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.

Abstract. The ECMWF OCEAN5 system is a global ocean and sea-ice ensemble of reanalysis and real-time analysis. This paper gives a full description of the OCEAN5 system, with the focus on upgrades of system components with respect to its predecessors, ORAS4 and ORAP5. An important novelty in OCEAN5 is the ensemble generation strategy that includes perturbation of initial conditions and a generic perturbation scheme for observations and forcing fields. Other upgrades include revisions to the a priori bias correction scheme, observation quality control and assimilation method for sea-level anomalies. The OCEAN5 historical reconstruction of the ocean and sea-ice state is the ORAS5 reanalysis, which includes five ensemble members and covers the period from 1979 onwards. Updated versions of observation data sets are used in ORAS5 production, with special attention devoted to the consistency of sea surface temperature (SST) and sea-ice observations. Assessment of ORAS5 through sensitivity experiments suggests that all system components contribute to an improved fit to observation in reanalyses, with the most prominent contribution from direct assimilation of ocean in situ observations. Results of observing system experiments further suggest that the Argo float is the most influential observation type in our data assimilation system. Assessment of ORAS5 has also been carried out for several key ocean state variables and verified against reference climate data sets from the ESA CCI (European Space Agency Climate Change Initiative) project. With respect to ORAS4, ORAS5 has improved ocean climate state and variability in terms of SST and sea level, mostly due to increased model resolution and updates in assimilated observation data sets. In spite of the improvements, ORAS5 still underestimates the temporal variance of sea level and continues exhibiting large SST biases in the Gulf Stream and its extension regions which are possibly associated with misrepresentation of front positions. Overall, the SST and sea-ice uncertainties estimated using five ORAS5 ensemble members have spatial patterns consistent with those of analysis error. The ensemble spread of sea ice is commensurable with the sea-ice analysis error. On the contrary, the ensemble spread is under-dispersive for SST.

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.

Abstract. The ECMWF OCEAN5 system is a global ocean and sea-ice ensemble of reanalysis and real-time analysis. This manuscript gives a full description of the OCEAN5 system, with the focus on upgrades of system components with respect to its predecessors ORAS4 and ORAP5. An important novelty in OCEAN5 is the ensemble generation strategy that includes perturbation of initial conditions, and a generic perturbation scheme for observations and forcing fields. Other upgrades include revisions to the a-priori bias correction scheme, observation quality control and assimilation method for sea-level anomaly. The OCEAN5 historical reconstruction of the ocean and sea-ice state is the ORAS5 reanalysis, which includes 5 ensemble members and covers the period from 1979 onwards, and with a backward extension until 1958. Updated version of observation data sets are used in ORAS5 production, with special attention devoted to the consistency of sea surface temperature (SST) and sea-ice observations. Assessment of ORAS5 in the observation space suggests that assimilation of observations contribute to reducing the analysis error, with the most prominent contribution from direct assimilation of ocean in-situ observations. Results of observing system experiment further suggest that Argo float is the most influential observation type in our data assimilation system. Assessment of ORAS5 has also been carried out with several key ocean state variables and verified against independent observation data sets from ESA CCI project. With respect to ORAS4, ORAS5 has improved ocean climate state and variability in terms of SST and sea-level, mostly due to increased model resolution and updates in assimilated observation data sets. In spite of the improvements, ORAS5 still underestimates the temporal variance of sea level, and continue exhibiting large SST biases in the Gulf Stream and extension regions which is possibly associated with misrepresentation of front positions. Overall, the SST and sea-ice uncertainties estimated using five ORAS5 ensemble members have spatial patterns consistent with those of analysis error. The ensemble spread of sea-ice is commensurable with the sea-ice analysis error. On the contrary, the ensemble is under-dispersive for SST.

Abstract. Sea level is a very sensitive index of climate change since it integrates the impacts of ocean warming and ice mass loss from glaciers and the ice sheets. Sea level has been listed as an essential climate variable (ECV) by the Global Climate Observing System (GCOS). During the past 25 years, the sea level ECV has been measured from space by different altimetry missions that have provided global and regional observations of sea level variations. As part of the Climate Change Initiative (CCI) program of the European Space Agency (ESA) (established in 2010), the Sea Level project (SL_cci) aimed to provide an accurate and homogeneous long-term satellite-based sea level record. At the end of the first phase of the project (2010)(2011)(2012)(2013), an initial version (v1.1) of the sea level ECV was made available to users . During the second phase of the project (2014-2017), improved altimeter standards were selected to produce new sea level products (called SL_cci v2.0) based on nine altimeter missions for the period 1993-2015 (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612; Legeais and the ESA SL_cci team, 2016c). Corresponding orbit solutions, geophysical corrections and altimeter standards used in this v2.0 dataset are described in detail in Quartly et al. (2017). The present paper focuses on the description of the SL_cci v2.0 ECV and associated uncertainty and discusses how it has been validated. Various approaches have been used for the quality assessment such as internal validation, comparisons with sea level records from other groups and with in situ measurements, sea level budget closure analyses and comparisons with model outputs. Compared with the previous version of the sea level ECV, we show that use of improved geophysical corrections, careful bias reduction between missions and inclusion of new altimeter missions lead to improved sea level products with reduced uncertainties on different spatial and temporal scales. However, there is still room for improvementPublished by Copernicus Publications. 282J.-F. Legeais et al.: An improved and homogeneous altimeter sea level record from the ESA since the uncertainties remain larger than the GCOS requirements (GCOS, 2011). Perspectives on subsequent evolution are also discussed.