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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Empirical Validation of UBEM: An Assessment of Bias in Urban Building Energy Modeling for Chicago

Residential and commercial buildings currently account for 30% of total global final energy consumption. Urban-scale building energy modeling (UBEM) can enable scalable investments and unlock building improvements by quantifying energy, demand, emissions, and cost reductions of specific measures or packages for building-specific technologies in large geographic regions. While the sophistication of UBEM data sources and technologies have increased dramatically in the past decade, there remains a knowledge gap for empirical validation and sources of bias between building-specific energy models and measured data at varying geographic scales.As UBEM continues to develop, systemic analysis of accuracy, bias, and limitations of the resulting models is necessary to inform best practices and move toward standardization. These are characterized for the Automatic Building Energy Modeling (AutoBEM) software suite with an initial case study involving metered electricity consumption data from 247,188 buildings in Chicago, Illinois, USA - averaged across years 2019-2021 - compared to the following datasets: (1) the AutoBEM-generated nation-scale Model America version 2 (MAv2) data for 596,064 buildings, (2) tax assessor data for 579,829 buildings, (3) tax assessor data filled with MAv2, and (4) 102 representative dynamic archetypes. The accuracy is reported for every building type and vintage combination, along with multiple sources of bias for unique building descriptors. The AutoBEM simulation workflow produced energy consumption estimates that closely match aggregated metered electricity consumption data for different types of buildings constructed during various time periods at the city scale - with initial normalized mean bias error of 10.9%, and 1.1% after removing outliers. Contribution of statistically significant factors including building type, land use, age, and size to variance in UBEM bias is quantified.

Garg, Ankur↗
DOE OSTI2025

Sensitivity of Regional WRF‐Chem Air Quality and Weather Simulations to Biomass‐Burning Emission Data Sets: A Case Study of the Impact of Canadian Wildfire on the US°

This study focuses on the period from June 26 to 29, 2023, when record‐breaking Canadian wildfires severely impacted air quality in the Midwest United States. Using the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) and four biomass‐burning data sets (Fire Inventory from NCAR version 1, Fire Inventory from NCAR version 2.5, Quick Fire Emissions Data set [QFED], and Regional ABI‐VIIRS Emission), we analyzed aerosol transport from Canada to the US and assessed the model's accuracy in predicting PM 2.5 , O 3 , CO and aerosol weather feedback. Model simulations were compared with ground‐based and remote sensing observations as well as field measurements from the Community Research on Climate and Urban Science (CROCUS) project. Our findings show that the movement of a low‐pressure system from the Great Lakes to the Atlantic, combined with the high‐pressure system over the Atlantic, caused the transport of aerosols from Canadian wildfires to the US. Results show WRF‐Chem significantly underestimated key atmospheric components: aerosol optical depth (AOD) by over 50%, PM 2.5 by 65%–90% and peak O 3 concentrations by 50%–55% across four biomass burning data sets. Additionally, CO and NO 2 concentrations were underpredicted. The substantial underestimation of PM 2.5 led to an overestimation of temperature by up to 3.6 °C primarily due to excessive downward shortwave radiation, which resulted from the underestimation of direct aerosol effects and an increase in sensible heat flux. Among the biomass‐burning data sets, QFED produced the most accurate AOD and PM 2.5 predictions due to improved wildfire emission estimates, leading to a 1.0 to 1.5 °C reduction in temperature overestimation during the daytime. These findings underscore the need for improving wildfire emission estimates for trace gases and aerosols to enhance air quality and weather feedback predictions.

WRF-chem model↗
NASA NTRS2019

NASA GeneLab Space Omics Database: Expanding from Space to Ionizing Radiation Data on the Ground

NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or ground experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). The GeneLab Data Systems (GLDS) version 4.0 will be available on October 1st 2019, and will provide a state-of-the-art bioinformatics platform for the space biology and radiation communities to upload their data into an omics data commons, to process their data with vetted standard workflows and to compare with existing analyses. Started in 2015 as a repository designed to archive omics data from space experiments, GeneLab has expanded its scope to all ionizing radiation omics experiments conducted on the ground and has put considerable effort in providing carefully characterized radiation metadata on all datasets. GeneLab is also providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome) to help users explore important questions: 1) Which genes or proteins are expressed differently in space for various living organisms? 2) What specific DNA mutations or epigenetic changes happen in space or after exposure to ionizing radiation? and 3) How does genetics affect these responses? Processed data available on GeneLab are derived by standard data analysis workflows vetted by hundreds of scientists who volunteered to join one of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). In this presentation, we will discuss how to bridge the gap between irradiation studies performed on earth and biological experiments conducted in space since the early 1990's. We will discuss how radiation dosimetry was estimated for datasets derived from samples collected during the Space Shuttle era on the International Space Station and on other orbiting platforms. Finally, we will address future strategies regarding dose monitoring in future missions into space, inter-agency efforts to unify data under one umbrella, and knowledge dissemination across the radiation research community and the space biology community.

open-science↗
NASA NTRSDate not supplied

Space Launch System Liftoff and Separation Dynamics Analysis Tool Chain

A flexible, hierarchical tool chain that is being applied to NASA’s Space Launch System (SLS) for critical dynamics phenomena is described. This tool chain, called CLVTOPS, is used to investigate lateral liftoff movement of the vehicle as it departs and clears the mobile launch tower and separation of the two solid rocket boosters without collision with the core stage and payload. The toolset’s architecture was configured to take advantage of a modern software-engineering approach for maximum flexibility and utilization of open-source simulations and associated tools. As opposed to a “monolithic” approach, scripting languages were used to “bind” together a tool chain to configure and organize input data, execute and produce analysis results, and post-process these results to facilitate a rapid iterative analysis process to quickly address issues and pursue alternatives with emphasis on analysis automation. Key capabilities in the tool chain include processing and mining of very large data sets, a wide range of graphical depictions, and high-fidelity, physics-based simulations. The paper begins with a problem description and the motivation for liftoff and separation dynamics analysis followed by a historical survey of dynamics analyses for previous NASA human-rated launch vehicles. Details of the tool chain and its components are then introduced divided, first, into description of the scripting language architecture used to “bind” the simulation tools, programs, and scripts together and, second, the physics models and simulations. Representative analyses and data products are shown for liftoff and booster separation dynamics that provide in-depth insight to the tool chain’s capabilities. Supporting activities such as simulation tool chain verification, version archiving and data management, and training are addressed. The paper concludes with case examples on how the tool chain can be tailored to related aerospace dynamics analyses, both large and small. These patterns and techniques for SLS dynamics tool construction can be applied for other aerospace simulations.

6DOF↗
NASA NTRS2006

Ozone Profiles in the High-latitude Stratosphere and Lower Mesosphere Measured by the Improved Limb Atmospheric Spectrometer (ILAS)-II: Comparison with other Satellite Sensors and Ozonesondes

A solar occultation sensor, the Improved Limb Atmospheric Spectrometer (ILAS)-II, measured 5890 vertical profiles of ozone concentrations in the stratosphere and lower mesosphere and of other species from January to October 2003. The measurement latitude coverage was 54-71degN and 64-88degS, which is similar to the coverage of ILAS (November 1996 to June 1997). One purpose of the ILAS-II measurements was to continue such high-latitude measurements of ozone and its related chemical species in order to help accurately determine their trends. The present paper assesses the quality of ozone data in the version 1.4 retrieval algorithm, through comparisons with results obtained from comprehensive ozonesonde measurements and four satellite-borne solar occultation sensors. In the Northern Hemisphere (NH), the ILAS-II ozone data agree with the other data within +/-10% (in terms of the absolute difference divided by its mean value) at altitudes between 11 and 40 km, with the median coincident ILAS-II profiles being systematically up to 10% higher below 20 km and up to 10% lower between 21 and 40 km after screening possible suspicious retrievals. Above 41 km, the negative bias between the NH ILAS-II ozone data and the other data increases with increasing altitude and reaches 30% at 61-65 km. In the Southern Hemisphere, the ILAS-II ozone data agree with the other data within 10% in the altitude range of 11-60 km, with the median coincident profiles being on average up to 10% higher below 20 km and up to 10% lower above 20 km.

Sugita, T.↗
NASA NTRS1992

Global change data sets: Excerpts from the Master Directory, version 2.0

The recent awakening to the reality of human-induced changes to the environment has resulted in an organized effort to promote global change research. The goal of this research as outlined by NASA's Earth System Science Committee (Earth System Science: A closer View, 1988) is to understand the entire Earth system on a global scale by describing how its component parts and their interactions have evolved, how they function, and how they may be expected to evolve on all timescales. The practical result is the capacity to predict that evolution over the next decade to century. Key variables important for the study of global change include external forcing factors (solar radiance, UV flux), radiatively and chemically important trace species (CO2, CH4, N2O, etc.), atmospheric response variables (temperature, pressure, winds), landsurface properties (river run-off, snow cover, albedo, soil moisture, vegetation cover), and oceanic variables (sea surface temperature, sea ice extent, sea level ocean wind stress, currents, chlorophyll, biogeochemical fluxes). The purpose of this document is to identify existing data sets available (both remotely sensed and in situ data) covering some of these variables. This is not intended to be a complete list of global change data, but merely a highlight of what is available. The information was extracted from the Master Directory (MD), an on-line scientific data information service which may be used by any researcher. This report contains the coverage dates for the data sets, sources (satellites, instruments) of the data and where they are archived.

Beier, Joy↗
NASA NTRS2018

GEOS S2S-2_1 File Specification: GMAO Seasonal and Sub-Seasonal Forecast Output

The NASA GMAO seasonal (9 months) and subseasonal (45 days) forecasts are produced with the Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model and Data Assimilation System Version S2S-2_1. The new system replaces version S2S-1.0 described in Borovikov et al (2017), and includes upgrades to many components of the system. The atmospheric model includes an upgrade from a pre-MERRA-2 version running on a latitude-longitude grid at approx. 1 degree resolution to a current version running on a cubed sphere grid at approximately 1/2 degree resolution. The important developments are related to the dynamical core (Putman et al., 2011), the moist physics (''two-moment microphysics'' of Barahona et al., 2014) and the cryosphere (Cullather et al., 2014). As in the previous GMAO S2S system, the land model is that of Koster et al (2000). GMAO S2S-2_1 now includes the Goddard Chemistry Aerosol Radiation and Transport (GOCART, Colarco et al., 2010) single moment interactive aerosol model that includes predictive aerosols including dust, sea salt and several species of carbon and sulfate. The previous version of GMAO S2S specified aerosol amounts from climatology, which were used to inform the atmospheric radiation only. The ocean model includes an upgrade from MOM4 to MOM5 (Griffies 2012), and continues to be run on the tripolar grid at approximately 1/2 degree resolution in the tropics with 40 vertical levels. As in S2S-1.0, the sea ice model is from the Los Alamos Sea Ice model (CICE4, Hunke and Lipscomb 2010). The Ocean Data Assimilation System (ODAS) has been upgraded from the one described in Borovikov et al., 2017 to one that uses a modified version of the Penny, 2014 Local Ensemble Transform Kalman Filter (LETKF), and now assimilates along-track altimetry. The ODAS also does a nudging to MERRA-2 SST and sea ice boundary conditions. The atmospheric data assimilation fields used to constrain the atmosphere in the ODAS have been upgraded from MERRA to a MERRA-2 like system. The system is initialized using a MERRA-2-like atmospheric reanalysis (Gelaro et al. 2017) and the GMAO S2S-2_1 ocean analysis. Additional ensemble members for forecasts are produced with initial states at 5-day intervals, with additional members based on perturbations of the atmospheric and ocean states. Both subseasonal and seasonal forecasts are submitted to the National MultiModel Ensemble (NMME) project, and are part of the US/Canada multimodel seasonal forecasts (http://www.cpc.ncep.noaa.gov/products/NMME/). A large suite of retrospective forecasts (''hindcasts'') have been completed, and contribute to the calculation of the model's baseline climatology and drift, anomalies from which are the basis of the seasonal forecasts.

Seasonal Forecast↗
NASA NTRS2012

Global Assimilation of EOS-Aura Data as a Means of Mapping Ozone Distribution in the Lower Stratosphere and Troposphere

Ozone in the lower stratosphere and the troposphere plays an important role in forcing the climate. However, the global ozone distribution in this region is not well known because of the sparse distribution of in-situ data and the poor sensitivity of satellite based observations to the lowermost of the atmosphere. The Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) instruments on EOS-Aura provide information on the total ozone column and the stratospheric ozone profile. This data has been assimilated into NASA s Global Earth Observing System, Version 5 (GEOS-5) data assimilation system (DAS). We will discuss the results of assimilating three years of OMI and MLS data into GEOS-5. This data was assimilated alongside meteorological observations from both conventional sources and satellite instruments. Previous studies have shown that combining observations from these instruments through the Trajectory Tropospheric Ozone Residual methodology (TTOR) or using data assimilation can yield useful, yet low biased, estimates of the tropospheric ozone budget. We show that the assimilated ozone fields in this updated version of GEOS-5 exhibit an excellent agreement with ozone sonde and High Resolution Dynamics Limb Sounder (HIRDLS) data in the lower stratosphere in terms of spatial and temporal variability as well as integrated ozone abundances. Good representation of small-scale vertical features follows from combining the MLS data with the assimilated meteorological fields. We then demonstrate how this information can be used to calculate the Stratosphere - Troposphere Exchange of ozone and its contribution to the tropospheric ozone column in GEOS-5. Evaluations of tropospheric ozone distributions from the assimilation will be made by comparisons with sonde and other in-situ observations.

Wargan, Krzysztof↗
NASA NTRSDate not supplied

Space Launch System Liftoff and Separation Dynamics Analysis Tool Chain

A flexible, hierarchical tool chain that is being applied to NASA’s Space Launch System (SLS) for critical dynamics phenomena is described. This tool chain, called CLVTOPS, is used to investigate lateral liftoff movement of the vehicle as it departs and clears the mobile launch tower and separation of the two solid rocket boosters without collision with the core stage and payload. The toolset’s architecture was configured to take advantage of a modern software engineering approach for maximum flexibility and utilization of open-source simulations and associated tools. As opposed to a “monolithic” approach, scripting languages were used to “bind” together a tool chain to configure and organize input data, execute and produce analysis results, and post-process these results to facilitate a rapid, iterative analysis process to quickly address issues and pursue alternatives with emphasis on analysis automation. Key capabilities in the tool chain include processing and mining of very large data sets, a wide range of graphical depictions, and high-fidelity, physics-based simulations. The paper begins with a problem description and the motivation for liftoff and separation dynamics analysis followed by a historical survey of dynamics analyses for previous NASA human-rated launch vehicles. Details of the tool chain and its components are then introduced and divided, first, into description of the scripting language architecture used to “bind” the simulation tools, programs, and scripts together and, second, the physics models and simulations. Representative analyses and data products for liftoff and booster separation dynamics are shown in order to provide in-depth insight into the tool chain’s capabilities. Supporting activities such as simulation tool chain verification, version archiving and data management, and training are addressed. The paper concludes with case examples on how the tool chain can be tailored to related aerospace dynamics analyses, both large and small. The flexibility and versatility of this tool chain in supporting analyses of such a diverse range of aerospace applications demonstrates the feasibility of applying these patterns and techniques for tool construction to other aerospace simulations.

6DOF↗
DOE OSTI2023

Solute chemistry for streams draining geomorphic features and varying land cover gradients in the East River watershed, Colorado

This dataset contains solute chemistry data and GPS coordinates for surface water samples collected in the East River watershed in the Elk and West Elk Ranges of Colorado from August 3rd through August 11th, 2022. Samples were collected from streams and groundwater seeps as part of a comprehensive analysis within the watershed of how different geomorphic features (such as landslides and rock glaciers) along with variations in land cover (such as the presence of vegetation) affect stream water quality in this Rocky Mountain headwater environment. This dataset includes concentrations of the following in a single csv file: fluoride, chloride, sulfate, nitrate, calcium, potassium, magnesium, sodium, silicon, and total organic carbon (TOC). All concentrations are reported in mg/L. The sulfate data in this version have been updated to account for an earlier ion chromatograph instrument method error whereby sulfate and bromide peaks overlapped in calibration solution samples, biasing calculated sulfate concentrations low by 30-50%. Sulfate data reported herein are from a re-run of the samples performed in December 2024 using a corrected instrument method. All samples were stored under refrigerated conditions and filtered on initial collection.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Airborne Hyperspectral Sensing of Monitoring Harmful Algal Blooms in the Great Lakes Region: System Calibration and Validation

Harmful algal blooms (HABs) in Lake Erie have been prominent in recent years. The bloom in 2014 reached a severe level causing the State of Ohio to declare a state of emergency. At that time NASA Glenn Research Center was requested by stakeholders to help monitor the blooms in Lake Erie. Glenn conducted flights twice a week in August and September and assembled and distributed the HAB information to the shoreline water resource managers using its hyperspectral imaging sensor (in development since 2006), the S􀂱3 Viking aircraft, and funding resources from the NASA Headquarters Earth Science Division. Since then, the State of Ohio, National Oceanic and Atmospheric Administration (NOAA), and U.S. Environmental Protection Agency (EPA) have elevated their funding and activities for observing, monitoring, and addressing the root cause of HABs. Also, the communities and stakeholders have persistently requested NASA Glenn􀂶s participation in HAB observation. Abundant field campaigns and sample analyses have been funded by Ohio and NOAA, which provided a great opportunity for NASA to advance science and airborne hyperspectral remote sensing economically. Capitalizing on this opportunity to advance the science of algal blooms and remote sensing, NASA Glenn conducted the Airborne Hyperspectral Observation of harmful algal blooms campaign in 2015 that was, in many respects, twice as large as the 2014 campaign. Focusing mostly on Lake Erie, but also including other small inland lakes and the Ohio River, the campaign was conducted in partnership with a large number of partners specializing in marine science and remote sensing. Airborne hyperspectral observation of HABs holds promise to distinguish potential HABs from nuisance blooms, determine their concentrations, and delineate their movement in an augmented spatial and temporal resolution and under clouds􀂲all of which are excellent complements to satellite observations. Working with collaborators at several Ohio and Michigan institutions as well as one in South Dakota and one in Alabama, this effort was able to provide next-day georeferenced estimates of cyanobacteria and scum concentrations. Very prompt processing and analysis of the hyperspectral imagery is necessary for the information to be acted upon. For example, a next-day report of an overflight over the Ohio River indicated that a bloom could be present as far downstream as the Cincinnati intake, but the Ohio EPA had not received visual reports of a bloom that far downstream. Water samples were obtained at the Cincinnati water intake, based on the flight data, and detected microcystins in the source water. The flight data helped State and municipal authorities realize the potential extent of that bloom, and triggered response sampling, before the visual river-wide scums started forming. The present document describes the process that was utilized to take raw remote sensing data and create information products; this includes system calibration and validation, efforts to correct atmospheric effects, and algorithms that produce the data products. Furthermore, successful research into improved algorithms for expanding the capability to delineate in water constituents is included. Finally, comparisons that show expected relationships between ground-based measurements and hyperspectral imager version 2 (HSI2) data results are presented, giving confidence in the remote sensing products.

Hyperspectral Imaging↗
DOE OSTI2022

The Fourth Catalog of Active Galactic Nuclei Detected by the Fermi Large Area Telescope: Data Release 3

Abstract An incremental version of the fourth catalog of active galactic nuclei (AGNs) detected by the Fermi Large Area Telescope is presented. This version (4LAC-DR3) derives from the third data release of the 4FGL catalog based on 12 yr of E > 50 MeV gamma-ray data, where the spectral parameters, spectral energy distributions (SEDs), yearly light curves, and associations have been updated for all sources. The new reported AGNs include 587 blazar candidates and four radio galaxies. We describe the properties of the new sample and outline changes affecting the previously published one. We also introduce two new parameters in this release, namely the peak energy of the SED high-energy component and the corresponding flux. These parameters allow an assessment of the Compton dominance, the ratio of the inverse-Compton to the synchrotron-peak luminosities, without relying on X-ray data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

SMAP Data Assimilation at the GMAO

The NASA Soil Moisture Active Passive (SMAP) mission has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. These observations are sensitive to surface(0-5 cm) soil moisture. Several of the key applications targeted by SMAP, however, require knowledge of deeper-layer, root zone (0-100 cm) soil moisture, which is not directly measured by SMAP. The NASA Global Modeling and Assimilation Office (GMAO) contributes to SMAP by providing Level 4 data, including the Level 4 Surface and Root Zone Soil Moisture(L4_SM) product, which is based on the assimilation of SMAP Tb observations in the ensemble-based NASA GEOS-5 land surface data assimilation system. The L4_SM product offers global data every three hours at 9 km resolution, thereby interpolating and extrapolating the coarser- scale (40 km) SMAP observations in time and in space (both horizontally and vertically). Since October 31, 2015, beta-version L4_SM data have been available to the public from the National Snow and Ice Data Center for the period March 31, 2015, to near present, with a mean latency of approx. 2.5 days.

Land Surface Model↗
NASA NTRS2019

GeneLab: A Systems Biology Platform for Omics Analysis

NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). The GeneLab Data Systems (GLDS) version 4.0 will be available on October 1st 2019, and will provide the latest in terms of professional state-of-the-art bioinformatics platform for the space biology and radiation community to upload their data into an omics data commons, to process their data with vetted standard workflows and to compare to existing analyses. Started in 2015 as a repository designed to archive omics data from space experiments, GeneLab has expanded its scope to all ionizing radiation omics experiments conducted on the ground and has put considerable effort in providing carefully characterized radiation metadata on all dataset. GeneLab is also providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome) to help users explore important questions: 1) Which genes or proteins are expressed differently in space for various living organisms? 2) What specific DNA mutations or epigenetic changes happen in space or after exposure to ionizing radiation? and 3) How does genetics affect these responses? Processed data available on GeneLab are derived by standard data analysis workflows vetted by hundreds of scientists who volunteered to join one of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). In this presentation, we will discuss how to bridge the gap between irradiation studies performed on earth and biological experiments conducted in space since the early 1990's. We will discuss how radiation dosimetry was estimated for datasets derived from samples collected during the Space Shuttle era or on the International Space Station. Finally, we will address future strategies regarding dose monitoring in future missions into space, inter-agency efforts to unify data under one umbrella, and knowledge dissemination across the radiation research community and the space biology community.

open-science↗
DOE OSTI2026

The ENDF/B Nuclear Data Library and Its Impact on Reactor Simulations

The ENDF/B library, which is developed, maintained, and distributed by the Cross Section Evaluation Working Group, is the main source of nuclear data for analyses and computational simulations in nuclear applications, like different nuclear reactors concepts, radiation shielding, medical applications, astrophysics, etc. The library is constantly being improved and updated, with each release bringing an optimal representation of nuclear interactions as they are understood in their time. The most recent release, ENDF/B-VIII.1, represents a significant improvement in terms of the performance and consistency of the measured differential data relative to previous versions, as it combines the most recent experimental differential data and advanced theoretical nuclear models. As one of the many highlights, ENDF/B-VIII.1 restores a high-burnup depletion performance, comparable to ENDF/B-VII.1, that had been degraded in ENDF/B-VIII.0, while further improving the performance in criticality benchmarks, such as those in the Mosteller’s suite. Additionally noteworthy is the improved performance of ENDF/B-VIII.1 in radiation shielding and thick-target leakage spectrum integral experiments, which are also important for fusion and reactor applications. In this work we present in a very summarized way the main updates implemented in the ENDF/B-VIII.1 release and its main impacts, and also begin to delineate the path forward as to what to expect in the future for the next ENDF/B release, which, based on the timeline of the past few releases, is estimated to happen around 5 years from now. We emphasize that the ENDF/B-VIII.1 release was the product of an enormous collaborative effort among many authors and that for a complete detailed picture, the reader is strongly encouraged to refer to the article accompanying the release, which is currently in the publication process, but available as preprint [G. P. A. Nobre et al. arXiv Preprint arXiv: 2511.03564 (2025)].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Hyper Suprime-Cam Legacy Archive

Abstract We present the launch of the Hyper Suprime-Cam Legacy Archive (HSCLA), a public archive of processed, science-ready data from the Hyper Suprime-Cam (HSC). HSC is an optical wide-field imager installed at the prime focus of the Subaru Telescope and has been in operation since 2014. While ∼1/3 of the total observing time of HSC has been used for the Subaru Strategic Program (SSP), the remainder of the time is used for Principal Investigator (PI)-based programs. We have processed the data from these PI-based programs and make the processed, high-quality data available to the community through HSCLA. The current version of HSCLA includes data taken in the first year of science operation, 2014. We provide both individual and coadd images as well as photometric catalogs. The photometric catalog from the coadd is loaded to the database, which offers a fast access to the large catalog. There are other online tools such as an image browser and an image cutout tool and they will be useful for science analyses. The coadd images reach 24–27th magnitudes at 5σ for point sources and cover approximately 580 square degrees in at least one filter with 150 million objects in total. We perform extensive quality assurance tests and verify that the photometric and astrometric quality of the data is good enough for most scientific explorations. However, the data are not without problems and users are referred to the list of known issues before exploiting the data for science. All the data and documentations can be found at the data release site, 〈https://hscla.mtk.nao.ac.jp/〉.

Tanaka, Masayuki↗
NASA NTRS2013

Infrared Spectra and Optical Constants of Astronomical Ices: I. Amorphous and Crystalline Acetylene

Here we report recent measurements on acetylene (C2H2) ices at temperatures applicable to the outer Solar System and the interstellar medium. New near- and mid-infrared data, including optical constants (n, k), absorption coefficients (alpha), and absolute band strengths (A), are presented for both amorphous and crystalline phases of C2H2 that exist below 70 K. Comparisons are made to earlier work. Electronic versions of the data are made available, as is a computer routine to use our reported n and k values to simulate the observed IR spectra. Suggestions are given for the use of the data and a comparison to a spectrum of Makemake is made.

IR spectroscopy↗
NASA NTRS2015

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set.

GEOS-5↗