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Spacecraft extended mission coverage does not generally carry a high priority, but Helios was fortunate in that a combination of separated viewperiods and unique utilization of the STDN Goldstone antenna have provided a considerable amount of additional science data return, particularly at key times such a perihelion and/or solar occultation.
The use of the Spacelab Glovebox on the recent First United States Microgravity Laboratory (USML-1) mission and the success with which the facility accommodated a large number of microgravity experiments are discussed. Sixteen Materials Science experiments were developed and successfully operated during the first microgravity usage of this new glovebox in space. This facility has a closed working volume to safely contain loose particles and droplets that may be inadvertently freed in setting up or conducting the experiments. The facility also offers an excellent photographic laboratory for observing and recording science data. The USML-1 Spacelab Globebox was a highly successful project that provided the motivation to begin the development of an Orbiter Middeck Glovebox and also provided valuable experience in setting the requirements for the Space Station Freedom Microgravity Science Glovebox (MSG).
In September 2001, Deep Space 1 (DS1) completed a high-risk and flawless encounter with comet 19P/Borrelly. Its data provide a detailed view of this comet and offere surprising and exciting insights. With this successful conclusion of its extended mission, DS1 undertook a hyperextended mission. Following this period of extremely agressive testing, with no further technology or science objectives, the mission was terminated on December 18, 2001, with the powering off of the spacecraft's trnasmitter, although the receiver was left on. By the end of its mission, DS1 had returned a wealth of important science data and engineering data for future missions.
A shell script has been written as a means of automatically making HDF-EOS-formatted data sets available via the World Wide Web. ("HDF-EOS" and variants thereof are defined in the first of the two immediately preceding articles.) The shell script chains together some software tools developed by the Data Usability Group at Goddard Space Flight Center to perform the following actions: Extract metadata in Object Definition Language (ODL) from an HDF-EOS file, Convert the metadata from ODL to Extensible Markup Language (XML), Reformat the XML metadata into human-readable Hypertext Markup Language (HTML), Publish the HTML metadata and the original HDF-EOS file to a Web server and an Open-source Project for a Network Data Access Protocol (OPeN-DAP) server computer, and Reformat the XML metadata and submit the resulting file to the EOS Clearinghouse, which is a Web-based metadata clearinghouse that facilitates searching for, and exchange of, Earth-Science data.
The Advanced Technology Microwave Sounder (ATMS) SN301 is an instrument onboard the QuickSounder Satellite System, QuickSounder mission (renamed QS). Throughout this document the mission may be referred to as QuickSounder or QS. The purpose of this document is to provide information needed to interpret and process QS ATMS science data. The contents of the data book incorporate results from pre-launch subsystem-level and instrument-level testing as well as post-launch testing performed during instrument commissioning. Major milestones include instrument thermal vacuum (TVAC) testing in May 2024 and observatory TVAC testing in 2026. QS launch will be no earlier than Feb. 15, 2027.
In this paper, we summarize briefly some of the future trends in synchrotron science as seen at the National Synchrotron Light Source II, a new, low emittance source recently commissioned at Brookhaven National Laboratory. We touch upon imaging techniques, the study of dynamics, the increasing use of multimodal approaches, the vital importance of data science, and finally, other enabling technologies. Each are presently undergoing a time of rapid change, driving the field of synchrotron science forward at an ever increasing pace. It is truly an exciting time and one in which Roger Cowley, to whom this journal issue is dedicated, would surely be both invigorated by, and at the heart of.
Surrogate model development is a key resource in the scientific modeling community for providing computational expedience when simulating complex systems without loss of great fidelity. The initial step to development of a surrogate model is identification of the primary governing components of the system. Principal component analysis (PCA) is a widely used data science technique that provides inspection of such driving factors, when the objective for modeling is to capture the greatest sources of variance inherent to a dataset. Although an efficient linear dimension reduction tool, PCA makes the fundamental assumption that the data is continuous and normally distributed. Thus, it provides ideal performance when these conditions are met. In the case for which cyber emulations provide realizations of a port scanning scenario, the data to be modeled follows a discrete time series function comprised of monotonically increasing piece-wise constant steps. The sources of variance are related to the timing and magnitude of these steps. Therefore, we consider using XPCA, an extension to PCA for continuous and discrete random variates. This report provides the documentation of the trade-offs between the PCA and XPCA linear dimension reduction algorithms, for the intended purpose to identify key components of greatest variance in our time series data. These components will ultimately provide the basis for future surrogate models of port scanning cyber emulations.
The paper describes the radar design of the Venus Radar Mapper (VRM), which is intended to acquire global radar imaging and altimetry data of the Venus surface. The radar design requirements are satisfied through the use of an existing Voyager antenna for the SAR function and newly developed sensor and altimeter antenna subsystems. The sensor utilizes a block adaptive quantizer to maximize science data return with minimum transmission of radar data back to earth.
The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in mid-2016, ICESat-2 will use a high repetition rate (10 kHz), small footprint (10 m nominal ground diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise range to the earth's surface. Using green light (532 nm), the six beams of ICESat-2 will provide improved spatial coverage compared with the single beam of ICESat, while the differences in transmit energy among the beams provide a large dynamic range. The six beams are arranged into three pairs of beams which allow slopes to measured on an orbit-by-orbit basis. In order to evaluate models of predicted ICESat-2 performance and provide ICESat-2-like data for algorithm development, an airborne ICESat-2 simulator was developed and first flown in 2010. This simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) was most recently deployed to Iceland in April 2012 and collected approx 85 hours of science data over land ice, sea ice, and calibration targets. MABEL uses a similar photon-counting measurement strategy to what will be used on ICESat-2. MABEL collects data in 16 green channels and an additional 8 channels in the infrared aligned across the direction of flight. By using NASA's ER-2 aircraft flying at 20km altitude, MABEL flies as close to space as is practical, and collects data through approx 95% of the atmosphere. We present background on the MABEL instrument, and data from the April 2012 deployment to Iceland. Among the 13 MABEL flights, we collected data over the Greenland ice sheet interior and outlet glaciers in the southwest and western Greenland, sea ice data over the Nares Strait and Greenland Sea, and a number of small glaciers and ice caps in Iceland and Svalbard. Several of the flights were coincident in time and space with NASA's Operation IceBridge, which provides an independent data set for validation. MABEL also collected data along CryoSat track 10482 in north central Greenland approximately one month after CryoSat passed overhead.
The National Aeronautics and Space Administration s (NASA) Lunar Reconnaissance Orbiter (LRO) launched on June 18, 2009 from the Cape Canaveral Air Force Station aboard an Atlas V launch vehicle into a direct insertion trajectory to the Moon LRO, designed, built, and operated by the NASA Goddard Space Flight Center in Greenbelt, MD, is gathering crucial data on the lunar environment that will help astronauts prepare for long-duration lunar expeditions. During the mission s nominal life of one year its six instruments and one technology demonstrator will find safe landing site, locate potential resources, characterize the radiation environment and test new technology. To date, LRO has been operating well within the bounds of its requirements and has been collecting excellent science data images taken from the LRO Camera Narrow Angle Camera (LROC NAC) of the Apollo landing sites have appeared on cable news networks. A significant amount of information on LRO s science instruments is provided at the LRO mission webpage. LRO s Attitude Control System (ACS), in addition to controlling the orientation of the spacecraft is also responsible for pointing the High Gain Antenna (HGA). A dual-axis (or double-gimbaled) antenna, deployed on a meter-long boom, is required to point at a selected Earth ground station. Due to signal loss over the distance from the Moon to Earth, pointing precision for the antenna system is very tight. Since the HGA has to be deployed in spaceflight, its exact geometry relative to the spacecraft body is uncertain. In addition, thermal distortions and mechanical errors/tolerances must be characterized and removed to realize the greatest gain from the antenna system. These reasons necessitate the need for an in-flight calibration. Once in orbit around the moon, a series of attitude maneuvers was conducted to provide data needed to determine optimal parameters to load onboard, which would account for the environmental and mechanical errors at any antenna orientation. The nominal geometry for the HGA involves an outer gimbal axis that is exactly perpendicular to the inner gimbal axis, and a target direction that is exactly perpendicular to the outer gimbal axis. For this nominal geometry, closed-form solutions of the desired gimbal angles are simple to get for a desired target direction specified in the spacecraft body fame. If the gimbal axes and the antenna boresight are slightly misaligned, the nominal closed-form solution is not sufficiently accurate for computing the gimbal angles needed to point at a target. In this situation, either a general closed-form solution has to be developed for a mechanism with general geometries, or a correction scheme has to be applied to the nominal closed-form solutions. The latter has been adopted for Solar Dynamics Observatory (SDO) as can be seen in Reference 1, and the former has been used for LRO. The advantage of the general closed-form solution is the use of a small number of parameters for the correction of nominal solutions, especially in the regions near singularities. Singularities here refer to cases when the nominal closed-form solutions have two or more solutions. Algorithm complexity, however, is the disadvantage of the general closed-form solution.
The Chandra X-ray Observatory (CXO), NASA' latest "Great Observatory", swas launched on July 23, 1999 and reached its final orbit on August 7, 1999. The CXO is in a highly elliptical orbit, approximately 140,000 km x 10,000 km, and has a period of approximately 63.5 hours (approx. 2.65 days). It transits the Earth's Van Allen belts once per orbit during which no science observations can be performed due to the high radiation environment. The Chandra X-ray Observatory Center currently uses the National Space Science Data Center's "near Earth" AP-8/AE-8 radiation belt model to predict the start and end times of passage through the radiation belts. Our earlier analysis demonstrated that our implementation of the AP-8/AE-8 model (a simple dipole model of the Earth's magnetic field) does not always give sufficiently accurate predictions of the start and end times of transit of the Van Allen belts. This led to a change in our operating procedure whereby we "padded" the start and end times of transit by 10 kiloseconds (ks) so that ACIS, the primary science instrument on-board Chandra, would not be exposed to the "fringes" of the Van Allen belts on ingress and egress for any given transit. This additional 20 ks per orbit during which Chandra is unable to perform science observations sums to approximately 3 Ms of "lost" science time per year and therefore reduces the science observing efficiency of the Observatory. To address the need for a higher fidelity radiation model appropriate for the Chandra orbit, the Chandra Radiation Model (CRM) was developed. The CRM is an ion model for the outer magnetosphere and is based on data from the EPIC/ICS instrument on-board the Geotail satellite as well as data from the CEPPAD/IPS instrument on-board the Polar satellite. With the production and implementation of the CRM, we present the results of a study designed to investigate the science observing time that may be recovered by using the CRM as a function of the additional low-energy proton exposure to ACIS.
The Chandra X-ray Observatory (CXO), NASA's latest "Great Observatory", was launched on July 23, 1999 and reached its final orbit on August 7, 1999. The CXO is in a highly elliptical orbit, approximately 140,000 km x 10,000 km, and has a period of approximately 63.5 hours (N 2.65 days). It transits the Earth's Van Allen belts once per orbit during which no science observations can be performed due to the high radiation environment. The Chandra X-ray Observatory Center currently uses the National Space Science Data Center's "near Earth" AP-8/AE-8 radiation belt model to predict the start and end times of passage through the radiation belts. Our earlier analysis demonstrated that our implementation of the AP-8/AE-8 model (a simple dipole model of the Earth's magnetic field) does not always give sufficiently accurate predictions of the start and end times of transit of the Van Allen belts. This led to a change in our operating procedure whereby we "padded" the start and end times of transit by 10 kiloseconds (ks) so that ACIS, the primary science instrument on-board Chandra, would not be exposed to the "fringes" of the Van Allen belts on ingress and egress for any given transit. This additional 20 ks per orbit during which Chandra is unable to perform science observations sums to approximately 3 Ms of "lost" science time per year and therefore reduces the science observing efficiency of the Observatory. To address the need for a higher fidelity radiation model appropriate for the Chandra orbit, the Chandra Radiation Model (CRM) was developed. The CRM is an ion model for the outer magnetosphere and is based on data from the EPIC/ICS instrument on-board the Geotail satellite as well as data from the CEPPAD/IPS instrument on-board the Polar satellite. With the production and Implementation of the CRM, we present the results of a study designed to investigate the science observing time that may be recovered by using the CRM as a function of the additional low-energy proton exposure to ACIS.
This video presents an overview of the first Tracking and Data Relay Satellite (TDRS-1) in the form of text, computer animations, footage, and an interview with its program manager. Launched by the Space Shuttle Challenger in 1983, TDRS-1 was the first of a network of satellites used for relaying data to and from scientific spacecraft. Most of this short video is silent, and consists of footage and animation of the deployment of TDRS-1, written and animated explanations of what TDRS satellites do, and samples of the astronomical and Earth science data they transmit. The program manager explains in the final segment of the video the improvement TDRS satellites brought to communication with manned space missions, including alleviation of blackout during reentry, and also the role TDRS-1 played in providing telemedicine for a breast cancer patient in Antarctica.
Data sets generated by models are substantially increasing in volume, due to increases in spatial and temporal resolution, and the number of output variables. Many users wish to download subsetted data in preferred data formats and structures, as it is getting increasingly difficult to handle the original full-size data files. For example, application research users such as those involved with wind or solar energy, or extreme weather events are likely only interested in daily or hourly model data at a single point (or for a small area) for a long time period, and prefer to have the data downloaded in a single file. With native model file structures, such as hourly data from NASA Modern-Era Retrospective analysis for Research and Applications Version-2 (MERRA-2), it may take over 10 hours for the extraction of parameters-of-interest at a single point for 30 years. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is exploring methods to address this particular user need. One approach is to create value-added data by reconstructing the data files. Taking MERRA-2 data as an example, we have tested converting hourly data from one-day-per-file into different data cubes, such as one-month, or one-year. Performance is compared for reading local data files and accessing data through interoperable services, such as OPeNDAP. Results show that, compared to the original file structure, the new data cubes offer much better performance for accessing long time series. We have noticed that performance is associated with the cube size and structure, the compression method, and how the data are accessed. An optimized data cube structure will not only improve data access, but also may enable better online analysis services
Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model architecture resulting in high-dimensional, difficult to interpret internal representations of input data. As DNNs become more ubiquitous across multiple sectors of our society, there is increasing recognition that mathematical methods are needed to aid analysts, researchers, and practitioners in understanding and interpreting how these models' internal representations relate to the final classification. In this paper we apply cutting edge techniques from TDA with the goal of gaining insight towards interpretability of convolutional neural networks used for image classification. We use two common TDA approaches to explore several methods for modeling hidden layer activations as high-dimensional point clouds, and provide experimental evidence that these point clouds capture valuable structural information about the model's process. First, we demonstrate that a distance metric based on persistent homology can be used to quantify meaningful differences between layers and discuss these distances in the broader context of existing representational similarity metrics for neural network interpretability. Second, we show that a mapper graph can provide semantic insight as to how these models organize hierarchical class knowledge at each layer. These observations demonstrate that TDA is a useful tool to help deep learning practitioners unlock the hidden structures of their models.
GRACE-D accelerometer data show significant bias jumps since one month after the launch of the GRACE Follow-On (GRACE-FO) satellites in May 2018, making them inapplicable for correcting GRACE-FO products for non-gravitational accelerations. The GRACE-FO Science Data System (SDS) compensated this issue by transplanting the GRACE-C accelerometer data toward that of GRACE-D. Recently, GRACE-FO SDS implemented an updated transplant method, used in the latest release of GRACE-FO data. Here, we examine the impact of updated accelerometer transplant data (ACH) on GRACE-FO measurements at all levels: (a) Level-1B inter-satellite laser ranging residuals measured along satellite orbit, (b) Level-2 time-variable gravity solutions from all SDS centers (JPL, CSR, and GFZ), and (c) Level-3 mascon solutions. We show that inter-satellite laser ranging residuals are modified at low frequencies below 1 mHz, affecting the along-orbit analysis of large-scale time-variable gravity signals. When mapped into monthly Level-2 spherical harmonic coefficients of geopotential, the low-frequency change in inter-satellite ranging residuals leads to substantial improvement of coefficients associated with resonant orders (i.e., 15, 30, 45, etc.) and C 30 . We also present an improved SLR-derived C 30 which significantly improves the agreement with updated GRACE-FO C 30 at seasonal and interannual timescales. Moreover, we demonstrate the noise reduction in mass change estimates from new GRACE-FO Level-2 data over oceans, Greenland, and Antarctica for all SDS solutions. GRACE-FO mascon solutions show a moderate change in the updated release. Our comprehensive analyses demonstrate high-quality estimates of non-gravitational accelerations by the updated transplant method, resulting in more accurate GRACE-FO time-variable gravity and mass change observations.
The Zwicky Transient Facility (ZTF) is a new robotic time-domain survey currently in progress using the Palomar 48-inch Schmidt Telescope. ZTF uses a 47 square degree field with a 600 megapixel camera to scan the entire northern visible sky at rates of ∼3760 square degrees/hour to median depths of g ~ 20.8 and r ~ 20.6 mag (AB, 5σ in 30 sec). We describe the Science Data System that is housed at IPAC, Caltech. This comprises the data-processing pipelines, alert production system, data archive, and user interfaces for accessing and analyzing the products. The real-time pipeline employs a novel image-differencing algorithm, optimized for the detection of point-source transient events. These events are vetted for reliability using a machine-learned classifier and combined with contextual information to generate data-rich alert packets. The packets become available for distribution typically within 13 minutes (95th percentile) of observation. Detected events are also linked to generate candidate moving-object tracks using a novel algorithm. Objects that move fast enough to streak in the individual exposures are also extracted and vetted. We present some preliminary results of the calibration performance delivered by the real-time pipeline. The reconstructed astrometric accuracy per science image with respect to Gaia DR1 is typically 45 to 85 milliarcsec. This is the RMS per-axis on the sky for sources extracted with photometric S/N ≥10 and hence corresponds to the typical astrometric uncertainty down to this limit. The derived photometric precision (repeatability) at bright unsaturated fluxes varies between 8 and 25 millimag. The high end of these ranges corresponds to an airmass approaching ∼2—the limit of the public survey. Photometric calibration accuracy with respect to Pan-STARRS1 is generally better than 2%. The products support a broad range of scientific applications: fast and young supernovae; rare flux transients; variable stars; eclipsing binaries; variability from active galactic nuclei; counterparts to gravitational wave sources; a more complete census of Type Ia supernovae; and solar-system objects.
The Apollo-derived Orion Crew Exploration Vehicle (CEV), part of NASA s now-cancelled Constellation Program, has become the reference design for the new Multi-Purpose Crew Vehicle (MPCV). The MPCV will serve as the exploration vehicle for all near-term human space missions. A strategic wind-tunnel test program has been executed at numerous facilities throughout the country to support several phases of aerodynamic database development for the Orion spacecraft. This paper presents a summary of the experimental static aerodynamic data collected to-date for the Orion Crew Module (CM) capsule. The test program described herein involved personnel and resources from NASA Langley Research Center, NASA Ames Research Center, NASA Johnson Space Flight Center, Arnold Engineering and Development Center, Lockheed Martin Space Sciences, and Orbital Sciences. Data has been compiled from eight different wind tunnel tests in the CEV Aerosciences Program. Comparisons are made as appropriate to highlight effects of angle of attack, Mach number, Reynolds number, and model support system effects.