Sources of skill in near-term climate prediction: generating initial conditions-Reference-Cited by-同舟云学术

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Sources of skill in near-term climate prediction: generating initial conditions

Published:2016-03-03 Issue:12 Volume:47 Page:3693-3712
ISSN:0930-7575
Container-title:Climate Dynamics
language:en
Short-container-title:Clim Dyn

Author:

Carrassi A.,Guemas V.,Doblas-Reyes F. J.,Volpi D.,Asif M.

Funder

IEF Marie Curie Project INCLIDA

MINECO PICA-ICE Project

EU-FP7 Sangoma Project

Publisher

Springer Science and Business Media LLC

Subject

Atmospheric Science

Link

http://link.springer.com/content/pdf/10.1007/s00382-016-3036-4.pdf

Reference51 articles.

1. Auroux D, Blum J (2008) A nudging-based data assimilation method: the back and forth nudging (BFN) algorithm. Nonlinear Process Geophys 15:305–319

2. Balmaseda M, Mogensen K, Weaver A (2013) Evaluation of the ECMWF ocean reanalysis system ORAS4. Q J R Meteorol Soc 139:1132–1161. doi: 10.1002/qj.2063

3. Booth B, Dunstone N, Halloran P, Andrews T, Bellouin N (2012) Aerosols implicated as a prime driver of twentieth-century north atlantic climate variability. Nature 484:228–232

4. Brodeau L, Barnier B, Treguier AM, Penduff T, Gulev S (2010) An ERA40-based atmospheric forcing for global ocean circulation models. Ocean Model 31:88–104

5. Carrassi A, Weber R, Guemas V, Doblas-Reyes F, Asif M, Volpi D (2014) Full-field and anomaly initialization using a low-order climate model: a comparison and proposals for advanced formulations. Nonlinear Process Geophys 21:521–537

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