Ensemble size versus bias correction effects in subseasonal-to-seasonal (S2S) forecasts

Abstract

Abstract This study explores the ensemble size effect on subseasonal-to-seasonal (S2S) forecasts of the European Center for Medium-Range Weather Forecasts (ECMWF) model. The ensemble forecast skill and its sensitivity to the ensemble size are assessed for the troposphere and stratosphere, and compared with theoretical estimates under the perfect model assumption. The degree of skill improvement in ensemble-mean forecasts with increasing ensemble size agrees well with theoretical estimates in the troposphere. However, in the stratosphere, increasing the ensemble size does not yield as much of the skill improvement as expected. Decomposition of the mean square skill score reveals that the weak ensemble size effect in the stratosphere is primarily caused by a large unconditional bias, which exhibits no apparent decrease with increasing ensemble size. Removing such bias significantly improves the S2S forecast skill and ensemble size effect, suggesting that bias correction is crucial for S2S forecasts, especially in the stratosphere.

Keywords

• Subseasonal-to-seasonal (S2S) forecast
• Ensemble size effect
• Bias correction