caa a22 4500 605475032 CHVBK 20210128100350.0 cr unu---uuuuu 210128e20150501xx s 000 0 eng 10.1007/s00382-014-2164-y doi (NATIONALLICENCE)springer-10.1007/s00382-014-2164-y An assessment of a multi-model ensemble of decadal climate predictions [Elektronische Daten] [A. Bellucci, R. Haarsma, S. Gualdi, P. Athanasiadis, M. Caian, C. Cassou, E. Fernandez, A. Germe, J. Jungclaus, J. Kröger, D. Matei, W. Müller, H. Pohlmann, D. Salas y Melia, E. Sanchez, D. Smith, L. Terray, K. Wyser, S. Yang] A multi-model ensemble of decadal prediction experiments, performed in the framework of the EU-funded COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) Project following the 5th Coupled Model Intercomparison Project protocol is examined. The ensemble combines a variety of dynamical models, initialization and perturbation strategies, as well as data assimilation products employed to constrain the initial state of the system. Taking advantage of the multi-model approach, several aspects of decadal climate predictions are assessed, including predictive skill, impact of the initialization strategy and the level of uncertainty characterizing the predicted fluctuations of key climate variables. The present analysis adds to the growing evidence that the current generation of climate models adequately initialized have significant skill in predicting years ahead not only the anthropogenic warming but also part of the internal variability of the climate system. An important finding is that the multi-model ensemble mean does generally outperform the individual forecasts, a well-documented result for seasonal forecasting, supporting the need to extend the multi-model framework to real-time decadal predictions in order to maximize the predictive capabilities of currently available decadal forecast systems. The multi-model perspective did also allow a more robust assessment of the impact of the initialization strategy on the quality of decadal predictions, providing hints of an improved forecast skill under full-value (with respect to anomaly) initialization in the near-term range, over the Indo-Pacific equatorial region. Finally, the consistency across the different model predictions was assessed. Specifically, different systems reveal a general agreement in predicting the near-term evolution of surface temperatures, displaying positive correlations between different decadal hindcasts over most of the global domain. Springer-Verlag Berlin Heidelberg, 2014 Bellucci A. Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viale A. Moro 44, 40127, Bologna, Italy aut Haarsma R. Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands aut Gualdi S. Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viale A. Moro 44, 40127, Bologna, Italy aut Athanasiadis P. Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viale A. Moro 44, 40127, Bologna, Italy aut Caian M. Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden aut Cassou C. European Centre for Research and Advanced Training in Scientific Computation (CERFACS), Toulouse, France aut Fernandez E. European Centre for Research and Advanced Training in Scientific Computation (CERFACS), Toulouse, France aut Germe A. CNRM, Météo-France, Toulouse, France aut Jungclaus J. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut Kröger J. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut Matei D. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut Müller W. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut Pohlmann H. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut Salas y Melia D. CNRM, Météo-France, Toulouse, France aut Sanchez E. European Centre for Research and Advanced Training in Scientific Computation (CERFACS), Toulouse, France aut Smith D. Met Office Hadley Centre, Exeter, UK aut Terray L. European Centre for Research and Advanced Training in Scientific Computation (CERFACS), Toulouse, France aut Wyser K. Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden aut Yang S. Danish Meteorological Institute (DMI), Copenhagen, Denmark aut Climate Dynamics Springer Berlin Heidelberg 44/9-10(2015-05-01), 2787-2806 0930-7575 44:9-10<2787 2015 44 382 https://doi.org/10.1007/s00382-014-2164-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00382-014-2164-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Bellucci A. Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viale A. Moro 44, 40127, Bologna, Italy aut NATIONALLICENCE 700 1- Haarsma R. Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands aut NATIONALLICENCE 700 1- Gualdi S. Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viale A. Moro 44, 40127, Bologna, Italy aut NATIONALLICENCE 700 1- Athanasiadis P. Centro Euro-Mediterraneo sui Cambiamenti Climatici, Viale A. Moro 44, 40127, Bologna, Italy aut NATIONALLICENCE 700 1- Caian M. Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden aut NATIONALLICENCE 700 1- Cassou C. European Centre for Research and Advanced Training in Scientific Computation (CERFACS), Toulouse, France aut NATIONALLICENCE 700 1- Fernandez E. European Centre for Research and Advanced Training in Scientific Computation (CERFACS), Toulouse, France aut NATIONALLICENCE 700 1- Germe A. CNRM, Météo-France, Toulouse, France aut NATIONALLICENCE 700 1- Jungclaus J. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut NATIONALLICENCE 700 1- Kröger J. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut NATIONALLICENCE 700 1- Matei D. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut NATIONALLICENCE 700 1- Müller W. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut NATIONALLICENCE 700 1- Pohlmann H. Max-Planck-Institut für Meteorologie, Hamburg, Germany aut NATIONALLICENCE 700 1- Salas y Melia D. CNRM, Météo-France, Toulouse, France aut NATIONALLICENCE 700 1- Sanchez E. European Centre for Research and Advanced Training in Scientific Computation (CERFACS), Toulouse, France aut NATIONALLICENCE 700 1- Smith D. Met Office Hadley Centre, Exeter, UK aut NATIONALLICENCE 700 1- Terray L. European Centre for Research and Advanced Training in Scientific Computation (CERFACS), Toulouse, France aut NATIONALLICENCE 700 1- Wyser K. Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden aut NATIONALLICENCE 700 1- Yang S. Danish Meteorological Institute (DMI), Copenhagen, Denmark aut NATIONALLICENCE 773 0- Climate Dynamics Springer Berlin Heidelberg 44/9-10(2015-05-01), 2787-2806 0930-7575 44:9-10<2787 2015 44 382