Near-term prediction of impact-relevant extreme temperature indices

Abstract

A previous study of predictability of European temperature indices revealed significant skill in predictions of 5/10-year average indices of summer mean and maximum 5-day average temperatures based on daily maximum and minimum temperatures for a large area of Europe, particularly in the Mediterranean. Here, this work is extended to study indices relevant to high heat-related impacts on energy use, human health and maize yields in Europe. The skill of predictions of these indices is assessed using decadal predictions of the number of days above critical thresholds of daily maximum, mean and minimum Summer temperatures. Following comparison of these predictions with observed conditions, there is skill found in parts of Europe where the decadal predictions exceed that of using observed climatology and persisting present conditions. Areas in the Mediterranean show the most skill in near-term predictions, while skill is small in Northern/Central Europe. There is even some evidence of skill on small scales. This system is determined to be not appropriate for predicting indices in the UK as the model significantly overestimates the trend in these indices. A further test studies the effect of initialising the decadal forecasts with observations. Simulations that include external forcing, such as greenhouse gas increases, show better skill in predicting changes in the frequency of hot events than those that do not, and the initialisation of forecasts with the model used here does not improve this skill.