SUMMARYThe European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) is described. In addition to an unperturbed (control) forecast, each ensemble comprises 32 10-day forecasts starting from initial conditions in which dynamically defined perturbations have been added to the operational analysis. The perturbations are constructed from singular vectors of a time-evolution operator linearized around the short-rangeforecast trajectory. These singular vectors approximately determine the most unstable phase-space directions in the early part of the forecast period, and are estimated using a forward and adjoint linear version of the ECMWF numerical weather-prediction model. An appropriate norm is chosen, and relationships between the structures of these singular vectors at initial time and patterns showing the sensitivity of short-range forecast error to changes in the analysis are discussed. A methodology to perform a phase-space rotation of the singular vectors is described, which generates hemispheric-wide perturbations and renormalizes them according to analysis-error estimates from the data-assimilation system.The validation of the ensembles is given firstly in terms of scatter diagrams and contingency tables of ensemble spread and control-forecast skill. The contingency tables are compared with those from a perfect-model ensemble system; no significant differences are found in some cases. Brier scores for the probability of European flow clusters are presented, which indicate predictive skill up to forecast-day 8 with respect to climatological probabilities. The dependence of these scores on flow-dependent model errors is also discussed. Finally, ensemble-member skillscore distributions are presented, which confirm the overall satisfactory performance of the EPS, particularly in summer and autumn 1993. In winter, cases of poor performance over Europe were associated with the Occurrence of a split westerly flow with a blocking high and/or a cut-off low in the verifying analysis.' h o cases are studied in detail, one having large ensemble dispersion, the other corresponding to a more predictable situation. The case studies are used to illustrate the range of ensemble products routinely disseminated to ECMWF Member States. These products include clusters of flow types, and probability fields of weather elements.

The entire 7‐year archive of ECMWF operational analysis and forecast data is used to assess the skill of the Centre's model in short‐ and medium‐range forecasting of atmospheric blocking. The assessment covers 7100‐day periods, from 1 December to 10 March of all winters from 1980‐81 to 1986‐87, inclusive. A slightly modified version of the Legenäs and Økland objective zonal index is used to quantify both observed and forecast occurrence of blocking. The study is performed on 500 hPa geopotential height and on Euro‐Atlantic and Pacific blocking separately. It is found that blocking frequency is severely underestimated in medium‐range forecasts; the model is, on average, reasonably skilful if the initial conditions are blocked, but blocking onset is poorly represented if it occurs more than a few days into the forecast. This inability in entering the blocking regime has a substantial impact on the systematic error of the model.

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The European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) is described. In addition to an unperturbed (control) forecast, each ensemble comprises 32 10-day forecasts starting from initial conditions in which dynamically defined perturbations have been added to the operational analysis. The perturbations are constructed from singular vectors of a time-evolution operator linearized around the short-rangeforecast trajectory. These singular vectors approximately determine the most unstable phase-space directions in the early part of the forecast period, and are estimated using a forward and adjoint linear version of the ECMWF numerical weather-prediction model. An appropriate norm is chosen, and relationships between the structures of these singular vectors at initial time and patterns showing the sensitivity of short-range forecast error to changes in the analysis are discussed. A methodology to perform a phase-space rotation of the singular vectors is described, which generates hemispheric-wide perturbations and renormalizes them according to analysis-error estimates from the data-assimilation system.The validation of the ensembles is given firstly in terms of scatter diagrams and contingency tables of ensemble spread and control-forecast skill. The contingency tables are compared with those from a perfect-model ensemble system; no significant differences are found in some cases. Brier scores for the probability of European flow clusters are presented, which indicate predictive skill up to forecast-day 8 with respect to climatological probabilities. The dependence of these scores on flow-dependent model errors is also discussed. Finally, ensemble-member skillscore distributions are presented, which confirm the overall satisfactory performance of the EPS, particularly in summer and autumn 1993. In winter, cases of poor performance over Europe were associated with the Occurrence of a split westerly flow with a blocking high and/or a cut-off low in the verifying analysis.' h o cases are studied in detail, one having large ensemble dispersion, the other corresponding to a more predictable situation. The case studies are used to illustrate the range of ensemble products routinely disseminated to ECMWF Member States. These products include clusters of flow types, and probability fields of weather elements.

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Abstract. In this paper we describe SEAS5, ECMWF's fifth generation seasonal forecast system, which became operational in November 2017. Compared to its predecessor, System 4, SEAS5 is a substantially changed forecast system. It includes upgraded versions of the atmosphere and ocean models at higher resolutions, and adds a prognostic sea-ice model. Here, we describe the configuration of SEAS5 and summarise the most noticeable results from a set of diagnostics including biases, variability, teleconnections and forecast skill. An important improvement in SEAS5 is the reduction of the equatorial Pacific cold tongue bias, which is accompanied by a more realistic El Niño amplitude and an improvement in El Niño prediction skill over the central-west Pacific. Improvements in 2 m temperature skill are also clear over the tropical Pacific. Sea-surface temperature (SST) biases in the northern extratropics change due to increased ocean resolution, especially in regions associated with western boundary currents. The increased ocean resolution exposes a new problem in the northwest Atlantic, where SEAS5 fails to capture decadal variability of the North Atlantic subpolar gyre, resulting in a degradation of DJF 2 m temperature prediction skill in this region. The prognostic sea-ice model improves seasonal predictions of sea-ice cover, although some regions and seasons suffer from biases introduced by employing a fully dynamical model rather than the simple, empirical scheme used in System 4. There are also improvements in 2 m temperature skill in the vicinity of the Arctic sea-ice edge. Cold temperature biases in the troposphere improve, but increase at the tropopause. Biases in the extratropical jets are larger than in System 4: extratropical jets are too strong, and displaced northwards in JJA. In summary, development and added complexity since System 4 has ensured that SEAS5 is a state-of-the-art seasonal forecast system which continues to display a particular strength in the El Niño Southern Oscillation (ENSO) prediction.

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