Low-Order Stochastic Mode Reduction for a Realistic Barotropic Model Climate

By Christian L. E. Franzke, Andrew J. Majda, Eric Vanden-Eijnden. 2005

159 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/abedd9e86b8bba7f90c156dd75a593af95053a8b

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Citations in the corpus

Multilevel Regression Modeling of Nonlinear Processes: Derivation and Applications to Climatic Variability (2005, methodology): “It is a pleasure to thank A. W. Robertson for helpful discussions and the three reviewers for constructive comments; one of these, A. J. Majda, kindly provided the reference to Franzke et al. (2005).”
Physics constrained nonlinear regression models for time series (2012, background): “Mathematics Subject Classification: 93E11, 62M20, 93E11, 62L12, 65C20, 62J02, 62M10 0951-7715/13/010201+17$33.00 © 2013 IOP Publishing Ltd & London Mathematical Society Printed in the UK & the USA 201”
Reconciling Non-Gaussian Climate Statistics with Linear Dynamics (2009, background): “The conditions under which the components of a dynamical system may be separable into slow and ‘‘fast enough’’ components in this sense, as well as procedures for classifying specific system components as such, have been the subject of many theoretical and empirical studies (e.g., Khas’minskii 1966;”
Low‐frequency nonlinearity and regime behavior in the Northern Hemisphere extratropical atmosphere (2017, background): “Systematically derived nonlinear dynamic-stochastic models contain the necessary damping in physically meaningful form as nonlinear damping [Majda et al., 1999, 2008, 2009; Franzke et al., 2005, 2015b; Franzke and Majda, 2006; Peavoy et al., 2015].”
FUNDAMENTAL LIMITATIONS OF AD HOC LINEAR AND QUADRATIC MULTI-LEVEL REGRESSION MODELS FOR PHYSICAL SYSTEMS (2012, unknown): “The approaches to address these issues range from analytic stochastic mode reduction strategies [1, 2, 3, 4] to purely data driven strategies [5, 6, 7, 23] to methods which use physical analytic properties to constrain data driven methods [8, 9, 10, 21].”
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective (2019, background): “It has been systematically explored for decades in many different areas including computational mechanics [201]–[204], combustion [205]–[207], cosmology [208]–[210], electrodynamics [211]–[214], meteorology [215]–[218], fluid mechanics [219]–[225], heat transfer [226]–[228] and various other multiph”
Normal forms for reduced stochastic climate models (2009, methodology): “For a 1-dimensional model with an stochastic differential equation (SDE) of the form (7) and associated Fokker–Planck equation of the form (10), there are 7 parameters to estimate as shown earlier.”