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NASA NTRS2018

Next-Generation Radioisotope Thermoelectric Generator Study

Radioisotope Thermoelectric Generators (RTGs) have been used to power NASA missions of various types throughout the past five decades. The most recent RTG iteration, used for NASA’s Mars Science Laboratory, is the Multi-Mission RTG (MMRTG), which is currently the only spaceflight-qualified system available. The U.S. planetary science community has expressed a desire for more power system options to be available to accommodate a range of ambitious future mission concepts across the solar system. Recent advancements in thermoelectric (TE) materials technology have raised a potential for significantly increased efficiency in future RTGs, which helped spur a recent in-depth NASA study of options for future systems. A “next-generation” RTG study was conducted to develop new RTG concepts that could meet the needs of planetary science missions through the 2030s and beyond. A Next-Generation RTG would aim to extend the types of potential NASA missions able to be supported, while fulfilling requirements related to technical risk and schedule. In this study, 21 potential thermoelectric couple configurations were analyzed by considering various high-performance, high-temperature TE materials and segmentation techniques that maximize convertor efficiency and power density. System modularity was explored, and found to be a promising means to offer improved flexibility for NASA mission concepts with varying scope and power requirements. This paper presents the results of the study, demonstrating the viability of developing an updated RTG system design, and defining conceptual system approaches for a new, potentially revolutionary RTG.

Matthes, Christopher S. R.↗

NASA NTRS2014

NASA's Asteroid Redirect Mission: A Robotic Boulder Capture Option for Science, Human Exploration, Resource Utilization, and Planetary Defense

NASA is examining two options for the Asteroid Redirect Mission (ARM), which will return asteroid material to a Lunar Distant Retrograde Orbit (LDRO) using a robotic solar electric propulsion spacecraft, called the Asteroid Redirect Vehicle (ARV). Once the ARV places the asteroid material into the LDRO, a piloted mission will rendezvous and dock with the ARV. After docking, astronauts will conduct two extravehicular activities (EVAs) to inspect and sample the asteroid material before returning to Earth. One option involves capturing an entire small (~4 - 10 m diameter) near-Earth asteroid (NEA) inside a large inflatable bag. However, NASA is also examining another option that entails retrieving a boulder (~1 - 5 m) via robotic manipulators from the surface of a larger (~100+ m) pre-characterized NEA. The Robotic Boulder Capture (RBC) option can leverage robotic mission data to help ensure success by targeting previously (or soon to be) well- characterized NEAs. For example, the data from the Japan Aerospace Exploration Agency's (JAXA) Hayabusa mission has been utilized to develop detailed mission designs that assess options and risks associated with proximity and surface operations. Hayabusa's target NEA, Itokawa, has been identified as a valid target and is known to possess hundreds of appropriately sized boulders on its surface. Further robotic characterization of additional NEAs (e.g., Bennu and 1999 JU3) by NASA's OSIRIS REx and JAXA's Hayabusa 2 missions is planned to begin in 2018. This ARM option reduces mission risk and provides increased benefits for science, human exploration, resource utilization, and planetary defense. Science: The RBC option is an extremely large sample-return mission with the prospect of bringing back many tons of well-characterized asteroid material to the Earth-Moon system. The candidate boulder from the target NEA can be selected based on inputs from the world-wide science community, ensuring that the most scientifically interesting boulder be returned for subsequent sampling. In addition, the material surrounding the boulder can be collected from the surface, thus providing geological contextual information and additional samples of NEA regolith. The robotic manipulators used for capturing the boulder will ensure some of the surface remains undisturbed and that the boulder will retain its structural integrity, which will preserve the context of any samples collected by the astronauts and ensure a high level of science return. Human Exploration: Due to the coherent nature of the boulder that will be collected, entire encapsulation of the asteroid material is not required. This facilitates exploration and sample collection of the boulder by astronauts in a variety of ways. The total time for EVA during the crew portion of the mission is very limited. Current estimates are that each of the two EVAs will only last four hours. The RBC option will allow crew members to have good situational awareness of the work site and quickly identify sample sites of interest. In addition, the samples to be collected can be readily accessed without having to deal with removal of an encapsulation system, which adds extra complexity and risk for the astronauts during EVA. Resource Utilization: One of the most crucial aspects for resource utilization is the identification and collection of appropriate materials (e.g., volatiles, organics, metals, etc.) that contain components of interest. Prior characterization of NEAs is required in order to increase the likelihood that appropriate materials will be returned. Ground-based observations of small (<10 m) NEAs are challenging, but characterization efforts of larger targets have demonstrated that NEAs with volatiles and organics have been identified. Two potential targets for the RBC option (Bennu and 1999 JU3) have been previously identified as potentially rich in resources, and both are already targets of currently planned robotic missions that will characterize their physical properties in great detail. Planetary Defense: The RBC option involves interaction with a well- characterized potentially hazardoussized NEA that would enable NASA to conduct one or more planetary defense demonstrations. The primary method would use the collected boulder to augment the mass of the ARV and perform an Enhanced Gravity Tractor (EGT) demonstration on the NEA. Additionally, other approaches could be demonstrated during the mission, such as Ion Beam Deflection (IBD) and/or observation of a Kinetic Impactor (KI). The relative effectiveness of a slow push-pull method such as the EGT or IBD could be directly compared and contrasted with the results of the more energetic KI method on the target NEA. Conclusions: This boulder option for NASA's ARM can leverage knowledge of previously characterized NEAs from prior robotic missions, which provides more certainty of the target NEA's physical characteristics and reduces mission risk. This increases the return on investment for NASA's future activities with respect to human exploration, resource utilization, and planetary defense.

Abell, P.↗

NASA NTRS2019

Earth Science Technology Office (ESTO) New Observing Strategies (NOS) and NOS-Testbed (NOS-T)

With the advancement of space hardware technologies such as smaller spacecraft, component and instrument miniaturization and high performance space processors, and with the advancement of software technologies in artificial intelligence, big data analysis and autonomous decision making, Earth Science is looking at novel ways to observe phenomena that previously could not have been studied or would have been too expensive to study with traditional missions. In particular, the New Observing Strategies (NOS) component of the NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program aims at leveraging these novel technologies as well as low cost and easy access to space to acquire multi-temporal or simultaneous multi-angular, multi-locations, multi-resolution and multi-spectral observations that will provide better multi-source measurements and will build a more dynamic and comprehensive picture of Earth Science phenomena that need to be studied and analyzed. For applications such as water resources management, air quality monitoring, biodiversity studies or disaster management, NOS will integrate the use of small instruments, small spacecraft, constellations of spacecraft and networks of sensors to design new missions that will provide the necessary measurements to improve future forecast and science modeling systems.Measurement acquisition will therefore be approached as a system of systems rather than on a mission basis, and a system of this complexity should not be expected to work without full integration and experimental characterization. Although most of the individual technologies enabling to link and coordinate multi-source observations are more or less mature, a few technologies need to be developed and all of them need to be integrated and tested as a system. In order for this validation to occur, the AIST Program is developing the NOS Testbed that includes 3 main goals:1.Validate novel NOS technologies, independently and as a system2.Demonstrate novel distributed operations concepts3.Socialize new Distributed Spacecraft Mission (DSM) and SensorWeb (SW) technologies and concepts to the science community by significantly retiring the risk of integrating these new technologies.The NOS Testbed will consist of multiple sensing nodes, simulated or actual, representing space, air and/or ground measurements, that are interconnected by a communications fabric (infrastructure that permits nodes to transmit and receive data between one another and interact with each other). Each node will be supported by hardware capabilities required to perform nodes monitoring and command & control, as well as intelligent "onboard" computing. The nodes will work together in a collaborative manner to demonstrate optimal science capabilities. The testbed will enable to validate technologies such as inter-node communication models, techniques and protocols; inter-node coordination; real-time data fusion and understanding; planning; sensor re-targeting; etc. Additionally, the testbed will have the capability to interact with various mission design tools, OSSEs and one or several forecast models. More details about the NOS Testbed will be presented at the confererence.

Earth Science missions; Advanced information Syste↗

NASA NTRS1991

The Pilot Land Data System (PLDS) at the Ames Research Center manages aircraft data in collaboration with an ecosystem research project

The Pilot Land Data System (PLDS) is a data and information system serving NASA-supported investigators in the land science community. The three nodes of the PLDS, one each at the Ames Research Center (ARC), the Goddard Space Flight Center (GSFC) and the Jet Propulsion Laboratory (JPL), cooperate in providing consistent information describing the various data holding in the hardware and software (accessible via network and modem) that provide information about and access to PLDS-held data, which is available for distribution. A major new activity of the PLDS node at the Ames Research Center involves the interaction of the PLDS with an active NASA ecosystem science project, the Oregon Transect Ecosystems Research involves the management of, access to, and distribution of the large volume of widely-varying aircraft data collected by OTTER. The OTTER project, is managed by researchers at the Ames Research Center and Oregon State University. Its principal objective is to estimate major fluxes of carbon, nitrogen, and water of forest ecosystems using an ecosystem process model driven by remote sensing data. Ten researchers at NASA centers and universities are analyzing data for six sites along a temperature-moisture gradient across the western half of central Oregon (called the Oregon Transect). Sensors mounted on six different aircraft have acquired data over the Oregon Transect in support of the OTTER project.

Angelici, Gary↗

NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms, etc.).Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as images, with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data-map sources.

Level 2↗

NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms,... etc.). Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as "images", with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data/map sources.

Aura↗

NASA NTRS2017

Revision to Global Persistent SAR Sampling with the NASA-ISRO SAR (NISAR) Mission

Abstract—The National Aeronautics and Space Administration (NASA) in the United States and the Indian Space Research Organisation (ISRO) are developing an Earth-orbiting science and applications mission that will exploit synthetic aperture radar to map Earth’s surface every 12 days, persistently on ascending and descending portions of the orbit, over all land and ice-covered surfaces. The mission’s primary objectives will be to study Earth land and ice deformation, and ecosystems, in areas of common interest to the US and Indian science communities. This single spacecraft solution with an L-band (24 cm wavelength) and S-band (10 cm wavelength) radar has a swath of over 240 km at fine resolution, using full polarimetry where needed, uses a reflector-feed system whereby the feed aperture elements are individually sampled to allow a scan-on-receive (“SweepSAR”) capability at both L-band and S-band. This design is in contrast to recent concepts towards large constellations of smaller radar satellites, and is driven by the science requirements for complete coverage over the 12-day repeat cycle, using repeat pass interferometry and polarimetry to measure deformation and surface properties. A single spacecraft with enough aperture, power, duty cycle, and downlink capacity was determined to be a more practical and implementable solution that multiple smaller spacecraft. The use of a single large aperture reflector for both the L- and Sband radars enables both to have comparable performance, leading to overall development and operational efficiencies.

Bhan, Rakesh↗

NASA NTRS2012

Moon Search Algorithms for NASA's Dawn Mission to Asteroid Vesta

A moon or natural satellite is a celestial body that orbits a planetary body such as a planet, dwarf planet, or an asteroid. Scientists seek understanding the origin and evolution of our solar system by studying moons of these bodies. Additionally, searches for satellites of planetary bodies can be important to protect the safety of a spacecraft as it approaches or orbits a planetary body. If a satellite of a celestial body is found, the mass of that body can also be calculated once its orbit is determined. Ensuring the Dawn spacecraft's safety on its mission to the asteroid Vesta primarily motivated the work of Dawn's Satellite Working Group (SWG) in summer of 2011. Dawn mission scientists and engineers utilized various computational tools and techniques for Vesta's satellite search. The objectives of this paper are to 1) introduce the natural satellite search problem, 2) present the computational challenges, approaches, and tools used when addressing this problem, and 3) describe applications of various image processing and computational algorithms for performing satellite searches to the electronic imaging and computer science community. Furthermore, we hope that this communication would enable Dawn mission scientists to improve their satellite search algorithms and tools and be better prepared for performing the same investigation in 2015, when the spacecraft is scheduled to approach and orbit the dwarf planet Ceres.

planetary sciences↗

NASA NTRSDate not supplied

NASA GLOBE CLOUD GAZE: Creating Data Quality Flags for Citizen Science Cloud Observations Matched to NASA Satellite Data

The GLOBE Program, NASA’s largest and longest lasting citizen science program about the Earth, has been collecting cloud observations matched to multiple satellite data daily. The program’s cloud protocol is historically the most popular protocol as your eyes are the only instruments you need to collect observations of the sky. This dataset includes over 3,300,000 cloud observations with variables like total cloud cover, cloud type and opacity that are collocated to the nearest overpass times of geostationary satellites (GOES-15, GOES-16, GOES-17, Meteosat-8, Meteosat-11, or Himawari-8), or to Clouds and the Earth’s Radiant Energy System (CERES) instruments onboard Aqua and Terra, or the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. In order to increase the usability of this dataset, the Community science project Leveraging Online and User Data through GLOBE And Zooniverse Engagement (CLOUD GAZE) has been developed to generate data quality flags of these ground-up and top-down perspectives of sky and clouds. Recently funded through NASA’s Citizen Science for Earth Systems Program, CLOUD GAZE has partnered with the Zooniverse online platform to obtain reference data and image tagging of sky photographs collected through The GLOBE Program’s clouds protocol. This paper will present the GLOBE Clouds dataset matched to NASA satellite data, integration of CLOUD GAZE to develop data quality flags, and research applications of the dataset (includes ground-up and top-down perspective comparisons, ground observations of dust storms and smoke plumes, and cloud observations in polar regions). The paper will also present on techniques and recommendations for classroom use and for community engagement, particularly for those looking to online resources.

Marilé Colón Robles↗

NASA NTRSDate not supplied

Physical Oceanography in the Solar System and Beyond

A key controller of a planet’s rotational evolution, and hence habitability, is tidal dissipation, which on Earth occurs primarily in the oceans. As the discovery of habitable exoplanets is a primary objective of exoplanet research, it is imperative that we understand how “exo-oceans” behave. Despite this importance, little research has investigated the physical oceanography of worlds other than Earth. This oversight has occurred even though the Earth science community has studied tidal flows in Earth’s oceans for over a century and developed sophisticated models that exquisitely match satellite altimetry data, e.g. Here, we present a) models of tidal effects on exoplanets to motivate the problem, b) the application of a physical oceanography model to a putative ancient Venus ocean, and c) the application of that model to an ensemble of “alternative Earths” with a range of continental configurations and seafloor properties. We find that oceanic tidal dissipation can span 5 orders of magnitude, revealing that simulating exo-oceans with Earth science tools will provide fundamental insight into exoplanet evolution and habitability

Physical Oceanography↗

NASA NTRSDate not supplied

JETT3: A Holistic, Integrated Analog for Artemis Lunar Surface Exploration

Since 1972, NASA astronauts have performed hundreds of Extravehicular Activities (EVAs) in support of Skylab, Space Shuttle and International Space Station missions. Not since Apollo, however, have EVAs been driven by discovery-based principles of scientific exploration. Upcoming Artemis missions are challenged to build on lessons learned from Apollo, merging 50 years of EVA experience with the planetary science community’s expertise in the remote surface exploration of Mars. The highest-fidelity preparation for Artemis includes both operational and scientific underpinning to represent the complete, complex picture of lunar surface operations. The Joint EVA & Human Surface Mobility Test Team (JETT) is an interdisciplinary team providing such an environment for collaborative analog testing. JETT builds upon prior analog campaigns (e.g., [1, 2]) to provide high-fidelity environments for hardware and concept of operations development. Sponsored by the NASA EVA & Human Surface Mobility Program (EHP), JETT includes representatives from EHP, NASA Engineering, the Science Mission Directorate (SMD), Human Health & Performance, and the Flight Operations Directorate (FOD). JETT tests evaluate NASA reference designs for EVA (e.g., suits and tools), address gaps and risks for Artemis lunar surface operations, develop capabilities for EVA and science tasks, enable technology maturation, and provide training for Artemis EVA operations. JETT3, the final JETT field test of FY22, occurred Oct 3-11, 2022 in the San Francisco Volcanic Field north of Flagstaff, AZ. The test focused on developing the Artemis concept of operations and systems, including integrating an Artemis-like Science Team into a NASA Flight Control Team (FCT) to plan and execute a series of simulated lunar EVAs in an environment analogous to Artemis 3.

T. E. Caswell↗

NASA NTRSDate not supplied

JETT3: A Holistic, Integrated Analog for Artemis Lunar Surface Exploration

T. E. Caswell↗

NASA NTRS1975

Jovian system science issues and implications for a Mariner Jupiter Orbiter mission

Science goals for missions to Jupiter in the early 1980's are reviewed and a case is made for the science community to play the key role in assigning relative priorities for these goals. A reference set of measurement requirements and their priorities is established and those high priority goals that are most demanding on spacecraft and mission design are used to develop a reference mission concept. An orbiter mission is required to satisfy a majority of the measurements, and a spacecraft data handling capability as least equivalent to the Mariner Jupiter/Saturn spacecraft is the major system design driver. This reference Mission Concept is called Mariner Jupiter Orbiter. The remaining measurement requirements are reviewed in light of the potential science return of this mission, and certain options are developed to augment this science return. Two attractive options fulfill high priority objectives not achieved by the reference Mariner Jupiter Orbiter mission alone: an atmospheric entry probe, released prior to orbit insertion; and a daughter satellite dedicated to particle and fields measurements, ejected into an independent orbit about Jupiter.

Beckman, J. C.↗

NASA NTRSDate not supplied

Transforming Science Prioritization Processes Using Artificial Intelligence

Artificial Intelligence (AI) and Machine Learning (ML) have potential to augment significantly the current labor-intensive processes of science prioritization, specifically by the National Academies’ Decadal Survey on behalf of NASA and NSF. Here we summarize what we believe to be the first exploratory demonstration-of-concept results from an application of AI/ML to Survey science prioritization. Specifically, we applied Latent Dirichlet Allocation (LDA) and Natural Language Processing (NLP) to reveal trends in published astrophysics research that may indicate science priorities and which could be applied to strategic planning. For the purpose of the work that we summarize here, AI/ML is able to analyze – that is, to “understand,” in a manner of speaking – a vast amount of text to reveal complex relationships among research topics, including the growth or decline of science community activities in those topics over time. We trained ourselves and AI/ML algorithms by using ~400,000 abstracts in the period 1998 to 2010 to “forecast” the Academies’ Astro2010 recommendations and compare with the solicited white papers. Comparing our results with actual Astro2010 recommendations allowed us to identify candidate metrics that better predicted the actual results of the Survey. We found, for example, that Compound Annual Growth Rate (CAGR) of papers published in a topic area is a good proxy measure for importance of this topic area of research. With this training complete, we identified candidate astrophysics astrophysics science priorities for the 2021+ period using the research during 2007 - 2019 . We conclude that appropriate application of AI can potentially significantly reduce the current workload of the Decadal Survey processes and reveal otherwise unrecognized characteristics in the body of astronomical research. We emphasize throughout the exploratory nature of our work, encouraging colleagues to pursue promising results further. Our most critical governing assumption was that increased (or decreased) research activity can be used to identify scientific or technology topic areas worthy of increased (or decreased) future emphasis. We discuss advantages, limitations, and recognize the “black box” nature of our technique. We note ethics issues associated, for example, with using AI/ML to reveal “hidden” meanings and biases in published work. Furthermore, inevitable improvements in AI may soon enable widespread and welcome identification of and advocacy for science and technology priorities by disparate and diverse groups and organizations. Consequently, we continue to urge a near-term, in-depth evaluation of appropriate applications of AI, including implications and consequences, as well as support for multiple follow-on assessments, of which ours is only a beginning.

Artificial Intelligence↗

NASA NTRS1991

A guide to NASA's Pilot Land Data System (PLDS)

NASA's Pilot Land Data System (PLDS) is a distributed information management system designed to support NASA's land science community. The PLDS provides a wide range of services including management of information about scientific data, access to a library of scientific data, a data ordering capability, communications, connection to data analysis facilities, and electronic mail. The PLDS provides these services by offering the scientist the capability to search for and order data, and to communicate electronically with other scientists and computers. Three functions enable scientists to find what data are available and where they reside. The first two, Find data summaries and Read detailed descriptions give summary and detailed descriptions about data sets or groups of related data sets, science, projects, and institutions which archive land data. The third, gives information about specific pieces of data. This last function has two components, Search systemwide inventory and Search local inventory. The first component enables the user to find data elements (images, geological samples, transects, maps, etc.) that exist anywhere in the PLDS while the second has only information about data at the local site. The first enables the user to find pieces of data from several different data sets with the same temporal and spatial coverage and other elements common to most data sets, while the second allows the user to select a data set based on these descriptors and on those that are unique to a data set. The PLDS provides capabilities that enable electronic file transfers, intercomputer connection, and electronic mail. Both TCP/IP and DECnet protocols are supported via the NASA Science Internet (NIS). Access is also available through Telenet.

Source record↗

NASA NTRS2001

Radarsat Antarctic Mapping Project: Antarctic Imaging Campaign 2

The Radarsat Antarctic Mapping Project is a collaboration between NASA and the Canadian Space Agency to map Antarctica using synthetic aperture radar (SAR). The first Antarctic Mapping Mission (AMM-1) was successfully completed in October 1997. Data from the acquisition phase of the 1997 campaign have been used to achieve the primary goal of producing the first, high-resolution SAR image map of Antarctica. The limited amount of data suitable for interferometric analysis have also been used to produce remarkably detailed maps of surface velocity for a few selected regions. Most importantly, the results from AMM-1 are now available to the general science community in the form of various resolution, radiometrically calibrated and geometrically accurate image mosaics. The second Antarctic imaging campaign occurred during the fall of 2000. Modified from AMM-1, the satellite remained in north looking mode during AMM-2 restricting coverage to regions north of about -80 degrees latitude. But AMM-2 utilized for the first time RADARSAT-1 fine beams providing an unprecedented opportunity to image many of Antarctica's fast glaciers whose extent was revealed through AMM-1 data. AMM-2 also captured extensive data suitable for interferometric analysis of the surface velocity field. This report summarizes the science goals, mission objectives, and project status through the acquisition phase and the start of the processing phase. The reports describes the efforts of team members including Alaska SAR Facility, Jet Propulsion Laboratory, Vexcel Corporation, Goddard Space Flight Center, Wallops Flight Facility, Ohio State University, Environmental Research Institute of Michigan, White Sands Facility, Canadian Space Agency Mission Planning and Operations Groups, and the Antarctic Mapping Planning Group.

Source record↗

NASA NTRS1992

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

The need to record some measure of the low-gravity environment of an orbiting space vehicle was recognized at an early stage of the U.S. Space Program. Such information was considered important for both the assessment of an astronaut's physical condition during and after space missions and the analysis of the fluid physics, materials processing, and biological sciences experiments run in space. Various measurement systems were developed and flown on space platforms beginning in the early 1970's. Similar in concept to land based seismometers that measure vibrations caused by earthquakes and explosions, accelerometers mounted on orbiting space vehicles measure vibrations in and of the vehicle due to internal and external sources, as well as vibrations in a sensor's relative acceleration with respect to the vehicle to which it is attached. The data collected over the years have helped to alter the perception of gravity on-board a space vehicle from the public's early concept of zero-gravity to the science community's evolution of thought from microgravity to milligravity to g-jitter or vibrational environment. Since the advent of the Shuttle Orbiter Program, especially since the start of Spacelab flights dedicated to scientific investigations, the interest in measuring the low-gravity environment in which experiments are run has increased. This interest led to the development and flight of numerous accelerometer systems dedicated to specific experiments. It also prompted the development of the NASA MSAD-sponsored Space Acceleration Measurement System (SAMS). The first SAMS units flew in the Spacelab on STS-40 in June 1991 in support of the first Spacelab Life Sciences mission (SLS-1). SAMS is currently manifested to fly on all future Spacelab missions.

Rogers, Melissa J. B.↗

NASA NTRS2023

Using Satellite-Based Terrestrial Water Storage Data: A Review

Land water storage plays a key role for the Earth’s climate, natural ecosystems, and human activities. Since the launch of the first Gravity Recovery and Climate Experiment (GRACE) mission in 2002, spaceborne observations of changes in terrestrial water storage (TWS) have provided a unique, global perspective on natural and human-induced changes in freshwater resources. Even though they have become much used within the broader Earth system science community, space-based TWS datasets still incorporate important and case-specific limitations which may not always be clear to users not familiar with the underlying processing algorithms. Here, we provide an accessible and illustrated overview of the measurement concept, of the main available data products, and of some frequently encountered technical terms and concepts. We summarize concrete recommendations on how to use TWS data in combination with other hydrological or climatological datasets, and guidance on how to avoid possible pitfalls. Finally, we provide an overview of some of the main applications of GRACE TWS data in the fields of hydrology and climate science. This review is written with the intention of supporting future research and facilitating the use of satellite-based terrestrial water storage datasets in interdisciplinary contexts.

Terrestrial water storage↗