Workshop on Predictability, dynamics and applications research using the TIGGE and S2S ensembles

Flow-dependent predictability of wintertime Euro-Atlantic weather regimes in medium-range forecasts

Speaker

Mio Matsueda (Center for Computational Sciences, University of Tsukuba)

Description

This study assesses the medium-range flow-dependent forecast skill of Euro-Atlantic weather regimes: the positive and negative phases of the North Atlantic Oscillation (NAO+ and NAO−), Atlantic ridge (ATLR), and Euro-Atlantic blocking (EABL), for extended winters (November–March) in the periods 2006/2007–2013/2014 and 1985/1986–2013/2014 using The Interactive Grand Global Ensemble (TIGGE) and the National Oceanic and Atmospheric Administration (NOAA)’s Global Ensemble Forecasting System (GEFS) reforecast datasets, respectively. The models show greater-than-observed (smaller-than-observed) frequencies of NAO− and ATLR (NAO+) with forecast lead time. The increased frequency of NAO− is not due to its excess persistence but due to more frequent transitions mainly from ATLR, but also from NAO+. In turn, NAO+ is under-persistent. The models show the highest probabilistic skill for forecasts initialised on NAO− and the NAO− forecasts during the TIGGE period. However, the GEFS reforecast during the period 1985/1986–2013/2014 revealed that these recent high skills reflect the occurrence of four long-lasting (>30 days) NAO− events in 2009/2010–2013/2014 and that the skill for forecasts initialised on NAO− before 2009/2010 (the longest duration was 22 days and the second-longest 16 days)was the lowest. The longer theNAO− events persist, the higher the skill of forecasts initialised on NAO−. The skill dependency on regime duration is less clearly observed for the other regimes. In addition, the GEFS reforecast also revealed that the highest skill of the NAO− forecasts during the period 1985/1986–2013/2014 is attributed to the higher skill of the NAO− forecasts during the active NAO− periods. The EABL forecasts initialised on ATLR show the lowest skill, followed by the NAO− (EABL) forecasts initialised on NAO+ or ATLR (NAO+). These results suggest that the recent models still have difficulties in predicting the onset of blocking.

Primary authors

Mio Matsueda (Center for Computational Sciences, University of Tsukuba) Prof. Tim Palmer (University of Oxford)

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