Multi-Model Ensembles: Metrics, Indexes, Data Assimilation and All that Jazz

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 en-semble 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 equiva-lent 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 en-semble Kalman filter application for data assimilation.

GALMARINI Stefano;  POTEMPSKI Slawomir; 

2013-02-01

Springer

JRC59401

978-94-007-1358-1,    978-94-007-1359-8,   

http://link.springer.com/chapter/10.1007%2F978-94-007-1359-8_71,    https://publications.jrc.ec.europa.eu/repository/handle/JRC59401,   

10.1007/978-94-007-1359-8_71,