Tim Palmer

Abstract:

Using 10-day forecast 500 mb height data from the last 7 yr, the potential to predict the skill of numerical weather forecasts is discussed. Four possible predictor sets are described. The skill of the predictors are tested, and the regression coefficients derived, on data from six winters, for both regional and hemispheric skill scores. As an independent test, the predictors are also applied separately to the seventh winter period 1986/87. It is concluded that some aspects of the low-frequency component of forecast skill variability can be satisfactorily predicted, though significant high frequency variability remains unpredicted. In discussing the physical mechanisms that underlie the use of these predictors, three important components of forecast skill variability are discussed: the quality of the initial analysis, the intrinsic instability of the flow, and the role of model systematic errors. -from Authors

Abstract:

Folland et al.1 have reported that persistently dry and wet periods of several years in the Sahel have been accompanied by global-scale patterns of sea-surface temperature (SST) anomaly. They also demonstrated that the response of a general circulation model (GCM) of the atmosphere to an observed composite SST difference field between a number of such dry and wet periods showed substantial reduction in Sahel rainfall compared with values from a simulation with climatological SSTs. I examine here the same model's response to the individual components of the composite SST difference field in the Atlantic, Pacific and Indian Oceans. It is found that over the western Sahel, the Atlantic and Pacific fields have a comparable effect in reducing rainfall whereas the Indian Ocean field produces a slight enhancement. Results suggest that, over the eastern Sahel, the Indian Ocean has the dominant role in reducing rainfall. © 1986 Nature Publishing Group.