An implementation of Hasselmann’s paradigm for stochastic climate modelling based on stochastic Lie transport

A generic approach to stochastic climate modelling is developed for the example of an idealised Atmosphere-Ocean model that rests upon Hasselmann’s paradigm for stochastic climate models. Namely, stochasticity is incorporated into the fast moving atmospheric component of an idealised coupled model by means of stochastic Lie transport, while the slow moving ocean model remains deterministic. More specifically the stochastic model stochastic advection by Lie transport (SALT) is constructed by introducing stochastic transport into the material loop in Kelvin’s circulation theorem. The resulting stochastic model preserves circulation, as does the underlying deterministic climate model. A variant of SALT called Lagrangian-averaged (LA)-SALT is introduced in this paper. In LA-SALT, we replace the drift velocity of the stochastic vector field by its expected value. The remarkable property of LA-SALT is that the evolution of its higher moments are governed by deterministic equations. Our modelling approach is substantiated by establishing local existence results, first, for the deterministic climate model that couples compressible atmospheric equations to incompressible ocean equation, and second, for the two stochastic SALT and LA-SALT models.

[1]  Colin J. Cotter,et al.  A Particle Filter for Stochastic Advection by Lie Transport: A Case Study for the Damped and Forced Incompressible Two-Dimensional Euler Equation , 2020, SIAM/ASA J. Uncertain. Quantification.

[2]  Albert Y. Zomaya,et al.  Partial Differential Equations , 2007, Explorations in Numerical Analysis.

[3]  Darryl D. Holm,et al.  Data Assimilation for a Quasi-Geostrophic Model with Circulation-Preserving Stochastic Transport Noise , 2019, Journal of Statistical Physics.

[4]  Darryl D. Holm,et al.  Modelling the Climate and Weather of a 2D Lagrangian-Averaged Euler–Boussinesq Equation with Transport Noise , 2019, Journal of Statistical Physics.

[5]  Darryl D. Holm,et al.  Lagrangian Averaged Stochastic Advection by Lie Transport for Fluids , 2019, Journal of Statistical Physics.

[6]  T. N. Palmer,et al.  Stochastic weather and climate models , 2019, Nature Reviews Physics.

[7]  Darryl D. Holm,et al.  Implications of Kunita–Itô–Wentzell Formula for k-Forms in Stochastic Fluid Dynamics , 2019, Journal of Nonlinear Science.

[8]  Darryl D. Holm,et al.  Numerically Modeling Stochastic Lie Transport in Fluid Dynamics , 2019, Multiscale Model. Simul..

[9]  Peter Korn,et al.  A Regularity-Aware Algorithm for Variational Data Assimilation of an Idealized Coupled Atmosphere–Ocean Model , 2018, J. Sci. Comput..

[10]  Darryl D. Holm,et al.  Circulation and Energy Theorem Preserving Stochastic Fluids , 2018, Proceedings of the Royal Society of Edinburgh: Section A Mathematics.

[11]  Darryl D. Holm,et al.  Modelling uncertainty using stochastic transport noise in a 2-layer quasi-geostrophic model , 2018, Foundations of Data Science.

[12]  Darryl D. Holm,et al.  Solution Properties of a 3D Stochastic Euler Fluid Equation , 2017, J. Nonlinear Sci..

[13]  Darryl D. Holm Variational principles for stochastic fluid dynamics , 2014, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[14]  Vladimir Maz’ya,et al.  Sobolev Spaces: with Applications to Elliptic Partial Differential Equations , 2011 .

[15]  H. Dijkstra Nonlinear Physical Oceanography , 2010 .

[16]  Richard Kleeman,et al.  Stochastic theories for the irregularity of ENSO , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[17]  Byron Schmuland,et al.  Yamada-Watanabe theorem for stochastic evolution equations in infinite dimensions , 2008 .

[18]  G. Vallis Atmospheric and Oceanic Fluid Dynamics , 2006 .

[19]  T. Kurtz,et al.  Stochastic equations in infinite dimensions , 2006 .

[20]  A. Moore,et al.  A Comparison of the Influence of Additive and Multiplicative Stochastic Forcing on a Coupled Model of ENSO , 2005 .

[21]  Andrew J. Majda,et al.  A mathematical framework for stochastic climate models , 2001 .

[22]  Henk A. Dijkstra,et al.  Nonlinear Physical Oceanography: A Dynamical Systems Approach to the Large Scale Ocean Circulation and El Niño, , 2000 .

[23]  Olga Vechtomova,et al.  Stochastic Gravity , 1999, gr-qc/9902064.

[24]  Darryl D. Holm,et al.  The Euler–Poincaré Equations and Semidirect Products with Applications to Continuum Theories , 1998, chao-dyn/9801015.

[25]  P. Protter,et al.  Weak Limit Theorems for Stochastic Integrals and Stochastic Differential Equations , 1991 .

[26]  Suhung Shen,et al.  On the Dynamics of Intraseasonal Oscillations and ENSO , 1988 .

[27]  S. Zebiak Atmospheric convergence feedback in a simple model for El Niño , 1986 .

[28]  Mark A. Cane,et al.  Experimental forecasts of El Niño , 1986, Nature.

[29]  K. Lau,et al.  The 40-50 day oscillation and the El Niño/Southern Oscillation: a new perspective , 1986 .

[30]  M. Cane,et al.  A Theory for El Ni�o and the Southern Oscillation , 1985, Science.

[31]  S. Zebiak A simple atmospheric model of relevance to El Nino , 1982 .

[32]  A. Majda,et al.  Singular limits of quasilinear hyperbolic systems with large parameters and the incompressible limit , 1981 .

[33]  A. E. Gill Some simple solutions for heat‐induced tropical circulation , 1980 .

[34]  R. Haney Surface Thermal Boundary Condition for Ocean Circulation Models , 1971 .

[35]  J. Bjerknes ATMOSPHERIC TELECONNECTIONS FROM THE EQUATORIAL PACIFIC1 , 1969 .

[36]  A. Vlasov,et al.  The vibrational properties of an electron gas , 1967, Uspekhi Fizicheskih Nauk.

[37]  H. McKean,et al.  A CLASS OF MARKOV PROCESSES ASSOCIATED WITH NONLINEAR PARABOLIC EQUATIONS , 1966, Proceedings of the National Academy of Sciences of the United States of America.

[38]  M. Hp A class of markov processes associated with nonlinear parabolic equations. , 1966 .

[39]  J. Gillis,et al.  Probability and Related Topics in Physical Sciences , 1960 .

[40]  G. Burton Sobolev Spaces , 2013 .

[41]  K. Hasselmann,et al.  Stochastic climate models , Part I 1 Application to sea-surface temperature anomalies and thermocline variability , 2010 .

[42]  By,et al.  Some simple solutions for heat-induced tropical circulation , 2006 .

[43]  L. Arnold Hasselmann’s program revisited: the analysis of stochasticity in deterministic climate models , 2001 .

[44]  J. David Neelin,et al.  ENSO theory , 1998 .

[45]  École d'été de probabilités de Saint-Flour,et al.  Ecole d'été de probabilités de Saint-Flour XIX, 1989 , 1991 .

[46]  A. Sznitman Topics in propagation of chaos , 1991 .

[47]  B. Rozovskii Stochastic Evolution Systems , 1990 .

[48]  S. Kanemaki,et al.  A Theory for the , 1986 .

[49]  T. Matsuno,et al.  Quasi-geostrophic motions in the equatorial area , 1966 .