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At least 775 records · Page 43

Open-Source Science-led Development of the AOS Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David M. Giles↗

DarkNESS: Characterization of Space Multi-Chip Module Skipper-CCDs

The DarkNESS mission is to send a 6U CubeSat fitted with an array of skipper-CCDs to see how well these sensors operate in Low Earth Orbit: take measurements of x-rays from the galactic center and strongly interacting sub-GeV dark matter from Cygnus X-1. Skipper-CCDs allow for low-noise astronomical observations which can extend the discovery reach for direct dark matter search experiments. This paper will discuss the characterization of the space Multi-Chip Module (sMCM) equipped with skipper-CCDs, and the challenges it faces during testing in the lab environment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Passive microwave sensing of the earth

The natural thermal radio radiation emitted by the terrestrial atmosphere and surface can be measured by passive microwave sensors. The receivers and antennas for the required sensing systems are briefly considered along with questions regarding the geophysical information obtainable. Satellite, aircraft, and ground-based observations are discussed. Attention is given to the possibility to monitor continually the evolution of the ice caps in polar regions.

Staelin, D. H.↗

Orbital debris environment for spacecraft in low earth orbit

Modeling and measurement results used in formulating an environment model that can be used for the engineering design of spacecraft are reviewed. Earth-based and space-based sensors are analyzed and it is noted that the effects of satellite breakups can be modeled to predict a uncatalogued population, if the nature of the breakup is understood. It is observed that the telescopic data indicate that the current model is too low for sizes slightly larger than 10 cm, and may be too low for sizes between 2 cm and 10 cm, while there is an uncertainty in the current development, especially for sizes smaller than 10 cm, and at altitudes different from 500 km. Projections for the catastrophic collision rate for different growth conditions are made, emphasizing that the rate of growth of fragments will be twice the rate of intact objects.

Kessler, Donald J.↗

International Satellite Cloud Climatology Project (ISCCP) Stage D2 Monthly Cloud Product - Revised Algorithm in Hierarchical Data Format (ISCCP_D2)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=TROPOSPHERE] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=280 Km; Longitude_Resolution=280 Km; Temporal_Resolution=Monthly].

CLOUD TOP PRESSURE↗

CLARREO: Reference Inter-Calibration on Orbit With Reflected Solar Spectrometer

The CLARREO approach for reference intercalibration is based on obtaining coincident highly accurate spectral reflectance and reflected radiance measurements, and establish an on-orbit reference for existing Earth viewing reflected solar radiation sensors: CERES and VIIRS on JPSS satellites, AVHRR and follow-on imagers on MetOp, and imagers on GEO platforms. The mission goal is to be able to provide CLARREO RS reference observations that are matched in space, time, and viewing angles with measurements from the aforementioned instruments, with sampling sufficient to overcome the random error sources from imperfect data matching and instrument noise. The intercalibration method is to monitor over time changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, spectral degradation, and sensitivity to polarization of optics.

Lukashin, C.↗

A Historical Overview of the NASA Orbital Debris Program Office’s Laboratory Optical Measurements

The NASA Orbital Debris Program Office (ODPO) has used laboratory measurements to help bring ground-based measurements together with models to ascertain Earth-orbiting target parameters of interest to support various orbital debris models. In 2005, the Optical Measurement Center (OMC) was established to simulate space-based illumination conditions using equipment and techniques that recreate telescopic observations, particularly source-target-sensor orientations. The intent was to recreate light curves using known aspect angles of known targets and phase angles (angle is defined by the vertex between illumination source-object-detector) to complement telescopic observations that could be used to update the current optical size estimation model (OSEM) – a model that converts object brightness into size for orbital debris models. To support the above goals, the laboratory has undergone several equipment upgrades to increase capabilities over almost 20 years of operation. The primary instrumentation acquires reflectance measurements and includes a solar-like light source, CCD camera with astrometric filters, and robotic arm. A rotary arm was added approximately five years after full operation to allow acquisition through a full 360° range of phase angles. Another part of the OMC instrumentation is a field spectrometer, predominately used for field operations to acquire pre- and post-flight spacecraft material spectral measurements. Additionally, reflectance spectroscopy of various materials is also of interest resulting from hypervelocity impact tests, pristine spacecraft materials, or samples of materials that are used in spacecraft design. These measurements are stored in NASA’s Spectral Material Database, a resource that is still being populated today. The study of spectral measurements also enabled the development of spectral unmixing routines to support the identification of spacecraft materials from spectral data gathered by ground based telescopes. Preliminary OMC investigations focused on feasibility studies to acquire 360° rotation light curves of simple shapes at a single-phase angle and extended to measurements of representative fragments from ground-based explosion tests. To correlate the light curves with ground-based optical measurements, a focused study on high area to mass materials was conducted in support of a newly identified population (at the time) in geosynchronous orbit (GEO) consisting of multi-layered insulation. To further characterize orbital debris, a larger selection of materials was analyzed using laboratory photometric measurements that included representative targets from pristine spacecraft materials and ground-based impact tests. Around 2012, an initiative was requested to understand the feasibility of active debris removal (ADR) of larger targets using grappling methods for spent rocket bodies. Using a priori information on selected targets, scaled-down versions of rocket bodies were generated thanks to improvements in 3D printing technology and machining. These targets were studied in the OMC to understand rotation characteristics. These were compared with telescopic data to determine if the tumble and rotation angles would allow ADR. In 2013, the OMC focused on combining spectral measurements with photometric data to characterize GEO orbital debris. Several years later, NASA acquired a Titan III Transtage test article from “The Boneyard” with a high-resemblance to on-orbit Titan III Transtage rocket bodies, allowing physical access to a representative rocket body that suffered fragmentations in GEO. This prompted the creation of 3D models using lidar technology and spectral measurements of the materials. Focused research also transitioned to specific materials (i.e., solar cells) when telescopic surveys requested characterization of specific GEO targets. In the different research products presented, the focus has been to understand the various parameters that influence optical size estimation, including albedo, phase functions, and brightness variations. Work in this area continues with newer sources of data, including DebriSat, a high-fidelity 56-kg spacecraft replica representative of a modern low Earth orbit (LEO) satellite subjected to a laboratory hypervelocity impact test to understand fragmentation events and to support updates to satellite breakup models and size estimation models. Utilizing the vast population of fragments from DebriSat and prior laboratory impact experiments, the ODPO has focused on acquiring bidirectional reflectance distribution function (BRDF) data to characterize targets in the laboratory, thus removing aspect angle dependencies. Additionally, the DebriSat project has provided improved processes for measuring size via image acquisition, such that a true fragment size can be directly compared to the derived size using the OSEM. The team continues to assess BRDFs and use spectral measurement data to investigate the parameters used in the OSEM, specifically magnitudes, albedo, and phase functions.

Heather Cowardin↗

Hourly Carbon Fluxes Estimation Using the GOES Advanced Baseline Imager (ABI) Data Over the Conterminous USA

Tremendous efforts by Fluxnet scientists over the past few decades have made thousands of site-years of carbon flux observations available for advancing our understanding of carbon cycling in terrestrial ecosystems. One of key Fluxnet measurements is net ecosystem exchange (NEE) as it is directly related to carbon budget of terrestrial ecosystems. However, carbon flux estimation studies using satellite remote sensing have focused mainly on daily Gross Primary Production (GPP). The satellite based carbon flux estimation used the polar orbiting satellite sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)), which allow us to observe target regions only once during the day. Because daily NEE is close to zero value, the carbon flux models using the polar orbiting satellite data have not been well used for NEE estimation. The new generation of geostationary satellite sensors (e.g., GOES Advanced Baesline Imager (ABI) and Himawari Advanced Himawari Imager (AHI)) provide frequent observations, often less than every 10 minutes. Here, we use GOES ABI data to estimate hourly NEE over the conterminous USA. We used the Terrestrial Observation Prediction System (TOPS) model for estimating hourly NEE. TOPS is a diagnostic ecosystem process model that simulates the fluxes of carbon and water through vegetation in response to climate variability. For the climate input, we developed hourly climate data using the same algorithm with NASA Earth Exchange Gridded Daily Meteorology (NEX-GDM) datasets based on machine learning techniques. The hourly climate data includes precipitation, maximum temperature, minimum temperature, dew point temperature, and, in particular, solar radiation that is directly derived from the Geostationary observations. The spatial patterns of ecosystem parameters used in TOPS are optimized using satellite Solar Induced Fluorescence (SIF) data. The high frequency GPP estimations from geostationary satellite sensors make it comparable to the instantaneous SIF data than daily GPP. We also used Fluxnet data for optimization of model parameters and the validation of the output. The derived data addresses the diurnal dynamics of carbon cycling at large scales and should help in reducing the uncertainties in carbon budget studies.

Geostationary satellite↗

Improved capabilities of the Multispectral Atmospheric Mapping Sensor (MAMS)

The Multispectral Atmospheric Mapping Sensor (MAMS) is an airborne instrument being investigated as part of NASA's high altitude research program. Findings from work on this and other instruments have been important as the scientific justification of new instrumentation for the Earth Observing System (EOS). This report discusses changes to the instrument which have led to new capabilities, improved data quality, and more accurate calibration methods. In order to provide a summary of the data collected with MAMS, a complete list of flight dates and locations is provided. For many applications, registration of MAMS imagery with landmarks is required. The navigation of this data on the Man-computer Interactive Data Access System (McIDAS) is discussed. Finally, research applications of the data are discussed and specific examples are presented to show the applicability of these measurements to NASA's Earth System Science (ESS) objectives.

Jedlovec, Gary J.↗

Solar maximum mission fine pointing sun sensor dawn and dusk errors flight data and model analysis

SMM flight system control errors occurring at spacecraft dawn and dusk are analyzed. The errors are associated with the fine pointing sun sensor (FPSS), which is a primary component of the SMM attitude control system. It is shown that the source of the FPSS dawn/dusk distortion is the incomplete masking of sunlight reflected off the earth by the optical baffle covering the FPSS sensor heads onboard the SMM during periods of orbit dawn and dusk. For the most part, the modeled behavior of the FPSS under dawn and dusk lighting conditions matches the observed behavior in the SMM flight data.

Kulp, D. R.↗

Atmospheric Science Measurements by the EOS Geoscience Laser Altimeter System

Scheduled for Launch in July 2001, the Geoscience Laser Altimeter System (GLAS) is to be the first satellite instrument to provide full global lidar profiling of clouds and aerosol in the earth's atmosphere. GLAS is an EOS program instrument that is on its own satellite, now called the Ice, Cloud and land Elevation Satellite. The instrument is both a surface laser ranging system and an atmospheric profiling lidar. A most important surface measurement for the instrument is to study the change in the mass balance of the polar ice sheets by measuring the change in regional altitudes to an accuracy of 1.5 cm per year. The strategy to combine the surface measurement with a Cloud and aerosol lidar profiling mission is based on the compatibility of the altimetry instrument requirements with those for the required lidar measurements. The primary atmospheric science goal of the GLAS cloud and aerosol measurement is to determine the radiative forcing and vertically resolved atmospheric heating rate due to cloud and aerosol by directly observing the vertical structure and magnitude of cloud and aerosol parameters that are important for the radiative balance of the earth-atmosphere system, but which are ambiguous or impossible to obtain from existing or planned passive remote sensors. A further goal is to directly measure the height of atmospheric transition layers (inversions) which are important for dynamics and mixing, the planetary boundary layer and lifting condensation level.

Spinhirne, James↗

1999-2003 Shortwave Characterizations of Earth Radiation Budget Satellite (ERBS)/Earth Radiation Budget Experiment (ERBE) Broadband Active Cavity Radiometer Sensors

From October 1984 through May 2005, the NASA Earth Radiation Budget Satellite (ERBS/ )/Earth Radiation Budget Experiment (ERBE)ERBE nonscanning active cavity radiometers (ACR) were used to monitor long-term changes in the earth radiation budget components of the incoming total solar irradiance (TSI), earth-reflected TSI, and earth-emitted outgoing longwave radiation (OLR). From September1984 through September 1999, using on-board calibration systems, the ERBS/ERBE ACR sensor response changes, in gains and offsets, were determined from on-orbit calibration sources and from direct observations of the incoming TSI through calibration solar ports at measurement precision levels approaching 0.5 W/sq m , at satellite altitudes. On October 6, 1999, the onboard radiometer calibration system elevation drive failed. Thereafter, special spacecraft maneuvers were performed to observe cold space and the sun in order to define the post-September 1999 geometry of the radiometer measurements, and to determine the October 1999-September 2003 ERBS sensor response changes. Analyses of these special solar and cold space observations indicate that the radiometers were pointing approximately 16 degrees away from the spacecraft nadir and on the anti-solar side of the spacecraft. The special observations indicated that the radiometers responses were stable at precision levels approaching 0.5 W/sq m . In this paper, the measurement geometry determinations and the determinations of the radiometers gain and offset are presented, which will permit the accurate processing of the October 1999 through September 2003 ERBE data products at satellite and top-of-the-atmosphere altitudes.

Lee, Robert B., III↗

Astronaut Photography of the Earth: A Long-Term Dataset for Earth Systems Research, Applications, and Education

The NASA Earth observations dataset obtained by humans in orbit using handheld film and digital cameras is freely accessible to the global community through the online searchable database at https://eol.jsc.nasa.gov, and offers a useful compliment to traditional ground-commanded sensor data. The dataset includes imagery from the NASA Mercury (1961) through present-day International Space Station (ISS) programs, and currently totals over 2.6 million individual frames. Geographic coverage of the dataset includes land and oceans areas between approximately 52 degrees North and South latitudes, but is spatially and temporally discontinuous. The photographic dataset includes some significant impediments for immediate research, applied, and educational use: commercial RGB films and camera systems with overlapping bandpasses; use of different focal length lenses, unconstrained look angles, and variable spacecraft altitudes; and no native geolocation information. Such factors led to this dataset being underutilized by the community but recent advances in automated and semi-automated image geolocation, image feature classification, and web-based services are adding new value to the astronaut-acquired imagery. A coupled ground software and on-orbit hardware system for the ISS is in development for planned deployment in mid-2017; this system will capture camera pose information for each astronaut photograph to allow automated, full georegistration of the data. The ground system component of the system is currently in use to fully georeference imagery collected in response to International Disaster Charter activations, and the auto-registration procedures are being applied to the extensive historical database of imagery to add value for research and educational purposes. In parallel, machine learning techniques are being applied to automate feature identification and classification throughout the dataset, in order to build descriptive metadata that will improve search capabilities. It is expected that these value additions will increase interest and use of the dataset by the global community.

Stefanov, William L.↗

Fire Analysis of the Thomas Fire in California Using NASA Data in a GIS

NASA's Earth Observing System Data Information System (EOSDIS) manages Earth Observation satellites and the Distributed Active Archive Centers (DAACs), where the data is stored and processed. This poster presents the use of satellite data from NASA's inventory that have the potential for use in identification and analysis of forest fire risk and subsequent after-effects within a geographic information system (GIS). The challenge is that Earth Observation data is complicated. There is plenty of data available, however, the science teams have had a "top-down" approach: define what it is you are trying to study -select a set of satellite(s) and sensor(s), and drill down for the data.

Worldview↗

Safe2Ditch Steer-To-Clear Development and Flight Testing

This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupant’s quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupant’s location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicle’s cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed.

Petty, Bryan J.↗

Calibrating CERES and VIIRS using CLARREO Pathfinder: Adjustment for the Viewing Geometry Mismatch

The Climate Absolute Radiance and Refractivity Observatory Pathfinder (CPF) mission on the International Space Station (ISS) will provide, for the first-time, an SI-traceable on-orbit calibration reference with a reflectance uncertainty of 0.3% (1 sigma). One major mission objective is to demonstrate the capability of transferring CPF’s radiometric accuracy to other satellite-based instruments, such as Clouds and Earth's Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) on NOAA-20. CPF inter-calibration measurements will be planned to obtain inter-calibration samples that closely match satellite-based target sensor observations in time, space, angle, and wavelength. The inter-calibration event observations cover a wide range of viewing geometry angles with potential angular mismatch between CPF and the target sensors which can introduce non-negligible errors against the mission’s inter-calibration uncertainty budget. We will introduce the CPF approach to adjust for angular mismatch differences, thereby reducing the incurred uncertainties to within the inter-calibration uncertainty budget. The angular adjustment algorithm has been developed and validated based on the high-fidelity simulations of the CPF spectra using the Principal Component based Radiative Transfer Model (PCRTM). The implementation of the algorithm on event simulation data and the characterization for the angular adjustment uncertainty will be presented.

Wan Wu↗

Antarctic Iceberg Tracking Based on Time Series of Aqua AMSRE Microwave Brightness Temperature Measurements

Observations of icebergs are identified as one of the requirements for the GEOSS (Global Earth Observation System of Systems) in the area of reducing loss of life and property from natural and human-induced disasters. However, iceberg observations are not included among targets in the GEOSS 10-Year Implementation Plan, and thus there is an unfulfilled need for iceberg detection and tracking in the near future. Large Antarctic icebergs have been tracked by the National Ice Center and by the academic community using a variety of satellite sensors including both passive and active microwave imagers, such as SSM/I (Special Sensor Microwave/Imager) deployed on the DMSP (Defense Meteorological Satellite Program) spacecraft. Improvements provided in recent years by NASA and non-NASA satellite radars, scatterometers, and radiometers resulted in an increased number of observed icebergs and even prompted a question: Is The Number of Antarctic Icebergs Really Increasing? [D.G. Long, J. Ballantyne, and C. Bertoia, Eos, Transactions of the American Geophysical Union 83 (42): 469 & 474, 15 October 2002]. AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System) represents an improvement over SSM/I, its predecessor. AMSR-E has more measurement channels and higher spatial resolution than SSM/I. For example, the instantaneous field of view of the AMSR-E s 89-GHz channels is 6 km by 4 km versus 16 km by 14 km for SSM/I s comparable 85-GHz channels. AMSR-E, deployed on the Aqua satellite, scans across a 1450-km swath and provides brightness temperature measurements with nearglobal coverage every one or two days. In polar regions, overlapping swaths generate coverage up to multiple times per day and allow for creation of image time series with high temporal resolution. Despite these advantages, only incidental usage of AMSR-E data for iceberg tracking has been reported so far, none in an operational environment. Therefore, an experiment was undertaken in the RPC (Rapid Prototyping Capability) of NASA s (National Aeronautics and Space Administration) Applied Science Program to demonstrate that passive microwave brightness temperature measurements acquired by AMSR-E can be effectively used to track iceberg movement around Antarctica. The RPC s robust computation environment enabled processing of terabytes of data products available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. Iceberg tracking based on the AMSR-E Level 2A data product was compared with records from the National Ice Center for currently existing icebergs. Some icebergs as small as roughly 10 km in size were easily observed, but tracking of many others, even larger ones, was obscured by presence of sea ice surrounding the icebergs. The best results, such as for the large iceberg A22A, were achieved when an iceberg was in open ocean.

Blonski, Slawomir↗

Science Autonomy in Robotic Exploration

Historical mission operations have involved: (1) return of scientific data; (2) evaluation of these data by scientists; (3) recommendations for future mission activity by scientists; (4) commands for these transmitted to the craft; and (5) the activity being undertaken. This cycle is repeated throughout the mission with command opportunities once or twice per day. For a rover, this historical cycle is not amenable to rapid long range traverses or rapid response to any novel or unexpected situations. In addition to real-time response issues, imaging and/or spectroscopic devices can produce tremendous data volumes during a traverse. However, such data volumes can rapidly exceed on-board memory capabilities prior to the ability to transmit it to Earth. Additionally, the necessary communication band-widths are restrictive enough so that only a small portion of these data can actually be returned to Earth. Such scenarios suggest enabling some science decisions to be made on-board the robots. These decisions involve automating various aspects of scientific discovery instead of the electromechanical control, health, and navigation issues associated with robotic operations. The robot retains access to the full data fidelity obtained by its scientific sensors, and is in the best position to implement actions based upon these data. Such an approach would eventually enable the robot to alter observations and assure only the highest quality data is obtained for analysis. Additionally, the robot can begin to understand what is scientifically interesting and implement alternative observing sequences, because the observed data deviate from expectations based upon current theories/models of planetary processes. Such interesting data and/or conclusions can then be prioritized and selectively transmitted to Earth; reducing memory and communications demands. Results of Ames' current work in this area will be presented.

Roush, Ted L.↗