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At least 775 records · Page 43

Using PCDS to study the influence of UV flux variation on the middle atmosphere

The value of the Pilot Climate Data System (PCDS) in examining the influences of short-period solar flux variations on the middle atmosphere was demonstrated. Several Nimbus satellite data sets proposed for the study exist in the PCDS. Planned for retrieval through the PCDS are ozone mixing ratios and cumulative ozone profiles available from the Backscatter Ultraviolet Spectrophotometer on Nimbus-4. Also to be accessed are Nimbus-7 data sets that will provide ozone and nitrogen dioxide mixing ratios, temperature profiles from the Limb Infrared Monitor of the Stratosphere, and ozone mixing ratio profiles from the Solar Backscatter Ultraviolet Spectrophotometer. Bypassing the time-consuming process of reading raw data tapes, the researchers plan to transfer the PCDS processed data to an IBM PC at Iowa State University. The IBM PC will serve as an intermediate vehicle for transferring the data to the NOAA CYBER 840 at Boulder, Colorado, where research will continue on both an eight-layer radiative-photochemical numerical model and on a nonlinear dynamical model. in this research are the FGGE and ERB data sets. These relevant data sets also reside in the PCDS. Problems associated with remote access to the PCDS were discussed in regard to all the PCDS data sets.

Heilman, W.↗

Provenance Representation in the Global Change Information System (GCIS)

Global climate change is a topic that has become very controversial despite strong support within the scientific community. It is common for agencies releasing information about climate change to be served with Freedom of Information Act (FOIA) requests for everything that led to that conclusion. Capturing and presenting the provenance, linking to the research papers, data sets, models, analyses, observation instruments and satellites, etc. supporting key findings has the potential to mitigate skepticism in this domain. The U.S. Global Change Research Program (USGCRP) is now coordinating the production of a National Climate Assessment (NCA) that presents our best understanding of global change. We are now developing a Global Change Information System (GCIS) that will present the content of that report and its provenance, including the scientific support for the findings of the assessment. We are using an approach that will present this information both through a human accessible web site as well as a machine readable interface for automated mining of the provenance graph. We plan to use the developing W3C PROV Data Model and Ontology for this system.

Tilmes, Curt↗

Distribution Substation Planning Toolkit (dsp-toolkit) v1.0

The Distribution Substation Planning Toolkit (DSP Toolkit) is a software suite designed to streamline the planning and optimization of distribution substations. This toolkit offers a comprehensive set of tools and APIs for data curation, short-term electric load forecasting, and weather-sensitive load adjustment, making it an essential resource for utility companies, engineers, and researchers. Features • Data Preprocessing and Curation: Efficiently manage and preprocess large datasets to ensure high-quality input for analysis. • Short-Term Load Forecasting: Utilize data-driven models to predict short-term electric loads accurately. • Weather-Sensitive Modeling: Automatically adjust load forecasts based on weather data to predict future peak demands more precisely. Uses The DSP Toolkit is ideal for planning and optimizing distribution substations, providing a user-friendly interface and comprehensive documentation. It is suitable for both novice and experienced users, facilitating efficient and accurate planning processes. Advantages • Efficiency: Automates complex planning tasks, reducing manual effort and minimizing errors. • Scalability: Handles large datasets and complex models, making it suitable for large-scale projects. • Community and Support: Open-source with active community contributions, ensuring continuous improvement and support. • Extensibility: Easily extendable with custom modules and plugins, allowing users to tailor the toolkit to their specific needs. The DSP Toolkit stands out by offering a robust, flexible, and user-friendly solution for distribution substation planning. Public Abstract

Li, Han [Lawrence Berkeley National Laboratory (LB↗

Global Retrieval of Cloud Particle Size and Optical Thickness Using ISCCP Data

The primary thrust of this investigation is to develop an algorithm to retrieve cloud particle sizes using ISCCP data. The research under this grant has been successful in obtaining initial results of global distribution of ice-particle sizes. Further research about possible problems caused by nonsphericity of ice particle sizes is currently underway. An algorithm of retrieving ice-cloud particle sizes using ISCCP CX data has been developed. The first survey of ice-particle size in a near-global scale has been completed. Comparison with in situ measurements of ice crystal sizes during FIRE I shows good agreement. The initial results show that the global mean size of ice crystals (De) is about 60 micron. This result is consistent with the range of in situ measurements all over the world if definitions of effective particle size are unified (see next section). The survey also shows that there is no distinct difference of ice-particle sizes between continental and maritime ice-clouds. There are many different definitions of effective particle size used in ice-cloud research. Simple comparisons between values of in situ measurement and satellite remote sensing are misleading and may lead to incorrect conclusions. We reviewed different definitions of effective particle sizes used in the literature and compared their relative magnitudes.

Welch, Ronald M.↗

Data-link alternatives for the NASA pilot data systems

There are several preliminary, or pilot, efforts for developing data systems for supporting NASA science research. The Pilot Data Systems consist of the Pilot Land Data System (PLDS), the Pilot Ocean Data System (PODS), the Pilot Climate Data System (PCDS), and the Pilot Planetary Data System (PPDS). The PLDS is likely to have the greatest communication needs of the various pilots. Communications issues and requirements are examined in the context of the mature PLDS as it may exist by 1990. The PLDS is seen as a distributed processing system linking resources at a number of NASA research centers and outside universities. Large image data sets, including LANDSAT scenes, are a major data type to be moved along the PLDS communications network. The unusually large size of these data files requires examining new technologies that may allow efficient and affordable communication at rates of up to 60 megabits per second. Potentially useful developments include portable satellite ground stations, and time division multiple access for sharing high-speed satellite links. Further pooling of communications for the various data systems into a single network would reduce costs and may make economic justification of access to the required data rates possible.

Likens, W. C.↗

Remote sensing applications in hydrometeorology

Monitoring of precipitation using remote sensing has been carried out successfully over oceans with passive microwave data and over land with visible and infrared data. Further research is necessary to improve accuracy and timeliness of estimations in a variety of rainfall situations. Snowmelt runoff prediction has been demonstrated using satellite snowcover data. Snow depth and wetness measurements are feasible using microwave techniques. The monitoring of ice cover, type, and thickness has been carried out successfully using remote methods. Results from remote sensing evapotranspiration studies have been inconclusive. The remote measurement of evapotranspiration seems to be the most challenging of all applications of remote sensing to hydrometeorology.

Rango, A.↗

Proposition to Optimize Fire Stations for Wildfires

The rising trend in wildfire occurrence and severity has put a strain on wildfire management organizations by spreading out limited resources to meet increasing demand. There has been extensive prior research and data collection to determine the areas of highest risk and to predict regional wildfire damages based on historical trends. Our group aims to utilize this data to best determine fire station placement, optimizing where resources are allocated to reduce the time and investment needed to effectively mitigate wildfires. Using existing research, we are able to calculate optimal fire station locations by utilizing a single-objective facility location problem algorithm incentivized for cost reduction. Further work would be needed to refine the algorithm to accommodate for more realistic factors including access to water and roadways as well as better accounting for the costs involved, but our work serves as a proof of concept and lays the foundation for future research. Implementation of this algorithm would allow public fire planning agencies (such as CAL FIRE and Forest Service) to shift resources to where they would be most effective.

Wildfires↗

Earth observational research using multistage EOS-like data

This grant was funded as a part of a program in which both research and educational impact were intended. Research work under this grant is directed at the understanding and use of future hyperspectral data such as that from imaging spectrometers. Specifically, the objectives of the work were: to prepare suitable means for analyzing data from sensors which have large numbers of spectral bands, to advance the fundamental understanding of the manner in which soils and vegetative materials reflect high spectral resolution optical wavelength radiation, and to maximize the impact of the results on the educational community. Over the life of the grant, the work has thus involved basic earth science research and information system technique understanding and development in a mutually supportive way. However, during the later years it became necessary to focus the work primarily on the first and last areas, due to a steadily decreasing level of effort.

Johannsen, C. J.↗

Earth observational research using multistage EOS-like data

This grant is funded as a part of a program in which both research and educational impact are intended. Research work under this grant is directed at the understanding and use of future hyperspectral data such as that from imaging spectrometers. Specifically, the objectives of the work are (1) to prepare suitable means for analyzing data from sensors which have large numbers of spectral bands, (2) to advance the fundamental understanding of the manner in which soils and vegetative materials reflect high spectral resolution optical wavelength radiation, and (3) to maximize the impact of the results on the educational community. Over the life of the grant, the work has thus involved basic Earth science research and information system technique understanding and development in a mutually supportive way, however, more recently it has become necessary to focus the work primarily on areas (1) and (3). During the last year, the level of effort on this grant has been reduced to half its previous value. We have also been advised that this grant will end with the current year, thus this will be the penultimate semiannual progress summary.

Johannsen, C. J.↗

Automated Vehicle Feasibility Study

This study collected automated vehicle (AV) performance data on public roadways in Athens, Ohio. The route for the study contained a combination of roads with different functional classifications, conditions, annual average daily traffic, and ownership responsibilities for maintenance and repair. Preparation for the public road deployment was done in a controlled environment at Transportation Research Center’s SMARTCenter, a dedicated AV test facility in East Liberty, Ohio. Researchers analyzed data and extracted insights relevant for both AV developers and infrastructure owners and operators. The study found that rural environments offer a unique set of roadway features such as hills and curves, which can challenge the driving behavior of an AV. Rural regions can also contain a large number of low-traffic gravel roads that lack pavement markings, which appear to be a crucial infrastructure element for operation of current generation AVs. Similarly, the presence of well-maintained lane lines along curves can influence the AV’s roadway departure tendencies. The study found that curvature-related behavior of an AV is also influenced by driving speed on the roadway segment. Such findings were consistent regardless of the time of day along the route or season of data collection. However, commentary about AV performance in active adverse weather cannot be made, as this is still an area of active research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA's Responsible AI Plan

Artificial Intelligence (AI) is an integral part of today’s process of conducting science and technology development. At NASA, AI has become an integral and important tool for researchers, engineers, data scientists, and technologists in pursuing the ground-breaking discoveries that we are known for, including the command and controlling of our spacecraft and other supporting infrastructures. Consequently, research and engineering efforts incorporating AI have permeated almost every area of our work. It is contributing to NASA’s drive toward the future, not just of space science, but for society here at home. We are dedicated to continuing the use of AI in a safe and fully transparent approach so that the public can have high confidence in the outcomes and benefits. We believe that the plan outlined here will be responsive and contribute to the call for openness across the federal government. NASA is committed to responsible use of AI in all of its activities and in all phases of development and deployment of its space and terrestrial programs missions. NASA does not deliberately focus on “AI Research” as a separate field (we have no single “AI office” or “AI program”), rather NASA uses AI to build tools for its programs. This plan, being put forward, adheres to the Responsible AI (RAI) principles set and laid down by the White House in its Presidential Executive Order 13960. Our research, engineering and technical communities have been made aware of these guidelines and we are committed to an on-going process of educating and monitoring its implementation to ensure adherence to those principles. The vast majority of NASA’s use cases, which number almost 75 today, are geared toward analyzing the petabytes of data that NASA collects from its fleet of spacecraft across all disciplines, in human space exploration, and in aeronautics, etc.

Artificial Intelligence↗

The preservation of LANDSAT data by the National Land Remote Sensing Archive

Digital data, acquired by the National Landsat Remote Sensing Program, document nearly two decades of global agricultural, environmental, and sociological change. The data were widely applied and continue to be essential to a variety of geologic, hydrologic, agronomic, and strategic programs and studies by governmental, academic, and commercial researchers. Landsat data were acquired by five observatories that use primarily two digital sensor systems. The Multispectral Scanner (MSS) was onboard all five Landsats, which have orbited over 19 years; the higher resolution Thematic Mapper (TM) sensor acquired data for the last 9 years on Landsats 4 and 5 only. The National Land Remote Sensing Archive preserves the 800,000 scenes, which total more than 60 terabytes of data, on master tapes that are steadily deteriorating. Data are stored at two terabytes of data, on master tapes that are steadily deteriorating. Data are stored at two locations (Sioux Falls, South Dakota and Landover, Maryland), in three archive formats. The U.S. Geological Survey's EROS Data Center has initiated a project to consolidate and convert, over the next 4 years, two of the archive formats from antiquated instrumentation tape to rotary-recorded cassette magnetic tape. The third archive format, consisting of 300,000 scenes of MSS data acquired from 1972 through 1978, will not be converted because of budgetary constraints. This data preservation project augments EDC's experience in data archiving and information management, expertise that is critical to EDC's role as a Distributed Active Archive Center for the Earth Observing System, a new and much larger national earth science program.

Boyd, John E.↗

Technical report series on global modeling and data assimilation. Volume 6: A multiyear assimilation with the GEOS-1 system: Overview and results

The Data Assimilation Office (DAO) at Goddard Space Flight Center has produced a multiyear global assimilated data set with version 1 of the Goddard Earth Observing System Data Assimilation System (GEOS-1 DAS). One of the main goals of this project, in addition to benchmarking the GEOS-1 system, was to produce a research quality data set suitable for the study of short-term climate variability. The output, which is global and gridded, includes all prognostic fields and a large number of diagnostic quantities such as precipitation, latent heating, and surface fluxes. Output is provided four times daily with selected quantities available eight times per day. Information about the observations input to the GEOS-1 DAS is provided in terms of maps of spatial coverage, bar graphs of data counts, and tables of all time periods with significant data gaps. The purpose of this document is to serve as a users' guide to NASA's first multiyear assimilated data set and to provide an early look at the quality of the output. Documentation is provided on all the data archives, including sample read programs and methods of data access. Extensive comparisons are made with the corresponding operational European Center for Medium-Range Weather Forecasts analyses, as well as various in situ and satellite observations. This document is also intended to alert users of the data about potential limitations of assimilated data, in general, and the GEOS-1 data, in particular. Results are presented for the period March 1985-February 1990.

Suarez, Max J.↗

Research studies on advanced optical module/head designs for optical devices

A summary is presented of research in optical data storage materials and of research at the center. The first section contains summary reports under the general headings of: (1) Magnetooptic media: modeling, design, fabrication, characterization, and testing; (2) Optical heads: holographic optical elements; and (3) Optical heads: integrated optics. The second section consist of a proposal entitled, Signal Processing Techniques for Optical Data Storage. And section three presents various publications prepared by the center.

Burke, James J.↗

Short-Term Prediction Research and Transition (SPoRT) Center: Transitioning Satellite Data to Operations

The Short-term Prediction Research and Transition (SPoRT) Center located at NASA Marshall Space Flight Center has been conducting testbed activities aimed at transitioning satellite products to National Weather Service operational end users for the last 10 years. SPoRT is a NASA/NOAA funded project that has set the bar for transition of products to operational end users through a paradigm of understanding forecast challenges and forecaster needs, displaying products in end users decision support systems, actively assessing the operational impact of these products, and improving products based on forecaster feedback. Aiming for quality partnerships rather than a large quantity of data users, SPoRT has become a community leader in training operational forecasters on the use of up-and-coming satellite data through the use of legacy instruments and proxy data. Traditionally, SPoRT has supplied satellite imagery and products from NASA instruments such as the Moderate-resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS). However, recently, SPoRT has been funded by the GOES-R and Joint Polar Satellite System (JPSS) Proving Grounds to accelerate the transition of selected imagery and products to help improve forecaster awareness of upcoming operational data from the Visible Infrared Imager Radiometer Suite (VIIRS), Cross-track Infrared Sounder (CrIS), Advanced Baseline Imager (ABI), and Geostationary Lightning Mapper (GLM). This presentation provides background on the SPoRT Center, the SPoRT paradigm, and some example products that SPoRT is excited to work with forecasters to evaluate.

Zavodsky, Bradley↗

The SPASE Data Model: A Metadata Standard for Registering, Finding, Accessing, and Using Heliophysics Data Obtained from Observations and Modeling

The Space Physics Archive Search and Extract Consortium has developed and implemented the SPASE Data Model that provides a common language for registering a wide range of Heliophysics data and other products. The Data Model enables discovery and access tools such that any researcher can obtain data easily, thereby facilitating research, including on space weather. The Data Model includes descriptions of Simulation Models and Numerical Output, pioneered by the Integrated Medium for Planetary Exploration (IMPEx) group in Europe, and subsequently adopted by the Community Coordinated Modeling Center (CCMC). The SPASE group intends to register all relevant Heliophysics data resources, including space-, ground-, and model-based. Substantial progress has been made, especially for space-based observational data and associated observatories, instruments, and display data. Legacy product registrations and access go back more than 50 years. Real-time data will be included. The National Aeronautics and Space Administration (NASA) portion of the SPASE group has funding that assures continuity in the upkeep of the Data Model and aids with adding new products. Tools are being developed for making and editing data descriptions. Digital Object Identifiers (DOIs) for Data Products can now be included in the descriptions. The data access that SPASE facilitates is becoming more uniform, and work is progressing on Web Service access via a standard Application Programming Interface. The SPASE Data Model is stable; changes over the past 9 years were additions of terms and capabilities that are backward compatible. This paper provides a summary of the history, structure, use, and future of the SPASE Data Model.

Roberts, D. Aaron↗

A Cold Moderator For Sub-Thermal Neutron Flux Enhancement at the RPI-LINAC

The importance of high-quality thermal neutron scattering kernels coupled with a lack of accurate sub-thermal total cross section data prompted researchers at Rensselaer Polytechnic Institute (RPI) to design a cold moderation system to enhance sub-thermal neutron flux (defined as flux below 5 meV), for nuclear data measurements at the RPI Gaerttner LINAC facility. Using a series of neutronic and heat transfer simulations obtained with MCNP and COMSOL, an optimized final design was produced. The final design exceeded current target sub-thermal neutron producing capabilities by a factor of 8 in the sub-thermal region and is easily configurable with existing neutron producing targets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗