An evaluation of experimental decadal predictions using CCSM4

• Published in: Climate dynamics Vol. 44; no. 3-4; pp. 907 - 923
• Main Authors: Karspeck, A., Yeager, S., Danabasoglu, G., Teng, H.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2015; Springer; Springer Nature B.V; Springer-Verlag
• Subjects: Atlantic Ocean; climate; Climate change; Climate models; Climate prediction; Climate system; Climatology; data collection; Decades; Earth and Environmental Science; Earth Sciences; Geophysics/Geodesy; Indian Ocean; Marine; Meteorology & Atmospheric Sciences; Methods; Numerical weather forecasting; Observations; Ocean-atmosphere interaction; Oceanography; Oceans; Pacific Ocean; prediction; Predictions; salinity; Sea ice; Sea surface temperature; Statistical models; Surface chemistry; surface water temperature; Weather forecasting; AN, North Atlantic; ANE, North Atlantic, Subpolar Gyre; ISW, Indian Ocean; Indian Ocean; Atlantic Ocean; Pacific Ocean; Initialization; Verification; Ocean data assimilation; CCSM4; Probabilistic skill score; Decadal prediction
• ISSN: 0930-7575; 1432-0894
• DOI: 10.1007/s00382-014-2212-7

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 5 years 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.