SEAS5: the new ECMWF seasonal forecast system

Abstract

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.

Excessive Momentum and False Alarms in Late‐Spring ENSO Forecasts

“…For instance, the correlation between the forecast March-April tendency and the forecast May-August tendency for a forecast initialized 10.1029/2020GL087008 in January is a measure of momentum that is more directly related to the dynamics of the forecast model and less to its initialization. Niño 3.4 was also computed in a short set of ECMWF SEAS5 hindcasts and forecasts (25 members; January 1993-December 2018 starts Johnson et al, 2019) and UKMO GloSea5-GC2 System13 hindcasts (28 members; January 1995-December 2016 starts MacLachlan et al, 2015) which extend 6 months.…”

Bias-adjusted seasonal forecasts of soil moisture for forestry applications in Finland

“…All bias adjustment methods tested improved on the raw, uncorrected forecasts, while giving very similar results compared to each other. We hypothesise that this is because all methods were able to correct the bias, but after the bias is corrected, the spread is much harder to improve (Manzanas et al, 2019). At first the use of EQM was considered.…”

A seamless filter for daily to seasonal forecasts, with applications to Iran and Brazil

“…Ideally, one would like to have skilful long-term predictions starting some time in autumn. According to Johnson et al (2019), fig. 20, both regions lie at the boundary of skilful tropical predictions (DJF, 1-month lead).…”

“…Originally used for the interface between weather and climate (Palmer et al, 2008;Shukla et al, 2009), the word "seamless" now refers to efforts of unifying prediction systems (initialization, parametrization, numerics) across all time-scales. This study emphasizes predictions ranging from days to seasons, specifically from lead times of 1 to 180 days, as produced by the latest seasonal prediction system SEAS5 of the European Centre of Medium-range Weather Forecasts (ECMWF) (Johnson et al, 2019). Potential atmospheric predictability at seasonal time-scales is grounded in, mostly coupled, atmosphere-ocean processes, such as the El-Niño-Southern Oscillation or the Madden-Julian Oscillation, that are themselves predictable at those time-scales (Rowell, 1998).…”