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At least 235 records · Page 13

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.↗

Tools and Data Services from the GSFC Earth Sciences DAAC for Aura Science Data Users

In these times of rapidly increasing amounts of archived data, tools and data services that manipulate data and uncover nuggets of information that potentially lead to scientific discovery are becoming more and more essential. The Goddard Space Flight Center (GSFC) Earth Sciences (GES) Distributed Active Archive Center (DAAC) has made great strides in facilitating science and applications research by, in consultation with its users, developing innovative tools and data services. That is, as data users become more sophisticated in their research and more savvy with information extraction methodologies, the GES DAAC has been responsive to this evolution. This presentation addresses the tools and data services available and under study at the GES DAAC, applied to the Earth sciences atmospheric data. Now, with the data from NASA's latest Atmospheric Chemistry mission, Aura, being readied for public release, GES DAAC tools, proven successful for past atmospheric science missions such as MODIS, AIRS, TRMM, TOMS, and UARS, provide an excellent basis for similar tools updated for the data from the Aura instruments. GES DAAC resident Aura data sets are from the Microwave Limb Sounder (MLS), Ozone Monitoring Instrument (OMI), and High Resolution Dynamics Limb Sounder (HIRDLS). Data obtained by these instruments afford researchers the opportunity to acquire accurate and continuous visualization and analysis, customized for Aura data, will facilitate the use and increase the usefulness of the new data. The Aura data, together with other heritage data at the GES DAAC, can potentially provide a long time series of data. GES DAAC tools will be discussed, as well as the GES DAAC Near Archive Data Mining (NADM) environment, the GIOVANNI on-line analysis tool, and rich data search and order services. Information can be found at: http://daac.gsfc.nasa.gov/upperatm/aura/. Additional information is contained in the original extended abstract.

Kempler, S.↗

Mission operations update for the restructured Earth Observing System (EOS) mission

The National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS) will provide a comprehensive long term set of observations of the Earth to the Earth science research community. The data will aid in determining global changes caused both naturally and through human interaction. Understanding man's impact on the global environment will allow sound policy decisions to be made to protect our future. EOS is a major component of the Mission to Planet Earth program, which is NASA's contribution to the U.S. Global Change Research Program. EOS consists of numerous instruments on multiple spacecraft and a distributed ground system. The EOS Data and Information System (EOSDIS) is the major ground system developed to support EOS. The EOSDIS will provide EOS spacecraft command and control, data processing, product generation, and data archival and distribution services for EOS spacecraft. Data from EOS instruments on other Earth science missions (e.g., Tropical Rainfall Measuring Mission (TRMM)) will also be processed, distributed, and archived in EOSDIS. The U.S. and various International Partners (IP) (e.g., the European Space Agency (ESA), the Ministry of International Trade and Industry (MITI) of Japan, and the Canadian Space Agency (CSA)) participate in and contribute to the international EOS program. The EOSDIS will also archive processed data from other designated NASA Earth science missions (e.g., UARS) that are under the broad umbrella of Mission to Planet Earth.

Kelly, Angelita Castro↗

PiFEx data and archival formats

A standard archival format is presented for the Jet Propulsion Laboratory Mobile Satellite Experiment (MSAT-X) Pilot Field Experiments (PiFEx), which will overcome the deficiencies of the current set-up. This format allows ease of data processing, flexibility for future experiments, and controllable data dissemination to other researchers.

Berner, Jeff B.↗

Accelerating Space Life Sciences: Successes and Challenges of Biospecimen and Data Sharing

NASA's current human space flight research is directed towards enabling human space exploration beyond Low Earth Orbit (LEO). To that end, NASA Space Flight Payload Projects; Rodent Research, Cell Science, and Microbial Labs, flown on the International Space Station (ISS), benefit the global life sciences and commercial space communities. Verified data sets, science results, peer-reviewed publications, and returned biospecimens, collected and analyzed for flight and ground investigations, are all part of the knowledge base collected by NASA's Human Exploration and Operations Mission Directorate's Space Life and Physical Sciences Research and Applications (SLPSRA) Division, specifically the Human Research and Space Biology Programs. These data and biospecimens are made available through the public Life Sciences Data Archive (LSDA) website to promote basic discovery, pre-clinical and clinical science.The NASA Institutional Scientific Collection (ISC), stores flight and ground biospecimens from Space Shuttle and ISS programs. These specimens are curated and managed by the Ames Life Sciences Data Archive (ALSDA), an internal node of NASA's LSDA. The ISC stores over 30,000 specimens from experiments dating from 1984 to present. Currently available specimens include tissues from the circulatory, digestive, endocrine, excretory, integumentary, muscular, neurosensory, reproductive, respiratory and skeletal systems.NASA's biospecimen collection represents a unique and limited resource of unique spaceflight payload and ground control research subjects. These specimens are harvested according to well established SOPs that maintain their quality and integrity. Once the primary scientific objectives have been met, the remaining specimens are made available to provide secondary opportunities for complementary studies or new investigations to broaden research without large expenditures of time or resources. Website: https://lsda.jsc.nasa.gov/

Scott, Ryan T.↗

The Honeycomb supernova remnant

At 2.5 min southeast of SN 1987A, the Honeycomb Nebula Supernova remnant (SNR) is named after its interesting morphology, which consists of over ten loops with sizes of 2-3 pc. High-dispersion spectra of these loops show hemispheres expanding toward the observer at 100-300 km/s. Using archival data X-ray data and a combination of new and archival radio data, we find bright X-ray and nonthermal radio emisssion associated with the Honeycomb Nebula. New CCD images further show enhanced (S II) H-alpha ratios. These results confirm a model in which the Honeycomb Nebula is due to a supernova shock front, traveling toward the observer, encountering an intervening sheet of dense, but porous, interstellar gas. The bulk of the supernova remnant resides in a low-density cavity, and is not otherwise visible. The situation is similar to the hidden supernova remnants postulated for the X-ray bright superbubbles. The Honeycomb Nebula has an unusually steep radio spectral index (S(sub nu) is proportional to nu(exp -1.2)), normally associated with young SNRs.

Chu, You-Hua↗

Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, scripts, model files

This model-data archive supports the research paper that demonstrates the integration of agricultural drainage features—specifically, narrow engineered ditches and tile drains—into a fully distributed, basin-scale integrated surface-subsurface hydrology model (ISSHM), Amanzi-ATS. The model employs innovative computational meshes aligned with agricultural ditches and incorporates the physically based Hooghoudt's drainage equation to simulate tile drainage, offering a novel strategy that enhances the accuracy of hydrological simulations.The archived dataset includes input parameters, model configurations, and select simulation outputs for the Amanzi-ATS model that successfully captured the streamflow patterns in the Portage River Watershed as validated by USGS gauge readings. Jupyter notebook for the preparation of model inputs and post-processing of outputs are also included. The model's predictive performance achieved a normalized Kling-Gupta Efficiency (KGE) of 0.81, surpassing SWAT without the necessity for site-specific calibration.The Amanzi-ATS model presented in this modeL-data archive allows for numerical experiments to explore the shifts in the flow structure under different drainage scenarios. As a tool for advancing the understanding of distributed hydrological responses and nutrient cycling, this archived model provides valuable insights for researchers, modelers, and decision-makers involved in watershed management and environmental modeling.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model, are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗

Biospecimen Culling: Temporal RNA Integrity Analysis Across Spaceflight Missions Dating from 1985 to 2011

The Ames Life Science Data Archive (ALSDA) at NASA Ames Research Center is managed by the Space Biosciences Division and has been operational since 1993. The ALSDA is responsible for archiving information and biospecimens collected from life science spaceflight experiments and matching ground control experiments. They are stored in the Ames biobank, which is located in the Biospecimen Storage Facility (BSF). The ALSDA also manages a Biospecimen Sharing Program, performs curation and long-term storage operations, and makes biospecimens available to the scientific community for research purposes via the Life Science Data Archive public website (https:lsda.jsc.nasa.gov). The BSF maintains both fixed and frozen spaceflight and ground tissues, collected from recent and past spaceflight missions. Due to the ever increasing demand for space to preserve current and future flight biospecimens, the ALSDA has initiated the development of a culling plan for biospecimens currently stored in the BSF. Culling enables the ALSDA to assess the quality of archived samples, and supports the development of standardized culling procedures that improve the operational efficiency of the BSF. The culling plan focuses on generating disposition recommendations for samples in the BSF, and currently is based on measuring ribonucleic acid (RNA) integrity number (RIN). The culling process includes (1) sorting and identification of candidate samples for RIN analysis, (2) completion of RIN analysis on select samples, and (3) development of disposition recommendations for specimens based on the RIN values. Furthermore, our approach allows for unique scientific opportunities, including development of a RIN-based methodology for culling, and temporal assessment of the quality of the tissues that have been stored in BSF since the 1980s. Results of this work will also support NASA open science initiatives.

biospecimen↗

The NASA Ames Research Center Institutional Scientific Collection: History, Best Practices and Scientific Opportunities

The NASA Ames Life Sciences Institutional Scientific Collection (ISC), which is composed of the Ames Life Sciences Data Archive (ALSDA) and the Biospecimen Storage Facility (BSF), is managed by the Space Biosciences Division and has been operational since 1993. The ALSDA is responsible for archiving information and animal biospecimens collected from life science spaceflight experiments and matching ground control experiments. Both fixed and frozen spaceflight and ground tissues are stored in the BSF within the ISC. The ALSDA also manages a Biospecimen Sharing Program, performs curation and long-term storage operations, and makes biospecimens available to the scientific community for research purposes via the Life Science Data Archive public website (https:lsda.jsc.nasa.gov). As part of our best practices, a viability testing plan has been developed for the ISC, which will assess the quality of archived samples. We expect that results from the viability testing will catalyze sample use, enable broader science community interest, and improve operational efficiency of the ISC. The current viability test plan focuses on generating disposition recommendations and is based on using ribonucleic acid (RNA) integrity number (RIN) scores as a criteria for measurement of biospecimen viablity for downstream functional analysis. The plan includes (1) sorting and identification of candidate samples, (2) conducting a statiscally-based power analysis to generate representaive cohorts from the population of stored biospecimens, (3) completion of RIN analysis on select samples, and (4) development of disposition recommendations based on the RIN scores. Results of this work will also support NASA open science initiatives and guides development of the NASA Scientific Collections Directive (a policy on best practices for curation of biological collections). Our RIN-based methodology for characterizing the quality of tissues stored in the ISC since the 1980s also creates unique scientific opportunities for temporal assessment across historical missions. Support from the NASA Space Biology Program and the NASA Human Research Program is gratefully acknowledged.

ALSDA↗

Investigation of the Transport of Solar Ions Through the Earth's Magnetosphere

The objective of this study has been to infer, by statistical means, the most probable mode of entry of solar wind plasma into Earth's magnetotail, using a particular set of archived data from the Lockheed Plasma Composition Experiment on the International Sun-Earth Explorer One (ISEE-1) satellite, jointly sponsored by the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) in the 1970's and 80's. Despite their considerable age, the Lockheed ISEE-1 data are still, at the time of this report, the only substantial ion composition data in the sub-keV to keV energy range available from the magnetotail beyond 9 R(sub E), because of various technical problems with ion mass spectrometers on later missions, and are therefore a unique source of information about the mixing of solar and terrestrial origin plasmas in the tail, within the ISEE-1 apogee of almost 23 R(sub E). The entire set of archived data used in this study, covering the 4.5 years of operation of the instrument and comprising not only tail measurements but also data from the inner magnetosphere as well as data from outside the magnetopause, is now available to the public via the WorldWideWeb at the address: http://cis.spasci.com/ISEE_ions The fundamental assumption of this and other studies of magnetosphere ion composition is that He++ and O+ ions are virtually certain "tags" of solar and terrestrial origins, respectively. This is an assumption with strong theoretical basis and it is corroborated by observational evidence, including the often substantial differences between the velocity distribution functions of those two species. The H+ ions can have a dual origin, in principle, but the close resemblance in the ISEE-1 data between the dynamics of H+ and He++ ions indicates a predominantly solar origin of the H+ ions in the tail, at least. By the same token, the usually minor He+ ions are probably almost entirely of terrestrial origin, because of their similarity to the O+ ions.

Lennartsson, O. W.↗

A Search for Nontriggered Gamma-Ray Bursts in the BATSE Database

We describe a search of archival data from the Burst and Transient Source Experiment (BATSE). The purpose of the search is to find astronomically interesting transients that did not activate the burst-detection (or "trigger") system on board the spacecraft. Our search is sensitive to events with peak fluxes (on the 1.024 s timescale) that are lower by a factor of approximately 2 than can be detected with the on-board burst trigger. In a search of 345 days of archival data, we detected 91 events in the 50-300 keV range that resemble classical gamma-ray bursts but that did not activate the on-board burst trigger. We also detected 110 low-energy (25-50 keV) events of unknown origin that may include activity from' soft gamma repeater (SGR) 1806-20 and bursts and flares from X-ray binaries. This paper gives the occurrence times, estimated source directions, durations, peak fluxes, and fluences for the 91 gamma-ray burst candidates. The direction and intensity distributions of these bursts imply that the biases inherent in the on-board trigger mechanism have not significantly affected the completeness of the published BATSE gamma-ray burst catalogs.

Kommers, Jefferson M.↗

Early High-contrast Imaging Results with Keck/NIRC2-PWFS: The SR 21 Disk

High-contrast imaging of exoplanets and protoplanetary disks depends on wave front sensing and correction made by adaptive optics instruments. Classically, wave front sensing has been conducted at optical wavelengths, which made high-contrast imaging of red targets such as M-type stars or extincted T Tauri stars challenging. Keck/NIRC2 has combined near-infrared (NIR) detector technology with the pyramid wave front sensor (PWFS). With this new module we observed SR 21, a young star that is brighter at NIR wavelengths than at optical wavelengths. Compared with the archival data of SR 21 taken with the optical wave front sensing we achieved ~20% better Strehl ratio in similar natural seeing conditions. Further post-processing utilizing angular differential imaging and reference-star differential imaging confirmed the spiral feature reported by the Very Large Telescope/Spectro-Polarimetric High-contrast Exoplanet REsearch instrument polarimetric observation, which is the first detection of the SR 21 spiral in total intensity at L' band. We also compared the contrast limit of our result (10 -4 at 0.'4 and 2 × 10 -5 at 1.'0) with the archival data that were taken with optical wave front sensing and confirmed the improvement, particularly at ≤0.'5. Our observation demonstrates that the NIR PWFS improves AO performance and will provide more opportunities for red targets in the future.

79 ASTRONOMY AND ASTROPHYSICS↗

Washington Air-Sea Interaction Research Facility Waves and Currents Test Data

This archive includes data from the University of Washington WASIRF (Washington Air-Sea Interaction Research Facility) flume. WASIRF is a laboratory testing tank at the Northwest National Marine Renewable Energy Center designed to investigate wind-wave-current interactions. It includes test data for simultaneous waves and current generation done at the WASIRF lab. A report included in the archive further details testing methodology. Wave and current data is provided in .dat files.

16 TIDAL AND WAVE POWER↗

Model data for numerical evaluation of photosensitive tracers as a strategy for separating surface and subsurface transient storage in streams

This model-data archive pertains to a study aimed at the numerical evaluation of the photosensitive tracers as a potential strategy for separating the effects of surface and hyporheic storage zones (SSZs and HSZs, respectively). Separating effects of SSZ and HSZ are important for accurately representing stream function as HSZs and SSZs expose solutes to significantly different biogeochemical conditions. We perform numerical experiments using a multiscale reactive transport model for stream corridors implemented in ATS code, which allows for representing multiple storage zones with their respective travel time distributions and biogeochemistry. For each of the numerical experiment, we provide in this model-data archive python wrapper to drive ATS (forward_model.py), synthetic observation (synthetic_btc.py, BTC_observed.csv), forward model files including ATS input (multiscale_transport.tpl), PFLOTRAN inputs (reactions_channel.tpl, reactions_hz.tpl, reactions_sz.tpl), MCMC (mcmc_run.py), predictive uncertainty (pred_uncert.py, BTCs_simulated_day.csv, BTCs_simulated_night.csv), MCMC outputs (tracer_test_GR.npy, tracer_test_logps.npy, tracer_test_parameters.npy) and Jupyter notebook for post-processing and visualization (post-processing.ipynb). For the denitrification application, ATS input file (denitrification_multisubgrid.tpl), PFLOTRAN input files (denitrification_channel.in, denitrification_hz.in), predictive uncertainty (pred_uncert_denitrification.py, BTCs_simulated_DO.csv, BTCs_simulated_DOC.csv, BTCs_simulated_Nitrate.csv).

54 ENVIRONMENTAL SCIENCES↗

Real time computations of cryogenic He properties

The Fermilab PIP-II (proton improvement plan - II) project is being constructed at Fermilab to deliver $800\,MeV$ protons of $>1\,MW$ beam power to replace the present LINAC and provide protons to the remainder of the existing accelerator complex. The new LINAC consists of a warm front end, 23 superconducting RF cryomodules, and a beam transfer line to the existing complex. The cryomodules (CMs) are to be tested at Fermilab's CryoModule Test Facility (CMTF).An important measurement in cryogenic testing is the heat load of each CM. Traditionally, at Fermilab, these measurements were made collecting archived data offline and analyzing it. The new control system for PIP-II is being developed with the EPICS (Experimental Physics and Industrial Control System) framework, which allows us to compute the heat load in real time using the HePak library.We are exploring other $He$ properties, such as flow, where flow meters are not available, which can also be calculated in real time and fed back to the cryogenics engineers.This paper details the real time heat load calculation and $He$ flow software developed for CM testing at CMTF, as well as the first results from the prototype HB650 CM. Future plans for 2-phase $LHe$ flow will also be outlined.

Hanlet, Pierrick [Fermilab]↗

Unravelling the origin of extended radio emission in narrow-line Seyfert 1 galaxies with the JVLA

Narrow-line Seyfert 1 galaxies (NLS1s) are believed to be active galactic nuclei (AGN) in the early stages of their evolution. Several dozen of them have been found to host relativistic jets, whilst the majority of NLS1s have not even been detected in radio, emphasising the heterogeneity of the class in this band. In this paper, our aim is to determine the predominant source of radio emission in a sample of 44 NLS1s, selected based on their extended kiloparsec-scale radio morphologies at 5.2 GHz. Here, we accomplish this by analysing their spatially resolved radio spectral index maps, centred at 5.2 GHz, as the spectral index carries information about the production mechanisms of the emission. In addition, we utilise several diagnostics based on mid-infrared emission to estimate the star formation activity of their host galaxies. These data are complemented by archival data to draw a more complete picture of each source. We find an extraordinary diversity among our sample. Approximately equal fractions (~10–12 sources) of our sources can be identified as AGN-dominated, composite, and host-dominated. Among the AGN-dominated sources are a few NLS1s with very extended jets, reaching distances of tens of kiloparsecs from the nucleus. One of these, J0814+5609, hosts the most extended jets found in an NLS1 so far. We also identify five NLS1s that could be classified as compact steep-spectrum sources. In addition, one source shows a possible kiloparsec-scale relic that reaches well outside the host galaxy as well as restarted nuclear activity, and one could belong to the sub-class of NLS1s that host relativistic jets that seem to be absorbed at lower radio frequencies (< 10 GHz). We further conclude that, due to the variety seen in NLS1s, simple proxies, such as the star formation diagnostics also employed in this paper and the radio loudness parameter, are not ideal tools for characterising NLS1s. We emphasise the necessity of examining NLS1s as individuals instead of making assumptions based on their classification. When these issues are properly taken into account, NLS1s offer an exceptional environment for studying the interplay between the host galaxy and several AGN-related phenomena, such as jets and outflows.

79 ASTRONOMY AND ASTROPHYSICS↗

Clustering-Based Predictive Analytics to Improve Scientific Data Discovery

Given the sheer volume of scientific data archived within the data-intensive projects at the US Department of Energy's Oak Ridge National Laboratory, finding precisely what data we are looking for may not be a trivial task; conversely, we may also miss a more prominent data product. To address such issues, we propose improving the data discovery system and using data analytics methods to comprehend what specific users might be interested in based on their physiological state, search patterns, and past data usage history. This work's primary goal is to prune the complexity, increase the visibility of popular data products, and direct users toward the data that best meet their needs. The proposed algorithm constructs a user profile based on the user's explicit or implicit interactions with the system, such as items they are currently looking at on-site and the key metadata mappings related to the data set. The pattern is then used to build a training data set, which will help find relevant data to recommend to the user.

Devarakonda, Ranjeet↗