@article{101056,
  author = {Yun Liu and Zhengyu Liu and Shaoqing Zhang and X. Rong and Robert Jacob and S. Wu and Feiyu Lu},
  title = {Ensemble-based parameter estimation in a coupled GCM using the adaptive spatial average method},
  abstract = { Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. For a complex system as a coupled ocean-atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. Here, we propose an adaptive spatial average (ASA) algorithm to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting {\textquotedblleft}good{\textquotedblright} values from the spatially varying posterior estimated parameter values; the {\textquotedblleft}good{\textquotedblright} values are then averaged to give the final global uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio. },
  year = {2014},
  journal = {Journal of Climate},
  volume = {27},
  pages = {4002{\textendash}4014},
  month = {06/2014},
  issn = {08948755},
  url = {http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-13-00406.1},
  doi = {10.1175/JCLI-D-13-00091.1},
  language = {eng},
}