Skip to main content

Massively Parallel Simulations of Motions in a Gaussian Velocity Field

  • Chapter
Stochastic Modelling in Physical Oceanography

Part of the book series: Progress in Probability ((PRPR,volume 39))

Abstract

The purpose of the present note is to describe the details of a set of simulation tools which we developed in order to study the statistical properties of the solutions of the equation:

$$ d{{X}_{t}} = \vec{v}(t,{{X}_{t}})dt $$

when \( \{ \vec{v}(t,x);t0,x \in {{\mathbb{R}}^{2}}\} \) is a stationary and homogeneous Gaussian field with a spectrum of Kolmogorov type. The study is motivated by problems of transport of passive tracer particles at the surface of a two dimensional medium. We are mostly concerned with mathematical modeling of problems from oceanography and we think of the surface of the ocean as a physical medium to which our modeling efforts could apply. For this reason we shall sometimes use the terminology drifters for the passive tracers. The programs have been written for the MASPAR II. We describe the different forms of the simulations and we give numerical results which illustrate the transport properties of such a random medium. These results lead to the formulation of several precise mathematical conjectures which we discuss in the last section.

Partially supported by ONR N00014-91-1010

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. R.J. Adler (1980): Geometry of Random Fields. Wiley, New York, N.Y.

    Google Scholar 

  2. A. Antoniadis and R. Carmona (1985): Infinite Dimensional Ornstein Uhlenbeck Processes. Probab. Th. Rel. Fields 74, 31–54.

    Article  MathSciNet  Google Scholar 

  3. M. Avellaneda and A. Majda (1990): Mathematical models with exact renormalization for turbulent transport. Commun. Math. Phys., 131, 381–429.

    Article  MathSciNet  MATH  Google Scholar 

  4. M. Avellaneda and A. Majda (1991): An integral representation and bounds on the effective diffusivity in passive advection by laminar and turbulent flows. Commun. Math. Phys., 138, 339–391.

    Article  MathSciNet  MATH  Google Scholar 

  5. P.H. Baxendale (1986): Asymptotic Behavior of Stochastic Flows of Diffeomorphisms: Two Case Studies. Proba. Th. Rel. Fields 73, 51–85.

    Article  MathSciNet  MATH  Google Scholar 

  6. J.F. Buzy, E. Bacry and A. Arneodo (1992): Multifractal formalism for fractal signals: the structure function approach versus the wavelet transform modulus maxima method. (preprint)

    Google Scholar 

  7. R. Carmona (1995): Transport Properties of Gaussian Velocity Fields. First S.M.F. Winter School in Random Media. Rennes 1994. (to appear)

    Google Scholar 

  8. R. Carmona and J. P. Fouque (1994): Diffusion-Approximation for the Advection-Diffusion of a Passive Scalar by a Space-Time Gaussian Velocity Field. Proc. Intern. Conf. on SPDE’s, Ascona, June 1993. Birkhäuser, Basel.

    Google Scholar 

  9. R. Carmona, S. Grishin and S.A. Molchanov (1995): Analysis of Ornstein Uhlenbeck Stochastic Flows with Finite Frequency Content. (in preparation)

    Google Scholar 

  10. R. Carmona and A. Wang (1994): Comparison Tests for the Spectra of Dependent Multivariate Time Series. (this volume)

    Google Scholar 

  11. E. Cinlar and C.L. Zirbel (1994): Dispersion of Particle Systems in Brownian Flows. (preprint)

    Google Scholar 

  12. R. Davis (1992): Observing the general circulation with floats. Deep Sea Res. 38, S531–S571.

    Google Scholar 

  13. A. Grorud and D. Talay (1995): Lyapunov Exponents of Nonlinear Stochastic Differential Equations. SIAM J. Appl. Mat. (to appear).

    Google Scholar 

  14. H. Kunita (1990): Stochastic Flows and Stochastic Differential Equations. Cambridge Univ. Press. Boston, MA.

    MATH  Google Scholar 

  15. Y. Le Jan (1984): Equilibre et exposants de Lyapunov de certains flots browniens. C. R. Acad. Sci. Paris Ser. A 298, 361–364.

    MATH  Google Scholar 

  16. F. Elliott and A. Majda (1994): A wavelet Monte Carlo method for turbulent diffusion with many spatial scales. (preprint)

    Google Scholar 

  17. F. Elliott, A. Majda, D. Horntrop and R. McLaughlin (1994): Hierarchical Monte Carlo methods for fractal random fields. (preprint)

    Google Scholar 

  18. S.A. Molchanov (1994): Lectures on Random Media. in St Flour Summer School in Probability, Lect. Notes in Math. Springer Verlag (to appear)

    Google Scholar 

  19. D. Talay (1991): Appriximation of Upper Lyapunov Exponents of Bilinear Stochastic Differential Systems. SIAM J. Numer. Anal. 28(4), 1141–1164.

    Article  MathSciNet  MATH  Google Scholar 

  20. A.M. Yaglom (1987): Correlation Theory of Stationary and Related Random Functions. vol. I: Basic Results. Springer Verlag, New York, N.Y.

    Google Scholar 

  21. C.L. Zirbel (1993): Stochastic Flows: Dispersion of a Mass Distribution and Lagrangian Observations of a Random Field. Ph.D. Princeton.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Birkhäuser Boston

About this chapter

Cite this chapter

Carmona, R.A., Grishin, S.A., Molchanov, S.A. (1996). Massively Parallel Simulations of Motions in a Gaussian Velocity Field. In: Adler, R.J., Müller, P., Rozovskii, B.L. (eds) Stochastic Modelling in Physical Oceanography. Progress in Probability, vol 39. Birkhäuser Boston. https://doi.org/10.1007/978-1-4612-2430-3_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-4612-2430-3_2

  • Publisher Name: Birkhäuser Boston

  • Print ISBN: 978-1-4612-7533-6

  • Online ISBN: 978-1-4612-2430-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics