Forecast quality of climate extreme predictions and its relevance for climate services

The forecast quality of multi-model seasonal-to-decadal climate predictions, as measured by metrics of, among others, accuracy and reliability, has been traditionally estimated considering time-average products and products for event thresholds that do not target the occurrence of unusual events of either monthly or seasonal duration. However, there is an increasing interest in some user communities for products that represent extreme and unusual events. This presentation will discuss the differences in forecast quality between traditional forecast products, like mean seasonal temperature, and products for intraseasonal extremes (e.g., those measured with the 95th percentile of high-frequency temperature over periods like a month or a season) and monthly and seasonal unusual events (such as the frequency of exceeding the 90th percentile of the daily climatological distribution of temperature at a given time of the year). The results will be discussed in the context of their implications to address a number of user requirements from different sectors. The relevance of the forecast quality estimated from hindcast sets and the role of the observational uncertainty will be discussed when delivering forecast products in a climate service context. The implications of this work for the standardisation of climate services based on climate predictions will also be discussed.