A Multisystem View of Wintertime NAO Seasonal Predictions

Abstract

Significant predictive skill for the mean winter North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) has been recently reported for a number of different seasonal forecasting systems. These findings are important in exploring the predictability of the natural system, but they are also important from a socioeconomic point of view, since the ability to predict the wintertime atmospheric circulation anomalies over the North Atlantic well ahead in time will have significant benefits for North American and European countries. In contrast to the tropics, for the mid latitudes the predictive skill of many forecasting systems at the seasonal time scale has been shown to be low to moderate. The recent findings are promising in this regard, suggesting that better forecasts are possible, provided that key components of the climate system are initialized realistically and the coupled models are able to simulate adequately the dominant processes and teleconnections associated with low-frequency variability. It is shown that a multisystem approach has unprecedented high predictive skill for the NAO and AO, probably largely due to increasing the ensemble size and partly due to increasing model diversity. Predicting successfully the winter mean NAO does not ensure that the respective climate anomalies are also well predicted. The NAO has a strong impact on Europe and North America, yet it only explains part of the interannual and low-frequency variability over these areas. Here it is shown with a number of different diagnostics that the high predictive skill for the NAO/AO indeed translates to more accurate predictions of temperature, surface pressure, and precipitation in the areas of influence of this teleconnection.

An Intercomparison of Skill and Overconfidence/Underconfidence of the Wintertime North Atlantic Oscillation in Multimodel Seasonal Forecasts

“…MFr‐S4 and JMA are omitted for clarity, because they were shown to have no skill for the NAO. For all systems, the ACC increases with ensemble size, in agreement with Kumar (), Scaife et al (), and Athanasiadis et al (). With the exception of ECMWF, all systems and the MME have a similar slope of the ACC curve, and much of the variation in ACC between systems can be explained by their different ensemble sizes.…”

“…Similarly, winters 1992–1993, 1994–1995, 1999–2000, 2007–2008, and 2011–2012 are those with the most strongly positive observed NAO and are also generally well forecast, with four or five systems forecasting the correct sign of NAO anomaly in each year. In years with weakly positive or weakly negative NAO, the forecast systems tend to do less well, consistent with the results of Athanasiadis et al () who showed low skill for middle‐tercile MSLP forecasts and Weisheimer et al (), who found low skill for weakly negative NAO years but much higher skill for strongly negative NAO winters in a long atmosphere‐only seasonal hindcast data set. The correlation skill is robust to removing individual winters with particularly high or low skill, which gives correlations within 0.1 of the values obtained from the full time series for all models and the MME.…”

“…Dobrynin et al (2018) showed that similarly high levels of skill (correlations of 0.86) can be obtained for the NAO using a combination of a single seasonal forecast system and a statistical model. Similar levels of skill have also been found for the wintertime Arctic Oscillation in some individual and multimodel seasonal forecast systems (e.g., Athanasiadis et al, 2017;Kang et al, 2014;Stockdale et al, 2015).…”

“…The same is true for interannual predictions . Athanasiadis et al (2017) found that the three models in their study and the MME were also underconfident. A similar underconfidence was found for the European Centre for Medium-Range Weather Forecasts (ECMWF) system Arctic Oscillation forecasts by Stockdale et al (2015).…”

Skill and Reliability of Seasonal Forecasts for the Chinese Energy Sector

“…Arribas et al 2011), recent advances in seasonal forecasting systems have led to major improvements in the skill of extratropical features such as the North Atlantic Oscillation (NAO, e.g. Athanasiadis et al 2014Athanasiadis et al , 2016Butler et al 2016;Smith et al 2016 and references therein). Scaife et al (2014) demonstrated skill in NAO forecasts from version 5 of the Met Office's Global Seasonal forecasting system, GloSea5 (MacLachlan et al 2015).…”