Atmospheric predictability and Rossby wave packets

Abstract

Historically, the objective identification of atmospheric wave‐packets has been very elusive. However, interest in these important sources of atmospheric variability has recently increased, and some automated tracking methods have been proposed. The Rossby wave packet (RWP) tracking algorithms opened the way to different types of investigation, ranging from climatology and predictability to assessing the impact of climate change on wave packet characteristics. The present study investigates the relationship between predictability (intrinsic and practical, i.e. predictive skill in a numerical weather prediction model) and the properties of RWPs, such as temporal duration, spatial extension and their area of genesis. Results suggest a significant correlation between RWP length and medium‐range skill over Europe and the Northern Hemisphere. Analysis of an ensemble system shows that the spread decreases when long‐living RWPs are present in the forecast, supporting the hypothesis that part of the observed increase in skill could indeed be attributed to higher intrinsic predictability induced by RWPs. Higher than average medium‐range forecast skill scores are often associated with the presence of long‐lasting RWPs (duration of at least 8 days) in the initial conditions, with a source often located in the west Pacific. On the contrary, bad medium‐range forecast skill scores tend to be associated with shorter RWPs coming from the central USA or western Atlantic. An analysis of the probabilistic skill scores confirms that predictive skill increases with the presence of long RWPs from the west Pacific, up to week 3.