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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Time-Evolving Chirality Loss in Molecular Photodissociation Monitored by X-ray Circular Dichroism Spectroscopy

In this work, the ultrafast photoinduced chirality loss of 2-iodobutane is studied theoretically by time- and frequency-resolved X-ray circular dichroism (TRXCD) spectroscopy. Following an optical excitation, the iodine atom dissociates from the chiral center, which we capture by quantum non-adiabatic molecular dynamics simulations. At variable time delays after the pump, the resonant X-ray pulse selectively probes the iodine and carbon atom involved in the chiral dissociation through a selected core-to-valence transition. The TRXCD signal at the iodine L 1 edge accurately captures the timing of C–I photodissociation and thereby chirality loss, c.a 70 fs. The strong electric dipole–electric quadrupole (ED–EQ) response makes this signal particularly sensitive to vibronic coherence at the high X-ray regime. At the carbon K-edges, the signals monitor the molecular chirality of the 2-butyl radical photoproduct and the spin state of the iodine atom. The ED–EQ response is masked under the strong electric dipole-magnetic dipole response, making this signal intuitive for the electronic population. The evolution of the core electronic states and its chiral sensitivity is discussed. Overall, the element-specific TRXCD signal provides a detailed picture of molecular dynamics and offers a unique sensitive window into the time-dependent chirality of molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Crystallographic Evidence of Size-Dependent Bond Flexibility in Metal–Organic Framework Nanocrystals

Size-dependent electronic, magnetic, and optical behavior suggests that metal–organic frameworks become softer materials as their particle sizes decrease, but direct evidence is lacking. Here, we report variable-temperature powder X-ray diffraction data of Fe(1,2,3-triazolate)2 particles that offer crystallographic insight into size-dependent bond flexibility. Rietveld refinement reveals size-dependent positive thermal expansion upon downsizing the crystalline domains from 178 to 9 nm, with a 6-fold increase from 16 MK –1 to 96 MK –1 . Here, this behavior occurs in tandem with size-dependent elongation of metal–ligand bonds and increasing thermal displacement parameters, consistent with pronounced metal-linker bond lability. We propose that these effects, as well as size-dependent annealing of crystallite sizes, originate from the high charge density and surface stress of smaller particles. Taken together, these results provide structural evidence that size reduction serves as a synthetic route to controlling the dynamic response of materials to external stimuli.

Crystals↗
DOE OSTI2020

Search for heavy Higgs bosons decaying to a top quark pair in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search is presented for additional scalar (H) or pseudoscalar (A) Higgs bosons decaying to a top quark pair in proton-proton collisions at a center-of-mass energy of 13 TeV. The data set analyzed corresponds to an integrated luminosity of 35.9 fb$^{-1}$ collected by the CMS experiment at the LHC. Final states with one or two charged leptons are considered. The invariant mass of the reconstructed top quark pair system and variables that are sensitive to the spin of the particles decaying into the top quark pair are used to search for signatures of the H or A bosons. The interference with the standard model top quark pair background is taken into account. A moderate signal-like deviation compatible with an A boson with a mass of 400 GeV is observed with a global significance of 1.9 standard deviations. New stringent constraints are reported on the strength of the coupling of the hypothetical bosons to the top quark, with the mass of the bosons ranging from 400 to 750 GeV and their total relative width from 0.5 to 25%. The results of the search are also interpreted in a minimal supersymmetric standard model scenario. Values of $m_\mathrm{A}$ from 400 to 700 GeV are probed, and a region with values of $\tan\beta$ below 1.0 to 1.5, depending on $m_\mathrm{A}$, is excluded at 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Feasibility of measuring the speed of sound of the quark-gluon plasma from the multiplicity and mean 𝑝 𝑇 of ultracentral heavy-ion collisions

The mean transverse momentum ⟨𝑝 𝑇 ⟩ of hadrons has been observed experimentally and in numerical simulations to have a power-law dependence on the hadronic multiplicity 𝑁 in ultracentral relativistic heavy-ion collisions: ⟨𝑝 𝑇 ⟩∝𝑁 𝑏 UC . It has been put forward that this exponent 𝑏 UC is the speed of sound of quark-gluon plasma measured at a temperature determined from ⟨𝑝 𝑇 ⟩. We study step by step the connection between (i) the energy and entropy of hydrodynamic simulations and (ii) experimentally measurable observables. We show that an argument based on energy and entropy should yield an exponent equal to the pressure over energy density 𝑃/ɛ, rather than the speed of sound 𝑐$_s^2$; however, we also observe that ⟨𝑝 𝑇 ⟩ and 𝑁 are not sufficiently accurate proxies for the energy and entropy to make this possible in practice. From simulations, we find that the exponent 𝑏 UC is significantly different whether the “effective volume” is strictly constant or not, a condition that cannot be enforced experimentally. Additional tests using a modified equation of state find that the exponent 𝑏 UC exhibits a variable degree of correlations with the speed of sound and with 𝑃/ɛ, but is not an accurate measurement of either quantity in general.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Variational AutoEncoders Reveal Intensifying GPP Extremes in Continental United States based on CESM2 Simulations

Climate extremes significantly impact terrestrial carbon cycle dynamics, necessitating robust methods for detecting and analyzing anomalous behavior in plant productivity. This study presents a novel application of variational autoencoders (VAE) for identifying extreme events in gross primary productivity (GPP) from Community Earth System Model version 2 simulations across four AR6 regions in the Continental United States. We compare VAE-based anomaly detection with traditional singular spectral analysis (SSA) methods across three time periods: 1850-80, 1950-80, and 2050-80 under SSP5-8.5 scenario. The VAE architecture employs three dense layers and a latent space with input sequence length of 12 months, training on normalized GPP time series to reconstruct the GPP and identify anomalies based on reconstruction errors. Extreme events are defined using 5th percentile thresholds applied to both VAE and SSA anomalies. Results demonstrate strong regional agreement between VAE and SSA methods in spatial patterns of extreme event frequencies, despite VAE consistently producing higher threshold values (179-756 GgC for VAE vs. 100-784 GgC for SSA across regions and periods). Both methods reveal increasing magnitudes and frequencies of negative carbon cycle extremes toward 2050-80, particularly in Western and Central North America. The VAE approach shows comparable performance to established SSA techniques while offering computational advantages and enhanced capability for capturing non-linear temporal dependencies in carbon cycle variability. This research demonstrates the potential of deep learning approaches for extremes detection and provides a foundation for improved understanding of future carbon cycle risks under future conditions.

Sharma, Bharat [ORNL] (ORCID:0000000266982487)↗
DOE OSTI2025

Improved Weld Residual Stress Modeling System in BlackBear

This report presents enhancements to the MOOSE-based BlackBear application aimed at improving its capability to simulate welding and other thermo-mechanical manufacturing processes. Two primary avenues of improvement are pursued. First, to enhance user accessibility, we introduce a centralized default block restriction mechanism that ensures coverage checks are performed within user-specified default blocks. This default setting is applied consistently to all block-describable objects, such as variables, kernels, and more. In addition, we develop a modular action for moving heat source simulations, which integrates path file parsing, subdomain modification, and heat source kernel enforcement into a single, streamlined configuration. Second, to improve solver robustness, we implement an alternative method for assigning initial conditions to the updated active domain during the simulation, thereby enhancing convergence behavior. To validate the framework, we design and conduct several benchmark simulations, including heat conduction with progressive material addition, linear elasticity with time-dependent material deposition, and viscoplasticity model with isotropic hardening under similar conditions. Finally, we demonstrate the effectiveness of the proposed framework through large-scale thermo-mechanical welding simulations in both two and three dimensions.

42 ENGINEERING↗
DOE OSTI2025

Optical vibrational spectroscopic signatures of ammonium diuranate process parameters

Ammonium diuranate (ADU) is commonly encountered in the nuclear fuel cycle; however, previous investigations have shown that ADU is a complex mixture of distinct compounds. Moreover, production parameters are known to heavily influence the composition of the resulting ADU. Here, we examine four samples of ADU prepared at Oak Ridge National Laboratory (ORNL), and one sample of ADU made at Pacific Northwest National Laboratory (PNNL), with the goal of further characterizing and elucidating the effect of processing parameters such as stir rate, strike direction, and temperature on material composition. Process parameters during ADU precipitation at ORNL and PNNL were well documented, and we relate process variables to optical vibrational spectroscopic signatures observed using Raman and infrared (IR) spectroscopy. In addition, powder X-ray diffraction (PXRD) reveals differences in the solid-phase composition of ADU precipitates, but we find that the primary phase is similar to the uranyl oxyhydroxyhydrate mineral metaschoepite. Despite the significant phase contributions of a metaschoepite-like phase, spectroscopic evidence of both nitrate and ammonium are observed for all samples. To gain a more holistic understanding of spectroscopic features of process parameters in ADU, principal component analysis (PCA) is employed and results in observable signatures that relate to the stir rate used during synthesis. These results provide further information about the process-dependence of ADU precipitate composition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Tropical High Cloud Feedback Relationships to Climate Sensitivity

Clouds constitute a large portion of uncertainty in predictions of equilibrium climate sensitivity (ECS). While low cloud feedbacks have been the focus of intermodel studies due to their high variability among global climate models, tropical high cloud feedbacks also exhibit considerable uncertainty. Here, we apply the cloud radiative kernel technique of Zelinka et al. to 22 models across the CMIP5 and CMIP6 ensembles to survey tropical high cloud feedbacks and analyze their relationship to ECS. We find that the net high cloud feedback and its altitude and optical depth feedback components are significantly positively correlated with ECS in the tropical mean. On the other hand, the tropical mean high cloud amount feedback is not correlated with ECS. These relationships are most pronounced outside of areas of strong climatological ascent, suggesting the importance of thin cirrus feedbacks. Finally, we explore connections between high cloud feedbacks, climate sensitivity, and mean state high cloud properties. In general, high ECS models are cloudier in the upper troposphere but have a thinner high cloud population. Furthermore, we find that having more thin cirrus in the mean state relates to more positive high cloud altitude and optical depth feedbacks, and it either amplifies or dampens the high cloud amount feedback depending on the large-scale dynamical regime (amplifying in descent and dampening in ascent). In summary, our analysis highlights the importance of tropical high cloud feedbacks for driving intermodel spread in ECS and suggests that mean state high cloud characteristics might provide a unique opportunity for observationally constraining high cloud feedbacks.

atmosphere↗
DOE OSTI2025

Aerosol Influences on Cloud Water: Insights From ARM EPCAPE Observations With Explainable Machine Learning

This study employs an explainable machine learning (ML) framework (XGBoost-SHapley Additive exPlanations analysis) to investigate controlling factors on cloud liquid water path (LWP) using EPCAPE observations near the California coast. Aerosols are found to be the dominant factor explaining LWP variability, surpassing meteorological factors (MFs). By isolating aerosol effects from meteorological influences, the ML reveals a negative linear relationship between LWP and cloud droplet number concentration (Nd) in log space, likely driven by entrainment drying via evaporation-entrainment feedback. This aligns with the negative regime of the inverted-V relationship reported in previous studies, while no positive LWP responses are found due to a limited number of precipitating cases in EPCAPE. Furthermore, the sensitivity of LWP to Nd shows a non-linear dependence on MFs like moisture contrast between surface and free troposphere and lower-tropospheric stability. This occurs due to the interplay between the MFs' direct effects on entrainment drying and indirect effects through LWP adjustments.

EPCAPE observations↗
DOE OSTI2026

SPRUCE Soil Volumetric Water Content in Experimental Plots, Marcell Experimental Forest, Minnesota, 2017-2025

This dataset contains soil volumetric water content (VWC) measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) Experiment. Measurements were made inside SPRUCE experimental plots in the S1 Bog at the US Forest Service Marcell Experimental Forest in northern Minnesota, USA from 2018-2025 (2018-06-14 to 2025-12-31). Observations were made with METER 10HS soil moisture sensors. To reduce bulk density related variability, 10HS sensors were placed inside mesh tubes filled with peat at a standard bulk density. The observations under standard bulk density represent relative differences in water content between hummock and hollow positions, and in response to experimental treatments. Productivity of peatlands, and their keystone species sphagnum, are highly dependent on water availability, which is affected by lateral inputs, precipitation, ground water depth and evapotranspiration. Knowledge of near surface and sphagnum water content is useful to understand peatland function. This dataset contains 8 data files in comma-separate values (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗
DOE OSTI2025

Simulating Isotropic Rayleigh Wave Horizontal to Vertical Ratios at Rock Valley

Elastic anisotropy in the subsurface can manifest from pre-existing structure or stress-induced cracking – both phenomena are of interest at the Rock Valley site in Nevada. The azimuthal dependence of Rayleigh wave ellipticity, also known as H/V, can reveal elastic anisotropy, but the effect of isotropic variability in H/V must first be accounted for. To that end, we simulate synthetic seismograms from a ring of sources in a fully 3-D isotropic velocity model that captures the geology at Rock Valley. We measure H/V from these waveforms and compare them with H/V predictions obtained using 1D models extracted at specific locations from the 3D model. We find that an average of the azimuthal H/V measurements from the 3-D simulations and 1-D predictions agree, but that the azimuthal variability of H/V is a large fraction of the mean value. These results estimate the noise character in azimuthal H/V so it can be factored out of future anisotropic simulations.

58 GEOSCIENCES↗
DOE OSTI2021

Pipe Parity Analysis of Seawater Desalination in the United States: Exploring Costs, Energy, and Reliability via Case Studies and Scenarios of Emerging Technology

As climate change-induced variables exacerbate water scarcities, the use of seawater reverse osmosis (SWRO) membrane desalination technology for treating seawater could potentially provide a long-term drought-proof source of drinking water. This study carried out a technoeconomic assessment (TEA) for three SWRO desalination plants in the U.S. and one in Israel to set baselines for the cost and energy consumption for seawater desalination. In addition, a breakeven curve for implementing SWRO desalination was estimated in relation to the cost of water conservation measures to meet drought-induced reduction of the traditional water supply. The results show that the cost of SWRO water production scales with the plant capacity while energy intensity is not dramatically different across the plants. The higher cost in some U.S. plants is due to high capital investment, including land acquisition and permitting. Variations in plant capacity utilization have the greatest impact on the levelized cost of water (LCOW) over the plant service life, suggesting the importance of reducing fouling and maintenance-related downtime. Scenario analysis of fixed labor cost reduction through process automation indicates investments in automation and sensing technology could result in long-term savings. Breakeven analysis shows the decision to adopt SWRO is highly dependent on the local cost associated with water conservation to meet water supply reduction. Moreover, a small reduction in SWRO cost can influence a shift toward the adoption of SWRO over water conservation measures. Incorporation of future water demand, water conservation potential, and water stress data around the nation indicates SWRO desalination could be an important contributor to the future municipal drinking water portfolio in the U.S.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Qubit Assignment Using Time Reversal

As quantum computers with large numbers of qubits become increasingly available, experiments executed on a given device may not utilize all available qubits. In this case, the outcome of executing a quantum program will depend on the ability to efficiently select a subset of high-performing physical qubits. For any given quantum program and device there are many ways to assign physical qubits for execution of the program, and assignments will differ in performance due to the variability in quality across qubits and entangling operations on a single device. Evaluating the performance of each assignment using fidelity estimation introduces significant experimental overhead and will be infeasible for many applications, while relying on standard device benchmarks provides incomplete information about the performance of any specific program. Furthermore, the number of possible assignments grows combinatorially in the number of qubits on the device and in the program, motivating the use of heuristic optimization techniques. We demonstrate a practical solution to the problem of qubit assignment by using simulated annealing with a cost function based on the Loschmidt echo, a diagnostic that measures the reversibility of a quantum process. We provide theoretical justification for this choice of cost function by demonstrating that the optimal qubit assignment coincides with the optimal qubit assignment based on state fidelity in the weak error limit, and we provide experimental justification using diagnostics performed on Google’s superconducting qubit devices. We then establish the performance of simulated annealing for qubit assignment using classical simulations of noisy devices as well as optimization experiments performed on a quantum processor. Our results demonstrate that the use of Loschmidt echoes and simulated annealing provides a scalable and flexible approach to optimizing qubit assignment on near-term hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Stakeholder Support for Wildlife Conservation Funding Policies

State wildlife management agencies in the United States have depended on a “user-pay” funding model for conservation efforts that relies on revenue from hunting license sales and a federal excise tax on firearms, ammunition, and archery equipment. Declines in hunting participation, however, jeopardize sustainability of the current funding model. Ensuring support among stakeholders for wildlife management and conservation may require expanding sources of funding and incorporating the perspectives and values of a diversifying constituency into decision making processes. We used a web-based survey of wildlife-associated recreationists in Michigan, USA to evaluate support for a range of conservation funding policies. Respondents self-identified primarily as hunters (n = 2,558) or wildlife watchers (n = 942). We used binary logistic regression to evaluate support for four conservation funding policy options: state sales tax, lottery proceeds, extractive industry revenue, and a user-based tax on outdoor gear (i.e., “backpack tax”). Determinants of support varied by type of policy and stakeholder characteristics. We found no statistically significant differences between hunters and wildlife watchers in their support for conservation funding policies when accounting for other variables such as wildlife value orientations, engagement in stewardship behaviors, age, and gender. The industry-based policy achieved the greatest level of approval, while the backpack tax had the lowest. Respondents were mixed in their support of the sales tax and lottery proceeds options. Cluster analysis revealed three homogenous groups related to conservation funding policies: “strong support,” “mixed/opposed,” and “anti-backpack tax.” Clusters differed in their support for conservation funding policies and on psychological and demographic variables. The “strong support” and “anti-backpack tax” groups differed in their levels of stewardship engagement, knowledge of conservation funding mechanisms, and support for the backpack tax option. The “mixed-opposed” group tended to be older, less educated, and less likely to be a member of a conservation organization. Results suggest support for conservation funding differs by policy type and social and psychological characteristics of stakeholders. Based on differences in policy support revealed in this study, we suggest a multi-tiered approach to funding conservation and building on support among wildlife stakeholders to mitigate the looming funding crisis for state wildlife agencies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Synthesizing land use and demographic change in Southeast Asia’s smaller urbanized areas from 2000–2015

The majority of the human population now reside in urban areas today. The United Nations estimates that nearly half of all urban dwellers currently live in cities smaller than 500 000 persons and the majority of future urban growth will take place in Asia and Africa, likely in these smaller urban areas, not mega cities. Thus, understanding the factors that influence urban demographic trajectories in small urban areas is critical to address sustainable and equitable policy initiatives related to food security, changing climate hazard exposure, and economic opportunities. Here we focus on Southeast Asia—a region historically characterized by lower urban population proportions, yet with a rapidly shifting dynamic demographic—to examine correlates of demographic change among smaller cities. We combine two open-source satellite-informed datasets: GHS urban center database (2015) and age-sex gridded data from WorldPop to calculate socio-demographic characteristics to model drivers of change in annualized urban population growth from 2000–2015 for 505 urbanized places. We find a general pattern of decreasing dependency ratios as city-size increases for most urban areas in Southeast Asia. Higher rates of growth and more variation is observed for smaller cities—those with fewer than 300 000 persons, the lowest population limit for UN data on urbanization. When examining covariates of urban population growth, we find significant statistical associations of population change in smaller urbanized areas with climatic, economic, and land cover/land use variables, but with country-specific variations. Characterizing a continuum of urban population development in the context of changing environmental, economic and climate conditions has been an important sustainable development and equity issue for decades, but newer analysis of city-level drivers allows for systematic inquiry thus moving beyond total population counts for policy-relevant insight.

Southeast Asia synthesis↗
DOE OSTI2026

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗
DOE OSTI2026

Unlocking plant-microbial interactions in deep Mollisols in the Midwestern US: Linking depth gradients in roots, microbial activity, and soil carbon in agroecosystems

Deep-rooted plants may build soil carbon (C) stocks, but most research has focused on shallow soils, leaving gaps in our understanding of how shifts in the balance between decomposition and C inputs drive soil C accumulation with depth. Thus, our objectives were to: (1) link depth gradients in root biomass with microbial activity and soil C stocks down to 1 m, and (2) examine the potential of simple C inputs to prime soil C across depths. To this end, we dug 5 quantitative soil pits in Argiudolls under mature perennial miscanthus plots in the SoyFACE Farm (Champaign-Urbana, IL). We added 13 C labeled glucose to our soils to determine the fate of simple C inputs with depth. We found that fine root biomass, total soil C, mineral-associated organic C (MAOC), particulate organic C (POC), and microbial activity (as measured by potential enzyme activity) declined with depth. POC declined more rapidly than MAOC, resulting in an increase in the ratio of MAOC-to-POC. Root biomass, enzyme activity (either acid phosphatase or n-acetyl-glucosaminadase) activity, and microbial respiration explained 74% and 38% of the variability in soil total C and MAOC, respectively, while POC was dependent on root biomass and microbial respiration (47%). Although the incorporation of simple 13 C inputs into MAOC was similar across depths, these inputs led to greater net MAOC losses in shallow soils than in deeper soils between 50 and 100 cm. The divergent impact of simple C inputs across depths may suggest that MAOC in shallow soils is more susceptible to priming losses, while C inputs into deep soils may instead be more persistent. Collectively, our results suggest that depth gradients in soil C stocks represents a balance between inputs, decomposition, and microbial necromass production and that increases in root C inputs by deep-rooted plants may have the potential to build stable MAOC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability

Snow plays a critical role in carbon cycling, vegetation dynamics, and permafrost hydrology at high latitudes by influencing surface energy exchange. Predicting snow distribution patterns is essential for understanding the evolution of Arctic ecosystems, yet scaling process-level knowledge to landscape predictions remains challenging. Here, we analyze snow depth (2019 and 2022), terrain elevation, and vegetation height from a watershed on the Seward Peninsula, Alaska, to examine how topography and shrubs shape snow redistribution across spatial scales. We find that snow depth is strongly coupled to terrain at scales below ∼60 m but becomes increasingly decoupled at larger scales. The topographic model of snow depth variation, which transforms terrain data to align with these scale-dependent snow patterns, is well correlated with local snow depth variations (linear fit R 2 > 0.5 for 85% of 100-m patches). A machine learning reconstruction of shrub canopy snow trapping reveals a simple exponential relationship between canopy structure and snow accumulation ( R 2 = 0.59), highlighting the combined influence of topography and vegetation on snow distribution. Together, these empirical relationships capture much of the observed snow variability in the watershed ( R 2 = 0.49, root mean square error (RMSE) = 30 cm), though systematic limitations persist in areas of strong scour and at coarser scales where wind-terrain interactions are more complex. These findings provide a framework for more efficient snow depth prediction and offer insights to improve snow-vegetation feedback representation in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗