Developments in dynamical seasonal forecasting relevant to agricultural management

Recent developments in dynamical seasonal forecasting of potential relevance to agricultural management are discussed. These developments emphasize the importance of using a fully probabilistic approach at all stages of the forecasting process, from the dynamical ocean–atmosphere models used to predict climate variability at seasonal and interannual time scales, through the models used to downscale the global output to finer scales, to the end-user forecast models. The final goal is to create an end-to-end multi-scale (both in space and time) integrated prediction system that provides skilful, useful predictions of variables with socio-economic interest. Multi-model ensemble predictions made with the leading European global coupled climate models as part of the DEMETER (Development of a European Multi-model Ensemble system for seasonal to inTERannual prediction) project are used as an example to illustrate the potential of producing useful probabilistic predictions of seasonal climate fluctuations and of applying them to crop yield forecasting.