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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 OSTI2021

Electronic Structure of Metallophthalocyanines, MPc (M = Fe, Co, Ni, Cu, Zn, Mg) and Fluorinated MPc

In this work, we compute the electronic structure and optical excitation energies of metal-free and transition-metal phthalocyanines (H2Pc and MPc for M = Fe, Co, Ni, Cu, Zn, Mg) using density functional theory with optimally tuned range-separated hybrid functionals (OT-RSH). We show that the OT-RSH approach provides photoemission spectra in quantitative agreement with experiments as well as optical band gaps within 10% of their experimental values, capturing the interplay of localized d-states and delocalized pi-pi* states for these organometallic compounds. We examine the tunability of MPcs and H 2 Pc through fluorination, resulting in quasi-rigid shifts of the molecular orbital energies by up to 0.7 eV. Our comprehensive data set provides a new computational benchmark for gas-phase phthalocyanines, significantly improving upon other density-functional-theory-based approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Improved Vertical Carrier Transport for Green III-Nitride LEDs Using ( In , Ga ) N Alloy Quantum Barriers

We report on experimental and simulation-based results using ( In , Ga ) N alloy quantum barriers in c -plane green light-emitting diode (LED) structures as a means to improve vertical carrier transport and reduce forward voltage ( V F ) . Three-dimensional device simulations that include random alloy fluctuations are used to understand carrier behavior in a disordered potential. The simulated current density–voltage ( J - V ) characteristics and modified electron-hole overlap | F mod | 2 indicate that increasing the indium fraction in the ( In , Ga ) N quantum barriers leads to a reduced polarization discontinuity at the interface between the quantum barrier and quantum well, thereby reducing V F and improving | F mod | 2 . Maps of electron and hole current through the device show a relatively homogenous distribution in the X Y plane for structures using Ga N quantum barriers; in contrast, preferential pathways for vertical transport are identified in structures with ( In , Ga ) N barriers as regions of high and low current. A positive correlation between hole (electron) current in the p -side ( n -side) barrier and indium fraction reveals that preferential pathways exist in regions of high indium content. Furthermore, a negative correlation between the strain ε z z and indium fraction shows that high indium content regions have reduced strain-induced piezoelectric polarization in the Z direction due to the mechanical constraint of the surrounding lower indium content regions. Experimentally, multiple quantum well green LEDs with ( In , Ga ) N quantum barriers exhibit lower V F and blue-shifted wavelengths relative to LEDs with Ga N quantum barriers, consistent with simulation data. These results can be used to inform heterostructure design of low V F , long-wavelength LEDs and provide important insight into the nature of carrier transport in III-nitride alloy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Using Pulsar Parameter Drifts to Detect Subnanohertz Gravitational Waves

Gravitational waves with frequencies below 1 nHz are notoriously difficult to detect. With periods exceeding current experimental lifetimes, they induce slow drifts in observables rather than periodic correlations. Observables with well-known intrinsic contributions provide a means to probe this regime. In this Letter, we demonstrate the viability of using observed pulsar timing parameters to discover such “ultralow” frequency gravitational waves, presenting two complementary observables for which the systematic shift induced by ultralow-frequency gravitational waves can be extracted. Using existing data for these parameters, we search the ultralow-frequency regime for continuous-wave signals, finding a sensitivity near the expected prediction from inspirals of supermassive black holes. We do not see an excess in the data, setting a limit on the strain of 1.3 × 10 –12 at 450 pHz with a sensitivity dropping approximately quadratically with frequency until 10 pHz. Finally, our search method opens a new frequency range for gravitational wave detection and has profound implications for astrophysics, cosmology, and particle physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Electronic Scanning Strategies in Adaptive Electrical Capacitance Volume Tomography: Tradeoffs and Prospects

Electrical Capacitance Volume Tomography (ECVT) has been applied for imaging of multiphase flows found in industrial applications. The ill-posed nature of the image reconstruction problem in ECVT and the consequent low resolution can be alleviated by employing electronic scanning enabled by electrode segmentation and reconfiguration during data acquisition. Here we study electronic scanning strategies that mimic physical rotation and shifting of the sensor along its symmetry axis. First, we study the feasibility of electronic scanning by analyzing the capacitance transducer circuit in SPICE. Then, we simulate electronic scanning using the finite element method for different electrode shapes, for which we compare the image reconstruction results and acquisition time. We find a noticeable improvement in image resolution for the scanning cases over conventional ECVT. Lastly, among the scanning cases, we emphasize a particular electrode shape that provides the best image resolution along with the minimal amount of acquisition time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Electrification Options for Multi-Family Water Heating in Cold Climates - Final Report

In multi-family buildings, large water storage tanks in centralized domestic hot water (DHW) systems can serve as thermal energy storage (TES) batteries to mitigate grid impact. These systems offer demand shift and efficiency benefits, significantly reducing peak power consumption, particularly in cold climates. This study evaluates the load-shifting benefits of a centralized heat pump water heater (HPWH) system equipped with a CO2 heat pump in multi-family buildings through simulation. The heat pump system and water storage tank are sized using design-day sizing. A finite-element-based stratified tank model and CO2 heat pump performance map from a commercial DHW product are used. Annual simulations are conducted to assess the benefits of the centralized DHW system for energy efficiency improvements, load shifting, and emission reductions. These simulations incorporate utility tariffs and marginal grid emission data from Los Angeles and Chicago. In Los Angeles, using a water tank as a thermal battery achieves 7.4% utility cost savings and 10.2% emission reduction. In Chicago, compared to HPWH conventional operation without preheating, TES-enabled central HPWH provides 15% utility cost savings and 13% emission reduction. The case study demonstrates that the demand reduction potential of central CO2 HPWHs is significant in cold climate regions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances

Abstract A spectral-energy distribution (SED) model for Type Ia supernovae (SNe Ia) is a critical tool for measuring precise and accurate distances across a large redshift range and constraining cosmological parameters. We present an improved model framework, SALT3, which has several advantages over current models—including the leading SALT2 model (SALT2.4). While SALT3 has a similar philosophy, it differs from SALT2 by having improved estimation of uncertainties, better separation of color and light-curve stretch, and a publicly available training code. We present the application of our training method on a cross-calibrated compilation of 1083 SNe with 1207 spectra. Our compilation is 2.5× larger than the SALT2 training sample and has greatly reduced calibration uncertainties. The resulting trained SALT3.K21 model has an extended wavelength range 2000–11,000 Å (1800 Å redder) and reduced uncertainties compared to SALT2, enabling accurate use of low- z I and iz photometric bands. Including these previously discarded bands, SALT3.K21 reduces the Hubble scatter of the low- z Foundation and CfA3 samples by 15% and 10%, respectively. To check for potential systematic uncertainties, we compare distances of low (0.01 < z < 0.2) and high (0.4 < z < 0.6) redshift SNe in the training compilation, finding an insignificant 3 ± 14 mmag shift between SALT2.4 and SALT3.K21. While the SALT3.K21 model was trained on optical data, our method can be used to build a model for rest-frame NIR samples from the Roman Space Telescope. Our open-source training code, public training data, model, and documentation are available at https://saltshaker.readthedocs.io/en/latest/ , and the model is integrated into the sncosmo and SNANA software packages.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Cold Climate Integrated Heat Pump with Energy Storage for Grid-Responsive Control

An air-source integrated heat pump (ASIHP) is a multifunctional unit, capable of space cooling, space heating, and water heating. We developed a packaged cold climate ASIHP, using a multi-stage compressor, capable of working down to -25°C, and providing 100% rated capacity down to -15°C with a heating COP > 2.2. An innovative system configuration and related controls were developed to solve charge balance in the integrated heat pump, smooth charge migration, and mode transition among multiple working modes. Extensive laboratory investigations for individual modes were performed to verify the performance. Its integrated heating capability provides speedy water heating to meet domestic hot water use and store heating energy in a phase change material ceiling/panel. The heating energy storage can be used to shift the load when the electricity price is high. Based on the performance data and a calibrated model from the laboratory testing, we conducted building energy simulations driven by a model predictive control, using EnergyPlus in one U.S. cold climate zone to investigate the grid-responsive control strategy and estimate the utility cost reduction potential.

Shen, Bo↗
DOE OSTI2022

Data from: "Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers"

This archive contains data used to draw conclusions in “Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers”, by Kueppers et al. 2017. Cone collection and field experiments were conducted on Niwot Ridge, Colorado, with the latter completed within the Alpine Treeline Warming Experiment (ATWE). Laboratory germination experiments were conducted at the University of California Merced. Geospatial files are also provided for additional geographical context.There are four data file formats in this package: comma-separated values (.csv), Microsoft Excel (.xlsx), keyhole markup language (.kml), and ESRI shapefile (.shp). The latter two are geospatial file formats. .csv files can be opened using any simple text editor program such as TextEdit (Mac) and Notepad (Windows), and .xlsx files can be opened using Microsoft Excel or Google Sheets. The .kml file contains coordinate data, and is compatible with Google Earth and Google Maps. ESRI shapefiles (.shp) are compatible with any geospatial software able to read the file type, such as QGIS and ESRI’s ArcGIS Suite. This data user’s guide is available in as a .pdf, and can be opened using software such as Adobe Acrobat Reader.-----------------------------------------------------------------------------------------------------------------------------------Accurately predicting upslope shifts in subalpine tree ranges with warming requires understanding how future forest populations will be affected by climate change, as these are the seed sources for new tree line and alpine populations. Early life history stages are particularly sensitive to climate and are also influenced by genetic variation among populations. We tested the climate sensitivity of germination and initial development for two widely distributed subalpine conifers, using controlled-environment growth chambers with one temperature regime from subalpine forest in the Colorado Rocky Mountains and one 5 °C warmer, and two soil moisture levels. We tracked germination rate and timing, rate of seedling development, and seedling morphology for two seed provenances separated by ~300 m elevation. Warming advanced germination timing and initial seedling development by a total of ~2 weeks, advances comparable to mean differences between provenances. Advances were similar for both provenances and species; however, warming reduced the overall germination rate, as did low soil moisture, only for Picea engelmannii. A three-year field warming and watering experiment planted with the same species and provenances yielded responses qualitatively consistent with the lab trials. Together these experiments indicate that in a warmer, drier climate, P. engelmannii germination, and thus regeneration, could decline, which could lead to declining subalpine forest populations, while Pinus flexilis forest populations could remain robust as a seed source for upslope range shifts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

PFLOTRAN-SIP: A PFLOTRAN Module for Simulating Spectral-Induced Polarization of Electrical Impedance Data

Spectral induced polarization (SIP) is a non-intrusive geophysical method that collects chargeability information (the ability of a material to retain charge) in the time domain or its phase shift in the frequency domain. Although SIP is a temporal method, it cannot measure the dynamics of flow and solute/species transport in the subsurface over long times (i.e., 10–100 s of years). Data collected with the SIP technique need to be coupled with fluid flow and reactive-transport models in order to capture long-term dynamics. To address this challenge, PFLOTRAN-SIP was built to couple SIP data to fluid flow and solute transport processes. Specifically, this framework couples the subsurface flow and transport simulator PFLOTRAN and geoelectrical simulator E4D without sacrificing computational performance. PFLOTRAN solves the coupled flow and solute-transport process models in order to estimate solute concentrations, which were used in Archie’s model to compute bulk electrical conductivities at near-zero frequency. These bulk electrical conductivities were modified while using the Cole–Cole model to account for frequency dependence. Using the estimated frequency-dependent bulk conductivities, E4D simulated the real and complex electrical potential signals for selected frequencies for SIP. These frequency-dependent bulk conductivities contain information that is relevant to geochemical changes in the system. This study demonstrated that the PFLOTRAN-SIP framework is able to detect the presence of a tracer in the subsurface. SIP offers a significant benefit over ERT in the form of greater information content. It provided multiple datasets at different frequencies that better constrained the tracer distribution in the subsurface. Consequently, this framework allows for practitioners of environmental hydrogeophysics and biogeophysics to monitor the subsurface with improved resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Preliminary Assessment for the Electric Load Shifting Potential of Integrating Thermal Energy Storage with Heat Pumps in Residential Buildings in Texas of United States

The widespread adoption of electric-driven heat pumps for heating and cooling is expected to significantly increase electric demand. Cooling electric demand will result in an increase in peak hours electric loads, placing additional strain on the grid during peak hours. This challenge, combined with the current rapidly increasing demand from data centers, exacerbates the electric demand duck curve problem. Integrating thermal energy storage (TES) with heat pump can shift electric use for heating and cooling from peak to off-peak hours of the electric grid, which can help flatten the daily electric demand profile of a building. This paper presents a novel design that integrates heat pump with TES (HP-TES), which uses phase change materials (PCM). Heat pump charges TES by melting or freezing PCM during off-peak hours when there is no thermal demand from the building. TES is then discharged (i.e., by freezing or melting PCM) during peak hours to provide a more favorable heat source or heat sink for the heat pump to meet the thermal demand of the building with lower electricity use than conventional air-source heat pumps. Computer simulations were developed to predict the performance of HP-TES applied to a typical single-family house in the US. The building-level simulation results were scaled up to preliminarily assess the aggregated impacts of deploying HP-TES across all single-family houses in Texas of the United States, including reduction of peak demand of the electric grid.

Anees, Fady [ORNL]↗
DOE OSTI2026

Extensive analysis of reconstruction algorithms for DESI 2024 baryon acoustic oscillations

Reconstruction of the baryon acoustic oscillation (BAO) signal has been a standard procedure in BAO analyses over the past decade and has helped to improve the BAO parameter precision by a factor of ∼2 on average. The Dark Energy Spectroscopic Instrument (DESI) BAO analysis for the first year (DR1) data uses the “standard” reconstruction framework, in which the displacement field is estimated from the observed density field by solving the linearized continuity equation in redshift space, and galaxy and random positions are shifted in order to partially remove non-linearities. There are several approaches to solving for the displacement field in real survey data, including the multigrid (MG), iterative Fast Fourier Transform (iFFT), and iterative Fast Fourier Transform particle (iFFTP) algorithms. In this work, we analyze these algorithms and compare them with various metrics including two-point statistics and the displacement itself using realistic DESI mocks. We focus on three representative DESI samples, the emission line galaxies (ELG), quasars (QSO), and the bright galaxy sample (BGS), which cover the extreme redshifts and number densities, and potential wide-angle effects. We conclude that the MG and iFFT algorithms agree within 0.4% in post-reconstruction power spectrum on BAO scales with the RecSym convention, which does not remove large-scale redshift space distortions (RSDs), in all three tracers. The RecSym convention appears to be less sensitive to displacement errors than the RecIso convention, which attempts to remove large-scale RSDs. However, iFFTP deviates from the first two; thus, we recommend against using iFFTP without further development. In addition, we provide the optimal settings for reconstruction for five years of DESI observation. The analyses presented in this work pave the way for DESI DR1 analysis as well as future BAO analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Influence of Tall Fescue Epichloë Endophytes on Rhizosphere Soil Microbiome

Tall fescue (Lolium arundinaceum (Schreb.) S.J. Darbyshire) often forms a symbiotic relationship with fungal endophytes (Epichloë coenophiala), which provides increased plant performance and greater tolerance to environmental stress compared to endophyte-free tall fescue. Whether this enhanced performance of tall fescue exclusively results from the grass–fungus symbiosis, or this symbiosis additionally results in the recruitment of soil microbes in the rhizosphere that in turn promote plant growth, remain a question. We investigated the soil bacterial and fungal community composition in iron-rich soil in the southeastern USA, and possible community shifts in soil microbial populations based on endophyte infection in tall fescue by analyzing the 16s rRNA gene and ITS specific region. Our data revealed that plant-available phosphorus (P) was significantly (p < 0.05) influenced by endophyte infection in tall fescue. While the prominent soil bacterial phyla were similar, a clear fungal community shift was observed between endophyte-infected (E+) and endophyte-free (E−) tall fescue soil at the phylum level. Moreover, compared to E− soil, E+ soil showed a greater fungal diversity at the genus level. Our results, thus, indicate a possible three-way interaction between tall fescue, fungal endophyte, and soil fungal communities resulting in improved tall fescue performance.

Mahmud, Kishan↗
DOE OSTI2025

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗
DOE OSTI2022

Recent progress in L-H transition studies at JET: Tritium, Helium, Hydrogen and Deuterium

In this report we present an overview of results from a series of L-H transition experiments undertaken at JET since the installation of the ITER-like-wall (JET-ILW), with Beryllium wall tiles and a Tungsten divertor. Tritium, Helium and Deuterium plasmas have been investigated. Initial results in Tritium show ohmic L-H transitions at low density and the power threshold for the L-H transition (P LH ) is lower in Tritium plasmas than in Deuterium ones at low densities, while we still lack contrasted data to provide a scaling at high densities. In Helium plasmas there is a notable shift of the density at which the power threshold is minimum (n e,min ) to higher values relative to Deuterium and Hydrogen references. Above n e,min (He) the L-H power threshold at high densities is similar for D and He plasmas. Transport modelling in slab geometry shows that in Helium neoclassical transport competes with interchange-driven transport, unlike in Hydrogen isotopes. Measurements of the radial electric field in Deuterium plasmas show that E r shear is not a good indicator of proximity to the L-H transition. Transport analysis of ion heat flux in Deuterium plasmas show a non-linearity as density is decreased below n e,min . Lastly, a regression of the JET-ILW Deuterium data is compared to the 2008 ITPA scaling law.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Impact of Increased Latent Generations on Sensitivity Calculations with SCALE

Analyses of cross section sensitivity data from systems with fissile material allow analysts to associate an importance for each material, nuclide, reaction, and neutron energy by simulating real world criticality scenarios. Although criticality safety validation efforts can be guided by the cross-section sensitivity and uncertainty data generated for a particular system, these calculations can often be computationally expensive and sometimes cumbersome without proper guidance. The TSUNAMI suite within the SCALE code package has several methods for generating sensitivity data, including multigroup and continuous energy (CE) capabilities. The release of SCALE 6.3 has three different CE methods for generating cross section sensitivity data: (1) the Iterated Fission Probability (IFP) method with the KENO Monte Carlo transport solver, (2) the IFP method with the Shift Monte Carlo transport solver, and (3) the Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method with the KENO Monte Carlo transport solver. Although the CLUTCH method has additional parameters for generating sensitivity data files relative to the IFP method, all three methods use latent generations, which are the generations between an event (i.e., fission) and the assessment of importance based on the asymptotic population of progeny neutrons. Increasing the number of latent generations in a calculation leads to increased discrimination of the sensitivity coefficients but at the cost of the increased uncertainty associated with those generated values. Analysts must balance the accuracy of the sensitivity calculations and its uncertainty with the associated computational cost involved in generating the values. This paper discusses the impact of adjusting the latent generation parameter for a range of sensitivity values and how these changes compare with the direct perturbation values obtained from a change of ±0.5% Δ k in both benchmark and safety application models. Two benchmarks from the International Handbook of Evaluated Criticality Safety Benchmark Experiments and the MPC-32 dual purpose canister for spent nuclear fuel are used for analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Efficient prediction of concentrating solar power plant productivity using data clustering

Concentrating solar power (CSP) plants convert solar energy to electricity and can be deployed with a thermal storage capability to shift electricity generation from time periods with available solar resource to those with high electricity demand or electricity price. Rigorous optimization of plant design and operational strategies can improve the market-competitiveness and commercial viability; however, such optimization may require hundreds of annual performance simulations, each of which can be computationally expensive when including considerations such as optimization of dispatch scheduling, sub-hourly time resolution, and stochastic effects due to uncertain weather or electricity price forecasts. This paper proposes a methodology to reduce the computational burden associated with simulation of electricity yield and revenue for CSP plants over a single- or multi-year period. Data-clustering techniques are employed to select a small number of limited-duration time blocks for simulation that, when appropriately weighted, can reproduce generation and revenue over a single year or within each year of a multi-year period. After selection of appropriate data features and weighting factors defining similarity between time-series profiles, the methodology captured annual revenue within 2.3%, 1.7%, or 1.2% using simulation of 10, 30, or 50 three-day exemplar time blocks, respectively, for each of three single-year location/weather/market scenarios and five plant configurations ranging from low to high solar multiple and storage capacity. When applied to multi-year datasets, the proposed methodology can capture inter-year variability that is unavailable from typical meteorological year (TMY) datasets while simultaneously requiring simulation of less than a single year of data.

14 SOLAR ENERGY↗
DOE OSTI2022

Benchmarking Demand Flexibility in Commercial Buildings and Flattening the Duck – Addressing Baseline and Commissioning Challenges

With the transition from our traditional electric grid to a cleaner grid with renewable power generation, there is a need to enable building loads to be flexible. Load shedding and shifting will be essential for flattening the “Duck” for decarbonization. This paper explored the trend in the timing of DR events as a reflection of the grid’s needs using recent four years of event data from 203 retail stores in 11 states. The events are becoming significantly shorter with 2-hour duration being the most popular; shifting to late afternoon and early evening is another trend beyond California. Benchmarking will be essential for accounting DF as a reliable grid resource. This paper addresses a challenging aspect of benchmarking – inaccuracies in counterfactual baseline methods can introduce significant DF metrics variations in addition to weather and building characteristics related factors. The conventional “10/10” with adjustment baseline method has inherent limitation by design for load shifting applications. Therefore, it is imperative to identify alternative methods. This study compared three hourly regression baseline methods with “10/10” methods using two groups of commercial buildings that participated in DR programs: (1) 121 big-box retail stores, and (2) 11 office buildings in CA. The 14-day hourly outdoor temperature regression method was found to produce least error in the tested datasets and is promising for load shifting. The paper also pointed out that commissioning issues can also be a significant barrier for achieving consistent DF performance, which building managers and utilities should be aware of.

Liu, Jingjing↗
DOE OSTI2020

Permafrost thermal conditions are sensitive to shifts in snow timing

Abstract Changes in snow precipitation at high latitudes can significantly affect permafrost thermal conditions and thaw depth, potentially exposing more carbon-laden soil to microbial decomposition. A fully coupled process-based surface/subsurface thermal hydrology model with surface energy balance is used to analyze the impact of intra-annual variability in snow on permafrost thermal regime and the active layer thickness. In the four numerical scenarios considered, simulations were forced by the same meteorological data, except the snow precipitation, which was systematically altered to change timing of snowfall. The scenarios represent subtle shifts in snow timing, but the snow onset/melt days, the end of winter snowpack depth, and total annual snow precipitation are unchanged among scenarios. The simulations show that small shifts in the timing of snow accumulation can have significant effects on subsurface thermal conditions leading to active layer deepening and even talik formation when snowfall arrives earlier in the winter. The shifts in snow timing have a stronger impact on wetter regions, especially soil underneath small ponds, as compared to drained regions. This study highlights the importance of understanding potential changes in winter precipitation patterns for reliable projections of active-layer thickness in a changing Arctic climate.

54 ENVIRONMENTAL SCIENCES↗