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 20072009. 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.