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

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.

In this article the concept of weather regimes is used to assess the flow-dependent skill of the European Centre for Medium-range Weather Forecast (ECMWF) ensemble predictions at the late medium-range. The flow patterns leading to more or less accurate predictions are identified and the variations of skill in these situations are quantified. The focus is on the Euro-Atlantic sector during the extended winter period when the atmospheric regime structure is most pronounced. Verification results show that, in the medium range, forecasts initiated in the negative phase of North Atlantic Oscillation (NAO−) are the most skillful. For these forecasts the ensemble spread over Europe is lower than average, showing that the ensemble spread provides useful information about the error of the ensemble-mean forecast. The performance of the ensemble is further assessed by stratifying the cases according to their initial conditions, as well as by their accuracy at forecast day 10. Results indicate that the least skillful predictions are mainly associated with missing the transitions to a blocking regime circulation. Forecasts also underestimate the blocking persistence, whereas they overestimate the persistence of zonal flows. Transitions to a positive phase of the NAO are also overrepresented.

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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 ENSO amplitude and an improvement in ENSO prediction skill over the central-west Pacific. Improvements in two-metre temperature skill are also clear over the tropical Pacific. 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 two-metre 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 two-metre 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 summer. In summary, development and added complexity since System 4 has ensured SEAS5 is a state-of-the-art seasonal forecast system which continues to display a particular strength in ENSO prediction.

No abstract

The European summer of 2003 is used as a case study to analyze the land surface role in augmenting the local temperature anomalies. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) analysis and the 40-yr ECMWF Re-Analysis (ERA-40) climate, it is shown that in the months preceding the extreme summer events, positive anomalies in the surface shortwave radiation and a large precipitation deficit indicated an impending dry summer in early June. The use of soil water analysis values as possible predictors for drought is currently limited by the systematic attenuation of its seasonal cycle. Several numerical simulations with the ECMWF atmospheric model have been used to explore the atmospheric model sensitivity to the initial soil water conditions. The atmospheric response to large initial perturbations in the root zone extends up to month 2 and is nonlinear, and larger for drier regimes. Perturbations to the whole soil depth increase the amplitude of the atmospheric anomaly and extend its duration up to 3 months. The response of large initial dry soil anomalies greatly exceeds the impact of the ocean boundary forcing. Results from numerical simulations indicate the possible benefit of using perturbations in the initial soil water conditions, commensurate with soil moisture uncertainties, in the generation of the seasonal forecast ensembles.

Stratosphere–troposphere coupling is often viewed from the perspective of the annular modes and their dynamics. Despite the obvious benefits of this approach, recent work has emphasised the greater tropospheric sensitivity to stratospheric variability in the Atlantic basin than in the Pacific basin. In this study, a new approach to understanding stratosphere–troposphere coupling is proposed, with a focus on the influence of the stratospheric state on North Atlantic weather regimes (during extended winter, November to March). The influence of the strength of the lower‐stratospheric vortex on four commonly used tropospheric weather regimes is quantified. The negative phase of the North Atlantic Oscillation is most sensitive to the stratospheric state, occurring on 33% of days following weak vortex conditions but on only 5% of days following strong vortex conditions. An opposite and slightly weaker sensitivity is found for the positive phase of the North Atlantic Oscillation and the Atlantic Ridge regime. For the North Atlantic Oscillation regimes, stratospheric conditions change both the probability of remaining in each regime and the probability of transitioning to that regime from others. A logistic regression model is developed to further quantify the sensitivity of tropospheric weather regimes to the lower stratospheric state. The logistic regression model predicts an increase of 40–60% in the probability of transition to the negative phase of the North Atlantic Oscillation for a one standard deviation reduction in the strength of the stratospheric vortex. Similarly it predicts a 10–30% increase in the probability of transition to the positive phase of the North Atlantic Oscillation for a one standard deviation increase in the strength of the stratospheric vortex. The stratosphere–troposphere coupling in the European Centre for Medium‐range Weather Forecasts Integrated Forecasting System model is found to be consistent with the re‐analysis data by fitting the same logistic regression model.