Atmospheric multiple equilibria and non‐Gaussian behaviour in model simulations

Multiple equilibria from general circulation models (GCMs) are investigated via Gaussian mixture models. The cross-validation technique based on bootstrap, used to find the possible number of clusters, is shown to have a tendency to display a bias in the number of clusters when the sample is not statistically independent. The method is shown, however, to give satisfactory results when applied with a strategy based on statistical independence. The mixture model is successfully applied to a few dynamical systems and data from the UK Universities Global Atmospheric Modelling Programme (UGAMP) GCM. The same analysis is then carried out and applied to the wintertime 500 mb geopotential height field taken from a 50-year run of the Hadley Centre HadAM3 GCM. Three regions, the North Pacific-American, the North Atlantic, and the northern hemisphere are investigated for nonlinear circulation regimes. It is shown that the model displays robust regime behaviour over the North Pacific-American sector, while only marginal regime behaviour is observed over the North Atlantic, and no trace of hemispheric regimes.

[1]  Tim N. Palmer,et al.  Regimes in the wintertime circulation over northern extratropics. I: Observational evidence , 1990 .

[2]  J. Wallace,et al.  Teleconnections in the Geopotential Height Field during the Northern Hemisphere Winter , 1981 .

[3]  E. Lorenz Atmospheric Predictability as Revealed by Naturally Occurring Analogues , 1969 .

[4]  David B. Stephenson,et al.  The “normality” of El Niño , 1999 .

[5]  Robert Vautard,et al.  Multiple Weather Regimes over the North Atlantic: Analysis of Precursors and Successors , 1990 .

[6]  Hannachi Probabilistic-based approach to optimal filtering , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[7]  J. Charney,et al.  Multiple Flow Equilibria in the Atmosphere and Blocking , 1979 .

[8]  John M. Wallace,et al.  Is There Evidence of Multiple Equilibria in Planetary Wave Amplitude Statistics , 1994 .

[9]  B. Anderson,et al.  Optimal Filtering , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  Padhraic Smyth,et al.  Multiple Regimes in Northern Hemisphere Height Fields via MixtureModel Clustering* , 1999, Journal of the Atmospheric Sciences.

[11]  Edward N. Lorenz,et al.  Climatic Change as a Mathematical Problem , 1970 .

[12]  K. Mo,et al.  Cluster analysis of multiple planetary flow regimes , 1988 .

[13]  X. Pichon,et al.  Marine Magnetic Anomalies, Geomagnetic Field Reversals, and Motions of the Ocean Floor and , 1968 .

[14]  Daniel F. Rex,et al.  Blocking Action in the Middle Troposphere and its Effect upon Regional Climate I. An Aerological Study of Blocking Action. , 1950 .

[15]  Daniel F. Rex,et al.  Blocking Action in the Middle Troposphere and its Effect upon Regional Climate II. The Climatology of Blocking Action , 1950 .

[16]  S. Childress,et al.  Topics in geophysical fluid dynamics. Atmospheric dynamics, dynamo theory, and climate dynamics. , 1987 .

[17]  P. Rowntree,et al.  A Mass Flux Convection Scheme with Representation of Cloud Ensemble Characteristics and Stability-Dependent Closure , 1990 .

[18]  S. T. Buckland,et al.  An Introduction to the Bootstrap. , 1994 .

[19]  Keith Haines,et al.  Weather Regimes in the Pacific from a GCM , 1995 .

[20]  Geoffrey J. McLachlan,et al.  Mixture models : inference and applications to clustering , 1989 .

[21]  J. Egger,et al.  Stochastically Driven Large-scale Circulations with Multiple Equilibria , 1981 .

[22]  F. Molteni,et al.  A dynamical interpretation of the global response to Equatorial Pacific SST anomalies , 1993 .

[23]  J. Michaelsen Cross-Validation in Statistical Climate Forecast Models , 1987 .

[24]  J. Namias Seasonal persistence and recurrence of European blocking during 1958–1960 , 1964 .

[25]  K. Pearson Contributions to the Mathematical Theory of Evolution , 1894 .

[26]  X. Cheng,et al.  Cluster Analysis of the Northern Hemisphere Wintertime 500-hPa Height Field: Spatial Patterns , 1993 .

[27]  Robert E. Livezey,et al.  The Evaluation of Forecasts , 1995 .

[28]  K. Hasselmann Climate change: Linear and nonlinear signatures , 1999, Nature.

[29]  J. Wolfe PATTERN CLUSTERING BY MULTIVARIATE MIXTURE ANALYSIS. , 1970, Multivariate behavioral research.

[30]  A. Hannachi,et al.  Weather Regimes in the Pacific from a GCM. Part II: Dynamics and Stability , 1997 .

[31]  C. E. Leith,et al.  The Standard Error of Time-Average Estimates of Climatic Means , 1973 .

[32]  Tim N. Palmer,et al.  Signature of recent climate change in frequencies of natural atmospheric circulation regimes , 1999, Nature.

[33]  Franco Molteni,et al.  Toward a dynamical understanding of planetary-scale flow regimes. , 1993 .

[34]  Tim Palmer,et al.  A Nonlinear Dynamical Perspective on Climate Prediction , 1999 .

[35]  P. Holmes,et al.  Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields , 1983, Applied Mathematical Sciences.

[36]  K. Tung,et al.  Theories of Multiple Equilibria-A Critical Reexamination. Part I: Barotropic Models , 1985 .

[37]  Siegmund Brandt,et al.  Statistical and Computational Methods in Data Analysis , 1971 .

[38]  E. Lorenz Deterministic nonperiodic flow , 1963 .

[39]  A. F. Smith,et al.  Statistical analysis of finite mixture distributions , 1986 .

[40]  M. Ghil,et al.  Multiple Flow Regimes in the Northern Hemisphere Winter. Part I: Methodology and Hemispheric Regimes , 1993 .

[41]  Alfonso Sutera,et al.  On the Probability Density Distribution of Planetary-Scale Atmospheric Wave Amplitude , 1986 .