caa a22 4500 605473099 CHVBK 20210128100341.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s00382-014-2212-7 doi (NATIONALLICENCE)springer-10.1007/s00382-014-2212-7 An evaluation of experimental decadal predictions using CCSM4 [Elektronische Daten] [A. Karspeck, S. Yeager, G. Danabasoglu, H. Teng] This study assesses retrospective decadal prediction skill of sea surface temperature (SST) variability in initialized climate prediction experiments with the Community Climate System Model version 4 (CCSM4). Ensemble forecasts initialized with two different historical ocean and sea-ice states are evaluated and compared to an ensemble of uninitialized coupled simulations. Both experiments are subject to identical twentieth century historical radiative forcings. Each forecast consists of a 10-member ensemble integrated over a 10-year period. One set of historical ocean and sea-ice conditions used for initialization comes from a forced ocean-ice simulation driven by the Coordinated Ocean-ice Reference Experiments interannually varying atmospheric dataset. Following the Coordinated Model Intercomparison Project version 5 (CMIP5) protocol, these forecasts are initialized every 5years from 1961 to 1996, and every year from 2000 to 2006. A second set of initial conditions comes from historical ocean state estimates obtained through the assimilation of in-situ temperature and salinity data into the CCSM4 ocean model. These forecasts are only available over a limited subset of the CMIP5 recommended start dates. Both methods result in retrospective SST prediction skill over broad regions of the Indian Ocean, western Pacific Ocean and North Atlantic Ocean that are significantly better than reference skill levels from a spatio-temporal auto-regressive statistical model of SST. However the subpolar gyre region of the North Atlantic stands out as the only region where the CCSM4 initialized predictions outperform uninitialized simulations. Some features of the ocean state estimates used for initialization and their impact on the forecasts are discussed. Springer-Verlag Berlin Heidelberg, 2014 Decadal prediction nationallicence Verification nationallicence CCSM4 nationallicence Initialization nationallicence Ocean data assimilation nationallicence Probabilistic skill score nationallicence Karspeck A. National Center for Atmospheric Research, P.O. Box 3000, 80307, Boulder, CO, USA aut Yeager S. National Center for Atmospheric Research, P.O. Box 3000, 80307, Boulder, CO, USA aut Danabasoglu G. National Center for Atmospheric Research, P.O. Box 3000, 80307, Boulder, CO, USA aut Teng H. National Center for Atmospheric Research, P.O. Box 3000, 80307, Boulder, CO, USA aut Climate Dynamics Springer Berlin Heidelberg 44/3-4(2015-02-01), 907-923 0930-7575 44:3-4<907 2015 44 382 https://doi.org/10.1007/s00382-014-2212-7 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/s00382-014-2212-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Karspeck A. National Center for Atmospheric Research, P.O. Box 3000, 80307, Boulder, CO, USA aut NATIONALLICENCE 700 1- Yeager S. National Center for Atmospheric Research, P.O. Box 3000, 80307, Boulder, CO, USA aut NATIONALLICENCE 700 1- Danabasoglu G. National Center for Atmospheric Research, P.O. Box 3000, 80307, Boulder, CO, USA aut NATIONALLICENCE 700 1- Teng H. National Center for Atmospheric Research, P.O. Box 3000, 80307, Boulder, CO, USA aut NATIONALLICENCE 773 0- Climate Dynamics Springer Berlin Heidelberg 44/3-4(2015-02-01), 907-923 0930-7575 44:3-4<907 2015 44 382