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Results of geodesy studies of Phobos and Deimos based on Mariner 9 imaging data are presented. This analysis includes a review of the surface coverage and high resolution pictures obtained and the determined sizes, shapes, topographies, and librations of the two Martian satellites. Also, exploration of Phobos and Deimos by missions such as Viking is discussed.
Fine second-phase particles, numerous in sintered alpha-SiC, were analyzed by scanning Auger microscopy and conventional techniques. The Auger analysis utilized computer-controlled data acquisition, multielement correlation diagrams, and a high spatial resolution of 100 nm. This procedure enabled construction of false color maps and the detection of fine compositional details within these particles. Carbon, silicon oxide, and boron-rich particles (qualitatively as BN or B4C) predominated. The BN particles, sometimes having a carbon core, are believed to result from reaction between B4C additives and nitrogen sintering atmospheres.
PG 1034+001 is an extremely hot, helium-rich DO-type star that excites the planetary nebula Hewett 1 and large parts of the surrounding interstellar medium. We present preliminary results of an ongoing spectral analysis by means of non-LTE model atmospheres that consider most elements from hydrogen to nickel. This analysis is based on high-resolution ultraviolet (FUSE, IUE) and optical (VLT/UVES, KECK) data. The results are compared with those of PG 1034+001's spectroscopic twin, the DO star PG 0038+ 199. Keywords. stars: abundances, stars: AGB and post-AGB, stars: atmospheres, stars: evolution, stars: individual (PG 1034+001, PG 0038+ 199), planetary nebulae: individual (Hewett 1)
A description of the S-054 X-ray telescope on Skylab is presented with a discussion of the experimental objectives, observing program, data reduction and analysis. Some results from the Skylab mission are given. The telescope photographically records high-resolution images of the solar corona in several broadband regions of the soft X-ray spectrum. It includes an objective grating used to study the line spectrum. The spatial resolution, sensitivity, dynamic range and time resolution of the instrument were chosen to survey a wide variety of solar phenomena. It embodies improvements in design, fabrication, and calibration techniques which were developed over a ten-year period. The observing program was devised to optimize the use of the instrument and to provide studies on a wide range of time scales. The data analysis program includes morphological studies and quantitative analysis using digitized images. A small sample of the data obtained in the mission is presented to demonstrate the type of information that is available and the kinds of results that can be obtained from it.
Atmospheric temperature profiles for the altitude range 58-90 km were calculated using data on global UV limb radiances from the SME satellite. The major elements of this climatology include a high vertical resolution (about 4 km) and the coverage of the 70-90 km altitude region. The analysis of this extensive data set provides a global definition of mesospheric-lower thermospheric temperature trends over the 1982-1986 period. The observations suggest a pattern of 1-2 K/year decreases in temperatures at 80-90-km altitudes accompanied by 0.5-1.5 K/year increases in temperatures at 65-80-km altitudes.
Science and technology applications for the Moon have not fully kept pace with technical advancements in sensor development and analytical information extraction capabilities. Appropriate unanswered questions for the Moon abound, but until recently there has been little motivation to link sophisticated technical capabilities with specific measurement and analysis projects. Over the last decade enormous technical progress has been made in the development of (1) CCD photometric array detectors; (2) visible to near-infrared imaging spectrometers; (3)infrared spectroscopy; (4) high-resolution dual-polarization radar imaging at 3.5, 12, and 70 cm; and equally important (5) data analysis and information extraction techniques using compact powerful computers. Parts of each of these have been tested separately, but there has been no programmatic effort to develop and optimize instruments to meet lunar science and resource assessment needs (e.g., specific wavelength range, resolution, etc.) nor to coordinate activities so that the symbiotic relation between different kinds of data can be fully realized. No single type of remotely acquired data completely characterizes the lunar environment, but there has been little opportunity for integration of diverse advanced sensor data for the Moon. Two examples of technology concepts for lunar measurements are given. Using VIS/near-IR spectroscopy, the mineral composition of surface material can be derived from visible and near-infrared radiation reflected from the surface. The surface and subsurface scattering properties of the Moon can be analyzed using radar backscattering imaging.
Efforts to construct long-term global precipitation data sets from the decades-long record of satellite (and other) data historically have fallen into one of two categories. Climate Data Records (CDR), such as the Global Precipitation Climatology Project (GPCP), prioritize homogeneity over fine-scale accuracy. On the other hand, High Resolution Precipitation Products (HRPP), such as the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), emphasize the use of data from all available satellites. For both types of products, experience has shown that it is critical to choose the appropriate reference standard to intercalibrate an ever-evolving constellation of satellite sensors. Towards this end, we have used passive microwave (PMW) in developing GPCP, and combined PMW-radar in TMPA.The launch of the TRMM follow-on Global Precipitation Measurement (GPM) mission in 2014 gave birth to several nearly-global HRPP's, including the Integrated Multi-satellitE Retrievals for GPM (IMERG). Our strategy in refining IMERG has been to first focus on the tropics and mid-latitudes, where we have relatively high confidence, and only more recently begin to expand into the lower-confidence high latitudes. Similarly, although GPCP has provided nearly-global estimates since its inception in the early 1990's, the advent of sensors such as CloudSat has facilitated new efforts to modernize its estimates at high latitudes.For each of these data sets, it is expected that the final merged estimate should tend to track along with its respective calibration standard. Time series depicting GPCP, TMPA, and IMERG will be presented, in order to demonstrate the extent to which this is so. Additionally, comparisons amongst the products will show areas of agreement and highlight areas where further improvements are needed.
A new analysis of the Doppler tracking data from the Lunar Prospector mission in 1999 revealed a number of previously-unseen gravity anomalies at spatial scales as small as 27 km over the nearside. The tracking data at low altitudes (50 km or below) were better analyzed to resolve the nearside features without dampening from a power law constraint, by partitioning the gravity parameters concentrated on either the nearside or farside. The resulting model presents gravity anomalies correlated with topography with a correlation coefficient of 0.7 or higher from degree 50 to 150, the widest bandwidth yet. The gravity-topography admittance of approx. 70 mGal/km is found from numerous craters of which diameters are 60 km or less. In addition, the new model produces orbits that fit to independent radio tracking data from the Lunar Reconnaissance Orbiter and Kaguya (SELENE) better than previous gravity models. This high-resolution model can be of immediate use to geophysical analysis of small craters. Our technique could be applied to an upcoming mission, the Gravity Recovery And Interior Laboratory and useful to extract short wavelength signals from the MESSENGER Doppler data.
The Interactive Data Language (IDL) is used to analyze high resolution spectra from the IUE. Like other interactive languages, IDL is designed for use by the scientist rather than the professional programmer, allowing him to conceive of his data as simple entities and to operate on this data with minimal difficulty. A package of programs created to analyze interstellar absorption lines is presented as an example of the graphical power of IDL.
Analysis and interpretation of data from the Orbiter Retarding Potential Analyzer (ORPA) onboard the Pioneer Venus Orbiter is reported. By comparing ORPA data to proton data from the Orbiter Plasma Analyzer (OPA), it was found that the ORPA suprathermal electron densities taken outside the Venusian ionopause represent solar wind electron densities, thus allowing the high resolution study of Venus bow shocks using both magnetic field and solar wind electron data. A preliminary analysis of 366 bow shock penetrations was completed using the solar wind electron data as determined from ORPA suprathermal electron densities and temperatures, resulting in an estimate of the extent to which mass loading pickup of O+ (UV ionized O atoms flowing out of the Venus atmosphere) upstream of the Venus obstacle occurred. The pickup of O+ averaged 9.95%, ranging from 0.78% to 23.63%. Detailed results are reported in two attached theses: (1) Comparison of ORPA Suprathermal Electron and OPA Solar Wind Proton Data from the Pioneer Venus Orbiter and (2) Pioneer Venus Orbiter Retarding Potential Analyzer Observations of the Electron Component of the Solar Wind, and of the Venus Bow Shock and Magnetosheath.
This study investigates the requirements, performs a gap analysis and makes a set of recommendations for mapping products and exploration tools required to support operations and scientific discovery for near- term and future NASA missions to small bodies. The mapping products and their requirements are based on the analysis of current mission scenarios (rendezvous, docking, and sample return) and recommendations made by the NEA Users Team (NUT) in the framework of human exploration. The mapping products that sat- isfy operational, scienti c, and public outreach goals include topography, images, albedo, gravity, mass, density, subsurface radar, mineralogical and thermal maps. The gap analysis points to a need for incremental generation of mapping products from low (flyby) to high-resolution data needed for anchoring and docking, real-time spatial data processing for hazard avoidance and astronaut or robot localization in low gravity, high dynamic environments, and motivates a standard for coordinate reference systems capable of describing irregular body shapes. Another aspect investigated in this study is the set of requirements and the gap analysis for exploration tools that support visualization and simulation of operational conditions including soil interactions, environment dynamics, and communications coverage. Building robust, usable data sets and visualisation/simulation tools is the best way for mission designers and simulators to make correct decisions for future missions. In the near term, it is the most useful way to begin building capabilities for small body exploration without needing to commit to specific mission architectures.
Small-angle x-ray scattering is used for the structure determination of superlattice for its superior resolution, nondestructive nature, and high penetration power of x rays. With the advent of high brilliance x-ray sources and innovative computing algorithms, there have been notable advances in small angle x-ray scattering analysis of superlattices. High brilliance x-ray beams have made data analyses less model-dependent. Additionally, novel data acquisition systems are faster and more competitive than ever before, enabling a more accurate mapping of the superlattices' reciprocal space. Fast and high-throughput computing systems and algorithms also make possible advanced analysis methods, including iterative phasing algorithms, non-parameterized fitting of scattering data with molecular dynamics simulations, and the use of machine learning algorithms. As a result, solving nanoscale structures with high resolutions has become an attainable task. In this review, we highlight new developments in the field and introduce their applications for the analysis of nanoscale ordered structures, including nanoparticle supercrystals, nanoscale lithography patterns, and supramolecular self-assemblies. Particularly, we highlight the reciprocal space mapping techniques and the use of iterative phase retrieval algorithms. We also cover coherent-beam-based small angle x-ray scattering techniques such as ptychography and ptycho-tomography in view of the traditional small angle x-ray scattering perspective.
The current generation of state-of-the-art global climate models are being run at increasingly higher horizontal resolutions, with the goal of resolving organised deep convection explicitly. How a kilometre-scale resolution impacts the representation of the atmospheric boundary layer is, however, not well known. Using statistical analysis on global fields as well as high-frequency data at selected locations, produced with the Integrated Forecasting System (IFS) model for the Next Generation Earth-system Models (nextGEMS) project, we investigate the horizontal resolution dependence of some boundary-layer processes. We find that a change in resolution from 9 to 2.8 km causes no substantial changes to boundary-layer properties and processes at most of the locations studied, although some global changes are detected that indicate circulation changes. Small changes to the boundary-layer depth and structure are found in the Tropics. The short simulation length and lack of data for optimal boundary-layer analysis limits the conclusions, especially in relation to the connection between the boundary layer and the atmosphere general circulation.
Wind flow data is critical in terms of investment decisions and policy making. High resolution data from wind flow model simulations serve as a supplement to the limited resource of original wind flow data collection. Given the large size of data, finding hidden patterns in wind flow model simulations are critical for reducing the dimensionality of the analysis. In this work, we first perform dimension reduction with two autoencoder models: the CNN-based autoencoder (CNN-AE) [1], and hierarchical autoencoder (HIER-AE) [2], and compare their performance with the Principal Component Analysis (PCA). We then investigate the super-resolution of the wind flow data. By training a Generative Adversarial Network (GAN) with 300 epochs, we obtained a trained model with 2× resolution enhancement. We compare the results of GAN with Convolutional Neural Network (CNN), and GAN results show finer structure as expected in the data field images. Also, the kinetic energy spectra comparisons show that GAN outperforms CNN in terms of reproducing the physical properties for high wavenumbers and is critical for analysis where high-wavenumber kinetics play an important role.
The instruments, techniques, and analysis methods employed in IR observations of solar-system objects are discussed and illustrated with sample data. Particular attention is given to (1) high-resolution (Doppler-limited) spectra of H2O in Comet Halley and Comet Wilson (1986l), obtained with the NASA Kuiper Airborne Observatory in 1985-1986, and (2) scanning observations of Jovian thermal emission, obtained with the NASA IRTF in 1987 and subjected to detailed time-series analysis to investigate atmospheric motion. The data are presented in spectra, energy-level diagrams, maps, and graphs and briefly characterized.
Machine learning techniques are attractive options for developing highly-accurate analysis tools for nanomaterials characterization, including high-resolution transmission electron microscopy (HRTEM). However, successfully implementing such machine learning tools can be difficult due to the challenges in procuring sufficiently large, high-quality training datasets from experiments. In this work, we introduce Construction Zone, a Python package for rapid generation of complex nanoscale atomic structures which enables fast, systematic sampling of realistic nanomaterial structures and can be used as a random structure generator for large, diverse synthetic datasets. Using Construction Zone, we develop an end-to-end machine learning workflow for training neural network models to analyze experimental atomic resolution HRTEM images on the task of nanoparticle image segmentation purely with simulated databases. Further, we study the data curation process to understand how various aspects of the curated simulated data—including simulation fidelity, the distribution of atomic structures, and the distribution of imaging conditions—affect model performance across three benchmark experimental HRTEM image datasets. Using our workflow, we are able to achieve state-of-the-art segmentation performance on these experimental benchmarks and, further, we discuss robust strategies for consistently achieving high performance with machine learning in experimental settings using purely synthetic data. Construction Zone and its documentation are available at https://github.com/lerandc/construction_zone.
The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-12 team's efforts focused on regional scale Surface Vegetation and Atmosphere (SVAT) modeling to improve parameterization of the heterogeneous BOREAS landscape for use in larger scale Global Circulation Models (GCMs). This regional land cover data set was developed as part of a multitemporal one-kilometer Advanced Very High Resolution Radiometer (AVHRR) land cover analysis approach that was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. This land cover classification was derived by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992). This regional data set was developed for use by BOREAS investigators, especially those involved in simulation modeling, remote sensing algorithm development, and aircraft flux studies. Based on regional field data verification, this multitemporal one-kilometer AVHRR land cover mapping approach was effective in characterizing the biome-level land cover structure, embedded spatially heterogeneous landscape patterns, and other types of key land cover information of interest to BOREAS modelers.The land cover mosaics in this classification include: (1) wet conifer mosaic (low, medium, and high tree stand density), (2) mixed coniferous-deciduous forest (80% coniferous, codominant, and 80% deciduous), (3) recent visible bum, vegetation regeneration, or rock outcrops-bare ground-sparsely vegetated slow regeneration bum (four classes), (4) open water and grassland marshes, and (5) general agricultural land use/ grasslands (three classes). This land cover mapping approach did not detect small subpixel-scale landscape features such as fens, bogs, and small water bodies. Field observations and comparisons with Landsat Thematic Mapper (TM) suggest a minimum effective resolution of these land cover classes in the range of three to four kilometers, in part, because of the daily to monthly compositing process. In general, potential accuracy limitations are mitigated by the use of conservative parameterization rules such as aggregation of predominant land cover classes within minimum horizontal grid cell sizes of ten kilometers. The AFM-12 one-kilometer AVHRR seasonal land cover classification data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).
Recent advancements and the accumulation of high-resolution, long-term phasor measurement unit (PMU) data have provided detailed insights into inter-area oscillations in power grids. This study conducts a comprehensive statistical analysis of inter-area oscillations within the United States Eastern Interconnection from 2017 to 2023. Utilizing data captured by the advanced wide-area Frequency Monitoring Network (FNET/GridEye), this investigation examines the occurrence patterns, dominant frequencies, damping ratios, and excitation mechanisms of these oscillations. Our analysis sheds light on the evolving statistical behaviors of inter-area oscillations, offering updated and critical information for grid operators and planners. The insights gained from this study can be instrumental in enhancing the operational resilience of the power network and guiding strategic developments in grid infrastructure to accommodate future challenges. Additionally, the study discusses emerging challenges associated with the modernization of the power grid, including increased renewable penetration, dynamic load variability, and cyber-physical vulnerabilities that complicate oscillation monitoring and control.