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Title: Simulating Venus' Cloud Level Dynamics Using a Middle Atmosphere General Circulation Model
The atmosphere of Venus is characterized by strong superrotation, in which the wind velocities at cloud heights are around 60 times faster than the surface rotation rate. The reasons for this strong superrotation are still not well understood. Motions in the atmosphere below the thick cloud deck are hard to determine remotely and in-situ measurements of the circulation below 40 km altitude are scarce. No model to date has been able to simulate superrotating winds with magnitudes comparable with those measured by entry probes, in the dense atmosphere between the surface and the clouds. However, important information on the dynamics and circulation of Venus' atmosphere can be determined by studying the atmosphere at cloud levels, where there are significantly more measurements than in the sub-cloud region, including the many recent observations made during the Venus Express and Akatsuki missions. In this work we describe a new Venus Middle atmosphere general circulation Model (VMM) to study the dynamics of the atmosphere at cloud altitudes. The model simulates the atmosphere from just below cloud deck to around 95 km altitude. We present simulations using the VMM with a simplified Newtonian cooling radiation scheme. Sensitivity studies have been performed to determine the most appropriate values for model parameters and the model has been validated by comparison with observations, including those from Venus Express and Akatsuki. The validated model provides some constraints on parameters which are poorly measured close to the boundary such as the mean winds and temperatures, and provides a basis for further investigations of the dynamics of Venus' cloud-level atmosphere. In future studies we will also investigate the influence of atmospheric waves, such as Kelvin and Rossby waves, to determine the role they play in generating the poorly-understood cloud-level structure at all latitudes.  more » « less
Award ID(s):
1614762
PAR ID:
10081993
Author(s) / Creator(s):
Date Published:
Journal Name:
arXiv.org
ISSN:
2331-8422
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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