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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

(abstract) Alaska SAR Facility Ocean and Ice Data Opportunities Over the Next Decade

The Alaska SAR Facility (ASF) is currently processing data from four satellites. All of these generate SAR data useful for ice observations and three of them generate data useful for ocean observations. The data sets from these satellites are available to approved US and other investigators although the approval mechanisms are different. More satellites are planned. These will carry SAR instruments of increased capability for ocean and ice observations. We will discuss the anticipated situation for access to these data sets by the scientific community and we will speculate on what the major oceanographic applications may be.

ice ocean observations SAR satellite observations ↗
NASA NTRS2007

NASA Lunar Base Wireless System Propagation Analysis

There have been many radio wave propagation studies using both experimental and theoretical techniques over the recent years. However, most of studies have been in support of commercial cellular phone wireless applications. The signal frequencies are mostly at the commercial cellular and Personal Communications Service bands. The antenna configurations are mostly one on a high tower and one near the ground to simulate communications between a cellular base station and a mobile unit. There are great interests in wireless communication and sensor systems for NASA lunar missions because of the emerging importance of establishing permanent lunar human exploration bases. Because of the specific lunar terrain geometries and RF frequencies of interest to the NASA missions, much of the published literature for the commercial cellular and PCS bands of 900 and 1800 MHz may not be directly applicable to the lunar base wireless system and environment. There are various communication and sensor configurations required to support all elements of a lunar base. For example, the communications between astronauts, between astronauts and the lunar vehicles, between lunar vehicles and satellites on the lunar orbits. There are also various wireless sensor systems among scientific, experimental sensors and data collection ground stations. This presentation illustrates the propagation analysis of the lunar wireless communication and sensor systems taking into account the three dimensional terrain multipath effects. It is observed that the propagation characteristics are significantly affected by the presence of the lunar terrain. The obtained results indicate the lunar surface material, terrain geometry and antenna location are the important factors affecting the propagation characteristics of the lunar wireless systems. The path loss can be much more severe than the free space propagation and is greatly affected by the antenna height, surface material and operating frequency. The results from this paper are important for the lunar wireless system link margin analysis in order to determine the limits on the reliable communication range, achievable data rate and RF coverage performance at planned lunar base work sites.

Hwu, Shian U.↗
NASA NTRS2012

GPM Mission Overview and U.S. Science Status

The Global Precipitation Measurement (GPM) Mission is an international satellite mission to unify and advance precipitation measurements from a constellation of research and operational sensors to provide "next-generation" precipitation products [1-2]. Water is fundamental to life on Earth. Knowing where and how much rain and snow falls globally is vital to understanding how weather and climate impact both our environment and Earth's water and energy cycles, including effects on agriculture, fresh water availability, and responses to natural disasters. Since rainfall and snowfall vary greatly from place to place and over time, satellites can provide more uniform observations of rain and snow around the globe than ground instruments, especially in areas where surface measurements are difficult. Relative to current global rainfall products, GPM data products will be characterized by: (l) more accurate instantaneous precipitation measurements (especially for light rain and cold-season solid precipitation), (2) more frequent sampling by an expanded constellation of domestic and international microwave radiometers including operational humidity sounders, (3) intercalibrated microwave brightness temperatures from constellation radiometers within a unified framework, and (4) physical-based precipitation retrievals from constellation radiometers using a common a priori cloud/hydrometeor database derived from GPM Core sensor measurements. The cornerstone of the GPM mission is the deployment of a Core Observatory in a unique 65 non-Sun-synchronous orbit to serve as a physics observatory and a reference standard to unify precipitation measurements by a constellation of dedicated and operational passive microwave sensors. The design of the GPM Core Observatory is an advancement of the Tropical Rainfall Measuring Mission (TRMM)'s highly successful rain-sensing package. The Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a multichannel (l0-183 GHz) GPM Microwave Radiometer (GMI). Since light rain and falling snow account for a significant fraction of precipitation occurrence in middle and high latitudes, the GPM instruments extend the capabilities of the TRMM sensors to detect falling snow, measure light rain, and provide, for the first time, quantitative estimates of microphysical properties of precipitation particles. The combined use of DPR and GMI measurements will place greater constraints on possible solutions to radiometer retrievals to improve the accuracy and consistency of precipitation retrievals from all constellation radiometers. The GMI uses 13 different microwave channels to observe energy from the different types of precipitation through clouds for estimating everything from heavy to light rain and for detecting falling snow. As the satellite passes over Earth, the GMI constantly scans a region 885 kilometers across. The Ball Aerospace and Technology Corporation built the GMI under contract with NASA Goddard Space Flight Center. The DPR provides three-dimensional information about precipitation particles derived from reflected energy by these particles at different heights within the cloud system. The two frequencies of the DPR also allow the radar to infer the sizes of precipitation particles and offer insights into a storm's physical characteristics. The Ka-band frequen~y scans across a region of 125 kilometers and is nested within the wider scan of the Ku-band frequency of 245 kilometers. The Japan Aerospace and Exploration Agency (JAXA) and Japan's National Institute of Information and Communications Technology (NICT) built the DPR. The Core Observatory satellite will fly at an altitude of 253 miles (407 kilometers) in a non-Sun-synchronous orbit that covers the Earth from 65 S to 65 N - from about the Antarctic Circle to the Arctic Circle. The GPM Core Observatory is being developed and tested at NASA Goddard Space Flight Center. Once complete, a Japanese H-lIA rocket will carry thPM Core Observatory into orbit from Tanegashima Island, Japan in 2014. The GPM constellation is envisioned to comprise 8 or more microwave sensors provided by partners, including both conical imagers and cross-track sounders. GPM is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA). Additional partnerships are under development to include microwave radiometers on the French-Indian Megha-Tropiques satellite and U.S. Defense Meteorological Satellite Program (DMSP) satellites, as well as humidity sounders or precipitation sensors on operational satellites such as the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), NOAA-NASA Joint Polar Satellite System (JPSS) satellites, European MetOp satellites, and DMSP follow-on sensors. In addition, data from Chinese and Russian microwave radiometers may be available through international cooperation under the auspices of the Committee on Earth Observation Satellites (CEOS) and Group on Earth Observations (GEO). GPM's next-generation global precipitation data will lead to scientific advances and societal benefits in the following areas: (1) Improved knowledge of the Earth's water cycle and its link to climate change (2) New insights into precipitation microphysics, storm structures and large-scale atmospheric processes (3) Better understanding of climate sensitivity and feedback processes (4) Extended capabilities in monitoring and predicting hurricanes and other extreme weather events (5) Improved forecasting capabilities for natural hazards, including floods, droughts and landslides. (6) Enhanced numerical prediction skills for weather and climate (7) Better agricultural crop forecasting and monitoring of freshwater resources. An overview of the GPM mission concept and science activities in the United States, together with an update on international collaborations in radiometer intercalibration and ground validation, will be presented.

Hou, Arthur Y.↗
NASA NTRS2012

Global Precipitation Measurement (GPM) Mission Applications: Activities, Challenges, and Vision

Global Precipitation Measurement (GPM) is an international satellite mission to provide nextgeneration observations of rain and snow worldwide every three hours. NASA and the Japan Aerospace Exploration Agency (JAXA) will launch a "Core" satellite carrying advanced instruments that will set a new standard for precipitation measurements from space. The data they provide will be used to unify precipitation measurements made by an international network of partner satellites to quantify when, where, and how much it rains or snows around the world. The GPM mission will help advance our understanding of Earth's water and energy cycles, improve the forecasting of extreme events that cause natural disasters, and extend current capabilities of using satellite precipitation information to directly benefit society. Building upon the successful legacy of the Tropical Rainfall Measuring Mission (TRMM), GPM's next-generation global precipitation data will lead to scientific advances and societal benefits within a range of hydrologic fields including natural hazards, ecology, public health and water resources. This talk will highlight some examples from TRMM's IS-year history within these applications areas as well as discuss some existing challenges and present a look forward for GPM's contribution to applications in hydrology.

Kirschbaum, Dalia↗
NASA NTRS2016

Lessons Learned while Exploring Cloud-Native Architectures for NASA EOSDIS Applications and Systems

As new, high data rate missions begin collecting data, the NASAs Earth Observing System Data and Information System (EOSDIS) archive is projected to grow roughly 20x to over 300PBs by 2025. To prepare for the dramatic increase in data and enable broad scientific inquiry into larger time series and datasets, NASA has been exploring the impact of applying cloud technologies throughout EOSDIS. In this talk we will provide an overview of NASAs prototyping and lessons learned in applying cloud architectures.

NGAP↗
NASA NTRS2018

Status of and Scientific Results from the ISIS-I Topside Digital Ionogram Data Enhancement Project

Selected original analog telemetry tapes from three of the topside-sounder satellites of the International Satellites for Ionospheric Studies (ISIS) program, namely Alouette 2, ISIS I, and ISIS II, were used in an earlier project to produce more than million digital topside ionograms; the resulting digital topside ionograms from ISIS II were used to produce morethan 86,000 globally-distributed vertical topside ionospheric electron density profiles Ne(h)that cover a time span of more than a solar cycle. These Ne(h) were produced using the TOPIST auto-scaling software. Before attempting to automatically process Alouette-2 orISIS-I ionograms a data-enhancement project was initiated so as to increase the auto processing success rate. These enhancements were mainly to correct problems that often occurred during the analog-to-digital conversion of the original telemetry tapes. Here we present the status of, and results from, this ongoing enhancement effort.

topside ionosphere↗
NASA NTRSDate not supplied

Examining Artifacts from GLOBE Program Research Symposia & Using Network Analysis Techniques to Characterize Students’ Authentic STEM Investigations

For the past several years, the GLOBE Program's International Virtual Science Symposia (IVSS) and Student Research Symposia (SRS) have provided opportunities for U.S. and international students to present their Earth science research investigations to the GLOBE community through online or in-person events. This presentation will share the techniques and findings of an evaluation study that used student posters and written reports to characterize their research investigations through multiple lenses and frameworks. The study began with a list of characteristics drawn from a literature review, an analysis of sample projects, and several reviews by expert stakeholders and scientists, which comprehensively covered diverse relevant frameworks including citizen science, student STEM learning through authentic experiences, and The GLOBE Program model. Once applied to 207 student projects, this list of codes revealed the frequency and prevalence of various qualities and experiences represented by GLOBE student research investigations. An innovative application of social network analysis techniques to the coded dataset revealed frequently cooccurring characteristics. This networking approach identified and conceptually mapped several "clusters" of characteristics that typified student projects, empirically based on the submitted projects themselves. The basic quantitative investigation of frequencies indicates the extent to which various characteristics are present in - or absent from - GLOBE SRS and IVSS projects, while the network analysis provides a descriptive framework for typifying projects. Ultimately, the descriptive framework fostered a suite of assessment tools to help The GLOBE Program's staff, scientists, and research project judges understand the diversity of student research projects. GLOBE can use these tools to identify and respond to areas of need; for instance, the descriptive framework illustrates the potential for further education and training resources related to data analysis, interpretation of data, and credibility of scientific claims. This presentation will share the novel utilization of network analysis techniques to holistically assess and react to student research contributions.

Ann Martin↗
NASA NTRSDate not supplied

Chasing Spacecraft

Measurements made during actual flight on a spacecraft represent the holy grail in supporting cutting edge research and providing critical vehicle health information during exposure to the harsh environments of launch and reentry. Remote optical imaging data obtained by the Scientifically Calibrated In-Flight Imagery (SCIFLI) team at NASA Langley Research Center (LaRC) is currently being used by NASA’s Artemis and Commercial Crew Programs to ensure the safety of astronauts. This emerging capability had its genesis during the Space Shuttle Program. A look toward the future will showcase the use of high-altitude long-endurance uncrewed aircraft coupled with novel sensors to support civilian and national flight-testing interests more effectively.

Tom Horvath↗
NASA NTRS2019

Connecting a Community of Observers Directly to NASA Satellites

The Global Learning and Observations to Benefit the Environment (GLOBE) program is an international science and education initiative that gives students and the public worldwide an opportunity to participate in data collection and the scientific process and to contribute meaningfully to our understanding of Earth and the global environment. GLOBE launched in 1995, with the vision of bringing a worldwide community of students, teachers, scientists, and citizens together to better understand, sustain, and improve Earth's environment at local, regional, and global scales (https://www.globe.gov/about/overview).

Linda Hayden↗
NASA NTRS2007

Heliophysics Data and Modeling Research Using VSPO

The primary advantage of Virtual Observatories in scientific research is efficiency: rapid searches for and access to data in convenient forms makes it possible to explore scientific questions without spending days or weeks on ancilary tasks. The Virtual Space Physics Observatory provides a general portal to Heliophysics data for this task. Here we will illustrate the advantages of the VO approach by examining specific geomagnetically active times and tracing the activity through the Sun-Earth system. In addition to previous and additional data sources, we will demonstrate an extension of the capabilities to allow searching for model run results from the range of CCMC models. This approach allows the user to quickly compare models and observations at a qualitative level; considerably more work will be needed to develop more seamless connections to data streams and the equivalent numerical output from simulations.

Roberts, D. Aaron↗
NASA NTRS2026

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization↗
NASA NTRS1993

The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data

The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the Spectral Image Processing System (SIPS) using IDL (the Interactive Data Language) on UNIX-based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to rapidly interact with entire datasets. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X-Windows-based, user friendly, and provides 'point and click' operation. SIPS is being used for multidisciplinary research concentrating on use of physically based analysis methods to enhance scientific results from imaging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).

Kruse, F. A.↗
NASA NTRS1997

Star Identification Without Attitude Knowledge: Testing with X-Ray Timing Experiment Data

As the budget for the scientific exploration of space shrinks, the need for more autonomous spacecraft increases. For a spacecraft with a star tracker, the ability to determinate attitude from a lost in space state autonomously requires the capability to identify the stars in the field of view of the tracker. Although there have been efforts to produce autonomous star trackers which perform this function internally, many programs cannot afford these sensors. The author previously presented a method for identifying stars without a priori attitude knowledge specifically targeted for onboard computers as it minimizes the necessary computer storage. The method has previously been tested with simulated data. This paper provides results of star identification without a priori attitude knowledge using flight data from two 8 by 8 degree charge coupled device star trackers onboard the X-Ray Timing Experiment.

Ketchum, Eleanor↗
NASA NTRS1985

The AMPTE Charge Composition Explorer science data system

The instrument complement on all three Active Magnetospheric Particle Tracer Explorer (AMPTE) spacecraft is devoted to the conduction of the unified measurements which are required to achieve the scientific aims. A single science data base for each spacecaft has, therefore, been established with the objective to facilitate unified analysis. The data are kept in Science Data Centers in the U.S., West Germany, and the United Kingdom. The Science Data Center dedicated to the Charge Composition Explorer (CCE) is located at the Applied Physics Laboratory of Johns Hopkins University where it was developed. The present paper is concerned with aspects of the computing center's design, development and operations.

Holland, B. B.↗
NASA NTRS1992

Knowledge-based assistance for science visualization and analysis using large distributed databases

Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scaleable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on the concept called the Data Hub. With the Data Hub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (access, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

Handley, Thomas H., Jr.↗
NASA NTRS1993

Knowledge-based assistance for science visualization and analysis using large distributed databases

Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scalable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded with this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on concept called the DataHub. With the DataHub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (address, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

Handley, Thomas H., Jr.↗
NASA NTRS1992

A Framework for the Design of Effective Graphics for Scientific Visualization

This proposal presents a visualization framework, based on a data model, that supports the production of effective graphics for scientific visualization. Visual representations are effective only if they augment comprehension of the increasing amounts of data being generated by modern computer simulations. These representations are created by taking into account the goals and capabilities of the scientist, the type of data to be displayed, and software and hardware considerations. This framework is embodied in an assistant-based visualization system to guide the scientist in the visualization process. This will improve the quality of the visualizations and decrease the time the scientist is required to spend in generating the visualizations. I intend to prove that such a framework will create a more productive environment for tile analysis and interpretation of large, complex data sets.

Miceli, Kristina D.↗
NASA NTRS2000

The SHADOZ Data Base: History, Archive Web Guide, and Sample Climatologies

SHADOZ (Southern Hemisphere Additional Ozonesonde) is a project to augment and archive ozonesonde data from ten tropical and subtropical ozone stations. Started in 1998 by NASA's Goddard Space Flight Center and other US and international co-investigators, SHADOZ is an important tool for tropospheric ozone research in the equatorial region. The rationale for SHADOZ is to: (1) validate and improve remote sensing techniques (e.g., the Total Ozone Mapping Spectrometer (TOMS) satellite) for estimating tropical ozone, (2) contribute to climatology and trend analyses of tropical ozone and (3) provide research topics to scientists and educate students, especially in participating countries. SHADOZ is envisioned as a data service to the global scientific community by providing a central public archive location via the internet: http://code9l6.gsfc.nasa.gov/Data_services/shadoz. While the SHADOZ website maintains a standard data format for the archive, it also informs the data users on the differing stations' preparation techniques and data treatment. The presentation navigates through the SHADOZ website to access each station's sounding data and summarize each station's characteristics. Since the start of the project in 1998, the SHADOZ archive has accumulated over 600 ozonesonde profiles and received over 30,000 outside data requests. Data also includes launches from various SHADOZ supported field campaigns, such as, the Indian Ocean Experiment (INDOEX), Sounding of Ozone and Water in the Equatorial Region (SOWER) and Aerosols99 Atlantic Cruise. Using data from the archive, sample climatologies and profiles from selected stations and campaigns will be shown.

White, J. C.↗