Explore the vast range of titles available.

Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992–2010 period performed by five different global coupled ocean–atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land–atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.

There has been growing interest in the vertical structure of the recent Arctic warming. We investigated temperatures at the surface, 925, 700, 500 and 300 hPa levels in the Arctic (north of 70° N) using observations and four reanalyses: ERA-Interim, CFSR, MERRA and NCEP II. For the period 1979–2011, the layers at 500 hPa and below show a warming trend in all seasons in all the chosen reanalyses and observations. Restricting the analysis to the 1998–2011 period, however, all the reanalyses show a cooling trend in the Arctic-mean 500 hPa temperature in autumn, and this also applies to both observations and the reanalyses when restricting the analysis to the locations with available IGRA radiosoundings. During this period, the surface observations mainly representing land areas surrounding the Arctic Ocean reveal no summertime trend, in contrast with the reanalyses whether restricted to the locations of the available surface observations or not. In evaluating the reanalyses with observations, we find that the reanalyses agree better with each other at the available IGRA sounding locations than for the Arctic average, perhaps because the sounding observations were assimilated into reanalyses. Conversely, using the reanalysis data only from locations matching available surface (air) temperature observations does not improve the agreement between the reanalyses. At 925 hPa, CFSR deviates from the other three reanalyses, especially in summer after 2000, and it also deviates more from the IGRA radiosoundings than the other reanalyses do. The CFSR error in summer T925 is due mainly to underestimations in the Canadian-Atlantic sector between 120° W and 0°. The other reanalyses also have negative biases in this longitude band.

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.