Articles | Volume 7, issue 1
https://doi.org/10.5194/gmd-7-453-2014
https://doi.org/10.5194/gmd-7-453-2014
Development and technical paper
 | 
28 Feb 2014
Development and technical paper |  | 28 Feb 2014

Ensemble initialization of the oceanic component of a coupled model through bred vectors at seasonal-to-interannual timescales

J. Baehr and R. Piontek

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Cited articles

Cai, M., Kalnay, E., and Toth, Z.: Bred Vectors of the Zebiak-Cane Model and their potential application to ENSO Predictions, J. Climate, 16, 40–56, 2003.
Cheng, Y., Tang, Y., Jackson, P., Chen, D., and Deng, Z.: Ensemble construction and verification of the probabilistic ENSO Prediction in the LDEO5 Model, J. Climate, 23, 5476–5497, 2010.
Du, H., Doblas-Reyes, F. J., García-Serrano, J., Guemas, V., Soufflet, Y., and Wouters, B.: Sensitivity of decadal predictions to the initial atmospheric and oceanic perturbations, Clim. Dynam., 7–8, 2013–2023, 2012.
Epstein, E. S.: Stochastic dynamic prediction, Tellus, 21, 739–759, 1969.
Hamill, T. M.: Interpretation of Rank Histograms for verifying ensemble forecasts, Mon. Weather Rev., 129, 550–560, https://doi.org/10.1175/1520-0493(2001)129<0550:IORHFV>2.0.CO;2, 2001.
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