Trajectory adjustment of lagged seasonal forecast ensembles

Seasonal forecasting has became a critical area of development in numerical weather prediction. Reliable forecasts beyond the two week time period are necessary for a number of industrial and societal planning applications and new approaches are being developed to extend the useful range of numerical weather prediction output. We investigate the performance of one such system, the UK Met Office’s GloSea5 system, an ensemble system with the novel feature that ensemble members are initiated in a rolling and staggered manner. Focusing on summer surface temperatures, we show that individual model runs from this system do not exhibit skill beyond the two-week time horizon and indeed substantially under-perform climatological forecasts at longer lead times. However, when combining the ensemble system and applying the Rapid Adjustment of Forecast Trajectories (RAFT) methodology to the individual runs, we show that the combined forecast can achieve performance which is always at least on par with climatology and in many circumstances exhibits modest outperformance.