AI 中文总结
研究利用金星快车VIRTIS仪器夜间红外数据，通过archNEMESIS代码、Multinest工具重新分析金星气溶胶垂直分布信息，分析三个区域，发现能获取气溶胶模式2、2'和3相关信息，提供最佳参数化，为后续研究做准备。
AI 中文摘要
金星呈现出复杂的云结构，气溶胶颗粒大小各异，主要位于海拔48公里至70公里之间。通常描述这种云结构的自由参数数量众多，因此常采用一些简化的参数化方法。本文重新分析了金星快车VIRTIS仪器在夜间收集的红外数据中气溶胶垂直分布的信息含量。从豪斯等人（2013年）的气溶胶垂直分布描述出发，使用archNEMESIS辐射传输代码和检索套件以及贝叶斯推理工具Multinest，基于模型参数的替代选择计算支持不同模型的证据。研究分析了三个不同区域：中纬度、所谓的冷环和南极涡旋。使用一个同时覆盖所有这些区域的数据立方体以及金星快车任务期间分布的其他观测数据。发现这些观测数据在单独检索各个参数时，提供了关于气溶胶模式2、2'和3的峰值粒子数密度、底部高度和层厚度的重要信息，比类似检索中常用的缩放“模式因子”更具信息量。然而，在模型中包含模式1并没有显著增加贝叶斯证据。检索到的云和气温度剖面与先前的研究总体一致，尽管在南极涡旋位置发现了更高的云顶。这项初步计算工作提供了一个最佳参数化，将使我们能够从整个VIRTIS-M红外数据库中更详细地研究瞬时水平云和气温度结构，这将在后续论文中讨论。
英文摘要
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.
DOI：10.1016/j.icarus.2026.117276
