Decoupling Jupiter's deep and atmospheric flows using the upcoming Juno gravity measurements and a dynamical inverse model

TL;DR

This paper presents a dynamical inverse model to decouple and analyze Jupiter's deep interior flows from the observable cloud-level winds using upcoming Juno gravity data, allowing for complex flow scenarios.

Contribution

It introduces a flexible adjoint inverse modeling approach to distinguish shallow and deep flows in Jupiter, accommodating various hypothetical deep flow structures.

Findings

Model can reconstruct deep and surface flows from gravity data.

Allows exploration of scenarios where deep flow dominates surface winds.

Provides a framework for integrating new observations and physical constraints.

Abstract

Observations of the flow on Jupiter exists essentially only for the cloud-level, which is dominated by strong east-west jet-streams. These have been suggested to result from dynamics in a superficial thin weather-layer, or alternatively be a manifestation of deep interior cylindrical flows. However, it is possible that the observed winds are indeed superficial, yet there exists deep flow that is completely decoupled from it. To date, all models linking the wind, via the induced density anomalies, to the gravity field, to be measured by Juno, consider only flow that is a projection of the observed could-level wind. Here we explore the possibility of complex wind dynamics that include both the shallow weather-layer wind, and a deep flow that is decoupled from the flow above it. The upper flow is based on the observed cloud-level flow and is set to decay with depth. The deep flow is constructed to produce cylindrical structures with variable width and magnitude, thus allowing for a wide range of possible scenarios for the unknown deep flow. The combined flow is then related to the density anomalies and gravitational moments via a dynamical model. An adjoint inverse model is used for optimizing the parameters controlling the setup of the deep and surface-bound flows, so that these flows can be reconstructed given a gravity field. We show that the model can be used for examination of various scenarios, including cases in which the deep flow is dominating over the surface wind. We discuss extensively the uncertainties associated with the model solution. The flexibility of the adjoint method allows for a wide range of dynamical setups, so that when new observations and physical understanding will arise, these constraints could be easily implemented and used to better decipher Jupiter flow dynamics.