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Oxygen is the most common element after hydrogen and helium in Jupiter’s atmosphere, and may have been the primary condensable (as water ice) in the protoplanetary disk. Prior to the Juno mission, in situ measurements of Jupiter’s water abundance were obtained from the Galileo probe, which dropped into a meteorologically anomalous site. The findings of the Galileo probe were inconclusive because the concentration of water was still increasing when the probe ceased sending data. Here we report on the water abundance in the equatorial region (0 to 4 degrees north latitude), based on data taken at 1.25 to 22 GHz from the Juno microwave radiometer, probing pressures of approximately 0.7 to 30 bar. Because Juno discovered the deep atmosphere to be surprisingly variable as a function of latitude, it remains to confirm whether the equatorial abundance represents Jupiter’s global water abundance. The water abundance at the equatorial region is inferred to be 2 . 5 − 1.6 + 2.2 × 1 0 3 ppm, or 2 . 7 − 1.7 + 2.4 times the elemental ratio of protosolar oxygen to hydrogen (1 σ uncertainties). If this reflects the global water abundance, the result suggests that the planetesimals that formed Jupiter were unlikely to have been water-rich clathrate hydrates. Juno’s microwave radiometer data could measure the water concentration in the deep atmosphere of Jupiter (0.7 to 30 bar) at the equator: 2 . 7 − 1.7 + 2.4 times the solar O/H abundance, with a thermal vertical structure compatible with a moist adiabat.

Juno's microwave radiometer experiment (MWR) provided the first spatially resolved observations beneath the surface of Ganymede's ice shell. The results indicate that scattering is a significant component of the observed brightness temperature, which is a combination of the upwelling ice emission and reflected emission from the sky and from Jupiter's synchrotron emission (Brown et al., 2023). Retrieval of the sub‐surface ice temperature profile requires that these confounding signals are estimated and removed to isolate the thermal signature of the ice. We present data analysis and model results to estimate the reflected synchrotron emission component. Our results indicate reflected emission over a broad range of observed angles, due to surface roughness and internal scattering. Based on viewing geometry, direct specular reflection from a smooth surface at a narrow angle is not observed. A microwave‐reflective medium is indicated, that is, a very rough surface and/or non‐homogeneous subsurface. Plain Language Summary On 7 June 2021, Juno had a close flyby of Jupiter's moon Ganymede, flying approximately 1,000 km above the surface. During the flyby, Juno's six channel Microwave Radiometer (MWR) mapped a portion of Ganymede, providing the first resolved observations of Ganymede's sub‐surface ice shell. The observed brightness temperature is composed of upwelling thermal emission from the ice shell and reflected radiation from the sky and from Jupiter's synchrotron emission. To study the sub‐surface ice shell temperature profile, we present data analysis and model results to estimate the reflected radiation component. The radiation is reflected diffusively by a very rough surface and/or non‐homogeneous subsurface. Key Points Reflected radiation from the sky and from Jupiter's synchrotron is an important component for Juno microwave radiometer experiment (MWR) observations at 0.6 and 1.2 GHz Absence of specular reflection indicating that Ganymede has a rough surface Reflections originate mostly from internal scattering

NASA's Juno spacecraft has been monitoring Jupiter in 53‐day orbits since 2016. Its six‐frequency microwave radiometer (MWR) is designed to measure black body emission from Jupiter over a range of pressures from a few tenths of a bar to several kilobars in order to retrieve details of the planet's atmospheric composition, in particular, its ammonia and water abundances. A key step toward achieving this goal is the determination of the latitudinal dependence of the nadir brightness temperature and limb darkening of Jupiter's thermal emission through a deconvolution of the measured antenna temperatures. We present a formulation of the deconvolution as an optimal estimation problem. It is demonstrated that a quadratic expression is sufficient to model the angular dependence of the thermal emission for the data set used to perform the deconvolution. Validation of the model and results from a subset of orbits favorable for MWR measurements is presented over a range of latitudes that cover up to 60° from the equator. A heuristic algorithm to mitigate the effects of nonthermal emission is also described. Plain Language Summary One of the instruments on the Juno spacecraft that is currently orbiting Jupiter every 53 days is the microwave radiometer (MWR). It has been sensing the atmosphere for the first time over a wide range of depths below the top‐most clouds, covering pressures from less than the Earth's surface pressure to several thousand times that value. This enables a deeper exploration than ever before of how winds distribute gases that can condense, such as water (as in the Earth's atmosphere) and ammonia (which forms Jupiter's highest level clouds). One challenge in understanding the MWR data is to convert each of its raw measurements into an estimate of the true brightness temperature of Jupiter as though it were observed in a perfect, narrow beam, a process known as a deconvolution. We determined that this correction for the angular dependence can be done reliably with a three‐term (quadratic) expression. The results of this approach have formed the basis of all of the analysis of MWR data to date, and we show some of the intriguing results from orbits that allowed for the best MWR observing geometry over latitudes that cover up to 60° from the equator. Key Points A method to deconvolve Jupiter's thermal emission measured by the Juno microwave radiometer is presented and validated Deconvolved nadir brightness temperatures and limb darkening results are presented for Juno observations between July 2016 and April 2018

The Juno spacecraft provides unique close-up views of Jupiter underneath the synchrotron radiation belts while circling Jupiter in its 53-day orbits. The microwave radiometer (MWR) onboard measures Jupiter thermal radiation at wavelengths between 1.37 and 50 cm, penetrating the atmosphere to a pressure of a few hundred bars and greater. The mission provides the first measurements of Jupiter's deep atmosphere, down to ~250 bars in pressure, constraining the vertical distributions of its kinetic temperature and constituents. As a result, vertical structure models of Jupiter's atmosphere may now be tested by comparison with MWR data. Taking into account the MWR beam patterns and observation geometries, we test several published Jupiter atmospheric models against MWR data. Our residual analysis confirms Li et al.'s (2017, https://doi.org/10.1002/2017GL073159) result that ammonia depletion persists down to 50–60 bars where ground-based Very Large Array was not able to observe. We also present an extension of the study that iteratively improves the input model and generates Jupiter brightness temperature maps which best match the MWR data. A feature of Juno's north-to-south scanning approach is that latitudinal structure is more easily obtained than longitudinal, and the creation of optimum two-dimensional maps is addressed in this approach.

Lightning has been detected on Jupiter by all visiting spacecraft through night-side optical imaging and whistler (lightning-generated radio waves) signatures 1 – 6 . Jovian lightning is thought to be generated in the mixed-phase (liquid–ice) region of convective water clouds through a charge-separation process between condensed liquid water and water-ice particles, similar to that of terrestrial (cloud-to-cloud) lightning 7 – 9 . Unlike terrestrial lightning, which emits broadly over the radio spectrum up to gigahertz frequencies 10 , 11 , lightning on Jupiter has been detected only at kilohertz frequencies, despite a search for signals in the megahertz range 12 . Strong ionospheric attenuation or a lightning discharge much slower than that on Earth have been suggested as possible explanations for this discrepancy 13 , 14 . Here we report observations of Jovian lightning sferics (broadband electromagnetic impulses) at 600 megahertz from the Microwave Radiometer 15 onboard the Juno spacecraft. These detections imply that Jovian lightning discharges are not distinct from terrestrial lightning, as previously thought. In the first eight orbits of Juno, we detected 377 lightning sferics from pole to pole. We found lightning to be prevalent in the polar regions, absent near the equator, and most frequent in the northern hemisphere, at latitudes higher than 40 degrees north. Because the distribution of lightning is a proxy for moist convective activity, which is thought to be an important source of outward energy transport from the interior of the planet 16 , 17 , increased convection towards the poles could indicate an outward internal heat flux that is preferentially weighted towards the poles 9 , 16 , 18 . The distribution of moist convection is important for understanding the composition, general circulation and energy transport on Jupiter. Observations of broadband emission from lightning on Jupiter at 600 megahertz show a lightning discharge mechanism similar to that of terrestrial lightning and indicate increased moist convection near Jupiter’s poles.

The Radar for Europa Assessment and Sounding: Ocean to Near-surface (REASON) is a dual-frequency ice-penetrating radar (9 and 60 MHz) onboard the Europa Clipper mission. REASON is designed to probe Europa from exosphere to subsurface ocean, contributing the third dimension to observations of this enigmatic world. The hypotheses REASON will test are that (1) the ice shell of Europa hosts liquid water, (2) the ice shell overlies an ocean and is subject to tidal flexing, and (3) the exosphere, near-surface, ice shell, and ocean participate in material exchange essential to the habitability of this moon. REASON will investigate processes governing this material exchange by characterizing the distribution of putative non-ice material (e.g., brines, salts) in the subsurface, searching for an ice–ocean interface, characterizing the ice shell’s global structure, and constraining the amplitude of Europa’s radial tidal deformations. REASON will accomplish these science objectives using a combination of radar measurement techniques including altimetry , reflectometry , sounding , interferometry , plasma characterization , and ranging . Building on a rich heritage from Earth, the moon, and Mars, REASON will be the first ice-penetrating radar to explore the outer solar system. Because these radars are untested for the icy worlds in the outer solar system, a novel approach to measurement quality assessment was developed to represent uncertainties in key properties of Europa that affect REASON performance and ensure robustness across a range of plausible parameters suggested for the icy moon. REASON will shed light on a never-before-seen dimension of Europa and – in concert with other instruments on Europa Clipper – help to investigate whether Europa is a habitable world.

Oxygen is the most common element after hydrogen and helium in Jupiter's atmosphere, and may have been the primary condensable (as water ice) in the protoplanetary disk. Prior to the Juno mission, in situ measurements of Jupiter's water abundance were obtained from the Galileo Probe, which dropped into a meteorologically anomalous site. The findings of the Galileo Probe were inconclusive because the concentration of water was still increasing when the probe died. Here, we initially report on the water abundance in the equatorial region, from 0 to 4 degrees north latitude, based on 1.25 to 22 GHz data from Juno Microwave radiometer probing approximately 0.7 to 30 bars pressure. Because Juno discovered the deep atmosphere to be surprisingly variable as a function of latitude, it remains to confirm whether the equatorial abundance represents Jupiter's global water abundance. The water abundance at the equatorial region is inferred to be \\(2.5_{-1.6}^{+2.2}\\times10^3\\) ppm, or \\(2.7_{-1.7}^{+2.4}\\) times the protosolar oxygen elemental ratio to H (1\\(\\sigma\\) uncertainties). If reflective of the global water abundance, the result suggests that the planetesimals formed Jupiter are unlikely to be water-rich clathrate hydrates.

A consistent and complete set of quasi-explicit algebraic closures for turbulent reacting flows is proposed as approximate solutions to the full second order moment equations. Quasi-explicit algebraic scalar flux models that are valid for three-dimensional turbulent flows are derived from a hierarchy of second-order moment closures. The mathematical procedure is based on the Cayley-Hamilton theorem and is an extension of the scheme developed by Taulbee (1992). Several closures for the pressure-scalar gradient correlations are considered and explicit algebraic relations are provided for the velocity-scalar correlations in both non-reacting and reacting flows. In the latter, the role of the Damkohler number is exhibited in isothermal turbulent flows with nonpremixed reactants. The relationship between these closures and traditional models based on the linear gradient diffusion approximation is theoretically established. The results of model predictions are assessed via comparison with available laboratory data in turbulent jet flows. The development of the quasi-explicit algebraic models for Reynolds stresses, temperature fluxes and reacting scalar fluxes is extended to high-speed turbulent reacting flows under a density weighted average formalism. New closures are proposed for the pressure-strain and the pressure-scalar gradient correlations. These accommodate compressibility corrections subject to the magnitude of the turbulent Mach number, the density gradient, the pressure gradient and the mean dilatation effects. Non-reacting and reacting flows with heat release are considered. In the latter, a second-order irreversible chemical reactions in turbulent flows with initially segregated reactants is considered. The models are tested in simple compressible free-shear flows. Comparisons are made between the full second order moment computations and the algebraic closure predictions. For a mixing layer, experimental data are used to validate the predicted results.

HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.