Jupiter's Turbulent Power Spectra From Hubble Space Telescope

Abstract

Turbulence in Jupiter's atmosphere was investigated with archival and ongoing observations from the Hubble Space Telescope. Data sets that include one full rotation (360° longitude coverage) were used to produce complete maps of the planet's upper cloud layer. The global maps were analyzed to generate the passive tracer power spectrum of cloud features for single rotation observations, while successive rotations produced pairs of maps such that zonal winds were calculated. An atmosphere's dimensionality and dynamics are reflected in the slopes of such turbulent power spectra. Many of the retrieved passive tracer power spectra have a shallow spectral index over wave numbers k∼1 − 30 and transition to the well‐known Kolmogorov k−5/3 relation at smaller scales between wave numbers k∼30 − 1,000. The transition scale is similar to the number of jets in Jupiter's zonal wind profile and is related to the Rhines scale and the beta effect induced anisotropy scale. We also report on differences found in anticyclonic and cyclonic shear region power spectra and how they correlate to latitudinal changes in the zonal wind profile. We found that properties of Jupiter's power spectra are consistent with quasi‐geostrophic turbulence for shallow fluids.

Turbulence Power Spectra in Regions Surrounding Jupiter's South Polar Cyclones From Juno/JIRAM

“…The values of the Rhines scale calculated from our results are in the range k~1-1.5 × 10 −4 , corresponding to an interval~2-8 in terms of zonal wave numberk z ¼ 2πR φ ð Þcos φ ð Þ 1=k. These values are very different from the ones reported inCosentino et al (2019) and…”

“…However, it should be noted that both the slopes, and consequently, the position of k f , depends on the value of the best‐fit starting point. This dependence has been noted also by Cosentino et al (2019) who investigate it by carrying out a sensitivity study on the dependence of the position of the transition in slopes on the k initial value. Future analyses will benefit from their detailed study.…”

“…The dynamics at the root of this configuration, which is unique in the Solar System, are not yet completely understood, though certain recent studies provide some hint of the possible underlying mechanisms (Brueshaber et al, 2019;Reinaud, 2019). Power spectral analysis previously has been used to study aspects of the dynamical mechanisms operating at various scales on cloud patterns of various planetary atmospheres ( Barrado-Izagirre et al, 2009;Choi & Showman, 2011;Cosentino et al, 2017Cosentino et al, , 2019Harrington et al, 1996;Peralta et al, 2007;Travis, 1978;Young & Read, 2017). Power spectral density is a practical way to capture the statistics of cloud fields over several wave number scales and can quantify the type of turbulence acting in the atmosphere by describing the distribution of energy at various scales across the Fourier components.…”

“…The study of atmospheric kinetic energy transfer, implicit in the power spectrum, generally requires the wind field measurement to have an accuracy better than 5 m/s (Sada et al, 1996;Travis, 1978), a goal that is very difficult to achieve over large areas by the instruments onboard current space missions. However, the connection between power spectra of cloud opacities/albedo and those of atmospheric kinetic energy, empirically established by Travis (1978), has been assumed in many previous studies (Barrado-Izagirre et al, 2009;Choi & Showman, 2011;Cosentino et al, 2017Cosentino et al, , 2019Harrington et al, 1996;Peralta et al, 2007;Young & Read, 2017).…”

Distributed chaos of the atmospheric tracers

“…Complete maps of Jupiter's upper cloud layer obtained using the Hubble Space Telescope (at optical wavelengths) were reported in recent Ref. [24]. The observed global Jupiter's maps were then used in the Ref.…”