Relative Skill of IFS Models
It is important to have measures of forecast skill of the HRES and CTRL, EM and individual members of ENS so that the forecaster can assess the strength of one product over another and the way this varies through the forecast period. This can be illustrated by use of by the Anomaly Correlation Coefficient (ACC) and by the Equitable Threat Score (ETS) when considering model output on a global scale. An assessment of the relative differences in error with lead-time among HRES, CNTL, and individual ensemble members is also important. Verification results suggest that, though HRES is better at providing detail, at least in the earlier part of the forecast, it becomes less precise later in the forecast period. It is important to be able to assess the forecast skill of HRES and ENS products at different forecast lead times so that relative weights can be given to each model in a more structured way.