Title: Multi-Model Ensembles: Metrics, Indexes, Data Assimilation and All that Jazz
Authors: GALMARINI StefanoPOTEMPSKI Slawomir
Publisher: Springer
Publication Year: 2012
JRC N°: JRC59401
ISBN: 978-94-007-1358-1 (Print)
978-94-007-1359-8 (PDF)
URI: http://link.springer.com/chapter/10.1007%2F978-94-007-1359-8_71
http://publications.jrc.ec.europa.eu/repository/handle/JRC59401
DOI: 10.1007/978-94-007-1359-8_71
Type: Articles in periodicals and books
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 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.
JRC Directorate:Sustainable Resources

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