Multi-model Ensembles: Metrics, Indexes, Data Assimilation and All That Jazz

Abstract

We investigate the possibility of using different metrics for the evaluation of multi-model ensembles, in the attempt to find the optimal representation of the ensemble spread and bias. We present basic properties of different metrics and we discuss the consequences of applying them in atmospheric dispersion multi-model ensemble systems. We show also how we can obtain relevant information equivalent to different statistical treatments of an ensemble by combining the application of various metrics for calculating the ensemble spread and bias. A digression is presented on the use of the optimal combination of model results within an ensemble Kalman filter application for data assimilation.