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AGU: Geophysical Research Letters

 

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  • Atmospheric Processes: Global climate models

Abstract

Theoretical examination of a multi-model composite for seasonal prediction

Jin Ho Yoo

School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea

In-Sik Kang

School of Earth and Environmental Sciences, Seoul National University, Seoul, Korea

The performance of a multi-model composite for seasonal prediction is theoretically examined in terms of a correlation skill. On the basis of theoretical analysis, we discuss the improvement of skill in the multi-model composite using the APCN multi-model seasonal prediction dataset. Although the skill of multi-model composite is generally increased by increasing the number of models, the highest skill can be obtained by selecting several skillful models which are less dependent each other.

Received 15 May 2005; accepted 22 August 2005; published 22 September 2005.

Citation: Yoo, J. H., and I.-S. Kang (2005), Theoretical examination of a multi-model composite for seasonal prediction, Geophys. Res. Lett., 32, L18707, doi:10.1029/2005GL023513.

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