Tropical-extratropical cloudbands over South America in state-of-the-art seasonal forecast systems.

The rainfall during the austral summer season over vast regions of South America is primarily associated with tropical-extratropical cloudbands. These northwest-southeast oriented clusters of convective clouds trigger widespread rainfall and are influenced by slowly varying tropical and subtropical sea surface temperatures. Remote teleconnections also occur through atmospheric Rossby waves at synoptic to subseasonal timescales. Therefore, to accurately forecast these high impact weather events, state-of-the-art prediction systems need to capture processes at various temporal and spatial scales. An automated cloudband detection algorithm based on outgoing longwave radiation (OLR) is used in this study to examine the ability of various seasonal prediction systems, namely, ECMWF SEAS5, UKMO GLOSEAS6, and CPTEC/INPE BAM v1.2, to forecast cloudband characteristics. We find that these systems can represent cloudband seasonality and climatology well, although biases exist. There is significant spatial variability in cloudband prediction skill; the forecast systems predict monthly cloudband statistics over Southeastern South America and parts of tropical Amazon with some skill, whereas the skill is relatively poor over the core South Atlantic convergence zone region. The spatial variability in skill appears to depend on the cloudband - El Niño Southern Oscillation relationship (ENSO). Prediction skill is relatively higher in the months when ENSO has a larger influence on monthly cloudband count. In addition, the presence of skill over South Brazil possibly indicates that the models represent the underlying Rossby wave dynamics to some extent although the absence of skill over Central and Eastern Brazil potentially suggests the need for improvement in representing these teleconnections. The skill is, however, found to decrease rapidly with an increase in lead time, which might have to do with processes at shorter time scales and intrinsic atmospheric variability as suggested by previous studies. In line with this, the composite evolution of upper-level v-wind anomalies in the lead-up to cloudband events appears to be more zonally oriented in the seasonal prediction systems compared to observation. Despite being continental scale weather regimes, differences in upper-level teleconnections indicate that predicting tropical-extratropical cloudband occurrence at seasonal timescales remains a challenge, although the intense rainfall associated with cloudbands are often more predictable than extreme rainfall occurring on non-cloudband days.