Ensemble dressing for hydrological applications

Abstract

This manuscript presents a simple yet effective method to account for uncertainty in hydrologic ensemble forecasting applications. Most operational hydrological ensemble forecasting systems only account for uncertainty in future climate (e.g. precipitation) forcings, ignoring other sources of uncertainty (e.g. model error). The result can be under-dispersive and overconfident forecasts. Ensemble dressing is a form of statistical post-processing to include information about the uncertainty of individual ensemble members. First, the historical simulations can be corrected to remove systematic biases. Next, the simulated and observed flow data are transformed to ensure that model residuals can ..