Statistical mechanics of two-dimensional and geophysical flows

Physics – Fluid Dynamics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

The theoretical study of the self-organization of two-dimensional and geophysical turbulent flows is addressed based on statistical mechanics methods. This review is a self-contained presentation of classical and recent works on this subject; from the statistical mechanics basis of the theory up to applications to Jupiter's troposphere and ocean vortices and jets. Emphasize has been placed on examples with available analytical treatment in order to favor better understanding of the physics and dynamics. The equilibrium microcanonical measure is built from the Liouville theorem. On this theoretical basis, we predict the output of the long time evolution of complex turbulent flows as statistical equilibria. This is applied to make quantitative models of two-dimensional turbulence, the Great Red Spot and other Jovian vortices, ocean jets like the Gulf-Stream, and ocean vortices. We also present recent results for non-equilibrium situations, for the studies of either the relaxation towards equilibrium or non-equilibrium steady states.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Statistical mechanics of two-dimensional and geophysical flows does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Statistical mechanics of two-dimensional and geophysical flows, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Statistical mechanics of two-dimensional and geophysical flows will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-685656

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.