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At least 1,171 records · Page 65

EOS ground data and operations support

The Earth Observing System (EOS) is planned as a space-based measurement system, earth-science research program, and data and information system (EOSDIS). It will consist of several observatories with multiple earth sensing instruments to provide investigators with a thorough, long-term view of the earth's environment. Providing the data handling and flight operations support for EOS will be the EOSDIS Core System (ECS). The ECS will command and control the observatories consisting of core service platforms and science instruments, and it will transport, process, and store the EOS data, provide access to the data for years, and support researchers. EOS and EOSDIS are briefly described to provide a context for a description of the ECS.

Smith, Gene↗

Development and status of data quality assurance program at NASA Langley research center: Toward national standards

As part of a continuing effort to re-engineer the wind tunnel testing process, a comprehensive data quality assurance program is being established at NASA Langley Research Center (LaRC). The ultimate goal of the program is routing provision of tunnel-to-tunnel reproducibility with total uncertainty levels acceptable for test and evaluation of civilian transports. The operational elements for reaching such levels of reproducibility are: (1) statistical control, which provides long term measurement uncertainty predictability and a base for continuous improvement, (2) measurement uncertainty prediction, which provides test designs that can meet data quality expectations with the system's predictable variation, and (3) national standards, which provide a means for resolving tunnel-to-tunnel differences. The paper presents the LaRC design for the program and discusses the process of implementation.

Hemsch, Michael J.↗

Database of Nonaqueous Proton-Conducting Materials

This work presents the assembly of 48 papers, representing 74 different compounds and blends, into a machine-readable database of nonaqueous proton-conducting materials. SMILES was used to encode the chemical structures of the molecules, and we tabulated the reported proton conductivity, proton diffusion coefficient, and material composition for a total of 3152 data points. The data spans a broad range of temperatures ranging from -70 to 260 °C. To explore this landscape of nonaqueous proton conductors, DFT was used to calculate the proton affinity of 18 unique proton carriers. The results were then compared to the activation energy derived from fitting experimental data to the Arrhenius equation. It was found that while the widely recognized positive correlation between the activation energy and proton affinity may hold among closely related molecules, this correlation does not necessarily apply across a broader range of molecules. This work serves as an example of the potential analyses that can be conducted using literature data combined with emerging research tools in computation and data science to address specific materials design problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing Novel Performance Measures for Traffic Congestion Management and Operational Planning Based on Connected Vehicle Data

In this study, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers' clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles' abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%-15% of all moving vehicles in the Dallas-Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle's actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials - a common visualization of arterial signal performance for transportation planning and operations.

33 ADVANCED PROPULSION SYSTEMS↗

The Silencing of U.S. Campuses Following the COVID-19 Response: Evaluating Root Mean Square Seismic Amplitudes Using Power Spectral Density Data

In response to the COVID-19 global pandemic, many populated and active regions have become deserted and show significant reductions in their background seismicity, especially campuses across the United States (U.S.). Seismic sensors located in the vicinity of or within U.S. campuses show that anthropogenic seismic noise remains elevated during the ordinary, nonpandemic, academic year, only subduing during periods of recess (e.g., winter break). Here, we use power spectral density (PSD) data computed by the Incorporated Research Institutions for Seismology Data Management Center for quality assessment to calculate root mean square (rms) amplitude and analyze the effects of the COVID-19 school closures. We processed and analyzed PSD data for 46 seismic stations located within 50 m of a U.S. university or college. Results show that 42 campus stations show an overall rms drop following a statewide school closure.

58 GEOSCIENCES↗

From Data to Discovery: AI's Transformative Role in Thin Film Research

The advancement of thin film technologies is pivotal for progress in numerous fields, including energy, electronics, and quantum computing. However, the traditional trial-and-error approach to materials discovery is inherently slow and inefficient. This presentation will showcase how artificial intelligence (AI) is transforming thin film research by enabling a data-driven paradigm shift. We will highlight our past successes in applying AI to understand radiation damage in thin film oxides, demonstrating how graph analytics can unravel complex material behavior. Additionally, we will provide insights into our current work at the National Renewable Energy Laboratory, where we are leading the charge in autonomous materials science. Backed by a $14M investment in our characterization facility, we are developing AI-guided workflows that seamlessly integrate experimentation and AI-guided decision-making. By harnessing the power of AI, we aim to accelerate the discovery and design of high-performance thin films, propelling innovation across a multitude of industries.

36 MATERIALS SCIENCE↗

A review of foreign technology in aircraft flight controls

A survey of U.S. and foreign technology in aircraft flight controls was conducted for NASA Langley Research Center as a data base for planning future research and technology programs. The survey covers control and hardware configurations of major contemporary systems on operational aircraft, R&D flight programs, advanced aircraft developments and significant research and technology programs. This paper concentrates on the foreign technology elements and findings of the survey with primary emphasis on Western Europe, where most of the advanced technology resides.

Hewett, M. D.↗

First Results from the Washington D.C. Metropolitan Area Lighting Map Demonstration Project

An experimental portable lightning mapping array (LMA) operating in the upper VHF TV band (Channels 7-13; 174-216 MHz) was deployed in the Washington DC Metropolitan area during the summer 2006 to locate and monitor the overall lightning activity. The LMA network provides total lightning data to support lightning research as well as proxy data to benefit the development of applications for planned observing systems such as the GOES-R Geostationary Lightning Mapper. The portable LMA hardware is a compactly-housed, easily deployed version of the LMA stations installed North Alabama, Oklahoma, and New Mexico, which operate in the lower VHF TV band (Channels 2-6,54-88 MHz). Real-time LMA data products are provided to the National Weather Service Weather Forecast Office (WFO) in Sterling, VA to aid in their forecast and warning operations. Forecasters at WFO Sterling have already found the lightning data from the Washington DC demonstration network to be very useful in assessing the development of storm systems. On July 4,2006, data from the LMA aided forecasters as they monitored an area of convection that later developed into a line of severe storms that moved southward through the Washington DC metropolitan area across the Washington Mall. Additional applications of lightning mapping data in the Baltimore-Washington DC urban environment will be discussed.

Goodman, Steven J.↗

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗

Dataset for 'Ombadi, M. & Varadharajan, C. (2022). Urbanization and aridity mediate distinct salinity response to floods in rivers and streams across the Contiguous United States, Water Research'

This package contains data sets and code used to obtain the results in Ombadi, M., & Varadharajan, C. (2022). Urbanization and aridity mediate distinct salinity response to floods in rivers and streams across the Contiguous United States. Water Research, 118664. The folder "data" contains 259 .csv files, each of which has daily time series of concurrent streamflow (Q) and specific conductance (SC) for each of the sites used in this study originally downloaded from the USGS National Water Information System (NWIS; USGS, 2016). The number of data points in each of the files is at least 3650 (i.e. 10 years of daily measurements). The folder "RF_single_data" contains 259 .csv files, each of which include data used to train and test the Random Forest models at individual sites for predicting SC during days of floods. The folder "RF_regional_data" contains 3 .csv files, each of which include scaled data compiled from all sites within each climate zone (arid, temperate and wet). "metadata.csv" contains the physical properties of the 259 catchments corresponding to the sites used in this study; this data was extracted from GAGES-II dataset (Falcone et al., 2010). "RF_implementation.ipynb" is a Jupyter notebook with the code needed to implement the analysis using Random Forest models either for individual sites or for the regional models (for each climate zone). The code utilizes the data in the two folders: "RF_single_data" and "RF_regional_data" and the metadata.csv file.

54 ENVIRONMENTAL SCIENCES↗

Large Scale Data Mining to Improve Usability of Data: An Intelligent Archive Testbed

Research in certain scientific disciplines - including Earth science, particle physics, and astrophysics - continually faces the challenge that the volume of data needed to perform valid scientific research can at times overwhelm even a sizable research community. The desire to improve utilization of this data gave rise to the Intelligent Archives project, which seeks to make data archives active participants in a knowledge building system capable of discovering events or patterns that represent new information or knowledge. Data mining can automatically discover patterns and events, but it is generally viewed as unsuited for large-scale use in disciplines like Earth science that routinely involve very high data volumes. Dozens of research projects have shown promising uses of data mining in Earth science, but all of these are based on experiments with data subsets of a few gigabytes or less, rather than the terabytes or petabytes typically encountered in operational systems. To bridge this gap, the Intelligent Archives project is establishing a testbed with the goal of demonstrating the use of data mining techniques in an operationally-relevant environment. This paper discusses the goals of the testbed and the design choices surrounding critical issues that arose during testbed implementation.

Ramapriyan, Hampapuram↗

The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy

Abstract Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon‐storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R‐shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision‐making.

Holmquist, James R.↗

Multimodal Chemical Characterization of Brown Carbon in Atmosphere and Snowpack during SAIL Field Campaign Report

The main goal of this field project was to characterize the chemical and physical properties of light-absorbing particles (LAP) present in the atmosphere and snowpack. The specific field efforts included: 1) online measurement and sampling of light-absorbing particles using a Magee Scientific model AE33 aethalometer (AE33) and a time-resolved aerosol collector (TRAC); and 2) sampling of snowpack during observed events of LAP deposition on snow, confirmed by onsite U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility measurements and meteorological data. The ongoing research objectives of our follow-up sample and data analysis include: 1) Characterization of aerosol regimes and sources, identifying particle-type populations, mixing states, and atmospheric transformations based on correlative analysis of our detailed chemical imaging and chemical characterization measurements and real-time records from the second ARM Mobile Facility (AMF2) and other instruments available from the Surface Atmosphere Integrated Field Laboratory (SAIL) experiment; 2) Assessment of the optical and chemical properties of snowpack deposits to investigate how aerosol deposition influences snowpack lifetime.

54 ENVIRONMENTAL SCIENCES↗

Selected results of the F-15 propulsion interactions program

A better understanding of propulsion system/airframe flow interactions could aid in the reduction of aircraft drag. For this purpose, NASA and the United States Air Force have conducted a series of wind-tunnel and flight tests on the F-15 airplane. This paper presents a correlation of flight test data from tests conducted at the NASA Dryden Flight Research Facility of the Ames Research Center, with data obtained from wind-tunnel tests. Flights were made at stabilized Mach numbers around 0.6, 0.9, 1.2, and 1.5 with accelerations up to near Mach number 2. Wind-tunnel tests used a 7.5 percent-scale F-15 inlet/airframe model. Flight and wind-tunnel pressure coefficients showed good agreement in most cases. Correlation of interaction effects caused by changes in cowl angle, angle-of-attack, and Mach number are presented. For the afterbody region, the pressure coefficients on the nozzle surfaces were influenced by boattail angles and Mach number. Boundary-layer thickness decreased as angle of attack increased above 4 deg.

Webb, L. D.↗

International Symposium on Remote Sensing of Environment, Third Thematic Conference: Remote Sensing for Exploration Geology, Colorado Springs, CO, April 16-19, 1984, Proceedings. Volumes 1 & 2

A photogeologic and remote sensing model of porphyry type mineral sytems is considered along with a Landsat application to development of a tectonic model for hydrocarbon exploration of Devonian shales in west-central Virginia, remote sensing and the funnel philosophy, Landsat-based tectonic and metallogenic synthesis of the southwest United States, and an evolving paradigm for computer vision. Attention is given to the neotectonics of the Tibetan plateau deduced from Landsat MSS image interpretation, remote sensing in northern Arizona, the use of an airborne laser system for vegetation inventories and geobotanical prospecting, an evaluation of Thematic Mapper data for hydrocarbon exploration in low-relief basins, and an evaluation of the information content of high spectral resolution imagery. Other topics explored are related to a major source of new radar data for exploration research, the accuracy of geologic maps produced from Landsat data, and an approach for the geometric rectification of radar imagery.

Source record↗

In Interactive, Web-Based Approach to Metadata Authoring

NASA's Global Change Master Directory (GCMD) serves a growing number of users by assisting the scientific community in the discovery of and linkage to Earth science data sets and related services. The GCMD holds over 8000 data set descriptions in Directory Interchange Format (DIF) and 200 data service descriptions in Service Entry Resource Format (SERF), encompassing the disciplines of geology, hydrology, oceanography, meteorology, and ecology. Data descriptions also contain geographic coverage information, thus allowing researchers to discover data pertaining to a particular geographic location, as well as subject of interest. The GCMD strives to be the preeminent data locator for world-wide directory level metadata. In this vein, scientists and data providers must have access to intuitive and efficient metadata authoring tools. Existing GCMD tools are not currently attracting. widespread usage. With usage being the prime indicator of utility, it has become apparent that current tools must be improved. As a result, the GCMD has released a new suite of web-based authoring tools that enable a user to create new data and service entries, as well as modify existing data entries. With these tools, a more interactive approach to metadata authoring is taken, as they feature a visual "checklist" of data/service fields that automatically update when a field is completed. In this way, the user can quickly gauge which of the required and optional fields have not been populated. With the release of these tools, the Earth science community will be further assisted in efficiently creating quality data and services metadata. Keywords: metadata, Earth science, metadata authoring tools

Pollack, Janine↗

NASA EOSDIS: Enabling Science by Improving User Knowledge

Lessons learned and impacts of applying these newer methods are explained and include several examples from our current efforts such as the interactive, on-line webinars focusing on data discovery and access including tool usage, informal and informative data chats with data experts across our EOSDIS community, data user profile interviews with scientists actively using EOSDIS data in their research, and improved conference and meeting interactions via EOSDIS data interactively used during hyper-wall talks and Worldview application. The suite of internet-based, interactive capabilities and technologies has allowed our project to expand our user community by making the data and applications from numerous Earth science missions more engaging, approachable and meaningful.

EOSDIS↗

Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals

By accounting for surface-based light source emissions and top-of-atmosphere (TOA) downward lunar fluxes, we adapted the spherical harmonics discrete ordinate method (SHDOM) 3-dimensional (3-D) radiative transfer model (RTM) to simulate nighttime 3-D TOA radiances as observed from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi-NPP satellite platform. Used previously for daytime 3-D applications, these new SHDOM enhancements allow for the study of the impacts of various observing conditions and aerosol properties on simulated VIIRS-DNB TOA radiances. Observations over Dakar, Senegal, selected for its bright city lights and a large range of aerosol optical depth (AOD), were investigated for potential applications and opportunities for using observed radiances containing VIIRS-DNB “bright pixels” from artificial light sources to conduct aerosol retrievals. We found that using the standard deviation (SD) of such bright pixels provided a more stable quantity for nighttime AOD retrievals than direct retrievals from TOA radiances. Further, both the mean TOA radiance and SD of TOA radiances over artificial sources are significantly impacted by satellite viewing angles. Light domes, the enhanced radiances adjacent to artificial light sources, are strong functions of aerosol properties and especially aerosol vertical distribution, which may be further utilized for retrieving aerosol layer height in future studies. Through inter-comparison with both day- and nighttime Aerosol Robotic Network (AERONET) data, the feasibility of retrieving nighttime AODs using 3-D RTM SHDOM over artificial light sources was demonstrated. Our study shows strong potential for using artificial light sources for nighttime AOD retrievals, while also highlighting larger uncertainties in quantifying surface light source emissions. This study underscores the need for surface light emission source characterizations as a key boundary condition, which is a complex task that requires enhanced input data and further research. We demonstrate how quality-controlled nighttime light data from NASA’s Black Marble product suite could serve as a primary input into estimations of surface light source emissions for nighttime aerosol retrievals.

Jianglong Zhang↗