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At least 37 records · Page 2

Caffeine v0.1.0

Caffeine is the CoArray Fortran Framework of Efficient Interfaces to Network Environments. Caffeine aims to produce a parallel runtime library that will support Fortran compilers with a programming-model-agnostic application binary interface (ABI) to various lower-level communication libraries. The current version of Caffeine uses the GASNet-EX networking middleware, also developed at Berkeley Lab. On many combinations of applications and platforms, GASNet-EX outperforms the widely used Message Passing Interface (MPI). Through GASNet-EX's support for communicating between graphics processing units (GPU), GASNet-EX has features that specifically target the emerging, leading-edge exascale computing platforms.

Rouson, Damian↗

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 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↗

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↗

The DUNE Far Detector Vertical Drift Technology. Technical Design Report

DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on a near and a far detector as it aims to determine the neutrino mass hierarchy and to make high-precision measurements of the PMNS matrix parameters, including the CP-violating phase. It will also stand ready to observe supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines the many tens-of-kiloton fiducial mass necessary for rare event searches with the sub-centimeter spatial resolution required to image those events with high precision. The addition of a photon detection system enhances physics capabilities for all DUNE physics drivers and opens prospects for further physics explorations. Given its size, the far detector will be implemented as a set of modules, with LArTPC designs that differ from one another as newer technologies arise. In the vertical drift LArTPC design, a horizontal cathode bisects the detector, creating two stacked drift volumes in which ionization charges drift towards anodes at either the top or bottom. The anodes are composed of perforated PCB layers with conductive strips, enabling reconstruction in 3D. Light-trap-style photon detection modules are placed both on the cryostat's side walls and on the central cathode where they are optically powered. This Technical Design Report describes in detail the technical implementations of each subsystem of this LArTPC that, together with the other far detector modules and the near detector, will enable DUNE to achieve its physics goals.

47 OTHER INSTRUMENTATION↗

DUNE Phase II: scientific opportunities, detector concepts, technological solutions

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a “Module of Opportunity”, aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

59 BASIC BIOLOGICAL SCIENCES↗

A New Electrode Paradigm Enabled by Co-Axial Electrospinning

A conventional electrode in a polymer electrolyte membrane fuel cell (PEMFC) often imposes competing requirements on the ionomer, which must enable efficient proton conduction while allowing sufficient oxygen transport. To address these material-level requirements, a co-axial electrospun electrode comprising of a pristine ionomer core and a multifunctional platinum-carbon-ionomer shell is introduced. By decoupling proton and oxygen transport pathways, this architecture enables independent tailoring of core and shell chemistries and their interfaces. The core-shell structure of the electrospun fibers is confirmed by microscopy, while electrochemical and transport properties are quantified using electrochemical impedance spectroscopy and limiting-current diagnostics. The co-axial fibers in their current version meet or exceed the performance of conventional ultrasonically sprayed electrode at relative humidities above 75%, enabled by improvements in non-Fickian diffusion processes. This work establishes co-axial electrospun electrodes as a versatile platform for advanced PEMFC electrodes and a wide range of electrochemical applications, including CO2 electrolysis, water electrolysis, and critical mineral separations.

08 HYDROGEN↗

Dependence of the kinetic energy absorption capacity of bistable mechanical metamaterials on impactor mass and velocity

Using an alternative mechanism to dissipation or scattering, bistable structures and mechanical metamaterials have shown promise for mitigating the detrimental effects of impact by reversibly locking energy into strained material. Herein, we extend prior works on impact absorption via bistable metamaterials to computationally explore the dependence of kinetic energy transmission on the velocity and mass of the impactor, with strain rates exceeding 10 2 s –1 . We observe a large dependence on both impactor parameters, ranging from significantly better to worse performance than a comparative linear material. We then correlate the variability in performance to solitary wave formation in the system and give analytical estimates of idealized energy absorption capacity under dynamic loading. In addition, we find a significant dependence on damping accompanied by a qualitative difference in solitary wave propagation within the system. The complex dynamics revealed in this study offer potential future guidance for the application of bistable metamaterials to applications including human and engineered system shock and impact protection devices.

42 ENGINEERING↗

Context matters: Natural tree mortality can lead to neighbor growth release or suppression

Where competition suppresses tree growth, mortality of adjacent trees can release the surviving individuals, leading to a growth increase. However, primary forests are complicated systems, where trees interact in both competitive and facilitative ways mediated by their size, species, and the broad ecological context in which they grow. Thus, the magnitude and even direction of growth responses to the mortality of nearby trees may vary, which has implications for our understanding of community- and ecosystem-level dynamics following mortality events. Unfortunately, although many studies focus on the impacts of light availability and general crowding on tree growth, we know relatively little about the effects of naturally occurring mortality events on the growth of neighboring trees. To address this issue, we used 40 years of data from 15 permanent forest-monitoring plots in Mt Rainier old-growth forests, comparing observed to expected radial growth of individual trees following the death of their nearest neighbor. Although we found evidence of a general growth-release response, this was not universal among all trees, with small trees in particular exhibiting growth suppression (rather than release) following neighboring tree mortality. In addition to small size, growth-suppression was more likely if the dead neighbor was the same species, consistent with facilitative effects as mediated through belowground networks. At the stand level, the average growth release after nearest neighbor mortality was greatest in low-density stands with large trees, with elevation and community composition also playing a role. Decades more monitoring could reveal how long growth release (or suppression) is sustained by individual trees following neighboring mortality events, as well as potential response lags and the role of species identity in determining whether interactions with neighbors are competitive or facilitative. Nonetheless, our results suggest that although mature trees have competitive effects on their larger neighbors, they also have an important role in supporting the ingrowth of small trees. More broadly, we demonstrate that the nature of interactions between individual neighboring trees is highly context dependent.

54 ENVIRONMENTAL SCIENCES↗

A PIPS + SrI 2 (Eu) detector for atmospheric radioxenon monitoring

The PIPS–SrI 2 (Eu) is a prototype atmospheric radioxenon detection system designed at Oregon State University in support of international efforts towards monitoring clandestine nuclear weapon testing activities. This detector aims to address some shortcomings found in currently deployed beta–gamma atmospheric radioxenon detection systems, such as lackluster energy resolution and memory effect, by employing modern detection materials and readout. The system uses a PIPSBox, a silicon-based gas cell, for electron detection, and a pair of ultrabright, D-shaped SrI 2 (Eu) scintillators coupled to silicon photomultipliers for photon detection. A custom eight-channel digital pulse processor equipped with a field programmable gate-array (FPGA) identifies electron–photon coincidences between the volumes in near real-time. Gas samples of the four radioxenon isotopes of interest were independently measured with the PIPS–SrI 2 (Eu) detection system to determine energy resolution and efficiency. Application of FPGA-based coincidence discrimination in near real-time reduced the ambient background count rate by 95.85 ± 0.04%. Using parameters from the Xenon International gas processing unit and assuming a blank sample and zero memory effect the minimum detectable concentrations (MDCs) for the isotopes were calculated to be 0.12 ± 0.03, 0.27 ± 0.05, 0.15 ± 0.02, and 1.00 ± 0.08 mBq/m 3 air for 131m Xe, 133 Xe, 133m Xe, and 135 Xe, respectively. These MDC estimates compare well with other radioxenon detection systems employed in the International Monitoring System (IMS) and indicate that the PIPS–SrI 2 (Eu) is in compliance with the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO) sensitivity requirement of ≤ 1 mBq/m 3 for 133 Xe.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗