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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Challenges in Obtaining and Visualizing Satellite Level 2 Data in GIS

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. One way to help users better understand the satellite data is to provide data along with Images, including accurate pixel coverage area delineation, and science team recommended quality screening for individual geophysical parameters. However, there are challenges of visualizing remote sensed non-gridded products: (1) different geodetics of space-borne instruments (2) data often arranged in a long-track and a cross-track axes (3) spatially and temporally continuous data chunked into granule files: data for a portion (or all) of a satellite orbit (4) no general rule of resampling or interpolations to a grid (5) geophysical retrieval only based on pixel center location without shape information. In this presentation, we will unravel a new Goddard Earth Sciences Data and Information Services Center (GES DISC) Level 2 (L2) visualization on-demand service. The service's front end provides various visualization and data accessing capabilities, such as overlay and swipe of multiply variables and subset and download of data in different formats. The backend of the service consists of Open Geospatial Consortium (OGC) standard-compliant Web Mapping Service (WMS) and Web Coverage Service. The infrastructure allows inclusion of outside data sources served in OGC compliant protocols and allows other interoperable clients, such as ArcGIS clients, to connect to our L2 WCS/WMS.

GI↗
NASA NTRS2017

An Evaluation of Teleconnections Over the United States in an Ensemble of AMIP Simulations with the MERRA-2 Configuration of the GEOS Atmospheric Model

The atmospheric general circulation model that is used in NASA's Modern Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) is evaluated with respect to the relationship between large-scale teleconnection patterns and daily temperature and precipitation over the United States (US) using a ten-member ensemble of simulations, referred to as M2AMIP. A focus is placed on four teleconnection patterns that are known to influence weather and climate in the US: El Nino Southern Oscillation, the Pacific Decadal Oscillation, the North Atlantic Oscillation, and the Pacific-North American Pattern. The monthly and seasonal indices associated with the patterns are correlated with daily temperature and precipitation statistics including: (i) monthly mean 2 m temperature and precipitation, (ii) the frequency of extreme temperature events at the 90th, 95th, and 99th percentiles, and (iii) the frequency and intensity of extreme precipitation events classified at the 90th, 95th, and 99th percentiles.Correlations obtained with M2AMIP data and thus the strength of teleconnections in the free-running model are evaluated through comparison against corresponding correlations computed from observations and from MERRA-2. Overall, the strongest teleconnections in all datasets occur during the winter and coincide with the largest agreement between the observations, MERRA-2, and M2AMIP. When M2AMIP does capture the correlation seen in observations, there is a tendency for the spatial extent to be exaggerated. The weakest agreement between the data sources, for all teleconnection patterns, is in the correlation with extreme precipitation; however there are discrepancies between the datasets in the number of days with at least 1 mm of precipitation: M2AMIP has too few days with precipitation in the Northwest and the Northern Great Plains and too many days in the Northeast. In JJA, M2AMIP has too few days with precipitation in the western two-thirds of the country and too many days with precipitation along the east coast.

JJA↗
NASA NTRS2017

An Update on Ozone Profile Trends for the Period 2000 to 2016

Ozone profile trends over the period 2000 to 2016 from several merged satellite ozone data sets and from ground-based data measured by four techniques at stations of the Network for the Detection of Atmospheric Composition Change indicate significant ozone increases in the upper stratosphere, between 35 and 48 kilometers altitude (5 and 1 hectopascals). Near 2 hectopascals (42 kilometers), ozone has been increasing by about 1.5 percent per decade in the tropics (20 degrees S to 20 degrees N), and by 2 to 2.5 percent per decade in the 35 to 60 degree latitude bands of both hemispheres. At levels below 35 kilometers (5 hectopascals), 2000 to 2016 ozone trends are smaller and not statistically significant. The observed trend profiles are consistent with expectations from chemistry climate model simulations. This study confirms positive trends of upper stratospheric ozone already reported, e.g., in the WMO/UNEP (World Meteorological Organization/United Nations Environmental Programme) Ozone Assessment 2014 or by Harris et al. (2015). Compared to those studies, three to four additional years of observations, updated and improved data sets with reduced drift, and the fact that nearly all individual data sets indicate ozone increase in the upper stratosphere, all give enhanced confidence. Uncertainties have been reduced, for example for the trend near 2 hectopascals in the 35 to 60 degree latitude bands from about plus or minus 5 percent (2 sigma) in Harris et al. (2015) to less than plus or minus 2 percent (2 sigma). Nevertheless, a thorough analysis of possible drifts and differences between various data sources is still required, as is a detailed attribution of the observed increases to declining ozone-depleting substances and to stratospheric cooling. Ongoing quality observations from multiple independent platforms are key for verifying that recovery of the ozone layer continues as expected.

chemistry climate model simulations↗
NASA NTRS2018

NASA's Black Marble Nighttime Lights Product Suite

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500 meters resolution since January 2012 with data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Key algorithm enhancements include: (1) lunar irradiance modeling to resolve non-linear changes in phase and libration; (2) vector radiative transfer and lunar bidirectional surface anisotropic reflectance modeling to correct for atmospheric and BRDF (Bidirectional Reflectance Distribution Function) effects; (3) geometric-optical and canopy radiative transfer modeling to account for seasonal variations in NTL; and (4) temporal gap-filling to reduce persistent data gaps. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Initial validation results are presented together with example case studies illustrating the scientific utility of the products. This includes an evaluation of temporal patterns of NTL dynamics associated with urbanization, socioeconomic variability, cultural characteristics, and displaced populations affected by conflict. Current and planned activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at different geographic locations and time periods representing the full range of retrieval conditions.

Suomi-NPP↗
NASA NTRS2017

Introduction to Remote Sensing Image Registration

For many applications, accurate and fast image registration of large amounts of multi-source data is the first necessary step before subsequent processing and integration. Image registration is defined by several steps and each step can be approached by various methods which all present diverse advantages and drawbacks depending on the type of data, the type of applications, the a priori information known about the data and the type of accuracy that is required. This paper will first present a general overview of remote sensing image registration and then will go over a few specific methods and their applications.

Pattern Recognition↗
NASA NTRS2018

Innovative Development of a Cross-Center Timeline Planning Tool

The Payload Operations Integration Center (POIC) at Marshall Space Flight Center (MSFC) supports planning, coordination and scheduling of science activities for the International Space Station (ISS) in coordination with other NASA centers, international partners, and payload developers. The ability to efficiently plan and re-plan in response to change is critical to the flight planning teams. With the achievement of supporting a fourth crew member aboard the ISS and an increasing amount of payload science activities, came the need for a dynamic, more efficient way of building timeline planning reports that could be readily updated as fast as payload science plans could change. This paper addresses software architecture considerations in the successful cross-center development of an automated planning tool with multiple data sources. It also discusses the practical implementation of a time-boxed, hybrid Agile Software Development (ASD) approach to deliver customer-driven value despite changing requirements with respect to low-Earth orbit operational planning activities. The goal of this paper is to open discussion with members of the international community and trade effective strategies for cross-center architectural and customer-developer driven collaborations, to support increasing utilization of planning and conducting science activities in space.

Pedoto, Ramon W.↗
NASA NTRS2018

Survey of Methods to Predict Controller Workload for Real-Time Monitoring of Airspace Safety

The Real Time Safety Monitoring (RTSM) approach allows for assessment and prediction of the safety margin in the National Airspace System (NAS) to help preempt incidents and accidents, rather than having to reactively mitigate them. In RTSM, the NAS is modeled using state variables, and safety metrics are defined in terms of these state variables. The safety metrics have been classified as weather-related, airspace-related, and human-related. Many of the formulated human-related safety metrics need an estimate of the controller workload for their computation. However, this computation is not trivial. Hence, in this report, we perform a literature survey to identify the different factors that enable the computation of controller workload and categorize these factors. Next, we describe studies undertaken to determine a minimal set of factors that pro- vide a correct assessment of controller workload. Lastly, we survey approaches for evaluating how well the selected factors correlate with the controllers' subjective assessment of their workload. Based on this survey, we present factors beneficial to computing and predicting controller workload in real time, and discuss the status of data sources necessary for these computations.

National Airspace System↗
NASA NTRS2018

NASA's Black Marble Product Suite: Validation Strategy

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500m resolution since January 2012 with data fro the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-terrain, vegetation, snow, lunar and stray light corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Current and planned validation activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at difference geographic locations and time periods representing the full range of retrieval conditions.

GEO Human Planet↗
NASA NTRS2019

Modeling Turboshaft Engines for the Revolutionary Vertical Lift Technology Project

Turboshaft engine performance and weight models were developed to support conceptual propulsion and vehicle mission design and performance under the Revolutionary Vertical Lift Technology (RVLT) Project. These models were developed using open data sources, assuming current and advanced technology levels, and range from 650 to 7,500 shaft output horsepower (485 to 5,600 kW). Documenting the methodology, assumptions, and resulting performance realizes important benefits NASA and the aviation community. NASA concept vehicle efforts using these propulsion models can be more readily shared among the government, industry and university community as common baselines to support current and future work. Assessing the benefits of advanced technologies and new configurations can be facilitated using these models, which helps guide technology investment. As the various modeling conceptual vehicle and mission analysis environments advanced, these models can be used directly for broader systems analysis studies, including optimization within the propulsion model itself. To perform this effort, the turboshaft engine is briefly discussed, highlighting the specific components and their expected performance characteristics over the power range and technology levels considered. Engine configurations will also be discussed as they will vary based on power output and assumed technology level. Engine performance, such as airflow, power output and weight will be reported, noting trends that are important for system studies. The effect of advanced propulsion technologies on RVLT concept vehicles are also reported. Finally, potential future propulsion modeling work will be proposed.

Snyder, Christopher A.↗
NASA NTRS2019

Modeling Turboshaft Engines for the Revolutionary Vertical Lift Technology Project

Turboshaft engine performance and weight models were developed to support conceptual propulsion and vehicle mission design in support of the National Aeronautics and Space Administration's (NASA) Aeronautics Mission Research Directorate's (ARMD) Revolutionary Vertical Lift Technology (RVLT) Project. These models were developed using open data sources, assuming current and advanced technology levels, and range from 650 to 7,500 shaft output horsepower (485 to 5,600 kilowatts). Documenting the methodology, assumptions, and resulting performance realizes important benefits for NASA and the aviation community. NASA concept vehicle efforts using these propulsion models can more readily shared among the government, industry and university community as common baselines to support current and future work. Assessing the benefits of advanced technologies and new configurations can be facilitated using these models, which helps guide technology investment. As the various modeling conceptual vehicle and mission analysis environments advance, these models can be used directly for broader systems analysis studies, including optimization within the propulsion model itself. To perform this effort, the turboshaft engine is briefly discussed, highlighting the specific components and their expected performance characteristics over the power range and technology levels considered. Engine configurations will also be discussed as they will vary based on power output and assumed technology level. Engine performance, such as airflow, power output and weight will be reported, noting trends that are important for system studies. The effect of advanced propulsion technologies on RVLT-concept vehicles are also reported. Finally, potential future propulsion modeling work will be proposed.

Snyder, Christopher A.↗
NASA NTRS2016

A Multi-Sensor Water Vapor, Temperature and Cloud Climate Data Record: Status of Our MEaSUREs 2012 Project

- Our primary objectives: Incorporate all A-Train water vapor, including small-scale, horizontal and vertical water vapor structure from MODIS (Moderate Resolution Imaging Spectroradiometer) and GPS (Global Positioning System); Use MODIS cloud classification that is collocated at the pixel-scale over the full AIRS/AMSU (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit) swath; Extend summaries to PDFs (Probability Distribution Functions)/higher order moments of water vapor sorted by cloud classes; Establish robust, scale-dependent statistical relationships between cloud, temperature, and water vapor PDFs for the climate modeling community. - We will also: Update our current data record to new CloudSat/CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) cloud classification; Provide merged AIRS and MLS (Microwave Limb Sounder) water vapor profiles using averaging kernels; Include temperature and water vapor from models (ECMWF - European Centre for Medium-Range Weather Forecasts) and re-analyses (MERRA - Modern Era-Retrospective Analysis for Research and Applications); Classify METOP-A (Meteorological Operational Satellite-A) and NOAA (National Oceanic and Atmospheric Administration) satellite water vapor with AVHRR (Advanced Very High Resolution Radiometer) during SNOs (Solar Neutrino Oscillations); Compare with the NVAP-M (re-analysis and extension of the NASA Water Vapor Project (NVAP)) water vapor climatologies; Use existing data sources and mature algorithms, and document processing algorithms.

Fetzer, Eric↗
NASA NTRS2018

Southern California Megacity CO2, CH4, and CO Flux Estimates Using Ground- and Space-Based Remote Sensing and a Lagrangian Model

We estimate the overall CO2, CH4, and CO flux from the South Coast Air Basin using an inversion that couples Total Carbon Column Observing Network (TCCON) and Orbiting Carbon Observatory-2 (OCO-2) observations, with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). Using TCCON data we estimate the direct net CO2 flux from the So-CAB to be 104±26 Tg CO2 yr(exp -1) for the study period of July 2013–August 2016. We obtain a slightly higher estimate of 120±30 Tg CO2 yr(exp -1) using OCO-2 data. These CO2 emission estimates are on the low end of previous work. Our net CH4 (360±90 Gg CH4 y(exp -1)) flux estimate is in agreement with central values from previous top-down studies going back to 2010 (342–440 Gg CH4 yr(exp -1)). CO emissions are estimated at 487±122 Gg CO yr(exp -1), much lower than previous top-down estimates (1440 Gg CO yr(exp -1)). Given the decreasing emissions of CO, this finding is not unexpected. We perform sensitivity tests to estimate how much errors in the prior, errors in the covariance, different inversion schemes, or a coarser dynamical model influence the emission estimates. Overall, the uncertainty is estimated to be 25%, with the largest contribution from the dynamical model. Lessons learned here may help in future inversions of satellite data over urban areas.

Total Carbon Column Observing Network (TCCON)↗
NASA NTRS2014

Remote Sensing of Above Cloud Aerosols

The direct and indirect radiative effects of aerosols suspended in the atmosphere above clouds (ACA) are a highly uncertain component of both regional and global climate. Much of this uncertainty is observational in nature most orbital remote sensing algorithms were not designed to simultaneously retrieve aerosol and cloud optical properties in the same vertical column. Thus the climate modeling community has limited data to inform model development efforts, which encapsulate the current understanding of climate. Furthermore, field measurements have identified regions with consistent ACA, and regional simulations show that the radiative forcing may be significant. For this reason, there has been a recent push to develop the ability to determine ACA distribution, optical properties and cloud interactions, while also providing a means to validate models. Several algorithms have been created that utilize existing instruments for these purposes. However, the observational data sources, algorithm characteristics, geophysical assumptions and retrieved products from these methods are highly variable. This chapter is a review of these techniques, their uncertainties, and the associated validation efforts. We will also discuss the future of ACA remote sensing, both with regards to new instruments and the potential for new algorithms.

Aerosols↗
NASA NTRS2019

The TASAR Project: Launching Aviation on an Optimized Route Toward Aircraft Autonomy

The Traffic Aware Strategic Aircrew Request (TASAR) concept applies onboard automation for the purpose of advising the pilot of route modifications that would be beneficial to the flight. Leveraging onboard computing platforms with connectivity to avionics and diverse data sources on and off the aircraft, TASAR introduces a new, powerful capability for in-flight trajectory management to the cockpit and its flight crew that is anticipated to induce a significant culture change in airspace operations. Flight crews empowered by TASAR and its derivative technologies could transform from today’s flight plan followers to proactive trajectory managers, taking an initial critical step towards increasing autonomy in the airspace system. TASAR was developed as a catalyst for operational autonomy, a future vision where the responsibilities and authorities of trajectory management reside with the aircraft operator and are distributed among participating aircraft, thus fulfilling a vision dating back decades and enabling a fully scalable airspace system. This NASA Technical Paper maps TASAR to its foundational vision and traces its research and development from initial concept generation to an operational evaluation by a U.S. airline in revenue service, the final stage before technology transfer and commercialization.

Wing, David J.↗
NASA NTRS2020

Honeywell Enhancing Airplane State Awareness (EASA) Project: Final Report on Refinement and Evaluation of Candidate Solutions for Airplane System State Awareness

The loss of pilot airplane state awareness (ASA) has been implicated as a factor in several aviation accidents identified by the Commercial Aviation Safety Team (CAST). These accidents were investigated to identify precursors to the loss of ASA and develop technologies to address the loss of ASA. Based on a gap analysis, two technologies were prototyped and assessed with a formative pilot-in-the-loop evaluation in NASA Langley’s full-motion Research Flight Deck. The technologies address: 1) data source anomaly detection in real-time, and 2) intelligent monitoring aids to provide nominal and predictive awareness of situations to be monitored and a mission timeline to visualize events of interest. The evaluation results indicated favorable impressions of both technologies for mitigating the loss of ASA in terms of operational utility, workload, acceptability, complexity, and usability. The team concludes that there is a feasible retrofit solution for improving ASA that would minimize certification risk, integration costs, and training impact.

Whitlow, Stephen D.↗
NASA NTRS2019

Deep Space Habitability Design Guidelines Based on the NASA NextSTEP Phase 2 Ground Test Program

This report summarizes habitation design guidelines for deep space habitats, which were derived from the NASA Next Space Technologies for Exploration Partnerships (NextSTEP) Phase 2 Habitat Ground Test Program. All data presented in this document have been contractor-deidentified and approved for public release. The report prioritizes capabilities and recommends allocating those capabilities to either the Habitation and Logistics Outpost (HALO) or the International Habitat (I-Hab). A review of the design guidelines is presented in the main body of the report, along with a list of the 170 specific design guidelines with references to the specific data sources from which they were derived.

Gernhardt, Michael↗
NASA NTRSDate not supplied

TPSAS-NF1676L-35370-DND

The above anvil cirrus plume (AACP) is a weather phenomenon that signifies an intense tropopause penetrating updraft which can inject cirrus clouds several kilometers into the stratosphere. Storms that have such intense updrafts are often supercells which generate severe weather such as tornadoes, high winds, and hail. In addition, AACPs moisten the stratosphere and influence the Earth's radiative balance. Though an AACP can be identified by the human eye, no automated AACP detection methods currently exist. Lack of detection inhibits understanding of where and how often AACPs occur, and how these storms influence stratospheric air composition. Previous work involved synthesis of multiple remote sensing and severe weather report/warning data sources to identify AACPs in Geostationary Operational Environmental Satellite system (GOES) satellite imagery and better understand their weather impacts (Bedka et al. (Wea. Forecasting, 2018)). This current study demonstrates an automated AACP identification method based on the application of a deep learning segmentation model known as a U-net. This study documents the development of a U-net model capable of identifying emergent AACPs using only satellite infrared (IR) and visible reflected sunlight imagery. The performance of a U-net is quantitatively benchmarked with human AACP identifications and qualitatively assessed through animations of detections generated from GOES-16 1-minute temporal resolution imagery.

Charles Liles↗