Assessing the Predictability of African Easterly Waves in ECMWF Ensemble Forecasts

During the boreal summer, African Easterly Waves (AEWs) are the primary synoptic-scale feature that influences North African weather, and are associated with the majority of summer rainfall found in this region. Although numerous studies have investigated the composite mean structure and evolution of these waves through observational case studies and idealized modeling, few studies have explored the skill and predictability of these systems in operational deterministic or ensemble forecasts. Furthermore, the question remains whether AEWs in these forecasts are more or less predictable under certain large-scale conditions or wave structures.

This study investigates the predictability of AEW forecasts, defined here as the magnitude of ensemble standard deviation, in the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble, which is available through the THORPEX Interactive Grand Global Ensemble (TIGGE) dataset, during July-August-September 2007—2009. Whereas the ensemble standard deviation in AEW position forecasts is relatively constant with time, the ensemble standard deviation in AEW intensity forecasts often exhibit rapid growth. As a consequence, this study explores forecasts exhibiting the largest standard deviation in intensity at 72h (top 10% of forecasts) and compares them against forecasts with the smallest standard deviation in intensity (bottom 10%). Preliminary results suggest the largest standard deviation occurs in forecasts with intensifying waves. The variability in these waves tends to grow in tandem with metrics related to nearby convection, suggesting that differences in the model's representation of convection could be a key factor in determining the growth of forecast errors associated with these systems.