Sensitivity and Variability Redux in Hot-Jupiter Flow Simulations

TL;DR

This paper investigates the sensitivity and variability in hot-Jupiter atmospheric flow simulations, revealing that the application of physical drags and vertical resolution significantly influence the persistence of variability and model convergence.

Contribution

It demonstrates how different drag implementations and vertical resolutions affect flow sensitivity and variability in 3D hot-Jupiter simulations, providing insights into model setup effects.

Findings

Sensitivity persists without strong Rayleigh drag in the lower atmosphere.

Vertical resolution increase leads to significant variability due to planetary waves.

Physical setup and convergence issues influence deep atmosphere simulation results.

Abstract

We revisit the issue of sensitivity to initial flow and intrinsic variability in hot-Jupiter atmospheric flow simulations, originally investigated by Cho et al. (2008) and Thrastarson & Cho (2010). The flow in the lower region (~1 to 20 MPa) `dragged' to immobility and uniform temperature on a very short timescale, as in Liu & Showman (2013), leads to effectively a complete cessation of variability as well as sensitivity in three-dimensional (3D) simulations with traditional primitive equations. Such momentum (Rayleigh) and thermal (Newtonian) drags are, however, ad hoc for 3D giant planet simulations. For 3D hot-Jupiter simulations, which typically already employ strong Newtonian drag in the upper region, sensitivity is not quenched if only the Newtonian drag is applied in the lower region, without the strong Rayleigh drag: in general, both sensitivity and variability persist if the two drags are not applied concurrently in the lower region. However, even when the drags are applied concurrently, vertically-propagating planetary waves give rise to significant variability in the ~0.05 to 0.5 MPa region, if the vertical resolution of the lower region is increased (e.g. here with 1000 layers for the entire domain). New observations on the effects of the physical setup and model convergence in `deep' atmosphere simulations are also presented.