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Abstract:

The L’Ralph instrument is a key component of NASA’s Lucy mission, intended to provide spectral image data of multiple Jupiter Trojans. The instrument operates from ∼0.35 to 4 μm using two focal plane assemblies: a 350–950 nm multispectral imager, Multi-spectral Visible Imaging Camera (MVIC), and a 0.97–4 μm imaging spectrometer, Linear Etalon Imaging Spectral Array (LEISA). Instrument calibration was established through ground testing before launch and has been monitored during cruise utilizing internal calibration sources and stellar targets. In-flight data have shown that the instrument thermal performance is exceeding expectations, allowing for early updates to LEISA radiometric and pointing calibrations. MVIC radiometric performance remains stable more than 3 yr since launch. The serendipitous identification of a new flyby target, (152830) Dinkinesh, allowed testing of instrument performance and interleaved LEISA and MVIC acquisitions on an asteroid target. Both MVIC and LEISA obtained data of Dinkinesh and its moon, Selam, demonstrating that they show good spectral agreement with an S- or Sq-type asteroid, along with evidence of a 3 μm absorption feature.

Abstract:

<jats:p>Voyager-2 radio occultation measurements have revealed changes in the atmospheric refractivity within a 2-4 km layer near the 1.2-bar level in Uranus and the 1.6-bar level in Neptune. These changes were attributed to the presence of a methane cloud, consistent with the observation that methane concentration decreases with altitude above these levels, closely following the saturation vapor pressure. However, no clear spectral signatures of such a cloud have been detected thus far in the spectra acquired from both planets. We examine methane cloud properties in the atmospheres of the ice giants, including vertical ice distribution, droplet radius, precipitation rates, timescales, and total opacity, employing microphysical simulations under different scenarios. We used a one-dimensional (1D) cloud microphysical model to simulate the formation of methane clouds in the ice giants. The simulations include the processes of nucleation, condensation, coagulation, evaporation, and precipitation, with vertical mixing simulated using an eddy-diffusion profile (K_eddy). Our simulations show cloud bases close to 1.24 bars in Uranus and 1.64 bars in Neptune, with droplets up to 100 μm causing high settling velocities and precipitation rates (∼370 mm per Earth year). The high settling velocities limit the total cloud opacity, yielding values at 0.8 μm of ∼0.19 for Uranus and ∼0.35 for Neptune, using K_ eddy = 0.5 m^2 s^-1 and a deep methane mole fraction (μ_CH_4) of 0.04. In addition, lower K_ eddy or μ_CH_4 values result in smaller opacities. Methane supersaturation is promptly removed by condensation, controlling the decline in μ_CH_4 with altitude in the troposphere. However, the high settling velocities prevent the formation of a permanent thick cloud. Stratospheric hazes made of ethane or acetylene ice are expected to evaporate completely before reaching the methane condensation level. Since hazes are required for methane heterogeneous nucleation, this suggests either a change in the solid phase properties of the haze particles, inhibiting evaporation, or the presence of photochemical hazes.</jats:p>

Abstract:

Ground test data from the Lunar Thermal Mapper instrument. Described in Bowles et al. 2025 submitted to JGR Planets.

Abstract:

ArchNEMESIS is an open-source Python package developed for the analysis of remote sensing spectroscopic observations of planetary atmospheres. It is based on the widely used NEMESIS radiative transfer and retrieval tool, which has been extensively used for the investigation of a wide variety of planetary environments. The main goal of archNEMESIS is to provide the capabilities of its Fortran-based predecessor, keeping or exceeding the efficiency in the calculations, and benefitting from the advantages Python tools provide in terms of usability and portability. ArchNEMESIS enables users to compute synthetic spectra for a wide variety of planetary atmospheres, 91̽»¨ing multiple spectral ranges, viewing geometries (e.g., nadir, limb, and solar occultation), and radiative transfer scenarios, including multiple scattering. Furthermore, it provides tools to fit observed spectra and retrieve atmospheric and surface parameters using both optimal estimation and nested sampling retrieval schemes. The code, stored in a public GitHub repository under a GPL-v3.0 license, is accompanied by detailed documentation available at https://archnemesis.readthedocs.io/.

Abstract: