• DOI:10.1175/MWR3466.1
• Corpus ID: 12067483

System Design and Evaluation of Coupled Ensemble Data Assimilation for Global Oceanic Climate Studies

@article{Zhang2007SystemDA,
  title={System Design and Evaluation of Coupled Ensemble Data Assimilation for Global Oceanic Climate Studies},
  author={Shaoqing Zhang and Matthew J. Harrison and Anthony J. Rosati and Andrew T. Wittenberg},
  journal={Monthly Weather Review},
  year={2007},
  volume={135},
  pages={3541-3564}
}

• Shaoqing Zhang, M. Harrison, +1 author A. Wittenberg
• Published 1 October 2007
• Environmental Science
• Monthly Weather Review

Abstract A fully coupled data assimilation (CDA) system, consisting of an ensemble filter applied to the Geophysical Fluid Dynamics Laboratory’s global fully coupled climate model (CM2), has been developed to facilitate the detection and prediction of seasonal-to-multidecadal climate variability and climate trends. The assimilation provides a self-consistent, temporally continuous estimate of the coupled model state and its uncertainty, in the form of discrete ensemble members, which can be used directly to initialize probabilistic climate forecasts. Here, the CDA is evaluated using a series of perfect model experiments, in which a particular twentieth-century simulation—with temporally varying greenhouse gas and natural aerosol radiative forcings—serves as a “truth” from which observations are drawn, according to the actual ocean observing network for the twentieth century. These observations are then assimilated into a coupled model ensemble that is subjected only to preindustrial forcings. By examining...