Venus Dynamics on the framework of Bepicolombo flyby to Venus and Akatsuki UVI coordinated observations with TNG HARPS-N observations

Introduction

One of the most crucial bases and tools in planetary sciences is the general circulation model of a planet’s atmosphere. These models come as a result of the analysis of great amounts of observations, in order to accurately describe the atmospheric circulation of a planet. For Venus, the better understanding of cloud circulation can yield important results such as the possibility to explain and describe one of its most fascinating characteristics: the superrotation of Venus’ atmosphere.

Methods and Tools

The cloud-tracking method consists of an analysis of a pair of navigated and processed images, provided that we know the time interval between both. It is possible to probe the motion of cloud features between the initial and second image, either by matching specific points or areas in both images.  This matching process allows us to measure displacements and velocities of cloud features and deduct the average velocity for a certain cloud layer of the atmosphere, selected in the wavelength range of the observations (Peralta et al. 2018).

The use of an evolved tool of cloud tracking based on phase correlation between images and other softwares (Hueso et al. 2010) allows to explore Venus' atmospheric dynamics based on coordinated space and ground observations including Akatsuki UVI instrument, TNG/HARPS-N, and data from BepiColombo’s first Venus' flyby. Images used were navigated and processed for optimal identification of cloud features which help with the matching processes described above.

The main goal of this work was to build wind profiles in different wavelengths which allow us to analyse several layers of the Venusian atmosphere. We present some results of this study following the works of Sánchez-Lavega et al. 2008, Hueso et al. 2013 and Horinouchi et al. 2018 and compare them with ground-based Doppler measurements (Machado et al. 2021).

The Doppler velocimetry method mentioned in this work was initially developed by Thomas Widemann (Widemann et al., 2008) and further evolved by Pedro Machado for both long slit and fibre-fed spectrographs, using UVES/VLT and ESPaDOnS/CFHT respectively (Machado et al., 2012, 2014).  This technique is based on solar light scattered on Venus’ dayside to provide instantaneous wind velocities measurements of its atmosphere. The sunlight is absorbed by cloud particles in Venus’ top clouds and then re-emitted in Earth’s direction in a single back-scatter approximation (Machado et al., 2012, 2014, 2017).   

Another goal of this study is connected to the detection and characterisation of atmospheric gravity waves. These waves are oscillatory disturbances on an atmospheric layer in which buoyancy acts as the restoring force. They can only exist in stably stratified atmospheres, that is, a fluid in which density varies mostly vertically (Silva et al. 2021).

Results

With this work we present new results of studies of zonal and meridional winds in both Venus’ hemispheres, using ground- and space-based coordinated observations. The wind velocities retrieved from space used an improved cloud-tracked technique and the results obtained from telescope observations were retrieved with a Doppler velocimetry method, both already described in “Methods and Tools”. There is evidence that the altitude level sensed by the Doppler velocimetry method is approximately four kilometres higher than that using ground-tracked winds which is shown by models which predict wind profiles developed at the Laboratoire de Meteorologie Dynamique (Machado et al. 2021).

 

References

[1] Hueso et al., The Planetary Laboratory for Image Analysis (PLIA). Advances in Space Research, 46(9):1120–1138, 2010. 

[2] Sánchez-Lavega et al., Variable winds on Venus mapped in three dimensions. Geophysical Research Letters, 35 (13), 2008

[3] Hueso et al., Venus winds from ultraviolet, visible and near infrared images from the VIRTIS instrument on Venus Express.  2013.

[4] Horinouchi et al., Mean winds at the cloud top of venus obtained from two-wavelength UV imaging by Akatsuki. Earth, Planets and Space, 70:10, 2018.

[7] Machado et al., Characterizing the atmospheric dynamics of Venus from ground-based Doppler velocimetry, Icarus, Volume 221, p.248-261, 2012.

[6] Machado et al., Wind circulation regimes at Venus’ cloud tops: Ground-based Doppler velocimetry using CFHT/ESPaDOnS and comparison with simultaneous cloud tracking measurements using VEx/VIRTIS in February 2011, Icarus, 2014.

[7] Machado et al., Venus Atmospheric Dynamics at Two Altitudes: Akatsuki and Venus Express Cloud Tracking, Ground-Based Doppler Observations and Comparison with Modelling. Atmosphere 2021, 12, 506.

[8] Machadoet al., Venus cloud-tracked and Doppler velocimetry winds from CFHT/ESPaDOnS and Venus Express/VIRTIS in April 2014. Icarus, vol. 285, p. 8-26, 2017.

[9] Peralta et al., Nightside Winds at the Lower Clouds of Venus with Akatsuki/IR2: Longitudinal, Local Time, and Decadal Variations from Comparison with Previous Measurements. The American Astronomical Society. The Astrophysical Journal Supplement Series, Volume 239, Number 2, 2018

[10] Widemann et al., Venus Doppler winds at cloud tops observed with ESPaDOnS at CFHT, Planetary and Space Science, Volume 56, p. 1320-1334, 2008.

[11] Silva et al., Characterising atmospheric gravity waves on the nightside lower clouds of Venus: a systematic analysis, A&A 649 A34, 2021.

 

Acknowledgements

We thank the JAXA’s Akatsuki team for support with coordinated observations. We gratefully acknowledge the collaboration of the TNG staff at La Palma (Canary Islands, Spain) - the observations were made with the Italian Telescopio Nazionale Galileo (TNG) operated on the island of La Palma by the Fundación Galileo Galilei of the INAF (Istituto Nazionale di Astrofisica) at the Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias. We acknowledge support from the Portuguese Fundação Para a Ciência e a Tecnologia (ref. PTDC/FIS-AST/29942/2017) through national funds and by FEDER through COMPETE 2020 (ref. POCI-01-0145 FEDER-007672) and through a grant of reference 2020.06389.BD.