A database containing sub-seasonal to seasonal forecasts from 11 operational 30 centres is available to the research community and will help advance our understanding of 31 the sub-seasonal to seasonal time range.Abstract 51 52Demands are growing rapidly in the operational prediction and applications communities for 53 forecasts that fill the gap between medium-range weather and long-range or seasonal 54

Seasonal forecasting systems, and related systems for decadal prediction, are crucial in the development of adaptation strategies to climate change. However, despite important achievements in this area in the last 10 years, significant levels of skill are only generally found over regions strongly connected with the El Niño–Southern Oscillation. With the aim of improving the skill of regional climate predictions in tropical and extratropical regions from intraseasonal to interannual time scales, a new Met Office global seasonal forecasting system (GloSea4) has been developed. This new system has been designed to be flexible and easy to upgrade so it can be fully integrated within the Met Office model development infrastructure. Overall, the analysis here shows an improvement of GloSea4 when compared to its predecessor. However, there are exceptions, such as the increased model biases that contribute to degrade the skill of Niño-3.4 SST forecasts starting in November. Global ENSO teleconnections and Madden–Julian oscillation anomalies are well represented in GloSea4. Remote forcings of the North Atlantic Oscillation by ENSO and the quasi-biennial oscillation are captured albeit the anomalies are weaker than those found in observations. Hindcast length issues and their implications for seasonal forecasting are also discussed.

We compare the performance of the Met Office's ocean–atmosphere coupled general circulation model (CGCM) seasonal prediction system with that of an atmosphere‐only system (AGCM). The CGCM and AGCM systems share the same atmospheric component and the performance comparison therefore provides insight into the skill benefits available from coupling atmosphere and ocean models. In this study, the AGCM is forced with predicted sea surface temperature (SST) based on persistence of prior observed SST anomalies. The analysis uses 43‐yr, nine‐member ensemble hindcast data sets generated with both systems as part of the European Union project DEMETER. Results are focused on global and regional comparisons of long‐term skill for probabilistic prediction of 2‐m temperature in the upper tercile, and on selected case studies for the tropics and Europe. Performance assessments using relative operating characteristic scores, Brier skill scores and the resolution and reliability terms of the Brier score decomposition are contrasted. The largest CGCM benefits are found in tropical regions, where benefits to both resolution (essentially ‘event detection’) and to reliability (essentially ‘calibration’ of the forecast probabilities) are demonstrated. Improvements to reliability are found to be substantially greater than improvements to resolution. Regional assessments show benefits, as expected, in the tropical east Pacific, from improved prediction of SST variability associated with the El Niño Southern Oscillation (ENSO). However, substantial benefits are also seen throughout the tropical belt in seasons associated with the peak and decay of ENSO activity. Such benefits appear associated with representation of lagged teleconnection responses to ENSO in the tropical Atlantic and Indian Oceans. In the extratropics, CGCM improvements to reliability are also substantial, although benefits to resolution (assessed over large regions) appear negligible. Two classes of benefit are described. First, advantages from improved ENSO predictions appear to benefit skill in the North Pacific and North American regions, through teleconnection responses. Secondly, there is evidence of benefits from representation of coupled processes over the North Atlantic. In particular, CGCM skill benefits for prediction of spring season temperature in the European region appear to derive, in part, from coupled model representation of linkage between a well‐documented tripole pattern in North Atlantic SST anomalies and the North Atlantic oscillation. This result provides encouraging evidence that use of CGCMs offers prospects for improving seasonal prediction in the extratropics through representation of coupled ocean–atmosphere processes in extratropical ocean basins, as well as through indirect impacts from improved prediction of ENSO and associated teleconnections.

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