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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Effect of Wind Speed on Aerosol Optical Depth over Remote Oceans, Based on Data from the Maritime Aerosol Network

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (approx. 0.004 - 0.005), even for strong winds over 10m/s. The relationships show significant scatter (correlation coefficients typically in the range 0.3 - 0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used

Smirnov, A.↗
NASA NTRS2000

BOREAS HYD-2 Estimated Snow Water Equivalent (SWE) from Microwave Measurements

The surface meteorological data collected at the Boreal Ecosystem-Atmosphere Study (BOREAS) tower and ancillary sites are being used as inputs to an energy balance model to monitor the amount of snow storage in the boreal forest region. The BOREAS Hydrology (HYD)-2 team used Snow Water Equivalent (SWE) derived from an energy balance model and in situ observed SWE to compare the SWE inferred from airborne and spaceborne microwave data, and to assess the accuracy of microwave retrieval algorithms. The major external measurements that are needed are snowpack temperature profiles, in situ snow areal extent, and SWE data. The data in this data set were collected during February 1994 and cover portions of the Southern Study Area (SSA), Northern Study Area (NSA), and the transect areas. The data are available from BORIS as comma-delimited tabular ASCII files. The SWE data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Powell, Hugh↗
NASA NTRS1980

Automated frequency standard stability data reduction

A design using a medium sized computer, a fiber optic communication link, and a desk top computer to reduce data collected at a remote site for analysis of frequency standard tests is described. Data generated at the Interim Frequency Standards Test Facility is collected on magnetic tape, which is then transported to a Sigma 5 computer. An Allan variance (two sample variance) is then calculated. The Allan variance (sigma vs tau) is then written to a data file in the Sigma 5. A fiber optic communication link between the Sigma 5 and a desk top computer was designed to transmit data in the Sigma 5 file to the desk top computer. A program was written for the desk top computer that will automatically access the data file in the Sigma 5, process the data and provide a data plot.

Knapp, L. J.↗
NASA NTRS2012

Light Curve Observations of Upper Stages in the Low Earth Orbit Environment

Active debris removal (ADR) is a potential means to remediate the orbital debris environment in low Earth orbit (LEO). Massive intact objects, including spent upper stages and retired payloads, with high collision probabilities have been suggested as potential targets for ADR. The challenges to remove such objects on a routine basis are truly monumental. A key piece of information needed for any ADR operations is the tumble motion of the targets. Rapid tumble motion (in excess of one degree per second) of a multiple-ton intact object could be a major problem for proximity and docking operations. Therefore, there is a need to characterize the general tumble motion of the potential ADR targets for future ADR planning. The NASA Orbital Debris Program Office has initiated an effort to identify the global tumble behavior of potential ADR targets in LEO. The activities include optical light curve observations, imaging radar data collection, and laboratory light curve simulations and modeling. This paper provides a preliminary summary of light curve data of more than 100 upper stages collected by two telescope facilities in Colorado and New Mexico between 2011 and 2012. Analyses of the data and implications for the tumble motions of the objects are also discussed in the paper.

Liou, J.-C.↗
NASA NTRS2000

BOREAS TGB-9 Above-canopy NMHC at SSA-OBS, SSA-OJP, and SSA-OA Sites

The BOREAS TGB-9 team collected data in order to inventory and quantify the anthropogenic and biogenic NMHCs over the BOREAS study areas. This data set contains concentration and mixing ratio values for several NMHCs collected at the BOREAS SSA from 27-May-1994 to 15-Sep-1994. The data are provided in tabular ASCII files.

Keiser, B. N.↗
NASA NTRS2012

Landsat Data Continuity Mission Expected Instrument Performance

The Landsat Data Continuity Mission (LDCM) is scheduled for a December 2012 launch date. LDCM is being managed by an interagency partnership between NASA and the U.S. Geological Survey (USGS). In order to provide the necessary spectral coverage of the visible through shortwave-infrared (SWIR) and the thermal-infrared (TIR), the satellite will carry two sensors. The Operational Land Imager (OLI) will collect data for nine visible to shortwave spectral bands with a spatial resolution of 30 m (with a 15 m panchromatic band). The Thermal Infrared Sensor (TIRS) will collect coincident image data for two TIR bands with a spatial resolution of 100 m. The OLI is fully assembled and tested and has been shipped by it's manufacturer, Ball Aerospace and Technology Corporation, to the Orbital Sciences Corporation (Orbital) facility where it is being integrated onto the LDCM spacecraft. Pre-launch testing indicates that OLI will meet all performance specification with margin. TIRS is in development at the NASA Goddard Space F!ight Center (GSFC) and is in final testing before shipping to the Orbital facility in January, 2012. The presentation will describe the LDCM satellite instrument systems, present pre-launch performance data for OLI and TIRS, and present simulated images to highlight notable features and expected imaging performance.

Dabney, Philip W.↗
NASA NTRS2004

Analysis of TRMM Microphysical Measurements: Tropical Rainfall Measuring Mission (TRMM)

SPEC Incorporated participated in three of the four TRMM field campaigns (TEFLUN-A, TEFLUN-B and KWAJEX), installing and operating a cloud particle imager (CPI) and a high volume precipitation spectrometer (HVPS) on the SPEC Learjet in TEFLUN-A, the University of North Dakota Citation in TEFLUN-B and KWAJEX, and a CPI on the NASA DC-8 in KWAJEX. This report presents and discusses new software tools and algorithms that were developed to analyze microphysical data collected during these field campaigns, as well as scientific interpretations of the data themselves. Software algorithms were developed to improve the analysis of microphysical measurements collected by the TRMM aircraft during the field campaigns. Particular attention was paid to developing and/or improving algorithms used to compute particle size distributions and ice water content. Software was also developed in support of production of the TRMM Common Microphysical Product (CMP) data files. CMP data files for TEFLUN-A field campaign were produced and submitted to the DAAC. Typical microphysical properties of convective and stratiform regions from TEFLUN-A and KWAJEX clouds were produced. In general, it was found that in the upper cloud region near -20 to -25 C, stratiform clouds contain very high (greater than 1 per cubic centimeter) concentrations of small ice particles, which are suspected to be a residual from homogeneous freezing and sedimentation of small drops in a convective updraft. In the upper cloud region near -20 to -25 C, convective clouds contain aggregates, which are not found lower in the cloud. Stratiform clouds contain aggregates at all levels, with the majority in the lowest levels. Convective cloud regions contain much higher LWC and drop concentrations than stratiform regions at all levels, and higher LWC in the middle and upper regions. Stratiform clouds contain higher IWC than convective clouds only at the lowest level. Irregular shaped ice particles are found in very high concentrations throughout both convective and stratiform cloud regions. A striking difference in particle shape in cirrus formed in situ, cirrus formed from maritime anvils and cirrus formed from continental anvils. Over 50% of the mass of in situ cirrus ice particles is composed of bullet rosettes, while bullet rosettes are virtually non-existent in maritime and tropical anvils. Tropical anvils are composed of mostly singular, plates, capped columns, and blocky irregular shapes, while continental anvils have a much higher percentage of aggregates, some of which are chains of small spheroidal particles that appear to result from homogeneous freezing of drops. A correlation between high electric fields in continental anvils and the formation of aggregates is hypothesized.

Source record↗
NASA NTRS2014

The EDSN Intersatellite Communications Architecture

The Edison Demonstration of Smallsat Networks (EDSN) is a swarm of eight 1.5U Cubesats developed by the NASA Ames Research Center under the Small Spacecraft Technology Program (SSTP) within NASA Space Technology Mission Directorate (STMD). EDSN, scheduled for launch in late 2014, is designed to explore the use of small spacecraft networks to make synchronized, multipoint scientific measurements, and to organize and pass those data to the ground through their network. Networked swarms of these small spacecraft will open new horizons in astronomy, Earth observations and solar physics. Their range of applications include the formation of synthetic aperture radars for Earth sensing systems, large aperture observatories for next generation telescopes and the collection of spatially distributed measurements of time varying systems, probing the Earth's magnetosphere, Earth-Sun interactions and the Earth's geopotential. The EDSN communications network is maintained and operated by a simple set of predefined rules operating independently on all eight spacecraft without direction from ground based systems. One spacecraft serves as a central node, requesting and collecting data from the other seven spacecraft, organizing the data and passing it to a ground station at regular intervals. The central node is rotated among the spacecraft on a regular basis, providing robustness against the failure of a single spacecraft. This paper describes the communication architecture of the EDSN network and its operation with small spacecraft of limited electrical power, computing power and communication range. Furthermore, the problems of collecting and prioritizing data through a system that has data throughput bottlenecks are addressed. Finally, future network enhancements that can be built on top of the current EDSN hardware are discussed.

Communications↗
NASA NTRS2007

Real-Time Wireless Data Acquisition System

Current and future aerospace requirements demand the creation of a new breed of sensing devices, with emphasis on reduced weight, power consumption, and physical size. This new generation of sensors must possess a high degree of intelligence to provide critical data efficiently and in real-time. Intelligence will include self-calibration, self-health assessment, and pre-processing of raw data at the sensor level. Most of these features are already incorporated in the Wireless Sensors Network (SensorNet(TradeMark)), developed by the Instrumentation Group at Kennedy Space Center (KSC). A system based on the SensorNet(TradeMark) architecture consists of data collection point(s) called Central Stations (CS) and intelligent sensors called Remote Stations (RS) where one or more CSs can be accommodated depending on the specific application. The CS's major function is to establish communications with the Remote Stations and to poll each RS for data and health information. The CS also collects, stores and distributes these data to the appropriate systems requiring the information. The system has the ability to perform point-to-point, multi-point and relay mode communications with an autonomous self-diagnosis of each communications link. Upon detection of a communication failure, the system automatically reconfigures to establish new communication paths. These communication paths are automatically and autonomously selected as the best paths by the system based on the existing operating environment. The data acquisition system currently under development at KSC consists of the SensorNet(TradeMark) wireless sensors as the remote stations and the central station called the Radio Frequency Health Node (RFHN). The RFF1N is the central station which remotely communicates with the SensorNet(TradeMark) sensors to control them and to receive data. The system's salient feature is the ability to provide deterministic sensor data with accurate time stamps for both time critical and non-time critical applications. Current wireless standards such as Zigbee(TradeMark) and Bluetooth(Registered TradeMark) do not have these capabilities and can not meet the needs that are provided by the SensorNet technology. Additionally, the system has the ability to automatically reconfigure the wireless communication link to a secondary frequency if interference is encountered and can autonomously search for a sensor that was perceived to be lost using the relay capabilities of the sensors and the secondary frequency. The RFHN and the SensorNet designs are based on modular architectures that allow for future increases in capability and the ability to expand or upgrade with relative ease. The RFHN and SensorNet sensors .can also perform data processing which forms a distributed processing architecture allowing the system to pass along information rather than just sending "raw data points" to the next higher level system. With a relatively small size, weight and power consumption, this system has the potential for both spacecraft and aircraft applications as well as ground applications that require time critical data.

Valencia, Emilio J.↗
NASA NTRS2016

GeneLab Phase 2: Integrated Search Data Federation of Space Biology Experimental Data

The GeneLab project is a science initiative to maximize the scientific return of omics data collected from spaceflight and from ground simulations of microgravity and radiation experiments, supported by a data system for a public bioinformatics repository and collaborative analysis tools for these data. The mission of GeneLab is to maximize the utilization of the valuable biological research resources aboard the ISS by collecting genomic, transcriptomic, proteomic and metabolomic (so-called omics) data to enable the exploration of the molecular network responses of terrestrial biology to space environments using a systems biology approach. All GeneLab data are made available to a worldwide network of researchers through its open-access data system. GeneLab is currently being developed by NASA to support Open Science biomedical research in order to enable the human exploration of space and improve life on earth. Open access to Phase 1 of the GeneLab Data Systems (GLDS) was implemented in April 2015. Download volumes have grown steadily, mirroring the growth in curated space biology research data sets (61 as of June 2016), now exceeding 10 TB/month, with over 10,000 file downloads since the start of Phase 1. For the period April 2015 to May 2016, most frequently downloaded were data from studies of Mus musculus (39) followed closely by Arabidopsis thaliana (30), with the remaining downloads roughly equally split across 12 other organisms (each 10 of total downloads). GLDS Phase 2 is focusing on interoperability, supporting data federation, including integrated search capabilities, of GLDS-housed data sets with external data sources, such as gene expression data from NIHNCBIs Gene Expression Omnibus (GEO), proteomic data from EBIs PRIDE system, and metagenomic data from Argonne National Laboratory's MG-RAST. GEO and MG-RAST employ specifications for investigation metadata that are different from those used by the GLDS and PRIDE (e.g., ISA-Tab). The GLDS Phase 2 system will implement a Google-like, full-text search engine using a Service-Oriented Architecture by utilizing publicly available RESTful web services Application Programming Interfaces (e.g., GEO Entrez Programming Utilities) and a Common Metadata Model (CMM) in order to accommodate the different metadata formats between the heterogeneous bioinformatics databases. GLDS Phase 2 completion with fully implemented capabilities will be made available to the general public in September 2017.

Space Biology↗
NASA NTRS2014

Aggregation Tool to Create Curated Data albums to Support Disaster Recovery and Response

Despite advances in science and technology of prediction and simulation of natural hazards, losses incurred due to natural disasters keep growing every year. Natural disasters cause more economic losses as compared to anthropogenic disasters. Economic losses due to natural hazards are estimated to be around $6-$10 billion dollars annually for the U.S. and this number keeps increasing every year. This increase has been attributed to population growth and migration to more hazard prone locations such as coasts. As this trend continues, in concert with shifts in weather patterns caused by climate change, it is anticipated that losses associated with natural disasters will keep growing substantially. One of challenges disaster response and recovery analysts face is to quickly find, access and utilize a vast variety of relevant geospatial data collected by different federal agencies such as DoD, NASA, NOAA, EPA, USGS etc. Some examples of these data sets include high spatio-temporal resolution multi/hyperspectral satellite imagery, model prediction outputs from weather models, latest radar scans, measurements from an array of sensor networks such as Integrated Ocean Observing System etc. More often analysts may be familiar with limited, but specific datasets and are often unaware of or unfamiliar with a large quantity of other useful resources. Finding airborne or satellite data useful to a natural disaster event often requires a time consuming search through web pages and data archives. Additional information related to damages, deaths, and injuries requires extensive online searches for news reports and official report summaries. An analyst must also sift through vast amounts of potentially useful digital information captured by the general public such as geo-tagged photos, videos and real time damage updates within twitter feeds. Collecting and aggregating these information fragments can provide useful information in assessing damage in real time and help direct recovery efforts. The search process for the analyst could be made much more efficient and productive if a tool could go beyond a typical search engine and provide not just links to web sites but actual links to specific data relevant to the natural disaster, parse unstructured reports for useful information nuggets, as well as gather other related reports, summaries, news stories, and images. This presentation will describe a semantic aggregation tool developed to address similar problem for Earth Science researchers. This tool provides automated curation, and creates "Data Albums" to support case studies. The generated "Data Albums" are compiled collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; information about the event contained in news reports, and images or videos to supplement research analysis. An ontology-based relevancy-ranking algorithm drives the curation of relevant data sets for a given event. This tool is now being used to generate a catalog of Hurricane Case Studies at Global Hydrology Resource Center (GHRC), one of NASA's Distribute Active Archive Centers. Another instance of the Data Albums tool is currently being created in collaboration with NASA/MSFC's SPoRT Center, which conducts research on unique NASA products and capabilities that can be transitioned to the operational community to solve forecast problems. This new instance focuses on severe weather to support SPoRT researchers in their model evaluation studies

Ramachandran, Rahul↗
NASA NTRS1980

The role of World Data Centers and the Lunar and Planetary Institute in the international exchange of lunar and planetary data

The success of many lunar and planetary investigations has resulted in the accumulation of a mass of data in a myriad of formats and medias. The application of these data to comparative planetology, origin of the solar system, and potential industrial applications of space has made it necessary for scientists from many disciplines to have access to the data. The collections of these data are so diverse that it is often difficult to select what is needed based on catalog information alone. The Lunar and Planetary Institute (LPI) proposes to bring the user and the data together. As a research support organization operated by the Universities Space Research Association, the LPI through its active Visiting Scientist Program, a balanced program of study workshops and topical conferences, and organized and supervised data collections has assisted scientists, educators, and students to review, study, and obtain the data necessary to the pursuit of their research.

Waranius, F. B.↗
NASA NTRSDate not supplied

Applied Uses of MERRA Reanalyses: Current and Future Prospects

During the initial planning of the Modern Era Retrospective-analysis for Research and Applications (MERRA), the project was envisioned to become a tool for applied sciences and decision makers, as well as weather and climate research. MERRA was the first reanalysis to provide data at 1 hourly frequencies. After discussions with wind energy users, 50m above the surface winds were included in the data collection to begin to represent the environment at the turbine height. MERRA-2 was the first reanalysis to include interactive and assimilated aerosols. From these, PM 1, 2.5 and 10 records have been computed and contribute to the climate and health sector. The US Center for Disease Control is accessing MERRA-2 data for comparison along with their health data. MERRA-2 Extreme Indices have been computed from the high frequency data (e.g. precipitation maxima, heat waves and fire weather). These have been used to characterize the changing extremes in the United States and around the globe as well as the weather associated with the extremes. The next-generation, MERRA-21C, includes increased resolution (25km) and continues to provide innovative Earth system data. For example, a boundary layer collection will provide constant height level data starting at 100m, continuing up to 4000m. This will provide detailed information about the boundary layer processes that greatly affect the biosphere. Chemical tracers for constituents are included in the system. The ensemble data assimilation is run with 32 members, and the variance for critical variables are stored. We will explore the use of this variance as one measure of uncertainty relevant for applied uses, which has not been included in any MERRA reanalysis. We will discuss use case scenarios developed to engage with the energy and financial sectors, to better understand their needs for climate data. Prospects for further downscaling of reanalyses will also be explored.

Michael Bosilovich↗
NASA NTRS2012

The Characterization of Virgo Data and Its Impact on Gravitational-Wave Searches

Between 2007 and 2010 Virgo collected data in coincidence with the LIGO and GEO gravitational-wave (GW) detectors. These data have been searched for GWs emitted by cataclysmic phenomena in the universe, by non-axisymmetric rotating neutron stars or from a stochastic background in the frequency band of the detectors. The sensitivity of GW searches is limited by noise produced by the detector or its environment. It is therefore crucial to characterize the various noise sources in a GW detector. This paper reviews the Virgo detector noise sources, noise propagation, and conversion mechanisms which were identified in the three first Virgo observing runs. In many cases, these investigations allowed us to mitigate noise sources in the detector, or to selectively flag noise events and discard them from the data. We present examples from the joint LIGO-GEO-Virgo GW searches to show how well noise transients and narrow spectral lines have been identified and excluded from the Virgo data. We also discuss how detector characterization can improve the astrophysical reach of gravitational wave searches.

Characterization↗
NASA NTRS2009

Feature Detection Systems Enhance Satellite Imagery

In 1963, during the ninth orbit of the Faith 7 capsule, astronaut Gordon Cooper skipped his nap and took some photos of the Earth below using a Hasselblad camera. The sole flier on the Mercury-Atlas 9 mission, Cooper took 24 photos - never-before-seen images including the Tibetan plateau, the crinkled heights of the Himalayas, and the jagged coast of Burma. From his lofty perch over 100 miles above the Earth, Cooper noted villages, roads, rivers, and even, on occasion, individual houses. In 1965, encouraged by the effectiveness of NASA s orbital photography experiments during the Mercury and subsequent Gemini manned space flight missions, U.S. Geological Survey (USGS) director William Pecora put forward a plan for a remote sensing satellite program that would collect information about the planet never before attainable. By 1972, NASA had built and launched Landsat 1, the first in a series of Landsat sensors that have combined to provide the longest continuous collection of space-based Earth imagery. The archived Landsat data - 37 years worth and counting - has provided a vast library of information allowing not only the extensive mapping of Earth s surface but also the study of its environmental changes, from receding glaciers and tropical deforestation to urban growth and crop harvests. Developed and launched by NASA with data collection operated at various times by the Agency, the National Oceanic and Atmospheric Administration (NOAA), Earth Observation Satellite Company (EOSAT, a private sector partnership that became Space Imaging Corporation in 1996), and USGS, Landsat sensors have recorded flooding from Hurricane Katrina, the building boom in Dubai, and the extinction of the Aral Sea, offering scientists invaluable insights into the natural and manmade changes that shape the world. Of the seven Landsat sensors launched since 1972, Landsat 5 and Landsat 7 are still operational. Though both are in use well beyond their intended lifespans, the mid-resolution satellites, which provide the benefit of images detailed enough to reveal large features like highways while still broad enough for global coverage, continue to scan the entirety of the Earth s surface. In 2012, NASA plans to launch the Landsat Data Continuity Mission (LDCM), or Landsat 8, to extend the Landsat program s contributions to cartography, water management, natural disaster relief planning, and more.

Source record↗
NASA NTRS1973

Detection of oil spills using a 13.3-GHz radar scatterometer.

This paper describes the results of an analysis of 13.3-GHz single-polarized scatterometer data collected during NASA/MSC mission 135, flown on March 16, 1970. Data were gathered over a crude oil spill on the Gulf of Mexico (test site 128) off the Mississippi delta. With the aid of RC-8 camera photographs the scattering cross section was correlated with the extent of the oil spill. The scattering cross section at higher incidence angles (25 to 50 deg) decreased by 5-10 db in the presence of the oil spill. This was attributed to the damping by oil of small gravity and capillary waves. The composite scattering theory and the scatterometer-acquired data were used to obtain an expression of radar scattering over ocean surfaces with oil spills. The study demonstrates that the presence and extent of oil spills can be detected with high-frequency radar systems.

Krishen, K.↗
NASA NTRS1979

Skylab medical data evaluation program (SMEDEP)

A day-by-day summary of selected data collected during the experiment is presented. The clinical and environmental data are presented in a mission-day format along with a tabulation of biomedical measurements whose values exceed three standard deviations from the preflight measurements.

Hoffler, G. W.↗
NASA NTRS1983

The effects of vegetation and soil hydraulic properties on passive microwave sensing of soil moisture: Data report for the 1982 fiels experiments

Field experiments to (1) study the biomass and geometrical structure properties of vegetation canopies to determine their impact on microwave emission data, and (2) to verify whether time series microwave data can be related to soil hydrologic properties for use in soil type classification. Truck mounted radiometers at 1.4 GHz and 5 GHz were used to obtain microwave brightness temperatures of bare vegetated test plots under different conditions of soil wetness, plant water content and canopy structure. Observations of soil moisture, soil temperature, vegetation biomass and other soil and canopy parameters were made concurrently with the microwave measurements. The experimental design and data collection procedures for both experiments are documented and the reduced data are presented in tabular form.

Oneill, P.↗