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At least 109 records · Page 6

infrastore [SWR-26-077]

Infrastore is time-series storage for energy-systems simulations, backed by HDF5 + SQLite, with Rust, Python, Julia, gRPC, and CLI bindings. It is a Rust library for managing time-series data in power-systems and energy simulations. Numerical arrays are persisted in HDF5, and the metadata associating each array with its owning component lives in SQLite. Identical arrays are stored once and shared through content addressing. It ships native Rust, Python (PyO3), and Julia (C ABI) interfaces, the infrastore command-line tool, and a read-only gRPC server with a Rust client. Documentation: https://natlabrockies.github.io/infrastore/latest/ — start with the Quick Start or the Architecture.

Thom, Daniel [National Laboratory of the Rockies (↗

Integrating LEO and GEO Observations: Toward Optimal Summertime Satellite Precipitation Retrieval

Abstract Reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for understanding the Earth’s hydrological cycle. Precipitation estimation over land and coastal regions is necessary for addressing the high degree of spatial heterogeneity of water availability and demand, and for resolving the extremes that modulate and amplify hazards such as flooding and landslides. Advancements in computation power along with unique high spatiotemporal and spectral resolution data streams from passive meteorological sensors aboard geosynchronous Earth-orbiting (GEO) and low Earth-orbiting (LEO) satellites offer exciting opportunities to retrieve information about surface precipitation phenomena using data-driven machine learning techniques. In this study, the capabilities of U-Net–like architecture are investigated to map instantaneous, summertime surface precipitation intensity at the spatial resolution of 2 km. The calibrated brightness temperature products from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) radiometer are combined with multispectral images (visible, near-infrared, and infrared bands) from the Advanced Baseline Imager (ABI) aboard the GOES-R satellites as main inputs to the U-Net–like precipitation algorithm. Total precipitable water and 2-m temperature from the Global Forecast System (GFS) model are also used as auxiliary inputs to the model. The results show that the U-Net–like algorithm can capture fine-scale patterns and intensity of surface precipitation at high spatial resolution over stratiform and convective precipitation regimes. The evaluations reveal the potential of extracting relevant, high spatial features over complex surface types such as mountainous regions and coastlines. The algorithm allows users to interpret the inputs’ importance and can serve as a starting point for further exploration of precipitation systems within the field of hydrometeorology.

Meteorology & Atmospheric Sciences↗

AmeriFlux US-xNW NEON Niwot Ridge Mountain Research Station (NIWO)

This is the AmeriFlux version of the carbon flux data for the site US-xNW NEON Niwot Ridge Mountain Research Station (NIWO). Site Description - The Niwot Ridge sits approximately 27 km west of Boulder, Colorado, and 6 km east of the Continental Divide. Topography, climate, and biota of the site are representative of Rocky Mountain alpine ecosystems, including extensive alpine tundra (mostly herbs, some shrubs and scree) and subalpine coniferous forests (Abies lasciocarpa and Picea engelmanii at higher elevations), talus slopes, wetlands and a variety of glacial landforms. Characterized by cold and relatively long winters, Niwot Ridge has an average annual temperature of 1.5°C and average annual precipitation of 800 mm. Most precipitation falls as snow and summer precipitation falls primarily during afternoon thunderstorms. Located on the eastern side of the Continental Divide at 3,000-3,500 m elevation, the site best captures chemical inputs produced along the Front Range and is well situated to observe other east/west flows across the Southern Rockies in conjunction with other NEON sites.

Network), NEON (National Ecological Observatory↗

AmeriFlux FLUXNET-1F CA-Gro Ontario - Groundhog River, Boreal Mixedwood Forest

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-Gro Ontario - Groundhog River, Boreal Mixedwood Forest. This is the FLUXNET version of the carbon flux data for the site CA-Gro Ontario - Groundhog River, Boreal Mixedwood Forest produced by applying the standard ONEFlux (1F) software. Site Description - Groundhog River (FCRN or CCP site "ON-OMW") is situated in a typical boreal mixedwood forest in northeastern Ontario (48.217 degrees north and 82.156 degrees west) about 80 km southwest of Timmins in Reeves Twp. near the Groundhog River. Rowe (1972) places the site in the Missinaibi-Cabonga Section of the Boreal Forest Region. In terms of ecoregion and ecozone, the site is in the Lake Timiskaming Lowlands of the Boreal Shield. The forest developed after high-grade logging in the 1930's. The average age in 2013 is estimated at beteen 75 and 80 years. The forest is dominated by five species characteristic of Ontario boreal mixedwoods: trembling aspen (Populus tremuloides Michx.), black spruce (Picea mariana (Mill.) B.S.P.), white spruce (Picea glauca (Moench.) Voss.), white birch (Betula papyrifera Marsh.), and balsam fir (Abies balsamea (L.) Mill.). The surficial geology is a lacustrine deposit of varved or massive clays, silts and silty sands. The soil is an orthic gleysol with a soil moisture regime classified as fresh to very fresh. Plonski (1974) rates it as a site class 1. The topography is simple and flat with an overall elevation of 340 m ASL.

McCaughey, Harry↗

AmeriFlux FLUXNET-1F US-xNW NEON Niwot Ridge Mountain Research Station (NIWO)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xNW NEON Niwot Ridge Mountain Research Station (NIWO). This is the FLUXNET version of the carbon flux data for the site US-xNW NEON Niwot Ridge Mountain Research Station (NIWO) produced by applying the standard ONEFlux (1F) software. Site Description - The Niwot Ridge sits approximately 27 km west of Boulder, Colorado, and 6 km east of the Continental Divide. Topography, climate, and biota of the site are representative of Rocky Mountain alpine ecosystems, including extensive alpine tundra (mostly herbs, some shrubs and scree) and subalpine coniferous forests (Abies lasciocarpa and Picea engelmanii at higher elevations), talus slopes, wetlands and a variety of glacial landforms. Characterized by cold and relatively long winters, Niwot Ridge has an average annual temperature of 1.5°C and average annual precipitation of 800 mm. Most precipitation falls as snow and summer precipitation falls primarily during afternoon thunderstorms. Located on the eastern side of the Continental Divide at 3,000-3,500 m elevation, the site best captures chemical inputs produced along the Front Range and is well situated to observe other east/west flows across the Southern Rockies in conjunction with other NEON sites.

Network), NEON (National Ecological Observatory [N↗

Local limits of detection for anthropogenic aerosol-cloud interactions

Ship tracks are quasi-linear cloud patterns produced from the interaction of ship emissions with low boundary layer clouds. They are visible throughout the diurnal cycle in satellite images from space-borne assets like the Advanced Baseline Imagers (ABI) aboard the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellites (GOES-R). However, complex atmospheric dynamics often make it difficult to identify and characterize the formation and evolution of tracks. Ship tracks have the potential to increase a cloud's albedo and reduce the impact of global warming. Thus, it is important to study these patterns to better understand the complex atmospheric interactions between aerosols and clouds to improve our climate models, and examine the efficacy of climate interventions, such as marine cloud brightening. Over the course of this 3-year project, we have developed novel data-driven techniques that advance our ability to assess the effects of ship emissions on marine environments and the risks of future marine cloud brightening efforts. The three main innovative technical contributions we will document here are a method to track aerosol injections using optical flow, a stochastic simulation model for track formations and an automated detection algorithm for efficient identification of ship tracks in large datasets.

54 ENVIRONMENTAL SCIENCES↗

Project report for year 1

In the first year of the project, we developed a fire event tracking system using active fire detections recorded by the Visible Infrared Imaging Radiometer Suite (VIIRS). We employed this algorithm to track all large fires that occurred in California from 2013 to 2020, and created a retrospective Fire Event Data Suite (FEDS) that contains the vector shapes of fire perimeters, active fire fronts, and the locations and fire radiative powers for each fire pixel at 12-hour temporal resolution for each fire event. Using the 2020 Creek Fire as a test bed, we also delineated hourly fire perimeters by combining the FEDS data with the hourly rates of spread derived from Geostationary Operational Environmental Satellite (GOES) Advanced Baseline Imager (ABI) fire data. This dataset will form the basis of the near-real-time hourly fire emissions product that we plan to develop at years 2 and 3 of the project.

54 ENVIRONMENTAL SCIENCES↗

BUILD: Binary Understanding and Integration Logic for Dependencies (Final Report)

Increasingly diverse mission needs, the emergence of AI and cloud, and increasing hardware diversity are driving HPC software to be more complex. Modern codes are built from hundreds of small, complex components, and much of the software development process involves integrating these components rather than developing new components from scratch. The goal of the BUILD project was to ease the task of software integration for developers across LLNL’s programs. The project focused on (1) modeling software compatibility, (2) modeling ABI compatibility with binary analysis, (3) developing solver techniques to reason about compatibility, and (4) developing AI/ML models to fill gaps in our understanding of software compatibility. The project has developed several key technologies that help developers—by accelerating development workflows, removing the need for rebuilds, and enabling faster, automatic, and less error-prone code sharing. These technologies are used in LLNL codes and will be ready for the new El Capitan Exascale system in Livermore Computing. Many of these technologies have been hardened and integrated with LLNL’s Spack package manager, and they are already in use by production code teams. Results of BUILD have laid the groundwork for future advances in software integration—the ML and binary modification techniques developed in this project still need to be operationalized but have great potential to further speed up software integration.

97 MATHEMATICS AND COMPUTING↗

Radical Coupling Reactions of Hydroxystilbene Glucosides and Coniferyl Alcohol: A Density Functional Theory Study

The monolignols, p-coumaryl, coniferyl, and sinapyl alcohol, arise from the general phenylpropanoid biosynthetic pathway. Increasingly, however, authentic lignin monomers derived from outside this process are being identified and found to be fully incorporated into the lignin polymer. Among them, hydroxystilbene glucosides, which are produced through a hybrid process that combines the phenylpropanoid and acetate/malonate pathways, have been experimentally detected in the bark lignin of Norway spruce (Picea abies). Several interunit linkages have been identified and proposed to occur through homo-coupling of the hydroxystilbene glucosides and their cross-coupling with coniferyl alcohol. In the current work, the thermodynamics of these coupling modes and subsequent rearomatization reactions have been evaluated by the application of density functional theory (DFT) calculations. The objective of this paper is to determine favorable coupling and cross-coupling modes to help explain the experimental observations and attempt to predict other favorable pathways that might be further elucidated via in vitro polymerization aided by synthetic models and detailed structural studies.

59 BASIC BIOLOGICAL SCIENCES↗

A semi-Lagrangian method for detecting and tracking deep convective clouds in geostationary satellite observations

Automated methods for the detection and tracking of deep convective clouds in geostationary satellite imagery have a vital role in both the forecasting of severe storms and research into their behaviour. Studying the interactions and feedbacks between multiple deep convective clouds (DCC), however, poses a challenge for existing algorithms due to the necessary compromise between false detection and missed detection errors. We utilise an optical flow method to determine the motion of deep convective clouds in GOES-16 ABI imagery in order to construct a semi-Lagrangian framework for the motion of the cloud field, independently of the detection and tracking of cloud objects. The semi-Lagrangian framework allows severe storms to be simultaneously detected and tracked in both spatial and temporal dimensions. For the purpose of this framework we have developed a novel Lagrangian convolution method and a number of novel implementations of morphological image operations that account for the motion of observed objects. These novel methods allow the accurate extension of computer vision techniques to the temporal domain for moving objects such as DCCs. By combining this framework with existing methods for detecting DCCs (including detection of growing cores through cloud top cooling and detection of anvil clouds using brightness temperature), we show that the novel framework enables reductions in errors due to both false and missed detections compared to any of the individual methods, reducing the need to compromise when compared with existing frameworks. The novel framework enables the continuous tracking of anvil clouds associated with detected deep convection after convective activity has stopped, enabling the study of the entire life cycle of DCCs and their associated anvils. Furthermore, we expect this framework to be applicable to a wide range of cases including the detection and tracking of low-level clouds and other atmospheric phenomena. In addition, this framework may be used to combine observations from multiple sources, including satellite observations, weather radar and reanalysis model data.

54 ENVIRONMENTAL SCIENCES↗

Subsets of geostationary satellite data over international observing network sites for studying the diurnal dynamics of energy, carbon, and water cycles

The latest generation of geostationary satellites provide Earth observations similar to widely used polar-orbiting sensors but at intervals as frequently as every 5–10 min, making them ideal for studying the diurnal dynamics of land–atmosphere interactions. The NASA Earth Exchange (NEX) group created the GeoNEX datasets by collating data from several geostationary platforms, including GOES-16/17/18, Himawari-8/9, and GK-2A, and placing them on a common grid to facilitate use by the Earth science community. Here, we document the GeoNEX Coincident Ground Observations (GeCGO) dataset for terrestrial ecosystem studies and provide examples for its use. Currently, GeCGO provides GOES-16 Advanced Baseline Imager (ABI) data over a 10 km × 10 km area surrounding 1586 network sites across the Americas. GeCGO makes it easy to compare the time series of geostationary data with the diurnal ground observations, including carbon/water fluxes and aerosol optical depth, and is extensible to other regions. We also develop GeoNEXTools to facilitate analyses that require both GeoNEX data and other NASA satellite data. The objectives of this paper are to introduce GeCGO and GeoNEXTools and demonstrate their applications. First, we describe the details of GeCGO and GeoNEXTools. Second, we explain how GeCGO can be integrated with other satellite data. Finally, we showcase comparisons between GeCGO and observations from three ground-based networks. GeCGO is available at https://doi.org/10.25966/y5pe-xp41 (Hashimoto et al., 2025).

Hashimoto, Hirofumi [NASA Ames Research Center (AR↗

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

A declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. The way that tree water demands respond to this change will have important impacts on forest health and downstream water subsidies. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common tree species (Picea engelmannii, Abies lasiocarpa and Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpack but high summer rainfall amounts of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to interannual spring snowpack variability. The trees that increased water use during the year with the large spring snowpack were all found in dense canopy stands – irrespective of species – while trees in open-canopy stands were more reliant on summer rains and, thus, more active during the years with modest snow and higher summer rain amounts. Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow. Interception of summer rain in dense stands reduces the throughfall of summer rain to surface soils, limiting the sensitivity of the dense stands to changes in summer rain. Shading in dense stands allows the snowpack to persist deeper into the growing season, providing high local reliance on snow during the fore-summer (early-summer) drought period. Combining data generated from natural gradients in stand density, like this experiment, with results from controlled forest-thinning experiments can be used to develop a better understanding of the responses of forested ecosystems to futures with reduced spring snowpack.

54 ENVIRONMENTAL SCIENCES↗

JANTX/N98B Zener diode

Tested diodes were manufactured aby Motorola and Siemens. Both sample lots performed well in groups 1 and 3 testing. Group 2 testing was most detrimental of three groups. Extreme heat was big factor in failure mode.

Source record↗

Sun angle, view angle, and background effects on spectral response of simulated balsam fir canopies

An experiment is described that examines the effects of solar zenith angle and background reflectance on the composite scene reflectance of small balsam fir (Abies balsamea (L.) Mill.) arranged in different densities. In this study, the shape, density, and, consequently, the needle area index and phytomass of the canopies, as well as the background reflectance, were controlled. The effects of sun angle, view angle, and background reflectance on the multispectral response of small balsam fir trees were significant. Regression models relating spectral vegetation indices (i.e., normalized difference (ND) and greenness (GR) to phytomass) showed very poor relationships for balsam fir canopies with a grass background. However, strong linear relationships were found for ND and GR with phytomass for a background that simulated the reflectance of snow. Changing solar zenith angle significantly affected the models relating ND to phytomass for the snow background, but was not significant in the model relating GR to phytomass for the snow background

Ranson, K. J.↗

C-band microwave scattering from small balsam fir

An experiment to examine the C-band backscattering characteristics of conifer trees was conducted using a truck-mounted scatterometer. Small (1 m tall) balsam fir (Abies balsamea) were arranged at various equidistant spacings on a platform to present canopies of varying density to the radar. C-band backscattering measurements of a range of canopy densities were acquired under different polarizations and incidence angles. The measured backscattering coefficient from the tree canopies increased with increasing biomass, but approached a maximum at a LAI of 2.5 and fresh biomass of 3.3 kg/sq m. A backscatter model was implemented using measured canopy attributes and showed close agreement with scatterometer measurements over the range of canopy densities. Model results indicated that branches were the prime scatterers of the radar while needles were found to only slightly attenuate the radar signal.

Ranson, K. J.↗

Surveying Dead Trees and CO2-Induced Stressed Trees Using AVIRIS in the Long Valley Caldera

Since 1980 the Long Valley Caldera in the eastern Sierra Nevada (California) has shown signs of renewed volcanic activity. Frequent earthquakes, a re-inflation of the caldera, hydrothermal activity and gas emissions are the outer symptoms of this renewed activity. In 1990 and 1991 several areas of dying trees were found around Mammoth Mountain. The cause of the die off of the trees was first sought in the persistent drought in the preceding years. However, the trees died regardless of age and species. Farrar et al. (1995) started a soil-gas survey in 1994 in the dead-tree areas and found carbon dioxide concentrations ranging from 30 to 96% at soil depths between 30 and 60 cm. CO2 concentrations in the atmosphere are usually around 0.03% and in the soil profile CO2 levels do commonly not exceed 4 to 5%. Although not much is known about the effect of high levels of carbon dioxide in the soil profile on roots, it is most likely that the trees are dying due to oxygen deprivation: the CO2 drives the oxygen out of the soil. So far, four sites of dead trees have been mapped around Mammoth Mountain. The two largest dying trees sites are located near Horseshoe Lake and near Mammoth Mountain Main Lodge covering approximately an area of 10 and 8 ha respectively. Analysis of the gas composition regarding the He-3/He-4 ratio and the percentage biogenic carbon reveals the source of the gas: the magma body beneath the Long Valley Caldera. Until recently it was not known that volcanoes release abundant carbon dioxide from their flanks as diffuse soil emanations. As a result of the magma gas emission around Mammoth Mountain there is an excellent sequence of dead trees, stressed trees, healthy trees and bare soil surfaces. This research site provides excellent opportunities to: (1) Study the capabilities of imaging spectrometry to map stressed (and dead) pine and fir species; (2) Study methods to separate the vivid vegetation, stressed vegetation and dead vegetation from the soil background of glacial deposits and crystalline rocks. The dead tree areas are located on the flanks of Mammoth Mountain (N:37 deg 37' 45" and W:119 deg 02' 05") at an elevation between 2600 and 3000 meters. The area is covered by an open type of Montane Forest. The dominant tree species are Lodgepole Pine (Pinus contorta), the Red Fir (Abies magnifica) and the Jeffrey Pine (Pinus jeffreyi). The soil surface near Horseshoe Lake is generally fairly bright. The surface is covered by glacial deposits (till) consisting mainly of weathered granitic rocks.

deJong, Steven M.↗

Late-Glacial to Early Holocene Climate Changes from a Central Appalachians Pollen and Macrofossil Record

A Late-glacial to early Holocene record of pollen, plant macrofossils and charcoal, based on two cores, is presented for Browns Pond in the central Appalachians of Virginia. An AMS radiocarbon chronology defines the timing of moist and cold excursions, superimposed upon the overall warming trend from 14,200 to 7,500 C-14 yr B.P. This site shows cold, moist conditions from approximately 14,200 to 12,700 C-14 yr B.P., with warming at 12,730, 11,280 and 10,050 C-14 yr B.P. A decrease in deciduous broad-leaved tree taxa and Pinus strobus (haploxylon) pollen, simultaneous with a re-expansion of Abies denotes a brief, cold reversal from 12,260 to 12,200 C-14 yr B.P. A second cold reversal, inferred from increases in montane conifers, is centered at 7,500 C-14 yr B.P. The cold reversals at Browns Pond may be synchronous with climate change in Greenland, and northwestern Europe. Warming at 11,280 C-14 yr B.P. shows the complexity of regional climate responses during the Younger Dryas chronozone.

Kneller, Margaret↗

[X-33 Systems]

Lockheed Martin Skunk Works has compiled an Annual Performance Report of the X-33/RLV Program. This report consists of individual reports from all industry team members, as well as NASA team centers. This portion of the report is comprised of a status report of Allied-Signal Aerospace's contribution to the program. The following is a summary of the work reviewed under their portion of the agreement: (1) Communication Systems; (2) Environmental Control Systems- Active Thermal Control System (ATCS), Purge and Vent System, Hydrogen Detection System (HDS), Avionics Bay Inerting System (ABIS), and Flush Air Data System (FADS); (2) Landing Systems; (3) Power Management and Generation Systems; (4) Flight Control Actuation System (FCAS)- Electric Power Control & Distribution System (EPCDS), and Battery Power System (BPS); and (5) Vehicle Management Systems (VMS)- VMS Hardware, VMS Software Development Activities, and System Integration Laboratory (SIL).

Source record↗