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At least 163 records · Page 9

Next-generation Strategies for Human Lunar Sorties

The science community has had success in remote field experiences using two distinctly different models for humans-in-the-loop: the Apollo Science Support team (science backroom), and the robotic exploration of Mars. In the Apollo experience, the science team helped train the crew, designed geologic traverses, and made real-time decisions by reviewing audio and video transmissions and providing recommendations for geologic sampling. In contrast, the Mars Exploration Rover (MER) and Mars Science Lab (MSL) missions have been conducted entirely robotically, with significant time delays between science- driven decisions and remote field activities. Distinctive operations methods and field methodologies were developed for MER/MSL [1,2] because of the reliance on the "backroom" science team (rather than astronaut crew members) to understand the surroundings. Additionally, data are relayed to the team once per day, giving the team many hours or even days to assimilate the data and decide on a plan of action.

Cohen, B. A.↗

Using Image Pro Plus Software to Develop Particle Mapping on Genesis Solar Wind Collector Surfaces

The continued success of the Genesis mission science team in analyzing solar wind collector array samples is partially based on close collaboration of the JSC curation team with science team members who develop cleaning techniques and those who assess elemental cleanliness at the levels of detection. The goal of this collaboration is to develop a reservoir of solar wind collectors of known cleanliness to be available to investigators. The heart and driving force behind this effort is Genesis mission PI Don Burnett. While JSC contributes characterization, safe clean storage, and benign collector cleaning with ultrapure water (UPW) and UV ozone, Burnett has coordinated more exotic and rigorous cleaning which is contributed by science team members. He also coordinates cleanliness assessment requiring expertise and instruments not available in curation, such as XPS, TRXRF [1,2] and synchrotron TRXRF. JSC participates by optically documenting the particle distributions as cleaning steps progress. Thus, optical document supplements SEM imaging and analysis, and elemental assessment by TRXRF.

Rodriquez, Melissa C.↗

Science Application Teams

This paper discusses the science application team activities. Science Application team are: (1) Represent the diversity of NASA onboard computing of the future. (2) Drive architecture and system software requirements. (3) Demonstrate the benefit of highly capable computing onboard. (4) Study the birth of the first galaxies. (5) Study formation of stars. (6) Discusses the next generation space telescope hardware/software requirement: image processing and on-board optical calibration. Also discusses gamma ray large area space telescope; orbital thermal imaging spectrometer; solar terrestrial probe program; autonomous Mars rover;fault tolerance and errors.

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Exploring the Relationship Between Science Funding and Science Productivity on Extended Missions

Introduction: The goal of this summer internship research project was to explore the relationship between the level of funding for science team research and science productivity for planetary spaceflight missions. The productivity and funding for the prime and extended missions were compared when possible. Determining the actual rather than anecdotal relationship between the level of science team funding and their productivity will help determine the adequacy of science team funding. Additionally, determining whether productivity increases or decreases over time (within missions, or within the years between different missions) provides insights into ongoing trends. This project was conducted using data from 11 extended missions within the Planetary Science Division. The main goals of this project were to 1) quantify the level of productivity of the science team during the extended portion of each mission, 2) compare the level of productivity between different types of missions, and 3) compare the level of productivity between the prime missions and extended missions. Methodology: The central metric enters around the “publication rate” of each mission. This rate is normalized in a variety of ways, including the number of publications per year, per Co-I, and per instruments. For the most part, this data was attainable through mission websites, team rosters, and data collected from previous projects. The publication data for this project utilized the SAO/NASA Astrophysics Data System, and it consisted of a search for any papers from the extended mission that had a co-investigator as an author. The time period for these searches also included an additional two years after the end of the extended mission to account for additional time it typically takes to finish data analysis and publish papers. Data from prime missions was collected from a previous project that measured similar metrics for the same missions. When comparing the different types of missions, three factors were used: mission size, dates of the prime and extended missions, and the type of the mission (rover, flyby, orbiter, or lander). To determine mission size, missions were compared by the number of Co-I’s on the mission, the number of instruments in the payload, and the mission class. Findings: On average, prime mission publication rates were generally higher than those of extended missions. Out of the nine missions used for this comparison, six had a higher prime mission publication rate and three had a higher extended mission publication rate. This distinction was interesting to observe, but it should be noted that the methodology for determing the number of published papers differed for the prime missions and the extended missions Discovery missions were found to be the most scientifically productive. Additionally, more recent extended missions tend to possess greater productivity. When comparing missions of different types, it was found that orbiters were much more productive than other types of missions. Future Work: There are a number of opportunities to extend and improve on this project in the future. Even though the metrics used were the same, the prime mission data could be recollected from the same sources as the extended mission data (Astrophysics Data System) to insure greater consistency. The impact level of the publications could also be accounted for, and financial data could be used to compare teams with different levels of funding. Additionally, more missions could be examined to increase the sample size of these comparisons, especially the comparison of different mission types which had an incredibly small sample size for some categories.

Cameron Maxwell Thompson↗

The Suomi National Polar-Orbiting Partnership (SNPP): Continuing NASA Research and Applications

The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).

remote sensing↗

Datalist: A Value Added Service to Enable Easy Data Selection

Imagine a user wanting to study hurricane events. This could involve searching and downloading multiple data variables from multiple data sets. The currently available services from the Goddard Earth Sciences Data and Information Services Center (GES DISC) only allow the user to select one data set at a time. The GES DISC started a Data List initiative, in order to enable users to easily select multiple data variables. A Data List is a collection of predefined or user-defined data variables from one or more archived data sets. Target users of Data Lists include science teams, individual science researchers, application users, and educational users. Data Lists are more than just data. Data Lists effectively provide users with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services, all available from one-stop shopping. Data Lists are created based on the software architecture of the GES DISC Unified User Interface (UUI). The Data List service is completely data-driven, and a Data List is treated just as any other data set. The predefined Data Lists, created by the experienced GES DISC science support team, should save a significant amount of time that users would otherwise have to spend.

Datalist↗

Thermosphere-ionosphere-mesosphere energetics and dynamics (TIMED). The TIMED mission and science program report of the science definition team. Volume 1: Executive summary

A Science Definition Team was established in December 1990 by the Space Physics Division, NASA, to develop a satellite program to conduct research on the energetics, dynamics, and chemistry of the mesosphere and lower thermosphere/ionosphere. This two-volume publication describes the TIMED (Thermosphere-Ionosphere-Mesosphere, Energetics and Dynamics) mission and associated science program. The report outlines the scientific objectives of the mission, the program requirements, and the approach towards meeting these requirements.

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The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.↗

Astronomical activities of the Apollo orbital science photographic team

A partial accounting of Apollo Orbital Science Photographic Team (APST) work is presented as reported by one of its members who provided scientific recommendations for, guidance in, and reviews of photography in astronomy. Background on the formation of the team and its functions and management are discussed. It is concluded that the APST clearly performed the overall objective for which it was established - to improve the scientific value of the Apollo lunar missions. Specific reasons for this success are given.

Mercer, R. D.↗

Overview of NASA's Microgravity Materials Science Program

The microgravity materials program was nearly eliminated in the middle of the aughts due to budget constraints. Hardware developments were eliminated. Some investigators with experiments that could be performed using ISS partner hardware received continued funding. Partnerships were established between US investigators and ESA science teams for several investigations. ESA conducted peer reviews on the proposals of various science teams as part of an ESA AO process. Assuming he or she was part of a science team that was selected by the ESA process, a US investigator would submit a proposal to NASA for grant funding to support their part of the science team effort. In a similar manner, a US materials investigator (Dr. Rohit Trivedi) is working as a part of a CNES selected science team. As funding began to increase another seven materials investigators were selected in 2010 through an NRA mechanism to perform research related to development of Materials Science Research Rack investigations. One of these has since been converted to a Glovebox investigation.

Downey, James Patton↗

Minutes of TOPEX/POSEIDON Science Working Team Meeting and Ocean Tides Workshop

This third TOPEX/POSEIDON Science Working Team meeting was held on December 4, 1994 to review progress in defining ocean tide models, precision Earth orbits, and various science algorithms. A related workshop on ocean tides convened to select the best models to be used by scientists in the Geophysical Data Records.

Fu, Lee-Lueng↗

Trajectory selection for the Mariner Jupiter/Saturn 1977 Project

This paper describes the use of decision analysis to facilitate a group decision-making problem in the selection of trajectories for the two spacecraft of the Mariner Jupiter/Saturn 1977 Project. This NASA project includes the participation of some eighty scientists divided by specialization among eleven science teams. A set of thirty-two candidate trajectory pairs was developed by the Project in collaboration with the science teams. Each science team then ordinally ranked and assigned cardinal utility function values to the trajectory pairs. These data and statistics derived from collective choice rules were used by the scientists in selecting the preferred trajectory pair.

Dyer, J. S.↗

Mercury Orbiter: Report of the Science Working Team

The results are presented of the Mercury Orbiter Science Working Team which held three workshops in 1988 to 1989 under the auspices of the Space Physics and Planetary Exploration Divisions of NASA Headquarters. Spacecraft engineering and mission design studies at the Jet Propulsion Lab were conducted in parallel with this effort and are detailed elsewhere. The findings of the engineering study, summarized herein, indicate that spin stabilized spacecraft carrying comprehensive particles and fields experiments and key planetology instruments in high elliptical orbits can survive and function in Mercury orbit without costly sun shields and active cooling systems.

Belcher, John W.↗

M3 Status and Science Discussion

Members of the M3 Science Team will attend the Chandrayaan-I Science Team Meeting in Bangalore, India to present a brief summary of instrument status and the near-term milestones (e.g., final I&T, pre-ship review). The principal purpose of the meeting is to interact with other members of the Chandrayaan-I Science Team to prepare for successful science return. The objectives are: 1) Characterize the diversity and extent of different types of basaltic volcanism; 2) Constrain evolution over time; and 3) Examine high priority regional sites.

Pieters, Carle↗

FIFE in 1992 - Results, scientific gains, and future research directions

A summary is presented of some of the more significant findings of the science teams and science staff of FIFE, emphasizing scientific gains, and outlining some future research directions. Attention is given to interactions between surface and boudary layer heat fluxes, momentum fluxes, and correlations between near-surface heat and CO2 fluxes and satellite data. Consideration is given to improved understanding of the exchanges between the land surface and the atmosphere at the local scale.

Sellers, P. J.↗

AXAF FITS standard for ray trace interchange

A standard data format for the archival and transport of x-ray events generated by ray trace models is described. Upon review and acceptance by the Advanced X-ray Astrophysics Facility (AXAF) Software Systems Working Group (SSWG), this standard shall become the official AXAF data format for ray trace events. The Flexible Image Transport System (FITS) is well suited for the purposes of the standard and was selected to be the basis of the standard. FITS is both flexible and efficient and is also widely used within the astronomical community for storage and transfer of data. In addition, software to read and write FITS format files are widely available. In selecting quantities to be included within the ray trace standard, the AXAF Mission Support team, Science Instruments team, and the other contractor teams were surveyed. From the results of this survey, the following requirements were established: (1) for the scientific needs, each photon should have associated with it: position, direction, energy, and statistical weight; the standard must also accommodate path length (relative phase), and polarization. (2) a unique photon identifier is necessary for bookkeeping purposes; (3) a log of individuals, organizations, and software packages that have modified the data must be maintained in order to create an audit trail; (4) a mechanism for extensions to the basic kernel should be provided; and (5) the ray trace standard should integrate with future AXAF data product standards.

Hsieh, Paul F.↗

MODIS Direct Broadcast and Remote Sensing Applications

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard both Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). Equipped with direct broadcast capability, the MODIS measurements can be received worldwide real time. There are 82 ingest sites (over 900 users, listed on the Direct Readout Portal) around the world for Terra/Aqua-MODIS Direct Broadcast DB) downlink. This represents 27 (6 from EOS science team members) science research organizations for DB land, ocean and atmospheric processing, and 53 companies that base their application algorithms and value added products on DB data. In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of aerosol/cloud optical properties, especially optical thickness and effective particle size. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Preliminary results will be presented and discussed their implications in regional-to-global climatic effects.

Tsay, Si-Chee↗

Geolab in NASA's First Generation Pressurized Excursion Module: Operational Concepts

We are building a prototype laboratory for preliminary examination of geological samples to be integrated into a first generation Habitat Demonstration Unit-1/Pressurized Excursion Module (HDU1-PEM) in 2010. The laboratory GeoLab will be equipped with a glovebox for handling samples, and a suite of instruments for collecting preliminary data to help characterize those samples. The GeoLab and the HDU1-PEM will be tested for the first time as part of the 2010 Desert Research and Technology Studies (DRATS), NASAs annual field exercise designed to test analog mission technologies. The HDU1-PEM and GeoLab will participate in joint operations in northern Arizona with two Lunar Electric Rovers (LER) and the DRATS science team. Historically, science participation in DRATS exercises has supported the technology demonstrations with geological traverse activities that are consistent with preliminary concepts for lunar surface science Extravehicular Activities (EVAs). Next years HDU1-PEM demonstration is a starting point to guide the development of requirements for the Lunar Surface Systems Program and test initial operational concepts for an early lunar excursion habitat that would follow geological traverses along with the LER. For the GeoLab, these objectives are specifically applied to enable future geological surface science activities. The goal of our GeoLab is to enhance geological science returns with the infrastructure that supports preliminary examination, early analytical characterization of key samples, insight into special considerations for curation, and data for prioritization of lunar samples for return to Earth.

Evans, C. A.↗