Astronomy & Astrophysics (A&A) is an international journal which publishes papers on all aspects of astronomy and astrophysics

Thermal inertia and albedo provide information on the distribution of surface materials on Mars. These parameters have been mapped globally on Mars by the Thermal Emission Spectrometer (TES) onboard the Mars Global Surveyor. Two-dimensional clusters of thermal inertia and albedo reflect the thermophysical attributes of the dominant materials on the surface. In this paper three automated, non-deterministic, algorithmic classification methods are employed for defining thermophysical units: Expectation Maximisation of a Gaussian Mixture Model; Iterative Self-Organizing Data Analysis Technique (ISODATA); and Maximum Likelihood. We analyse the behaviour of the thermophysical classes resulting from the three classifiers, operating on the 2007 TES thermal inertia and albedo datasets. Producing a rigorous mapping of thermophysical classes at ~3 km/pixel resolution remains important for constraining the geologic processes that have shaped the Martian surface on a regional scale, and for choosing appropriate landing sites. The results from applying these algorithms are compared to geologic maps, surface data from lander missions, features derived from imaging, and previous classifications of thermophysical units which utilized manual (and potentially more time consuming) classification methods. These comparisons comprise data suitable for validation of our classifications. Our work shows that a combination of the algorithms—ISODATA and Maximum Likelihood—optimises the sensitivity to the underlying dataspace, and that new information on Martian surface materials can be obtained by using these methods. We demonstrate that the algorithms used here can be applied to define a finer partitioning of albedo and thermal inertia for a more detailed mapping of surface materials, grain sizes and thermal behaviour of the Martian surface and shallow subsurface, at the ~3 km scale.

The abundance of SO dimers (SO)₂ in the upper atmosphere of Venus and their implications for the enigmatic ultraviolet absorption has been investigated in several studies over the past few years. However, the photochemistry of sulfur species in the upper atmosphere of Venus is still not well understood and the identity of the missing ultraviolet absorber(s) remains unknown. Here we update an existing photochemical model of Venus’ upper atmosphere by including the photochemistry of SO dimers. Although the spectral absorption profile of SO dimers fits the unknown absorber, their abundance is found to be too low for them to contribute significantly to the absorption. It is more likely that their photolysis and/or reaction products could contribute more substantively. Reactions of SO dimers are found to be important sources of S₂O, and possibly higher order S_nO species and polysulfur, S_n. All of these species absorb in the critical ultraviolet region and are expected to be found in both the aerosol and gas phase. indicating that in-situ high resolution aerosol mass spectrometry might be a useful technique for identifying the ultraviolet absorber on Venus.

A full diurnal measurement of stratospheric column NO₂ has been made over the Jet Propulsion Laboratory's Table Mountain Facility (TMF) located in the mountains above Los Angeles, California, USA (2.286 km above mean sea level, 34.38^∘ N, 117.68^∘ W). During a representative week in October 2018, a grating spectrometer measured the telluric NO₂ absorptions in direct solar and lunar spectra. The stratospheric column NO₂ is retrieved using a modified minimum-amount Langley extrapolation, which enables us to accurately treat the non-constant NO₂ diurnal cycle abundance and the effects of tropospheric pollution near the measurement site. The measured 24 h cycle of stratospheric column NO₂ on clean days agrees with a 1-D photochemical model calculation, including the monotonic changes during daytime and nighttime due to the exchange with the N₂O₅ reservoir and the abrupt changes at sunrise and sunset due to the activation or deactivation of the NO₂ photodissociation. The observed daytime NO₂ increasing rate is $(\mathrm{1.34}\pm \mathrm{0.24})\times {\mathrm{10}}^{\mathrm{14}}$ cm⁻² h⁻¹. The observed NO₂ in one of the afternoons during the measurement period was much higher than the model simulation, implying the influence of urban pollution from nearby counties. A 24 h back-trajectory analysis shows that the wind first came from inland in the northeast and reached southern Los Angeles before it turned northeast and finally arrived at TMF, allowing it to pick up pollutants from Riverside County, Orange County, and downtown Los Angeles.