ALBERT

Description: A set of relaxation experiments using the ECMWF atmospheric model is used to analyse the severe European winter of 1962/63. We argue that the severe winter weather was associated with a wave train that originated in the tropical Pacific sector (where weak La Nina conditions were present) and was redirected towards Europe, a process we suggest was influenced by the combined effect of the strong easterly phase of the Quasi-Biennial Oscillation (QBO ) and unusually strong easterly winds in the upper equatorial troposphere that winter. A weak tendency towards negative North Atlantic Oscillation (NAO) conditions in December, associated with extratropical sea surface temperature and sea-ice anomalies, might have acted as a favourable preconditioning. The redirection of the wave train towards Europe culminated in the stratospheric sudden warming at the end of January 1963. We argue that in February, the sudden warming event helped maintain the negative NAO regime, allowing the severe weather to persist for a further month. A possible influence from the Madden-Julian Oscillation, as well as a role for internal atmospheric variability, is noted.

Description: The phase and the amplitude of the North Atlantic Oscillation (NAO) are influenced by numerous factors, which include Sea Surface Temperature (SST) anomalies in both the Tropics and extratropics and stratospheric extreme events like Stratospheric Sudden Warmings (SSWs). Analyzing seasonal forecast experiments, which cover the winters from 1979/80–2013/14, with the European Centre for Medium-Range Weather Forecast model, we investigate how these factors affect NAO variability and predictability. Building on the idea that the tropical influence might happen via the stratosphere, special emphasis is placed on the role of major SSWs. Relaxation experiments are performed, where different regions of the atmosphere are relaxed towards ERA-Interim to obtain perfect forecasts in those regions. By comparing experiments with relaxation in the tropical atmosphere, performed with an atmosphere-only model on the one hand and a coupled atmosphere–ocean model version on the other, the importance of extratropical atmosphere–ocean interaction is addressed. Interannual variability of the NAO is best reproduced when perfect knowledge about the NH stratosphere is available together with perfect knowledge of SSTs and sea ice, in which case 64% of the variance of the winter mean NAO is projected to be accounted for with a forecast ensemble of infinite size. The coupled experiment shows a strong bias in the stratospheric polar night jet (PNJ) which might be associated with a drift in the modelled SSTs resembling the North Atlantic cold bias and an underestimation of blockings in the North Atlantic/Europe sector. Consistent with the stronger PNJ, the lowest frequency of major SSWs is found in this experiment. However, after statistically removing the bias, a perfect forecast of the tropical atmosphere and allowing two-way atmosphere–ocean coupling in the extratropics seem to be key ingredients for successful SSW predictions. In combination with SSW occurrence, a clear shift of the predicted NAO towards lower values occurs.

Description: We quantify seasonal prediction skill of tropical winter rainfall in 14 climate forecast systems. High levels of seasonal prediction skill exist for year‐to‐year rainfall variability in all tropical ocean basins. The tropical East Pacific is the most skilful region, with very high correlation scores, and the tropical West Pacific is also highly skilful. Predictions of tropical Atlantic and Indian Ocean rainfall show lower but statistically significant scores. We compare prediction skill (measured against observed variability) with model predictability (using single forecasts as surrogate observations). Model predictability matches prediction skill in some regions but it is generally greater, especially over the Indian Ocean. We also find significant inter‐basin connections in both observed and predicted rainfall. Teleconnections between basins due to El Niño–Southern Oscillation (ENSO) appear to be reproduced in multi‐model predictions and are responsible for much of the prediction skill. They also explain the relative magnitude of inter‐annual variability, the relative magnitude of predictable rainfall signals and the ranking of prediction skill across different basins. These seasonal tropical rainfall predictions exhibit a severe wet bias, often in excess of 20% of mean rainfall. However, we find little direct relationship between bias and prediction skill. Our results suggest that future prediction systems would be best improved through better model representation of inter‐basin rainfall connections as these are strongly related to prediction skill, particularly in the Indian and West Pacific regions. Finally, we show that predictions of tropical rainfall alone can generate highly skilful forecasts of the main modes of extratropical circulation via linear relationships that might provide a useful tool to interpret real‐time forecasts.

Description: Recent studies using reanalysis data and complex models suggest that the Tropics influence midlatitude blocking. Here, the influence of tropical precipitation anomalies is investigated further using a dry dynamical model driven by specified diabatic heating anomalies. The model uses a quasi‐realistic setup based on idealized orography and an idealized representation of the land‐ocean thermal contrast. Results concerning the El Niño Southern Oscillation and the Madden‐Julian Oscillation are mostly consistent with previous studies and emphasize the importance of tropical dynamics for driving the variability of blocking at midlatitudes. It is also shown that a common bias in models of the Coupled Model Intercomparison Project Phase 5 (CMIP5), namely, excessive tropical precipitation, leads to an underestimation of midlatitude blocking in our model, also a common bias in the CMIP5 models. The strongest blocking anomalies associated with the tropical precipitation bias are found over Europe, where the underestimation of blocking in CMIP5 models is also particularly strong.