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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) Validation of Ozone and Water Vapor Data

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument installed on the International Space Station (ISS) has completed four years of data collection and production of science data products. The SAGE III/ISS is a solar and lunar occultation instrument that scans the light from the Sun and Moon through the limb of the Earth’s atmosphere to produce vertical profiles of aerosol, ozone, water vapor, and other trace gases. It continues the legacy of previous SAGE instruments dating back to the 1970s to provide data continuity of stratospheric constituents critical for assessing trends in the ozone layer. Recently, the latest version 5.2 data product has been released to the public. This presentation shows the validation results of comparing v5.2 SAGE III/ISS ozone and water vapor vertical profiles with those of in situ and satellite data.

SAGE Stratosphere Stratospheric Mesospheric Ozone ↗
NASA NTRSDate not supplied

The Impact and Usage of Near Real-Time and Low Latency Solutions from the Satellite Needs Working Group

The Satellite Needs Working Group (SNWG) is an interagency effort of the U.S. Government to identify the Earth observation gaps and data needs across civilian U.S. federal agencies. Within short time frames of 2 to 5 years, on behalf of SNWG, NASA formulates and implements a range of remote sensing-based solutions that benefit the entire Earth Science community and society at large. More than 20 such solutions are underway, with several addressing needs for near real-time and low latency information as a result of priorities identified in the survey. In this talk, we will present and discuss the impact and usage of such solutions, including ICESat-2 Atlas products (data delivered within 72 hours instead of the standard 45-day latency for ATLAS science products), near real-time air quality TEMPO products derived from the recently launched TEMPO mission (these products include SO 2 , NO 2 , HCHO, O 2 -O 2 cloud cover, and aerosols with a planned latency of one hour), and low latency Harmonized Landsat-Sentinel-2 (HLS) data (HLS data with a latency of 6 hours). We will talk about how these solutions are being co-designed by federal agencies to maximize their impact and usage by the scientific community. Finally, we will also invite additional stakeholders and users to get involved in the formulation, implementation, and operationalization of these solutions.

Pontus Olofsson↗
NASA NTRS1976

Synthesis and distribution of environmental satellite data

The activities of two National Oceanographic and Atmospheric Administration and two National Aeronautics and Space Administration facilities involved in the synthesis or distribution of space environmental data are reviewed. The data products, user services, and pertinent publications are given. The computer systems that support three of these facilities are discussed and some details of the synthesis procedures are given. Data from the following satellite series are included in the discussion: TIROS, NIMBUS, ESSA, NOAA, SMS/GOES, ATS, and SOLRAD. Orbital position data for HAWKEYE 1, IMP H and J, VELA 5B, PIONEERS 6-9, PIONEER 11, HELIOS 1 and 2, and SOLRAD 11A and 11B in several coordinate systems are discussed.

Vette, J. I.↗
NASA NTRS1983

Ascent air data system results from the space shuttle flight test program

The ascent air data system of the Space Shuttle consists of a simple biconic spike probe on the nose of the external tank. Pressure measurements were calibrated in a wind tunnel to obtain vehicle attitude and speed (relative to the air) and dynamic pressure. The wind tunnel test data analysis and the calibration are discussed in terms of test problems and calibration parameter formulation. The flight pressures are traced from telemetry data to final air data products. Analysis of the flight results showed that static pressure could not be accurately determined at the higher Mach numbers (above approx. 2.0). By replacing static pressure with data from a postflight estimated trajectory the ascent air data system performance met the user requirements. Lessons learned are enumerated, the most important being the need for a thorough systems integration effort.

Hillje, E. R.↗
NASA NTRS1990

Satellite radar altimetry over ice. Volume 1: Processing and corrections of Seasat data over Greenland

The data-processing methods and ice data products derived from Seasat radar altimeter measurements over the Greenland ice sheet and surrounding sea ice are documented. The corrections derived and applied to the Seasat radar altimeter data over ice are described in detail, including the editing and retracking algorithm to correct for height errors caused by lags in the automatic range tracking circuit. The methods for radial adjustment of the orbits and estimation of the slope-induced errors are given.

Zwally, H. Jay↗
NASA NTRS2012

VIIRS On-Orbit Calibration for Ocean Color Data Processing

The NASA VIIRS Ocean Science Team (VOST) has the task of evaluating Suomi NPP VIIRS ocean color data for the continuity of the NASA ocean color climate data records. The generation of science quality ocean color data products requires an instrument calibration that is stable over time. Since the VIIRS NIR Degradation Anomaly directly impacts the bands used for atmospheric correction of the ocean color data (Bands M6 and M7), the VOST has adapted the VIIRS on-orbit calibration approach to meet the ocean science requirements. The solar diffuser calibration time series and the solar diffuser stability monitor time series have been used to derive changes in the instrument response and diffuser reflectance over time for bands M1-M11.

Eplee, Robert E., Jr.↗
NASA NTRSDate not supplied

Developing a Customizable Composite Drought Index for Pakistan

Pakistan has experienced intense agricultural droughts in recent years, with the southern provinces experiencing the most severe drought conditions. These prolonged dry conditions often result in failed crop production, impacting families and communities. To reduce the impacts a drought may have on a community by identifying dry conditions, drought indices are used. A customizable composite drought index (CDI) is developed to improve the spatial and temporal understanding of historical agricultural droughts that have affected Pakistan. An in depth analysis using 9 input variables will provide information regarding the most important variables for differing locations. This framework can enhance drought monitoring and forecasting systems. The performance of the CDI will be evaluated by using production data from different crops that have significant economic value in Pakistan. These crops include wheat, rice, maize, cotton and barley. The expected relationship between the CDI and crop production would be to see production decrease when the CDI decreases, an indication that crops failed due to drought. The CDI is made more precise by evaluating only agricultural areas using the months of the growing season for each specific crop. This will allow for a custom drought index to be developed based on crop type and geographic location that only uses the most important variables, while still capturing the full extent of historical drought.

Caily Schwartz↗
NASA NTRSDate not supplied

PACE OCI Short-Wave Infrared Detection Assembly frequency-dependent linearity characterization and uncertainty analysis

The Ocean Color Instrument (OCI), the primary payload of the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE)observatory, will collect data to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared(SWIR) Detection Assembly (SDA) was built and characterized by the Utah State University Space DynamicsLaboratory (SDL) and is a subsystem of OCI. The SDA measures seven bands centered at 940, 1038, 1250, 1378,1615, 2130, and 2260 nm, with standard- and high-gain varieties for the 1250 and 1615 nm bands, resulting in nine total detection configurations in the SWIR. The delivery of high-quality science data is critically dependent upon accurately characterizing the linearity of the SDA. Two metrology techniques were employed to measure the linearity and characterize the frequency-dependent linearity uncertainty of the system. The first technique used superposition linearity measurements to determine the DC linearity, and the second technique involved an oscillating small-signal response at seven frequencies to determine the frequency-dependent linearity. Discrepancies between the DC and frequency-dependent linearities constrain the uncertainty between the two. Examining the difference between these two methods for all SDA channels, we find most channels experience an uncertainty below0.2% with a worst-case measurement uncertainty of 0.31%. Averaging SDA channels with similar detectors, optical filters, and electronics to simulate the flight-like data products yields a worst-case frequency-dependence linearity uncertainty of 0.12%, demonstrating minimal frequency dependence, implying an excellent linearity knowledge.Detailed performance knowledge, including linearity performance, verifies data quality and builds confidence in the success of the PACE mission.

PACE↗
NASA NTRSDate not supplied

Transitioning a Flexible and Scalable Satellite Ground Station Observation Network (GSON) Framework to an Operational Environment

Obtaining accurate and timely satellite observations is of paramount importance in fields like disaster management, weather diagnoses/forecasting, and Earth Sciences remote sensing. Stored mission data (SMD), from low Earth orbiting (LEO) satellite sensors, provides important observations for these fields and applications, however data access to SMD can be delayed from one and half hours to three hours from the time the observations were made. This data latency poses a significant impact on data product optimal use. We developed a Ground Station Observation Network (GSON) that utilizes commercial ground station as a service (GSaaS) providers to acquire low latency direct broadcast (DB) data from AQUA, SNPP, and JPSS-1 satellites using antennas located in strategic locations around the world. We will discuss techniques to improve the deployment efficiency and code reliability and quality of the GSON framework. Topics include right-sizing and containerization of the code to facilitate integration and adaptation with continuous delivery (CD) pipeline, locating non-code assets in referenceable repositories separated from code, adaptation of pipelines as code and simplification of CD, intersecting with code quality tests and checks as part of the pipeline execution and deployment, and establishing distributed repositories, registries, and system identities in a way that mitigates compromise to the CD pipeline. These techniques enable deployment of processing systems that are both highly specific but also dynamically modifiable. This new class of system allows for a flexible and scalable deployment while avoiding the “black box” issues that can plague large system deployments.

cluster↗
NASA NTRS1979

Seasat-A ASVT: Commercial demonstration experiments. Results analysis methodology for the Seasat-A case studies

The SEASAT-A commercial demonstration program ASVT is described. The program consists of a set of experiments involving the evaluation of a real time data distributions system, the SEASAT-A user data distribution system, that provides the capability for near real time dissemination of ocean conditions and weather data products from the U.S. Navy Fleet Numerical Weather Central to a selected set of commercial and industrial users and case studies, performed by commercial and industrial users, using the data gathered by SEASAT-A during its operational life. The impact of the SEASAT-A data on business operations is evaluated by the commercial and industrial users. The approach followed in the performance of the case studies, and the methodology used in the analysis and integration of the case study results to estimate the actual and potential economic benefits of improved ocean condition and weather forecast data are described.

Source record↗
NASA NTRS2011

Informing Aerosol Transport Models With Satellite Multi-Angle Aerosol Measurements

As the aerosol products from the NASA Earth Observing System's Multi-angle Imaging SpectroRadiometer (MISR) mature, we are placing greater focus on ways of using the aerosol amount and type data products, and aerosol plume heights, to constrain aerosol transport models. We have demonstrated the ability to map aerosol air-mass-types regionally, and have identified product upgrades required to apply them globally, including the need for a quality flag indicating the aerosol type information content, that varies depending upon retrieval conditions. We have shown that MISR aerosol type can distinguish smoke from dust, volcanic ash from sulfate and water particles, and can identify qualitative differences in mixtures of smoke, dust, and pollution aerosol components in urban settings. We demonstrated the use of stereo imaging to map smoke, dust, and volcanic effluent plume injection height, and the combination of MISR and MODIS aerosol optical depth maps to constrain wildfire smoke source strength. This talk will briefly highlight where we stand on these application, with emphasis on the steps we are taking toward applying the capabilities toward constraining aerosol transport models, planet-wide.

Limbacher, J.↗
NASA NTRS2015

Operating in "Strange New Worlds" and Measuring Success - Test and Evaluation in Complex Environments

Software tools are being developed by the Autonomy Incubator at NASA's Langley Research Center that will provide an integrated and scalable capability to support research and non-research flight operations across several flight domains, including urban and mixed indoor-outdoor operations. These tools incorporate a full range of data products to support mission planning, approval, flight operations, and post-flight review. The system can support a number of different operational scenarios that can incorporate live and archived data streams for UAS operators, airspace regulators, and other important stakeholders. Example use cases are described that illustrate how the tools will benefit a variety of users in nominal and off-nominal operational scenarios. An overview is presented for the current state of the toolset, including a summary of current demonstrations that have been completed. Details of the final, fully operational capability are also presented, including the interfaces that will be supported to ensure compliance with existing and future airspace operations environments.

Qualls, Garry↗
NASA NTRS2019

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412,443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 x 10(exp -4), 5.49 x 10(exp -4), 4.48 x 10(exp -4), 2.51 x 10(exp -4), 8.83 x 10(exp -5), and 1.36 x 10(exp -4)/sr, respectively, and 1.09 x 10(exp -2)/cu.mgm for the chlorophyll-a concentration (Chl-a), 2.09 x 10(exp -3)/m for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (a(sub g) (412)), and 3.7 mg/cu.m for particulate organic carbon (POC). These R(sub rs) values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Concha, Javier↗
NASA NTRS2019

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 × 10−4, 5.49 × 10−4, 4.48 × 10−4, 2.51 × 10−4, 8.83 × 10−5, and 1.36 × 10−4 sr−1, respectively, and 1.09 × 10−2 mg m−3 for the chlorophyll-a concentration (Chl-a), 2.09 × 10−3 m−1 for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (ag (412)), and 3.7 mg m−3 for particulate organic carbon (POC). These Rrs values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Geostationary Ocean Color Imager (GOCI)↗
NASA NTRSDate not supplied

A New Statistical Estimate of the Radar Coverage of the Low Earth Orbit Debris Environment

For over three decades, the NASA Orbital Debris Program Office (ODPO) has used the Goldstone Orbital Debris Radar, Haystack Ultrawideband Satellite Imaging Radar (HUSIR), and Haystack Auxiliary (HAX) radar assets to collect data on the low Earth orbit (LEO) debris environment. Each radar, with its unique beamwidth, altitude and inclination coverage, and limiting size threshold, operates in a beam park mode to statistically sample the orbital debris population in LEO. Provided that these assets are shared with other users, the orbital debris data collection is not continuous; rather, intermittent data collects are acquired and sent to the NASA ODPO. To understand the sampling process conducted by each radar over time and any related observational biases, a Statistical Confirmation of Radar Uniformity or Bias (SCRUB) code has been implemented to model the coverage of these assets for informing future operations, as well as usage of the data collected from these ground-based sensors. For this analysis, Right Ascension of the Ascending Node (RAAN) is used as a metric to measure statistical coverage. A complete survey of the LEO environment is understood to be measurements that sufficiently sample all values of RAAN for each altitude-inclination pair visible from the radar asset. Regions of incompleteness or statistical bias can help inform future observation campaigns. The SCRUB tool evaluates the coverage of the LEO environment, not by examining individual objects that may pass through a sensor’s field of view (FOV), but by determining which orbit planes pass through the FOV. Once a pointing geometry for a radar site, observation time, and range extent are configured by the user, SCRUB computes the inclinations and altitudes that are visible by the sensor. For each inclination-altitude pair, there is a distinct pair of possible RAAN values, corresponding to the ascending and descending orbit passing through that point in the sensor cone. Repeating this process for all points in the beam, and for multiple time periods during an observation window, creates a matrix of all inclination-altitude-RAAN combinations that are visible during a sensor run. This process can then be repeated for all observations within a year (for an annual survey), propagating all the RAAN values to a common epoch, typically the start of a calendar year, and combining the observations to assemble a full estimate of the RAAN coverage of the LEO environment. This RAAN coverage can then be analyzed for uniformity of sampling, within a certain inclination-altitude pair, or between larger regions of the space environment. This paper provides a general overview of the radar assets utilized by ODPO, typical analysis data products assuming circular orbits, and a discussion of the algorithms that feed between modeling and measurement operations. Following the description of the algorithm, estimates of coverage using HUSIR radar data collected from multiple years are developed and compared.

Chris L Ostrom↗
NASA NTRS2003

Level 1B products from the Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft

The Atmospheric Infrared Sounder (AIRS) was launched May 4, 2002 on the EOS Aqua Spacecraft. A discussion is given of the objectives of the AIRS experiment, including requirements on the data products. We summarize the instrument characteristics, including sensitivity, noise, and spectral response, and preflight calibration results leading to the estimate of the calibration accuracy. The Level 1B calibration algorithm is presented as well as the results of in-flight stability and sensitivity measurements.

sounding↗
NASA NTRS2005

Managed Development Environment Successes for MSFC's VIPA Team

This paper outlines the best practices of the Vehicle Design Team for VIPA. The functions of the VIPA Vehicle Design (VVD) discipline team are to maintain the controlled reference geometry and provide linked, simplified geometry for each of the other discipline analyses. The core of the VVD work, and the approach for VVD s first task of controlling the reference geometry, involves systems engineering, top-down, layout-based CAD modeling within a Product Data Manager (PDM) development environment. The top- down approach allows for simple control of very large, integrated assemblies and greatly enhances the ability to generate trade configurations and reuse data. The second VVD task, model simplification for analysis, is handled within the managed environment through application of the master model concept. In this approach, there is a single controlling, or master, product definition dataset. Connected to this master model are reference datasets with live geometric and expression links. The referenced models can be for drawings, manufacturing, visualization, embedded analysis, or analysis simplification. A discussion of web based interaction, including visualization, between the design and other disciplines is included. Demonstrated examples are cited, including the Space Launch Initiative development cycle, the Saturn V systems integration and verification cycle, an Orbital Space Plane study, and NASA Exploration Office studies of Shuttle derived and clean sheet launch vehicles. The VIPA Team has brought an immense amount of detailed data to bear on program issues. A central piece of that success has been the Managed Development Environment and the VVD Team approach to modeling.

Finckenor, Jeff↗
NASA NTRS1975

GEOS-3 phase B ground truth summary

Ground truth data collected during the experiment systems calibration and evaluation phase of the Geodynamics experimental Ocean Satellite (GEOS-3) experiment are summarized. Both National Weather Service analyses and aircraft sensor data are included. The data are structured to facilitate the use of the various data products in calibrating the GEOS-3 radar altimeter and in assessing the altimeter's sensitivity to geophysical phenomena. Brief statements are made concerning the quality and completeness of the included data.

Parsons, C. L.↗