PSJC #188 April 3 2015

Boris Galperin (USF)

Anisotropic turbulence and zonal jets on giant planets, in the ocean and in a laboratory

Almost all planetary, oceanic and atmospheric flows feature eddies and zonal jets. Their relative strength and variability change from one flow to another but their basic physical foundation remains the same and goes back to the interaction between turbulence and waves. Turbulent flow regime is stipulated by very large Reynolds numbers on all planets while the waves arise from such factors as stable stratification, planetary rotation, and the variation of the Coriolis parameter with latitude due to the sphericity of a planet, i.e., a β-effect. The corresponding waves are known as Rossby waves. On large, planetary scales a β-effect is strong and causes turbulence anisotropization and formation of zonal jets.

In many situations, turbulence and Rossby waves co-exist and form fascinating jigsaw puzzles. Possible flow regimes can be classified by several characteristic length scales and their ratios. A regime of zonostrophic turbulence appears to be pertinent to giant planets of the solar system where zonal jets are powerful and long lived. This flow regime is characterized by a strongly anisotropic spectrum with different slopes in the zonal and nonzonal directions. Recently, this spectrum was established for Jupiter using the data collected by the Cassini spaceship. A similar spectrum was detected in computer simulations of the deep North Pacific Ocean thus pointing to the universality of physical laws that govern the oceanic and planetary circulations.

We created a westward zonal jet in a laboratory facility. Being maintained by the electromagnetic force, the jet was unstable and generated westward propagating eddies. The spectrum of the flow field was similar to those found on Jupiter and in the ocean both in slopes and amplitudes. Using the experimental data, we have designed an algorithm that allows one to diagnose the large-scale turbulence characteristics based upon a limited amount of data. This algorithm offers a great promise for diagnosing macroturbulence in large-scale planetary systems.