Predictability of Long-lived of Rossby Wave Packets during Southern Hemisphere Summer

Rossby wave packets (or RWPs) are synoptic scale perturbations that appear in the high atmosphere of mid-latitudes that are linked to the occurrence of extreme weather events. Normally these packets last between 3-6 days, but under certain conditions, they can gain enough stability to last from several days to 2-3 weeks in the atmosphere before disappearing, RWPs that last more than 8 days in the atmosphere are referred as long-lived RWPs or LLRWPs. Thus, a skillful prediction of the apparition and propagation of LLRWPs can improve extreme weather prediction in the sub-seasonal scale. In this study we aim to measure the NCEP CFSv2 S2S model skill at forecasting the development and propagation of LLRWPs, and how climatic modes such as El Niño-Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) affect the skill on LLRWPs forecasting. First, we calculated the envelope of austral summer meridional winds at 300 hPa from ERA 5 reanalysis, and applied a tracking algorithm to detect the formation and propagation of LLRWPs. Secondly, we repeated the same methodology but using NCEP reforecast data, starting the analysis the dates a LLRWPs was detected in the reanalysis so that we can track the trajectory of the RWPs forecasted by the model, these packets will be referred as Forecasted Rossby Wave packets (FRWPs). Next, we studied the propagation characteristics of the FRWPs against the original LLRWPs tracked in the reanalysis, and classified the FRWPs according to the dominant phases of ENSO and SAM to assess whether the predictability of the LLRWPs is affected by large scale climate modes. Results showed that the model is able to detect the formation and propagation of FRWPs in 88% of the simulations, but only 40 % of the FRWPs surpass the 8 days threshold. In addition, forecasted packets show an eastward bias displacement and propagate slower compared to the original LLRWPs. During ENSO events, years with El Niño, Neutral and La Niña events, the model was able to forecast FRWPs in 85, 96 and 76% of simulations respectively. Nonetheless, the model struggles to predict long episodes of RWPs during Neutral ENSO events. Nonetheles, during negative (positive) phases of SAM, the model FRWPs detection is around 85% (65 %) , and near 88% in neutral SAM phases.