Venus has no seasons, slow rotation and a very massive atmosphere, which is mainly carbon dioxide with clouds primarily of sulphuric acid droplets. Infrared observations by previous missions to Venus revealed a bright 'dipole' feature surrounded by a cold 'collar' at its north pole. The polar dipole is a 'double-eye' feature at the centre of a vast vortex that rotates around the pole, and is possibly associated with rapid downwelling. The polar cold collar is a wide, shallow river of cold air that circulates around the polar vortex. One outstanding question has been whether the global circulation was symmetric, such that a dipole feature existed at the south pole. Here we report observations of Venus' south-polar region, where we have seen clouds with morphology much like those around the north pole, but rotating somewhat faster than the northern dipole. The vortex may extend down to the lower cloud layers that lie at about 50 km height and perhaps deeper. The spectroscopic properties of the clouds around the south pole are compatible with a sulphuric acid composition.

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We propose an innovative workflow based on the complementary use of Rayleigh waves alongside standard P-wave refraction tomography, which better depicts the shallow part of the near-surface P-wave velocity model. Our surface-wave processing sequence led to an S-wave near-surface velocity field that can be used as a constraint for P-wave tomography and can improve P-wave statics determination. Rayleigh waves are processed in three steps. The first step consists of an accurate frequency-dependent traveltime measurement for each selected source-receiver pair in which the phase difference between two adjacent traces is used to derive the phase velocity. Then, a frequency-dependent surface-wave velocity tomography is performed from the picked traveltimes. Finally, after surface-wave tomography, the frequency-dependent phase velocity volume output by the tomography is inverted to deliver an S-wave near-surface velocity model. This model is used to constrain the first-arrival P-wave tomography. To illustrate our method, we use a 3D narrow-azimuth land data set, acquired along a river valley. Strong lateral velocity variations exist in the shallow part, with slow velocities around the unconsolidated sediments of the riverbed and faster velocities in the consolidated sediments of the surrounding hills. A combined first-arrival tomography using the S-wave velocity model, the initial unconstrained refracted P-wave velocity model, and the original first arrivals is used to obtain a more accurate near-surface P-wave velocity model. This new approach led to a constrained P-wave velocity model from which primary statics are derived and then applied, leading to an improved image with better focusing and continuity of thin layers in the shallowest part.

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