Fractional Brownian motion, the Matérn process, and stochastic modeling of turbulent dispersion

Lilly, Jonathan M.; Sykulski, Adam M.; Early, Jeffrey J.; Olhede, Sofia C.

doi:https://doi.org/10.5194/npg-24-481-2017

Articles | Volume 24, issue 3

https://doi.org/10.5194/npg-24-481-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/npg-24-481-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 24, issue 3

Research article

|

21 Aug 2017

Research article |

| 21 Aug 2017

Fractional Brownian motion, the Matérn process, and stochastic modeling of turbulent dispersion

Jonathan M. Lilly, Adam M. Sykulski, Jeffrey J. Early, and Sofia C. Olhede

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Final revised paper (published on 21 Aug 2017)
Supplement to the final revised paper
Preprint (discussion started on 28 Mar 2017)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review', Peter Ditlevsen, 19 Apr 2017
- AC1: 'Response to Reviewer 1', Jonathan Lilly, 05 Jul 2017
RC2: 'Comments on 'Fractional Brownian motion, the Matérn process, and stochastic modeling of turbulent dispersion'', Anonymous Referee #2, 11 May 2017
- AC2: 'Response to Reviewer 2', Jonathan Lilly, 05 Jul 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Jonathan Lilly on behalf of the Authors (05 Jul 2017) Author's response Manuscript

ED: Publish as is (08 Jul 2017) by Stéphane Vannitsem

AR by Jonathan Lilly on behalf of the Authors (08 Jul 2017) Author's response Manuscript

Short summary

This work arose from a desire to understand the nature of particle motions in turbulence. We sought a simple conceptual model that could describe such motions, then realized that this model could be applicable to an array of other problems. The basic idea is to create a string of random numbers, called a stochastic process, that mimics the properties of particle trajectories. This model could be useful in making best use of data from freely drifting instruments tracking the ocean currents.