Turbulent Cloud Structure and Power Spectrum from 23 years of HST Observations
Abstract
Images of Jupiter’s clouds show that turbulence is a ubiquitous phenomenon over many orders of scale size. According to Kolmogorov’s theory for turbulence, the frequency/distribution of clouds at various scales can be used to produce an energy power spectrum of a passive tracer. Kolmogorov theory predicts the spectral slopes for “shallow” and “deep” fluids in motion by following how energy is injected and dissipated in the fluid. We are quantifying the turbulent nature of Jupiter’s clouds over 23 years of Hubble Space Telescope (HST) observations using an algorithm first presented in Choi and Showman (2011, Icarus 216). We applied the power spectrum fitting algorithm to a variety of filters from available HST data and tested its sensitivity to free parameters and compare our results to Choi and Showman (2011). We will comment on the evidence for a 2D turbulent regime In Jupiter’s clouds and will report on empirical values found in the spectra and their physical interpretations, such as the Rhines scale. We also will report on the behavior of the passive tracer power spectrum and trends that exist over time for different latitudinal regions, primarily the belts and zones and the north and south equatorial belts.
- Publication:
-
American Astronomical Society Meeting Abstracts #231
- Pub Date:
- January 2018
- Bibcode:
- 2018AAS...23114406C