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At least 469 records · Page 26

The EOS Data and Information System (EOSDIS)

The Earth Observing System (EOS) is the centerpiece of NASA's Mission to Planet Earth initiative. It is a pivotal part of the U.S. Global Change Research Program and hence of the international effort to understand global change and the increasing demands of human activity. EOS consists of a space-based observing system, a Data and Information System (EOSDIS) and a scientific research program. The space component consists of two series of polar-orbiting spacecraft, the first scheduled for launch in 1998, that will collect data for 15 years. EOS is completing its conceptual design phase and is preparing to enter the design phase with the selection and construction of the instruments for the first platform. EOSDIS will allow researchers to quickly and easily access data about the Earth system. Development of EOSDIS has already begun; it will support research and analysis with existing data. Geophysical and biological products will be created from the satellite data to be used to a broad range of the scientific community. NASA has also committed to providing smaller missions - called Earth Probes - dedicated to near-term observations of specific Earth processes. The scientific research program was initiated in 1990, with funding for 28 interdisciplinary teams, to begin development of models that will use EOS data and define the data requirements from the instruments, nine facility instruments and their science teams, 23 instrument investigations and definition studies for a synthetic-aperture radar.

Dozier, J.↗

HDF-EOS Web Server

A shell script has been written as a means of automatically making HDF-EOS-formatted data sets available via the World Wide Web. ("HDF-EOS" and variants thereof are defined in the first of the two immediately preceding articles.) The shell script chains together some software tools developed by the Data Usability Group at Goddard Space Flight Center to perform the following actions: Extract metadata in Object Definition Language (ODL) from an HDF-EOS file, Convert the metadata from ODL to Extensible Markup Language (XML), Reformat the XML metadata into human-readable Hypertext Markup Language (HTML), Publish the HTML metadata and the original HDF-EOS file to a Web server and an Open-source Project for a Network Data Access Protocol (OPeN-DAP) server computer, and Reformat the XML metadata and submit the resulting file to the EOS Clearinghouse, which is a Web-based metadata clearinghouse that facilitates searching for, and exchange of, Earth-Science data.

Ullman, Richard↗

Climate Extremes and Risks: Links Between Climate Science and Decision-Making

The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.

climate extremes↗

Achievements and Prospects of Global Broadband Seismographic Networks After 30 Years of Continuous Geophysical Observations

Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and data exchange. The mid- to late-twentieth century saw the creation of the World-Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced global geographic coverage as seismometer bandwidth increased greatly allowing for the recording of the Earth's principal seismic spectrum. The modern era of global observations and rapid data access began during the 1980s, and notably included the inception of the GEOSCOPE initiative (1982) and GSN (1988). Through continual improvements, GEOSCOPE and the GSN have realized near-real time recording of ground motion with state-of-art data quality, dynamic range, and timing precision to encompass 180 seismic stations, many in very remote locations. Data from GSNs are increasingly integrated with other geophysical data (e.g., space geodesy, infrasound and Interferometric Synthetic Aperture Radar). Globally distributed seismic data are critical to resolving crust, mantle, and core structure; illuminating features of the plate tectonic and mantle convection system; rapid characterization of earthquakes; identification of potential tsunamis; global nuclear test verification; and provide sensitive proxies for environmental changes. As the global geosciences community continues to advance our understanding of Earth structure and processes controlling elastic wave propagation, GSN infrastructure offers a springboard to realize increasingly multi-instrument geophysical observatories. Here, we review the historical, scientific, and monitoring heritage of GSNs, summarize key discoveries, and discuss future associated opportunities for Earth Science.

58 GEOSCIENCES↗

Dataset for "A primer on forest structure measurement with lidar for ecologists"

This repository includes data and code accompanying the case study included in the manuscript "A primer on forest structure measurement with lidar for ecologists" (submitted to Ecosphere). We compiled lidar datasets from multiple platforms in a common area to: 1. Demonstrate how differences in sensor characteristics influence density and resolution of lidar data. 2. Provide open-source, co-located datasets for users to further inspect differences in lidar data. 3. Provide example code to perform basic lidar analysis. This case study is meant to allow readers to get hands-on experience with real-world data from different platforms. This case study is not meant to be a rigorous comparison of derived ecological metrics among all sensors; such comparisons can be found throughout other publications referenced throughout the main manuscript. Code includes basic functions in R commonly used to visualize and manipulate lidar data accessible with a normal laptop computer; more sophisticated algorithms for advanced users are also referenced throughout the main manuscript. Terrestrial laser scanning (TLS), mobile laser scanning (MLS), UAS laser scanning (ULS), airborne laser scanning (ALS), and spaceborne laser scanning (SLS) data were collected within the Smithsonian Environmental Research Center (SERC) forest dynamics plot in Maryland, USA. TLS, MLS, and ALS data were collected within 1 month of the 2021 growing season; ULS data were collected in November 2020 (“leaf-off” data) and July 2022 (“leaf-on” data).

54 ENVIRONMENTAL SCIENCES↗

CAD/CAE Integration Enhanced by New CAD Services Standard

A Government-industry team led by the NASA Glenn Research Center has developed a computer interface standard for accessing data from computer-aided design (CAD) systems. The Object Management Group, an international computer standards organization, has adopted this CAD services standard. The new standard allows software (e.g., computer-aided engineering (CAE) and computer-aided manufacturing software to access multiple CAD systems through one programming interface. The interface is built on top of a distributed computing system called the Common Object Request Broker Architecture (CORBA). CORBA allows the CAD services software to operate in a distributed, heterogeneous computing environment.

Claus, Russell W.↗

Characterize Aerosols from MODIS MISR OMI MERRA-2: Dynamic Image Browse Perspective

Among the known atmospheric constituents, aerosols still represent the greatest uncertainty in climate research. To understand the uncertainty is to bring altogether of observational (in-situ and remote sensing) and modeling datasets and inter-compare them synergistically 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 these earth science data (satellite and modeling) are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite-borne sensors routinely measure aerosols. There is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) have developed a new visualization service (NASA Level 2 Data Quality Visualization, DQViz)supporting various visualization and data accessing capabilities from satellite Level 2(MODISMISROMI) and long term assimilated aerosols from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2 displaying at their own native physical-retrieved spatial resolution. Functionality will include selecting data sources (e.g., multiple parameters under the same measurement), defining area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting and reformatting.

data quality↗

Cumulus: NASA's Cloud Based Distributed Active Archive Center Prototype

NASAs Earth Science Data System (ESDS) Program serves as a central cog in order to facilitate the implementation of NASA's Earth Science strategic plan. Since 1994, the ESDS Program has committed to the full and open sharing of Earth science data obtained from NASA instruments to all users. One of the key responsibilities of the ESDS Program is to continuously evolve the entire data and information system to maximize returns on the collected NASA data. An independent review was conducted in 2015 to holistically review the EOSDIS in order to identify gaps. The review recommendations were to investigate two areas: one, whether commercial cloud providers offer potential for storage, processing, and operational efficiencies, and two, the potential development of new data access and analysis paradigms. In response, ESDS has initiated several prototypes investigating the advantages and risks of leveraging cloud computing. This paper describes one such prototyping activity named Cumulus. Cumulus is being designed and developed as a "native" cloud-based data ingest, archive and management system that can be used for all future NASA Earth science data streams. Cumulus will foster design of new analysisvisualization tools that can leverage collocated data from all of the distributed DAACs as well as elastic cloud computing resources.

Earth Science Informatics↗

Infrared Algorithm Development for Ocean Observations with EOS/MODIS

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.

Brown, Otis B.↗

Advancing the Power and Utility of Server-Side Aggregation

During the upcoming Summer 2016 meeting of the ESIP Federation (July 19-22), OpenDAP will hold a Developers and Users Workshop. While a broad set of topics will be covered, a key focus is capitalizing on recent EOSDIS-sponsored advances in Hyrax, OPeNDAPs own software for server-side realization of the DAP2 and DAP4 protocols. These Hyrax advances are as important to data users as to data providers, and the workshop will include hands-on experiences of value to both. Specifically, a balanced set of presentations and hands-on tutorials will address advances in1.server installation,2.server configuration,3.Hyrax aggregation capabilities,4.support for data-access from clients that are HTTP-based, JSON-based or OGC-compliant (especially WCS and WMS),5.support for DAP4,6.use and extension of server-side computational capabilities, and7.several performance-affecting matters.Topics 2 through 7 will be relevant to data consumers, data providers andnotably, due to the open-source nature of all OPeNDAP softwareto developers wishing to extend Hyrax, to build compatible clients and servers, andor to employ Hyrax as middleware that enables interoperability across a variety of end-user and source-data contexts. A session for contributed talks will elaborate the topics listed above and embrace additional ones.

aggregation↗

Status Update on TRAC: A DOE-EM Tool for Tracking Groundwater Cleanup and Progress Toward Site Closure - 20245

The U.S. Department of Energy (DOE) Office of Environmental Management (EM) uses a customized, web-based mapping tool called TRAC (Tracking Restoration and Closure) to communicate information on plume sizes, remedial approaches, regulatory drivers, exit strategies, and long-term stewardship requirements at all sites within the DOE-EM complex. The web-based GIS story maps provide robust geospatial visualization of plumes at DOE sites using an intuitive interface that allows users to explore the plume maps, explanatory text, photographs, and video. This collection of story maps not only communicates information for each individual site, but also summarizes pertinent metrics on cleanup and remaining contaminants across all EM sites. This paper describes a new design within TRAC for communicating metrics on plume status, regulatory cleanup progress, and technology implementation. A principal benefit of TRAC is the ability to view individual pieces of data at a time, permitting targeted questions to be addressed, such as the status of regulatory decisions, site cleanup priorities, and site closure needs for each site within the DOE-EM complex. TRAC manages communication and supports decision-making through knowledge access, data and information transparency and traceability, and inclusive participation. It serves as a common resource that provides consistent information for DOE managers, site personnel, regulators and stakeholders. Because long-term stewardship of legacy waste sites requires ongoing coordination and communication among DOE, regulators, and stakeholders, TRAC can also be used to help transition EM sites to the Office of Legacy Management at site closure. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Open Science for Climate at NASA

The US National Aeronautics and Space Administration (NASA) currently provides more than 75 Petabytes of open access data through NASA’s Earth Science Data and Information System (ESDIS). Many of these datasets are commonly used in WCRP research, including the Global Precipitation Measurement (GPM) mission dataset, the Soil Moisture Active Passive (SMAP) mission dataset, the IceBridge dataset, and the Atmospheric Infrared Sounder (AIRS) dataset. These datasets are essential tools for understanding patterns in precipitation, soil moisture, ice mass changes, atmospheric circulation, and their impacts on climate. NASA is also a leader in the White House OSTP’s “Federal Year of Open Science” in 2023, promoting open access and open source solutions.

Climate Data↗

Merging Analytic Collaborative Frameworks with New Observing Strategies Toward a Digital Twin: Earth – Episodic Pulse Event Impacts on Ocean Carbon Cycle as an Example

Virtual representations of the Earth will allow us to address some of the most critical environmental issues of our time. Here, we show the first steps toward representation of riverine, estuarine, and coastal carbon processes to enable scenario driven “what-if” analyses of the carbon system and human footprint. Excess sediment and nutrient runoff from land-based human activities impact water quality and can pose serious threats to coastal and marine ecosystems. Episodic pulse events, such as extreme precipitation events, can increase the amount of nutrients entering estuaries and coastal regions, potentially leading to large phytoplankton blooms followed by anoxic conditions. Consequences of coastal runoff are predicted to increase with the higher intensity and frequency of extreme events. Beyond the threat to coastal ecosystems, recent findings suggest these episodic pulses might play a significant role for biological production influencing regional and global carbon fluxes and budgets. An improved understanding of these events through optimal, dynamic observing strategies will increase our knowledge of the land-ocean continuum and how regional events and nutrient fluxes affect the carbon cycle and ocean ecosystem. This conceptual framework enables focused science investigations by pairing data analytics and artificial intelligence tools (otherwise termed an Analytic Center Framework, ACF) with targeted measurement acquisition through distributed sensing and intelligent asset tasking (or New Observing Strategies, NOS). This NOS and ACF iterative approach acquires and integrates complementary and coincident satellite, in-situ and model data to build a more complete and in-depth picture of science phenomena. Specifically, Apache Science Data Analytic Platform (SDAP) is extended to incorporate relevant datasets for data access, harmonized analysis, and anomaly detection. When conditions are met for a likely pulse event, NASA’s D-SHIELD (Distributed Spacecraft with Heuristic Intelligence to Enable Logistical Decisions) tool is triggered to optimize asset overpass frequency and schedule observations for persistent monitoring. Targeted data is ingested by SDAP for enhanced investigation via iterative analysis until the trigger criteria is no longer met - steps toward a digital twin.

Laura Rogers↗

Share Data with OPeNDAP Hyrax: New Features and Improvements

During the upcoming Summer 2016 meeting of the ESIP Federation (July 19-22), OpenDAP will hold a Developers and Users Workshop. While a broad set of topics will be covered, a key focus is capitalizing on recent EOSDIS-sponsored advances in Hyrax, OPeNDAPs own software for server-side realization of the DAP2 and DAP4 protocols. These Hyrax advances are as important to data users as to data providers, and the workshop will include hands-on experiences of value to both. Specifically, a balanced set of presentations and hands-on tutorials will address advances in 1. server installation, 2. server configuration, 3. Hyrax aggregation capabilities, 4. support for data-access from clients that are HTTP-based, JSON-based or OGC-compliant (especially WCS and WMS), 5. support for DAP4,6.use and extension of server-side computational capabilities, and7.several performance-affecting matters. Topics 2 through 7 will be relevant to data consumers, data providers and notably, due to the open-source nature of all OPeNDAP software to developers wishing to extend Hyrax, to build compatible clients and servers, and/or to employ Hyrax as middleware that enables interoperability across a variety of end-user and source-data contexts. A session for contributed talks will elaborate the topics listed above and embrace additional ones.

OPeNDAP↗

Evaluation of Data Retention Characteristics for Ferroelectric Random Access Memories (FRAMs)

Data retention and fatigue characteristics of 64 Kb lead zirconate titanate (PZT)-based Ferroelectric Random Access Memories (FRAMs) microcircuits manufactured by Ramtron were examined over temperature range from -85 C to +310 C for ceramic packaged parts and from -85 C to +175 C for plastic parts, during retention periods up to several thousand hours. Intrinsic failures, which were caused by a thermal degradation of the ferroelectric cells, occurred in ceramic parts after tens or hundreds hours of aging at temperatures above 200 C. The activation energy of the retention test failures was 1.05 eV and the extrapolated mean-time-to-failure (MTTF) at room temperature was estimated to be more than 280 years. Multiple write-read cycling (up to 3x10(exp 7)) during the fatigue testing of plastic and ceramic parts did not result in any parametric or functional failures. However, operational currents linearly decreased with the logarithm of number of cycles thus indicating fatigue process in PZT films. Plastic parts, that had more recent date code as compared to ceramic parts, appeared to be using die with improved process technology and showed significantly smaller changes in operational currents and data access times.

Sharma, Ashok K.↗

Digital Twin for Hydropower System Object Modeling: Alder Dam (FY2023)

Hydropower is the world's largest source of renewable electricity, and hydropower plants are distributed all over the world. Typical major components of a hydropower plant are the governor, excitation, generator, thrust bearing, hydraulic turbine, transformer, the main lead, metering and control, tailwater depression, and dissolved oxygen. For each component, various measures are taken. The measurements are acquired by various heterogeneous systems, including standalone sensors, programmable logic controllers (PLC), Supervisory control and data acquisition (SCADA), Internet of Things (IoT), and data acquisition and integration platforms such as OSI/PI. The measured data are often archived within the plant by a data management platform, and many institutions have cloud-based archive systems, such as Hydropower Research Institution (HRI), U.S. Army Corps of Engineers (USACE), and Columbia River Data Access in Real Time (DART). Object Modeling is a general framework for designing information systems. It focuses on objects, the actions they perform, and the messages they send to one another to cause those actions to be taken. The major differences among object modeling, network modeling, data modeling, and process modeling are that in the first we focus on the actions in response to information, objects which form the system, the actions they perform, and how they pass information to one another, while in the second we concentrate on where, when and how much information is moved, while in the third we focus on what information is moved and where it is moved, while in the last we focus on how it is moved and when it is moved. Object modeling was developed basically as a method to develop object-oriented systems and to support object-oriented programming. It describes the static structure of the system. The object Modeling Technique is easy to draw and use. That is why we choose object modeling to connect physical hydropower plants to Digital Twin. It recognizes the objects and the relationship between them. It identifies the attributes and functions of each class. Dynamic Modeling: It explains how objects respond to events. Functional Modeling indicates the processes executed in an object and how data changes when it moves to objects. It has been used in many applications like telecommunication, transportation, etc.

13 HYDRO ENERGY↗

Urban-scale Energy Modeling: Scaling Beyond Tax Assessor Data

In an attempt to attain building-specific characteristics for urban-scale building energy models, county-specific tax assessors’ data is often an initial data source. This data source can contain valuable information such as year built, area, height, HVAC type, and roof/wall descriptions.We will show examples of 2,000 fields from Hamilton County in Tennessee with examples of many fields which are not relevant to urban-scale building energy modeling, are incorrect compared to other data sources, and highlight some lessons learned working with such a data source.There are currently 3,142 counties in the United States, each with their own data format, field definitions, and data access policy. As urban-scale involves city-scale analysis potentially covering multiple counties and matures toward state- or nation-scale analysis, county-by-county approaches are not scalable. While there are efforts to unify these datasets, there is an increasing proliferation of data and algorithms that can cover wider areas and provide more accurate inputs for urban-scale models. This paper summarizes computer vision of imagery, cartographic layers, building type assessment, and model generation used to achieve scalable detection and analysis of buildings.

New, Joshua↗

Affine transformations from aerial photos to computer compatible tapes

During the development of a project to estimate wheat production, it became necessary to pull data, corresponding to particular fields in a test site, off an ERTS computer compatible tape. Aerial photographs and topographic maps were on hand for the test site. A method was devised, using an affine transformation, to relate the aerial photographs or topographic maps to the tapes. One can thereby access data on the tape corresponding to regions covered by only a few pixels. The theory can be used for the registration of two tapes for the same area and for the geometric correction of images.

Peet, F. G.↗