Multivariate Bayesian analysis of atmosphere–ocean general circulation models

[1]  Richard L. Smith,et al.  Quantifying Uncertainty in Projections of Regional Climate Change: A Bayesian Approach to the Analysis of Multimodel Ensembles , 2005 .

[2]  Myles R. Allen,et al.  Constraining climate forecasts: The role of prior assumptions , 2005 .

[3]  Montserrat Fuentes,et al.  Model Evaluation and Spatial Interpolation by Bayesian Combination of Observations with Outputs from Numerical Models , 2005, Biometrics.

[4]  Christian P. Robert,et al.  Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.

[5]  L. M. Berliner,et al.  Hierarchical Bayesian space-time models , 1998, Environmental and Ecological Statistics.

[6]  Sw. Banerjee,et al.  Hierarchical Modeling and Analysis for Spatial Data , 2003 .

[7]  F. Joos,et al.  Probabilistic climate change projections using neural networks , 2003 .

[8]  S. Raper,et al.  An Observationally Based Estimate of the Climate Sensitivity , 2002 .

[9]  Reto Knutti,et al.  Constraints on radiative forcing and future climate change from observations and climate model ensembles , 2002, Nature.

[10]  Andrei P. Sokolov,et al.  Quantifying Uncertainties in Climate System Properties with the Use of Recent Climate Observations , 2002, Science.

[11]  J. Houghton,et al.  Climate change 2001 : the scientific basis , 2001 .

[12]  T. Wigley,et al.  Interpretation of High Projections for Global-Mean Warming , 2001, Science.

[13]  L. Mark Berliner,et al.  Spatiotemporal Hierarchical Bayesian Modeling Tropical Ocean Surface Winds , 2001 .

[14]  S. Schneider.  What is 'dangerous' climate change? , 2001, Nature.

[15]  José M Bernardo and Adrian F M Smith.  Bayesian Theory , 2001 .

[16]  Noel A Cressie,et al.  Long-Lead Prediction of Pacific SSTs via Bayesian Dynamic Modeling , 2000 .

[17]  Hoon Kim,et al.  Monte Carlo Statistical Methods , 2000, Technometrics.

[18]  John F. B. Mitchell,et al.  Quantifying the uncertainty in forecasts of anthropogenic climate change , 2000, Nature.

[19]  C. Covey,et al.  Intercomparison of present and future climates simulated by coupled ocean-atmosphere GCMs , 2000 .

[20]  G. Meehl,et al.  The Coupled Model Intercomparison Project (CMIP) , 2000 .

[21]  N. Cressie,et al.  A dimension-reduced approach to space-time Kalman filtering , 1999 .

[22]  T. Gneiting.  Correlation functions for atmospheric data analysis , 1999 .

[23]  H. Storch,et al.  Anthropogenic climate change , 1999 .

[24]  S. Cohn,et al.  Ooce Note Series on Global Modeling and Data Assimilation Construction of Correlation Functions in Two and Three Dimensions and Convolution Covariance Functions , 2022 .

[25]  Ross Ihaka,et al.  Gentleman R: R: A language for data analysis and graphics , 1996 .

[26]  Peter Green,et al.  Markov chain Monte Carlo in Practice , 1996 .

[27]  G. Müller,et al.  The Scientific Basis , 1995 .

[28]  J. R. Wallis,et al.  An Approach to Statistical Spatial-Temporal Modeling of Meteorological Fields , 1994 .

[29]  A. Ron,et al.  Strictly positive definite functions on spheres in Euclidean spaces , 1994, Math. Comput..

[30]  Peter Talkner,et al.  Some remarks on spatial correlation function models , 1993 .

[31]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[32]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[33]  M. Budyko,et al.  Anthropogenic Climate Change , 1991 .

[34]  Adrian F. M. Smith,et al.  Sampling-Based Approaches to Calculating Marginal Densities , 1990 .

[35]  A. Yaglom.  Correlation Theory of Stationary and Related Random Functions I: Basic Results , 1987 .

[36]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[37]  Richard H. Jones,et al.  Stochastic Processes on a Sphere , 1963 .

[38]  I. J. Schoenberg.  Positive definite functions on spheres , 1942 .