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Package consisting of three separate programs used to accurately predict temperature distribution of spacecraft in planetary orbit is invaluable tool for design and analysis of other structures that must function in complex thermal environment.
Methods for determining atmospheric structure exploit the opacities provided by the collision induced H2 dipole and the nu4 fundamental of CH4. In addition to earth-based observations, useful measurements of thermal emission from Jupiter and Saturn have been or soon will be made by several spacecraft, with results cross-checked with independent radio occultaion results. For Uranus and Neptune, only a limited set of whole-disk earth-based data exists. All the outer planets show evidence for stratospheric temperature inversions; temperature minima range from about 105 K for Jupiter and 87 K for Saturn, to roughly 55 K for Uranus and Neptune. Remaining problems may be resolved by better quantitative understanding of gas and aerosol absorption and scattering properties, chemical composition, and non-LTE source functions. Ultimately, temperature structure results must be supplemented by quantitative energy equilibrium models which will allow some meaning to be given to the relationships between such characteristics as temperature, clouds, incident solar and planetary radiation, and chemical composition.
A planetary model is described which requires fractional vapor/liquid condensation, planet accumulation during condensation, a late start for accumulation of the Moon, and volatile accretion to the surfaces of each planet only near the end of the accumulation process. In the model, initial accumulation of small objects is helped if the agglomerating particles are somewhat sticky. Assuming that growth proceeds through this range, agglomeration continues. If the reservoir of vapor is being preferentially depleted in iron by fractional condensation, an iron-rich planetary core forms. As the temperature decreases, condensing material becomes progressively richer in silicates and poorer in iron, forming the silicate-rich mantle of an already differentiated Earth. A second center of agglomeration successfully forms near the growing Earth after most of the iron in the reservoir has been used up. The bulk composition of the Moon then is similar to the outer mantle of the accumulating Earth.
Given a suitable strategy for conducting measurements, satellite-based remote sensing of the earth can furnish valuable information on the dynamic changes of such planetary characteristics as ocean surface temperatures and atmospheric CO2. Observations must be global and synoptic, quantitatively validated, and consistent over the long term. A program spanning 20 years will study such critical variables as solar flux, stratospheric temperature, aerosols and ozone, cloud cover, tropospheric gases and aerosols, radiation balance, surface temperature, albedo, precipitation, vegetation cover, moisture, snow and ice, as well as oceanic color, topography, and wind stress.
It has been suggested that nonthermal Na atoms with velocities in excess of 2.1 km/sec in the Mercury atmosphere can be accelerated off the planet by solar radiation pressure; Na abundance may accordingly be expected to decrease with increasing radiation pressure. While this is confirmed by the present measurements, high resolution line profile measurements on Na emission indicate that very little, if any, of the Na is nonthermal, while the bulk is at a temperature approaching that of the planetary surface. Attention is given to explanations for the observed variation.
We have measured the spectral line intensities of the metal poor planetary nebula IC 4634. Using a photo-ionization model calculation, we try to fit the the optical and UV region spectra, i.e., Hamilton Echelle and IUE observations. From direct images, one expects complicated density variations, but the model predicts a range in densities that may be smaller than actually exist. We find N(sub epsilon) approximates 5000 /cubic meter. In spite of the geometrical complexity of the S shaped double-lobed structure, the simple photoionization model with a spherical symmetry can fit most emission lines, fairly well. The derived chemical composition has been compared with previous estimates and also with the Sun - The metallicity in IC 4634 appears to be lower than in the Sun or the average planetary nebula. The most likely temperature of the central ionizing source of IC 4634 appears to be about 55,000 K. We find a central star mass of about 0.55 Solar Mass from comparison with theoretical evolutionary tracks.
The mass, size and shape of planets and their satellites and are essential information from which one can consider the balance of gravity and tensile strength, chemical makeup and such factors as internal temperature or porosity. Orbits and planetary rotation are also useful clues concerning origin, internal structure and tidal history. The tables compiled here include some of the latest results such as detection of densities of Pluto-Charon from analysis of HST images and the latest results for Venus' shape, gravity field and pole orientation based on Magellan spacecraft data. Data concerning prominent asteroids, comets and Sun are also included. Most of the material here is presented as tables. They are preceded by brief explanations of the relevant geophysical and orbit parameters. More complete explanations can be found in any of several reference texts on geodesy, geophysics and celestial mechanics.
The hot-electron bolometer (HEB) mixer made from a high-T(sub c) superconductor (HTS) was introduced recently as a competing alternative to a Schottky mixer. The HEB mixer would require 100-times less LO power and thus would be a desirable candidate for long-term observational missions such as atmospheric remote-sensing and planetary science. The required cooling temperatures between 65 K and 75 K can be achieved with available space-qualified coolers or even with passive radiative coolers.
Recent observations of the 2001 dust storms encircling Mars confirm predictions of environmental challenges for exploration. Martian dust has been found to completely mantle the Martian surface over thousands of square kilometers and the opacity of airborne dust has been shown to be capable of modifying atmospheric temperature, radiative transfer and albedo. Planetary dust cycling dynamics are suggested to be a key factor in the evolution of the Martian surface. Long-term robotic and manned exploration of Mars will be confronted by dust deposition in periods of atmospheric calm and violent wind storms. Aeolian dust deposition recorded during the Mars Pathfinder mission was estimated to fall at rates of 20-45 microns per Earth year. Although many tools of exploration will be challenged by coating, adhesion, abrasion and possible chemical reaction of deposited, wind blown and actively disturbed Martian dust, solar cells are thought to be of primary concern. Recent modeling work of power output by gallium arsenide/germanium solar cells was validated by the Pathfinder Lander data and showed power output decreases of 0.1 to 0.5% per Martian day. A major determinant for the optimal positioning angle of solar panels employed in future missions is the angle of repose of the settling dust particles that is dependent on a variety of physical and chemical properties of the particles, the panel surface, and the environmental conditions on the Mars surface. While the effects of many of these factors are well understood qualitatively, quantitative analyses, especially under physical and chemical conditions prevailing on the Mars surface are lacking.
Cost: Use heritage hardware, especially use a tested landing system to reduce cost (Phoenix or MSL EDL stage). The sky crane technology delivers higher mass to the surface and enables reaching targets at higher elevation, but at a higher mission cost. Rover vs. Stationary Lander: Rover-mounted instrument enables tomography, but the increased weight of the rover reduces the allowable payload weight. Mass is the critical design constraint for an instrument for a planetary mission. Many factors that are minor factors or do not enter into design considerations for terrestrial operation are important for a planetary application. (Landing site, diurnal temperature variation, instrument portability, shock/vibration)
Laboratory work is the cornerstone of experimental planetary geochemistry, mineralogy, and petrology, but much is to be gained by "experiments" while on a planet surface. Earth-bound experiments are often limited in ability to control multiple conditions relevant to planetary bodies (e.g. cycles in temperature and vapor pressure of water), but observations on-planet provide a unique opportunity where conditions are native to the planet and those affected by sampling and analysis can be constrained. The CheMin XRD instrument on Mars Science Laboratory has been able to test mineral hydration in samples held for up to 300 Mars days (sols). Clay minerals sampled at Yellowknife Bay early in the mission had both collapsed (10 Å) and expanded (13.2 Å) basal spacing. Collapsed interlayers were expected, but larger spacing was not; it was uncertain whether larger basal spacing would collapse on prolonged exposure to warmer conditions inside CheMin. Observation over several hundred sols showed no collapse, with the conclusion that expanded interlayer spacing was due to partial intercalation by metal-hydroxyl groups that resist dehydration. More recently, a sample of the Murray Formation, Oudam, provided the first XRD detection of gypsum and a chance to observe gypsum stability. Laboratory work suggests gypsum should be stable at Mars surface conditions, and indeed gypsum has been observed from orbit at higher latitudes and in thick veins at Yellowknife Bay by Mastcam reflectance spectra. Laboratory experiments have shown that on dehydration the gypsum would not become X-ray amorphous but would rather transform to a water-deficient bassanite structure. Over a period of 37 sols, it was observed that the Oudam sample in CheMin transformed from an assemblage of gypsum+anhydrite, to gypsum+bassanite+anhydrite, and finally to bassanite+anhydrite. Mg-sulfates were also anticipated but have not been observed in CheMin despite chemical evidence for their presence. Unlike gypsum, hydrated Mg-sulfates can transition to an X-ray amorphous form. Crystalline Mg-sulfates are expected higher in the section on Mount Sharp, where it should be possible to determine whether they persist or are destabilized after sampling, providing further insight into hydrous mineral stability at Mars near-equatorial conditions.
Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.
The mass, size and shape of planets and their satellites and are essential information from which one can consider the balance of gravity and tensile strength, chemical makeup and such factors as internal temperature or porosity. Orbits and planetary rotation are also useful clues concerning origin, internal structure and tidal history. Compiled data tables include some of the latest results.
An extensive number of studies have experimentally investigated how elements distribute between metal and silicate phases, to better constrain core-mantle chemical equilibrium. Here, we present a new database compiling all (to our knowledge) experimental data on liquid metal-silicate partitioning from 118 peer-reviewed publications. We applied various machine learning techniques to gain further insights into these partitioning equilibria and their dependencies. We performed a network analysis to investigate the relationship between experiments and partition coefficients, which enables visualizing gaps in the experimental dataset and biases related to varying experimental conditions and analytical setup. In addition, semi-empirical thermodynamic models are commonly used to extrapolate these chemical reactions to the wide range of pressure, temperature and compositional conditions of planetary differentiation. These models are based on linear regressions that assume continuous relationship between partition coefficients and experimental variables. Here, we considered random forest regressions, which are algorithms based on ensembles of decision trees and does not consider continuous effects of each variable. The application of this regression significantly improves the prediction of metal-silicate partitioning for several elements including Ni, Si and Cr. We will show how this new approach improves our understanding of elemental exchange between metal and silicate and their implications for the Earth’s core formation.
Particulate matter (PM) with a diameter of less or equal to 2.5 μm, known as PM , affects human health as it penetrates the respiratory system. The Environmental Protection Agency (EPA) measures the atmospheric concentration of PM using air quality monitors stationed throughout the Continental United States (CONUS). Such measurements are points on a spatial domain and therefore, might not be representative of the air quality at nearby areas considering that the composition of the atmosphere is highly variable from place to place. Satellite based AOD permits a spatially uniform means of estimating PM and new geostationary satellites provide high temporal and spatial resolution estimation of AOD. However, the concentration of PM is non-linearly dependent on other atmospheric parameters that include relative humidity, temperature, and height of the planetary boundary layer. This information may be estimated at similar spatial and temporal resolutions as AOD from numerical modeling such as from the National Oceanic and Atmospheric Administration’s (NOAA) High Resolution Rapid Refresh (HRRR) model which resolves near real-time atmospheric conditions over the CONUS. The estimation of PM concentration is a multi-parametric problem that considers the effect of temporal dependencies among the different parameters. Deep learning approaches are appropriate for such complex estimation problems as they intrinsically capture relations among multiple non-linear parameters. This study compares deep-learning methods to traditional regression analysis to demonstrate the capabilities of these methods in predicting PM2.5 concentrations. Additionally, a novel ensemble learning approach is employed to identify scientific processes that could further improve the estimation of PM concentration. Utilizing Long Short-Term Memory (LSTM) neural networks, which are suitable for multivariate time series estimation problems as they are capable of learning long-term dependencies, individual models are created for each EPA station and trained on the aforementioned dataset collocated over each station. Individual station models are merged if the model's performance is improved by reducing the root mean squared error (RMSE) metric. This ensemble training method ultimately reduces the RMSE value. Evaluation of these results provide insights into physical processes and related observable parameters that may contribute to PM concentrations. Identified parameters evaluated to be statistically different between the merged and unmerged models are expected to improve overall performance. These new parameters are then utilized for reevaluation of the deep learning methods with an extreme gradient boosting model with an RMSE of 5.5 providing the best results.
• GRAMs are engineering-oriented atmospheric models that estimate mean values and statistical variations of atmospheric properties for numerous planetary destinations – Outputs atmospheric density, temperature, pressure, winds, and chemical composition along a user-defined path – Provide mean values and variability for any point in an atmosphere – Includes seasonal, geographic, and altitude variations – Used by engineering community because of their ability to create realistic atmospheric dispersions; can be integrated into high fidelity flight dynamic simulations of launch, entry, descent, and landing (EDL), aerobraking, and aerocapture • GRAMs are not forecast models • GRAMs are available for: Earth, Mars, Venus, Neptune, Titan, Jupiter, and Uranus • Available through the NASA Software Catalog https://software.nasa.gov/software/MFS-33888-1
A similarity model is developed for the vertical profiles of turbulent flow variables in an entraining turbulent boundary layer of arbitrary buoyant stability. In the general formulation the vertical profiles, internal rotation of the velocity vector, discontinuities or jumps at a capping inversion and bulk aerodynamic coefficients of the boundary layer are given by solutions to a system of ordinary differential equations in the similarity variable. To close the system, a formulation for buoyantly interactive eddy diffusivity in the boundary layer is introduced which recovers Monin-Obukhov similarity near the surface and incorporates a hypothesis accounting for the observed variation of mixing length throughout the boundary layer. The model is tested in simplified versions which depend only on roughness, surface buoyancy, and Coriolis effects by comparison with planetary-boundary-layer wind- and temperature-profile observations, measurements of flat-plate boundary layers in a thermally stratified wind tunnel and observations of profiles of terms in the turbulent kinetic-energy budget of convective planetary boundary layers. On balance, the simplified model reproduced the trend of these various observations and experiments reasonably well, suggesting that the full similarity formulation be pursued further.
Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.