date.