Mare Crisium - Compositional inferences from low altitude X-ray fluorescence data
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Advanced techniques considered by Kamide et al. (1981) seem to have the potential for providing observation-based high time resolution pictures of the global ionospheric current and electric field patterns for interesting events. However, a reliance on the proposed magnetogram-inversion schemes for the deduction of global ionospheric current and electric field patterns requires proof that reliable results are obtained. 'Theoretical' tests of the accuracy of the magnetogram inversion schemes have, therefore, been considered. The present investigation is concerned with a test, involving the developed KRM algorithm and the Rice Convection Model (RCM). The test was successful in the sense that there was overall agreement between electric fields and currents calculated by the RCM and KRM schemes.
A flared-anode MPD thruster has been modified to permit injection of propellant through the backplate near the anode wall. At 6 g/sec argon, this thruster displays an onset current of 41.4 kA, almost double the value observed for propellant injection at the cathode and intermediate radial positions. A magnetic field survey of the interelectrode region shows current density is highest at the upstream and downstream ends of the chamber. The operating efficiency at onset current inferred from magnetic field data exceeds 50 percent, but swinging-gate thrust stand measurements reveal a progressive divergence between inferred and actual thrust with increasing power. Near onset, the measured thrust is approximately 20 percent lower than that inferred from magnetic probing. Explanations for this behavior have been explored with viscous drag emerging as the most probable cause of performance degradation.
It has long been known that cholera outbreaks can be initiated when Vibrio cholerae, the bacterium that causes cholera, is present in drinking water in sufficient numbers to constitute an infective dose, if ingested by humans. Outbreaks associated with drinking or bathing in unpurified river or brackish water may directly or indirectly depend on such conditions as water temperature, nutrient concentration, and plankton production that may be favorable for growth and reproduction of the bacterium. Although these environmental parameters have routinely been measured by using water samples collected aboard research ships, the available data sets are sparse and infrequent. Furthermore, shipboard data acquisition is both expensive and time-consuming. Interpolation to regional scales can also be problematic. Although the bacterium, V. cholerae, cannot be sensed directly, remotely sensed data can be used to infer its presence. In the study reported here, satellite data were used to monitor the timing and spread of cholera. Public domain remote sensing data for the Bay of Bengal were compared directly with cholera case data collected in Bangladesh from 1992-1995. The remote sensing data included sea surface temperature and sea surface height. It was discovered that sea surface temperature shows an annual cycle similar to the cholera case data. Sea surface height may be an indicator of incursion of plankton-laden water inland, e.g., tidal rivers, because it was also found to be correlated with cholera outbreaks. The extensive studies accomplished during the past 25 years, confirming the hypothesis that V. cholerae is autochthonous to the aquatic environment and is a commensal of zooplankton, i.e., copepods, when combined with the findings of the satellite data analyses, provide strong evidence that cholera epidemics are climate-linked.
Tutorials in this technical memorandum explain how to use the Protégé ontology editor to import data from Excel and export data from Protégé in the JavaScript Object Notation Linked Data (JSON-LD) format then how to transform the JSON-LD file into variables for web apps. These tutorials apply JavaScript and R programming languages and 3D graphics libraries. Ontologies enable standardization, data sharing, and semantic interoperability. An ontology models a domain of knowledge as taxonomies of annotated classes, data properties, relational object properties, and inference rules. This technical memorandum includes a data dictionary for a subset of the Space Situational Awareness Ontology (SSAO).
Available seismic and ground based gravity data are combined to infer the three dimensional crust and upper mantle structure in selected regions. This synthesis and interpretation proceeds from large-scale average models suitable for early comparison with high-altitude satellite potential field data to more detailed delineation of structural boundaries and other variations that may be significant in natural resource assessment. Seismic and ground based gravity data are the primary focal point, but other relevant information (e.g. magnetic field, heat flow, Landsat imagery, geodetic leveling, and natural resources maps) is used to constrain the structure inferred and to assist in defining structural domains and boundaries. The seismic data consists of regional refraction lines, limited reflection coverage, surface wave dispersion, teleseismic P and S wave delay times, anelastic absorption, and regional seismicity patterns. The gravity data base consists of available point gravity determinations for the areas considered.
A computer generated false color program which creates digital multicolor graphics to display geophysical surface parameters measured by the Seasat-A satellite scatterometer (SASS) is described. The data is incrementally scaled over the range of acceptable values and each increment and its data points are assigned a color. The advantage of the false color display is that it visually infers cool or weak data versus hot or intense data by using the rainbow of colors. For example, with wind speeds, levels of yellow and red could be used to imply high winds while green and blue could imply calmer air. The SASS data is sorted into geographic regions and the final false color images are projected onto various world maps with superimposed land/water boundaries.
Passive microwave data collected by Nimbus 7 were used to classify and monitor the Arctic multilayer sea ice cover. Sea ice concentration maps during several summer minima are analyzed to obtain estimates of ice floes that survived summer, and the results are compared with multiyear-ice concentrations derived from these data by using an algorithm that assumes a certain emissivity for multiyear ice. The multiyear ice cover inferred from the winter data was found to be about 25 to 40 percent less than the summer ice-cover minimum, indicating that the multiyear ice cover in winter is inadequately represented by the passive microwave winter data and that a significant fraction of the Arctic multiyear ice floes exhibits a first-year ice signature.
The Nimbus 4 temperature-humidity infrared radiometer (THIR) monitors radiation in the 6.5 to 7.2 micron water vapor absorption with a 23 kilometer spatial resolution at the sub-satellite point. Radiation monitored in this spectral region results primarily from emission in the 250 to 500 millibar region of the upper troposphere. The THIR 6.7 micron observations are readily available in photofacsimile imagery form which shows very distinctive patterns associated with spatial variations in atmospheric water vapor. These radiometric observations were combined in several instances with moisture values measured in the upper troposphere by the standard radiosonde network. In each instance, the result is a much more consistent analysis showing increased spatial detail that agrees with the radiometric observations and does not compromise the conventional data. The improved moisture analyses show relatively dry and moist tongues that are very difficult or impossible to infer from the conventional data alone. The patterns in the moisture fields can be tracked over 12 and 24 hour periods. In addition, by keeping in mind the advective properties of the moisture field, success was achieved in improving streamline analyses at the 400 mb level over data sparse regions on a global scale.
The Nimbus 4 temperature-humidity infrared radiometer (THIR) monitors radiation in the 6.5 to 7.2-micron water vapor absorption region with a 23-km spatial resolution at the subsatellite point. Radiation monitored in this spectral region results primarily from emission in the 250 to 500-mb region of the upper troposphere. The THIR 6.7-micron observations are readily available in photofacsimile imagery form which shows very distinctive patterns associated with spatial variations in atmospheric water vapor. These radiometric observations have been combined in several instances with moisture values measured in the upper troposphere by the standard radiosonde network. In each instance, the result is a much more consistent analysis showing increased spatial detail that agrees with the radiometric observations and does not compromise the conventional data. The improved moisture analyses show relatively dry and moist tongues that are very difficult or impossible to infer from the conventional data alone.
The performance analysis results of a fault inferring nonlinear detection system (FINDS) using sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment is presented. First, a statistical analysis of the flight recorded sensor data was made in order to determine the characteristics of sensor inaccuracies. Next, modifications were made to the detection and decision functions in the FINDS algorithm in order to improve false alarm and failure detection performance under real modelling errors present in the flight data. Finally, the failure detection and false alarm performance of the FINDS algorithm were analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minute flight data. In general, the detection speed, failure level estimation, and false alarm performance showed a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed was faster for filter measurement sensors soon as MLS than for filter input sensors such as flight control accelerometers.
The study of palagonitic soils is an active area of research in martian geoscience because the spectral and magnetic properties of a subset are spectral and/or magnetic analogues of martian bright regions. An understanding of the composition, distribution, and mineralogy of ferric-bearing phases for palagonitic soils forms, through spectral and magnetic data, a basis for inferring the nature of ferric-bearing phases on Mars. Progress has been made in this area, but the data set is incomplete, especially with respect to the nature of pigmenting phases. The purpose of this study is to identify the nature of the pigment for Hawaiian palagonitic soil PN-9 by using extraction procedures to selectively remove iron oxide phases. This soil was collected at the same locale as samples Hawaii 34 and VOL02. All three soils are good spectral analogues for martian bright regions.
Measurements made by the Special Sensor Microwave/Imager (SSM/I) radiometer over the oceans, at 19, 37, and 85 GHz in dual polarization, are used to develop a model to classify rain into light-stratiform, moderately convective, and heavy convective types in the mesoscale convective systems (MCS). It is observed that the bulk of the 19- and 37-GHz data are linearly correlated with respect to one another, and generally increase together in brightness as the mean rain rate in the field of view (FOV) of the radiometer increases. However, a significant fraction of the data from these channels departs from this linear relationship, reflecting the nonuniform rain that is convective vs. the relatively light stratiform rain. It is inferred from the SSM/I data, in a MCS, when the slope dT sub 3/dT sub 19 is greater than unity there are optically thin clouds which produce light uniform rain. On the other hand, when dT sub 3/dT sub 19 is close to unity, the rain cells have an open structure and correspond to the convective type of rain. The openings between the cells are apparently a result of the downdrafts and/or entrainment. Relatively low values of 85-GHz brightness temperatures that are present when dT sub 37/dT sub 19 is close to unity support these views and, in addition, leads us to conclude that when the convection is heavy this brightness temperature decreases due to scattering by hydrometeors. On the basis of this explanation of the SSM/I data, an empirical rain retrieval algorithm is developed. Radar backscatter observations over the Atlantic Ocean next to Florida are used to demonstrate the applicability of this method. Three monthly mean maps of rainfall over the oceans from 50 degrees N to 50 degrees S, are presented to illustrate the ability of this method to sense seasonal and interannual variations of rain.
This manuscript describes a method to class@ cirrus cloud ice particle shape using lidar depolarization measurements as a basis for segregating different particle shape regimes. Measurements from the ER-2 Cloud Physics Lidar (CPL) system during CRYSTAL-FACE provide the basis for this work. While the CPL onboard the ER-2 aircraft was providing remote sensing measurements of cirrus clouds, the Cloud Particle Imager (CPI) onboard the WB-57 aircraft was flying inside those same clouds to sample particle sizes. The results of classifying particle shapes using the CPL data are compared to the in situ measurements made using the CPI , and there is found to be good agreement between the particle shape inferred from the CPL data and that actually measured by the CPI. If proven practical, application of this technique to spaceborne observations could lead to large-scale classification of cirrus cloud particle shapes.
The moderately siderophile element molybdenum has been used as an indicator in planetary differentiation processes, and is particularly relevant to core formation [for example, 1-6]. However, models that apply experimental data to an equilibrium differentiation scenario infer the oxidation state of molybdenum from solubility data or from multivariable coefficients from metal-silicate partitioning data [1,3,7]. Partitioning behavior of molybdenum, a multivalent element with a transition near the J02 of interest for core formation (~IW-2) will be sensitive to changes in JO2 of the system and silicate melt structure. In a silicate melt, Mo can occur in either 4+ or 6+ valence state, and Mo6+ can be either octahedrally or tetrahedrally coordinated. Here we present first XANES measurements of Mo valence in basaltic run products at a range of P, T, and JO2 and further quantify the valence transition of Mo.
Quantile data analysis and functional statistical inference methods are introduced and applied to provide representations of spectral data which may lead to simple statistical discriminators effective for the estimation of ground truth from satellite spectral measurements. To estimate the ground truth of a pixel, the probability of each possible ground truth is estimated, given observed (estimated) quantile theoretic statistical characteristics of the multispectral image data corresponding to the pixel and its neighboring pixels. A strategy for determining which statistical characteristics discriminate best is described. Results are reported of quantile data analysis of an extensive collection of training files of image data.
A multiprocessing architecture for performing real time monitoring and analysis using knowledge-based problem solving techniques is discussed. To handle asynchronous inputs and perform in real time, the system consists of three or more separate processes which run concurrently on one or more processors and communicate via a message passing scheme. The Data Management Process gathers, compresses, scales and sends the incoming telemetry data to other tasks. The Inference Process consists of a proprietary high performance inference engine that runs at 1000 rules per second using telemetry data to perform real time analysis on the state and health of the Space Telescope. The multiprocessing architecture has been interfaced to a simulator and is able to process the incoming telemetry in real time.
Seven instrumented sensor plugs were installed on the Mars Science Laboratory heat shield in December 2008 as part of the Mars Science Laboratory Entry, Descent, and Landing Instrumentation (MEDLI) project. These sensor plugs contain four in-depth thermocouples and one Hollow aErothermal Ablation and Temperature (HEAT) sensor. The HEAT sensor follows the time progression of a 700 C isotherm through the thickness of a thermal protection system (TPS) material. The data can be used to infer char depth and, when analyzed in conjunction with the thermocouple data, the thermal gradient through the TPS material can also be determined. However, the uncertainty on the isotherm value is not well defined. To address this uncertainty, a team at NASA Ames Research Center is carrying out a HEAT sensor calibration test program. The scope of this test program is described, and initial results from experiments conducted in the laboratory to study the isotherm temperature of the HEAT sensor are presented. Data from the laboratory tests indicate an isotherm temperature of 720 C 60 C. An overview of near term arc jet testing is also given, including preliminary data from 30.48cm 30.48cm PICA panels instrumented with two MEDLI sensor plugs and tested in the NASA Ames Panel Test Facility. Forward work includes analysis of the arc jet test data, including an evaluation of the isotherm value based on the instant in time when it reaches a thermocouple depth.