Information content on Venusian aerosols in VIRTIS-M infrared data
arXiv:2607.22187 · doi:10.1016/j.icarus.2026.117276
Abstract
Venus presents a complex cloud structure with aerosol particles of different sizes located mainly between 48 km and 70 km in altitude. However, the number of free parameters that can describe such a cloud structure is usually overwhelming, and a number of simplified parameterizations are commonly assumed. In this work, we re-analyze the information content on aerosol vertical distribution provided by the nightside infrared data collected by VIRTIS instrument onboard Venus Express. Starting from Haus et al. (2013) aerosol vertical distribution description, we use the archNEMESIS radiative transfer code and retrieval suite together with the Bayesian inference tool Multinest to compute the evidence supporting different models based on alternative choices of model parameters. This study analyzes locations at three different regions: mid-latitudes, the so-called cold collar, and the South Polar Vortex. We use a data cube that covers all of these regions simultaneously and additional observations distributed throughout the Venus Express mission. We find that these observations provide significant information about the peak particle number density, base altitude and layer thickness of aerosol modes 2, 2' and 3 when individual parameters are retrieved - a more informative description than the scaling `mode factors' often used in similar retrievals. Including mode 1 in our models, however, does not provide a significant increase of Bayesian evidence. Our retrieved cloud and temperature profiles are in general agreement with previous studies, although we find higher cloud tops in the South Polar Vortex locations. This initial computing effort provides an optimal parameterization that will allow us to study in greater detail the instantaneous horizontal cloud and temperature structure from the entire VIRTIS-M infrared database, which we will discuss in a forthcoming paper.
References in corpus (13)
- MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics
- X-ray spectral modelling of the AGN obscuring region in the CDFS: Bayesian model selection and catalogue
- Bayes in the sky: Bayesian inference and model selection in cosmology
- Six years of Venus winds at the upper cloud level from UV, visible and near infrared observations from VIRTIS on Venus Express
- Venus upper clouds and the UV-absorber from MESSENGER/MASCS observations
- Latitudinal Variation of Clouds' Structure Responsible for Venus' Cold Collar
- Significance Tests for Periodogram Peaks
- A chaotic long-lived vortex at Venus southern pole
- Instantaneous Three-dimensional Thermal Structure of the South Polar Vortex of Venus
- A model of scattered thermal radiation for Venus from 3 to 5 m
- Potential Vorticity of the South Polar Vortex of Venus
- The role of cloud particle properties on WASP-39b transmission spectrum based on JWST/NIRSpec observations
- archNEMESIS: an open-source Python package for analysis of planetary atmospheric spectra