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Abstract. We describe the HadGEM2 family of climate configurations of the Met Office Unified Model, MetUM. The concept of a model "family" comprises a range of specific model configurations incorporating different levels of complexity but with a common physical framework. The HadGEM2 family of configurations includes atmosphere and ocean components, with and without a vertical extension to include a well-resolved stratosphere, and an Earth-System (ES) component which includes dynamic vegetation, ocean biology and atmospheric chemistry. The HadGEM2 physical model includes improvements designed to address specific systematic errors encountered in the previous climate configuration, HadGEM1, namely Northern Hemisphere continental temperature biases and tropical sea surface temperature biases and poor variability. Targeting these biases was crucial in order that the ES configuration could represent important biogeochemical climate feedbacks. Detailed descriptions and evaluations of particular HadGEM2 family memCorrespondence to: G. M. Martin (gill.martin@metoffice.gov.uk) bers are included in a number of other publications, and the discussion here is limited to a summary of the overall performance using a set of model metrics which compare the way in which the various configurations simulate present-day climate and its variability.

[1] Most seasonal forecasts of Atlantic tropical storm numbers are produced using statistical-empirical models. However, forecasts can also be made using numerical models which encode the laws of physics, here referred to as ''dynamical models''. Based on 12 years of re-forecasts and 2 years of real-time forecasts, we show that the socalled EUROSIP (EUROpean Seasonal to Inter-annual Prediction) multi-model ensemble of coupled ocean atmosphere models has substantial skill in probabilistic prediction of the number of Atlantic tropical storms. The EUROSIP real-time forecasts correctly distinguished between the exceptional year of 2005 and the average hurricane year of 2006. These results have implications for the reliability of climate change predictions of tropical cyclone activity using similar dynamically-based coupled ocean-atmosphere models. Citation: Vitart, F., M. R.

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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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and in updates during the autumn, the Met Office predicted a two-inthree chance of colder-than-average temperatures for the forthcoming winter season (2005/06) over Europe. Statements were issued to UK government, media and the public warning of the potential for a winter colder than any since 1995/96. Over subsequent months actions were taken to ensure the effective communication of the forecast. These included briefings with UK government departments, heads of industry and local authority contingency planners. Numerous interviews were provided to press, radio and TV. The forecast for winter 2005/06 was the first Met Office long-range forecast to be disseminated widely across all sectors of the UK.This article discusses how the forecast was formulated from a number of predictive signals and why the sum total of evidence was considered sufficient to raise an 'amber alert' for a colder-than-normal Europe/UK winter season. Some key events surrounding the communication of the forecast are also summarised. A companion paper (Folland et al. 2006; hereafter Part 2) provides more details on the prediction methods used and compares the winter 2005/06 forecast with the actual winter conditions observed over Europe and the UK.

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