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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effects of Site and Magnetic Disorder on the Oxygen Vacancy Formation and Electronic and Optical Properties of La x Sr 1– x CoO 3–δ and SrFe y Co 1– y O 3–δ [plus supplemental information]

Disorder is an inevitable issue in practical applications of perovskites with the A-site occupied by La/Sr and the B-site occupied by Co/Fe. We performed density functional theory calculations to reveal the site and magnetic disorder effect on the oxygen vacancy formation and the electronic and optical properties of La x Sr 1–x CoO 3–δ and SrFe y Co 1–y O 3–δ systems. Generally, site disorder has little influence on the physical properties we studied, while magnetic disorder has a property-dependent effect for La A-site and Fe B-site doping of SrCoO 3 . Compared to ordered ferromagnetic (FM) calculations, disordered paramagnetic (PM) results can better describe the high-temperature behavior of lattice expansion and the multiple spin states of Co ions in La x Sr 1–x CoO 3 . The oxygen vacancy formation energy results show that the magnetic disorder has a more remarkable effect on SrFe y Co 1–y O 3–δ systems with a robust magnetic order than that on the La x Sr 1–x CoO 3–δ systems with a fragile magnetic order. The electronic structures in the PM phase have less spin polarization and broadened bands, by which the optical absorptions from the single spin channel transition in the FM phase have an obvious change in the magnitude and/or the trend. Furthermore, our work provides guidance for where and why to consider the disorder.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Modeling Material Interfaces with the Six-Equation Model in FLEXO

FLEXO is a multiphysics code developed at Sandia National Laboratories for predictive simulation of pulsed power target physics with extended magnetohydrodynamics modeling. Given this application space, FLEXO must be able to perform high-fidelity simulations of pulsed-power systems that include multiple materials. This work presents the augmentation of FLEXO with a six-equation model for multimaterial flow. We design and analyze discretizations of the six-equation model, emphasizing desirable properties for robust multimaterial simulation. We also present solution limiting, bounds preservation, and pressure equilibration/relaxation techniques that enhance the robustness of the overall multimaterial scheme. We present a suite of test problems to document these new capabilities of the FLEXO code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Temperature Measurements in Hypersonic Wind Tunnels via Femtosecond Coherent Anti-Stokes Raman Scattering

A femtosecond coherent anti-Stokes Raman scattering (fs CARS) instrument is developed to perform gas-phase thermometry in cold-flow hypersonic wind tunnels. Measurements are reported for Mach 8 and 14 pure-nitrogen flows. The fs CARS instrument includes a 100 fs pump/Stokes pulse and a spectrally narrow probe pulse from a second harmonic bandwidth compressor. Important experimental considerations such as limits on the pump/Stokes pulse energy are discussed. The fs CARS focusing and collimating optics are mounted on a two-axis translation stage system to scan the measurement location during a 30 second wind tunnel run. Single-laser-shot rotational CARS spectra are recorded at the laser repetition rate of 1 kHz in the wind tunnel freestream and near simple cone models. Spectral fitting is used to determine quantitative gas temperatures. Freestream temperatures at Mach 8 and 14 spanned ranges of 40–75 and 35–50 K, respectively, depending on tunnel operating conditions. Temperature variations across the central 100 mm span of the wind tunnel were quantified. Measured temperature jumps across conical bow shocks from various models varied by less than 1% from predicted values. Hypersonic boundary layer measurements were demonstrated. In conclusion, these measurements illustrate the utility and robustness of this instrument for the study of complex fluid flow phenomena in challenging ground test facilities.

Aerodynamics↗
DOE OSTI2024

Data for Hydrothermal Conditioning of Oleaginous Yeast Cells to Enable Recovery of Lipids as Potential Drop-in Fuel Precursors

Lipids produced using oleaginous yeast cells are an emerging feedstock to manufacture commercially valuable oleochemicals ranging from pharmaceuticals to lipid-derived biofuels. Production of biofuels using oleaginous yeast is a multistep procedure that requires yeast cultivation and harvesting, lipid recovery, and conversion of the lipids to biofuels. The quantitative recovery of the total intracellular lipid from the yeast cells is a critical step during the development of a bioprocess. Their rigid cell walls often make them resistant to lysis. The existing methods include mechanical, chemical, biological and thermochemical lysis of yeast cell walls followed by solvent extraction. In this study, an aqueous thermal pretreatment was explored as a method for lysing the cell wall of the oleaginous yeast Rhodotorula toruloides for lipid recovery. Hydrothermal pretreatment for 60 min at 121 °C with a dry cell weight of 7% (w/v) in the yeast slurry led to a recovery of 84.6 ± 3.2% (w/w) of the total lipids when extracted with organic solvents. The conventional sonication and acid-assisted thermal cell lysis led to a lipid recovery yield of 99.8 ± 0.03% (w/w) and 109.5 ± 1.9% (w/w), respectively. The fatty acid profiles of the hydrothermally pretreated cells and freeze-dried control were similar, suggesting that the thermal lysis of the cells did not degrade the lipids. This work demonstrates that hydrothermal pretreatment of yeast cell slurry at 121 °C for 60 min is a robust and sustainable method for cell conditioning to extract intracellular microbial lipids for biofuel production and provides a baseline for further scale-up and process integration.

Conversion↗
DOE OSTI2020

Multi-omics Characterization of the Host Response to COVID-19

This project is a multi-disciplinary collaboration between investigators at PNNL with expertise in mass spectrometry (MS)-based omics technology development, omics measurement methods development and application, statistics, machine learning and integration of disparate datasets for a systems-level understanding, and expertise in pathogenic coronaviruses, and investigators at the University of Wisconsin-Madison (UW-Madison) with expertise in pathogenic respiratory viruses (e.g. influenza). The goal of this project is to obtain a comprehensive picture of the human host factors critical for the outcome of SARS-CoV-2 infection. We will generate broad untargeted multi-omics profiles using both state-of-the-art and novel instrumentation and approaches to enable the identification of the molecular mechanisms and host response pathways that impact human COVID-19 outcomes. We anticipate these results will lead to the generation of biomarker panels that are predictive of disease outcomes and mechanistic hypotheses that can be further interrogated in future studies and will provide the basis for vaccine or therapeutic development. To do so, we are obtaining and analyzing blood samples from COVID-19 patients with a range of disease outcomes that were treated at the Center Hospital of the National Center for Global Health and Medicine in Tokyo, Japan and other collaborating hospitals in our network. Specifically, this project will fund proteomics and metabolomics analyses of clinical COVID samples, machine learning-based integration of the data, and pathway-based interpretation of the data. This project was funded in June 2020. In the time span of June to September 2020, the project team developed an analytically and statistically robust analysis plan and made various preparations to facilitate sample receipt from our UW-Madison collaborators. This included blocking and randomization of sample prep orders, ordering of reagents and reference materials, and shipping of materials needed for preparation of the samples under BSL3 conditions to our collaborators at UW-Madison. As of FY21, this project has been picked up via a sponsor, the Naval Medical Research Center, which will cover the remainder of the proposed scope of work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

First-Principles Statistical Mechanics Study of Magnetic Fluctuations and Order–Disorder in the Spinel LiNi 0.5 Mn 1.5 O 4 Cathode

While significant magnetic interactions exist in lithium transition metal oxides, commonly used as Li-ion cathodes, the interplay between magnetic couplings, disorder, and redox processes remains poorly understood. In this work, we focus on the high-voltage spinel LiNi 0.5 Mn 1.5 O 4 (LNMO) cathode as a model system on which to apply a computational framework that uses first principles-based statistical mechanics methods to predict the finite temperature magnetic properties of materials and provide insights into the complex interplay between magnetic and chemical degrees of freedom. Density functional theory calculations on multiple distinct Ni–Mn orderings within the LNMO system, including the ordered ground-state structure (space group P4332), reveal a preference for a ferrimagnetic arrangement of the Ni and Mn sublattices due to strong antiferromagnetic superexchange interactions between neighboring Mn 4+ and Ni 2+ ions and ferromagnetic Mn–Mn and Ni–Ni couplings, as revealed by magnetic cluster expansions. These results are consistent with qualitative predictions using the Goodenough-Kanamori-Anderson rules. Simulations of the finite temperature magnetic properties of LNMO are conducted using Metropolis Monte Carlo. We find that a “semiclassical” Monte Carlo sampling method based on the Heisenberg Hamiltonian accurately predicts experimental magnetic transition temperatures observed in magnetometry measurements. This study highlights the importance of a robust computational toolkit that accurately captures the complex chemomagnetic interactions and predicts finite temperature magnetic behavior to help analyze experimental magnetic and magnetic resonance spectroscopy data acquired ex situ and operando.

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

Parametric model-order-reduction development for unsteady convection

A time-averaged error indicator with POD- h Greedy is developed to drive parametric model order reduction (pMOR) for 2D unsteady natural convection in a high-aspect ratio slot parameterized with the Prandtl number, Rayleigh number, and slot angle with respect to the gravity. The error indicator is extended to accommodate the energy equation and Leray regularization. Despite being two-dimensional and laminar, the target flow regime presents several challenges: 1) there is a bifurcation in the angle parameter space; 2) the solution can be multivalued, even at steady state; and 3) the solution exhibits spatio-temporal chaos at several points in the parameter space. The authors explore several reduced-order models (ROMs) and demonstrate that Leray-regularized Galerkin ROMs provide a robust solution approach for this class of flows. They further demonstrate that error-indicated pMOR can efficiently predict several QOIs, such as mean flow, mean Nusselt number and mean turbulent kinetic energy, even in the presence of a bifurcation. Finally, they show that spatio-temporal chaos can lead to lack of reproducibility in both the full-order model and the reduced-order model and that the variance in the full-order model provides a lower bound on the pMOR error in these cases.

leray regularization↗
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Site-Selective Probes of Mixed-Node Metal Organic Frameworks for Photocatalytic Hydrogen Generation

Metal organic frameworks (MOFs) have emerged as a novel platform offering new promise for photocatalytic applications. In this work, we report a mixed-node MOF (MOF-74) based on earth-abundant metals (i.e., Co and Fe) as highly active and robust photocatalysts for visible light-driven H 2 generation. Using in situ X-ray absorption spectroscopy which allows us to selectively probe the individual metal node in MOFs, we unambiguously identified the catalytic active sites and captured the key intermediate species under the standard catalytic conditions. We show that both Co and Fe centers in MOF-74 are the reversible active sites, and the accumulation of their reduced states is responsible for the observed induction period for H 2 generation. Moreover, we captured the key intermediate species formed when the reaction reaches equilibrium, which is featured by an elongated Co–O bond at the Co center and a more distorted octahedral geometry at the Fe center with respect to their original geometry. These results not only demonstrate the potential of MOF-74 as a single site catalyst for H 2 generation but also provide new insight into the catalytic mechanism for further development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hydrothermal conditioning of oleaginous yeast cells to enable recovery of lipids as potential drop-in fuel precursors

Abstract Background Lipids produced using oleaginous yeast cells are an emerging feedstock to manufacture commercially valuable oleochemicals ranging from pharmaceuticals to lipid-derived biofuels. Production of biofuels using oleaginous yeast is a multistep procedure that requires yeast cultivation and harvesting, lipid recovery, and conversion of the lipids to biofuels. The quantitative recovery of the total intracellular lipid from the yeast cells is a critical step during the development of a bioprocess. Their rigid cell walls often make them resistant to lysis. The existing methods include mechanical, chemical, biological and thermochemical lysis of yeast cell walls followed by solvent extraction. In this study, an aqueous thermal pretreatment was explored as a method for lysing the cell wall of the oleaginous yeast Rhodotorula toruloides for lipid recovery. Results Hydrothermal pretreatment for 60 min at 121 °C with a dry cell weight of 7% (w/v) in the yeast slurry led to a recovery of 84.6 ± 3.2% (w/w) of the total lipids when extracted with organic solvents. The conventional sonication and acid-assisted thermal cell lysis led to a lipid recovery yield of 99.8 ± 0.03% (w/w) and 109.5 ± 1.9% (w/w), respectively. The fatty acid profiles of the hydrothermally pretreated cells and freeze-dried control were similar, suggesting that the thermal lysis of the cells did not degrade the lipids. Conclusion This work demonstrates that hydrothermal pretreatment of yeast cell slurry at 121 °C for 60 min is a robust and sustainable method for cell conditioning to extract intracellular microbial lipids for biofuel production and provides a baseline for further scale-up and process integration. Graphical abstract

09 BIOMASS FUELS↗
DOE OSTI2026

Comparative Assessment of Radiological Consequences from Sabotage-Induced Releases in Diverse Microreactor Designs

Many microreactor design developers are planning to reduce on-site physical protection measures and emergency planning zones by relying on robust fuel and reactor designs and leveraging passive safety systems. These reductions raise the risk of sabotage at these microreactors. To evaluate these requirements, this study assessed the radiological consequences of sabotage-induced accidents at microreactors. For the assessment, five diverse designs, each producing 30 MWt, were considered. These designs included pressurized water microreactors (PWMs), sodium-cooled fast microreactors (SFMs), high-temperature helium-cooled prismatic microreactors (HTPMs), heat pipe–cooled microreactors (HPMs), and molten salt–cooled microreactors (MSMs). For each design, two postulated sabotage-induced accidents were defined along with the associated release percentages of fission products. Additionally, consequences from the release of activation products were assessed. With regard to evaluating physical protection and emergency planning requirements, the consequences of sabotage-induced accidents for each design type were found to be comparable. The differences were primarily because of the distinct fuel forms (and associated release mechanisms), burnup, and neutron spectra of the different microreactor types. Future effort will further investigate the release percentages of fission products to perform accurate dose consequence assessment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Accelerated Selectrion of Optimal Perovskite Alloys for Solar PV using a Combined Quantum and Machine Learning Hierachiral Approach

The project aims to: (i) accelerate the discovery of “Missing HP alloys” by combining quantum mechanics and artificial intelligence machine learning approaches, and (ii) analyze the stabilities of candidate alloys, including those that do not pass selection filters (and are thus expected to degrade over time) to decipher the nature of the instabilities to guide the development of durable solar cell materials. Successful candidates will be subjected to validation experiments at NREL's state-of-the-art facilities. The discoveries this effort will provide will be directly testable and implementable and will greatly impact U.S. progress in HP PV as they will provide clear direction and motivation for experimental studies including specific material synthetic targets, device optimization, and device stability protocols. A key advantage of this effort is the feedback and guidance provided by the Industry Collaborative Work Group that we established to coordinate academic and national lab research with industry needs. The proposed work will provide a basis for and direct the development of robust and reliable HP PV. It will also provide a timely, valuable and extensive roadmap to the experimental HP PV community to enable it to focus its efforts on improving and fine-tuning promising HP compositions that this effort predicts will likely be the best performers rather than wandering in the vast chemical space for decades spending enormous resources mostly evaluating unpromising candidate materials.

14 SOLAR ENERGY↗
DOE OSTI2024

Enhancing detection of topological order by local error correction

The exploration of topologically-ordered states of matter is a long-standing goal at the interface of several subfields of the physical sciences. Such states feature intriguing physical properties such as long-range entanglement, emergent gauge fields and non-local correlations, and can aid in realization of scalable fault-tolerant quantum computation. However, these same features also make creation, detection, and characterization of topologically-ordered states particularly challenging. Motivated by recent experimental demonstrations, we introduce a paradigm for quantifying topological states—locally error-corrected decoration (LED)—by combining methods of error correction with ideas of renormalization-group flow. Our approach allows for efficient and robust identification of topological order, and is applicable in the presence of incoherent noise sources, making it particularly suitable for realistic experiments. We demonstrate the power of LED using numerical simulations of the toric code under a variety of perturbations. We subsequently apply it to an experimental realization, providing new insights into a quantum spin liquid created on a Rydberg-atom simulator. Finally, we extend LED to generic topological phases, including those with non-abelian order.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Valley splittings in Si/SiGe quantum dots with a germanium spike in the silicon well

Silicon-germanium heterostructures have successfully hosted quantum dot qubits, but the intrinsic near-degeneracy of the two lowest valley states poses an obstacle to high-fidelity quantum computing. Here we present a modification to the Si/SiGe heterostructure by the inclusion of a spike in germanium concentration within the quantum well in order to increase the valley splitting. The heterostructure is grown by chemical vapor deposition and magnetospectroscopy is performed on gate-defined quantum dots to measure the excited state spectrum. We demonstrate a large and widely tunable valley splitting as a function of applied vertical electric field and lateral dot confinement. We further investigate the role of the germanium spike by means of tight-binding simulations in single-electron dots and show a robust doubling of the valley splitting when the spike is present, as compared to a standard (spike-free) heterostructure. This doubling effect is nearly independent of the electric field, germanium content of the spike, and spike location. This experimental evidence of a stable, tunable quantum dot, despite a drastic change to the heterostructure, provides a foundation for future heterostructure modifications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The coexistence of the streaming instability and the vertical shear instability in protoplanetary disks

The streaming instability is a promising mechanism to induce the formation of planetesimals. Nonetheless, this process has been found in previous studies to require either a dust-to-gas surface density ratio or a dust size that is enhanced compared to observed values. Employing two-dimensional global simulations of protoplanetary disks, we show that the vertical shear instability and the streaming instability in concert can cause dust concentration that is sufficient for planetesimal formation for lower surface density ratios and smaller dust sizes than the streaming instability in isolation, and in particular under conditions that are consistent with observational constraints. This is because dust overdensities forming in pressure bumps induced by the vertical shear instability act as seeds for the streaming instability and are enhanced by it. While our two-dimensional model does not include self-gravity, we find that strong dust clumping and the formation (and dissolution) of gravitationally unstable overdensities can be robustly inferred from the evolution of the maximum or the mean dust-to-gas volume density ratio. The vertical shear instability puffs up the dust layer to an average mid-plane dust-to-gas density ratio that is significantly below unity. We therefore find that reaching a mid-plane density ratio of one is not necessary to trigger planetesimal formation via the streaming instability when it acts in unison with the vertical shear instability.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Progress toward Accelogic compression in ROOT

For the last 7 years, Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom-line outcome will be to provide state-of-the-art compression algorithms --and accompanying software libraries-- able to surpass the performance of the compression engines currently available in the ROOT [7] framework. The resulting technology has the capability to enable substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4 [6].As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility.In this contribution, we will present our efforts integrating our concepts of “functionally lossless compression” within the ROOT framework implementation, with the purpose of producing a basic solution readily integrated into HENP applications. We will also present our progress applying this compression through realistic examples of analysis from both the STAR and CMS experiments.

Canal, Ph.↗
DOE OSTI2023

Probing the Origin of Changing-look Quasar Transitions with Chandra

Extremely variable quasars can also show strong changes in broad-line emission strength and are known as changing-look quasars (CLQs). To study the CLQ transition mechanism, we present a pilot sample of CLQs with X-ray observations in both the bright and faint states. From a sample of quasars with bright-state archival SDSS spectra and (Chandra or XMM-Newton) X-ray data, we identified five new CLQs via optical spectroscopic follow-up and then obtained new target-of-opportunity X-ray observations with Chandra. No strong absorption is detected in either the bright- or the faint-state X-ray spectra. The intrinsic X-ray flux generally changes along with the optical variability, and the X-ray power-law slope becomes harder in the faint state. Large-amplitude mid-infrared variability is detected in all five CLQs, and it echoes the variability in the optical with a time lag expected from the light-crossing time of the dusty torus for CLQs with robust lag measurements. The changing-obscuration model is not consistent with the observed X-ray spectra and spectral energy distribution changes seen in these CLQs. It is highly likely that the observed changes are due to the changing accretion rate of the supermassive black hole, so the multiwavelength emission varies accordingly, with promising analogies to the accretion states of X-ray binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Causes and evolution of winter polynyas north of Greenland

During the 42-year period (1979–2020) of satellite measurements, four major winter (December–March) polynyas have been observed north of Greenland: one in December 1986 and three in the last decade, i.e., February of 2011, 2017, and 2018. The 2018 polynya was unparalleled in its magnitude and duration compared to the three previous events. Given the apparent recent increase in the occurrence of these extreme events, this study aims to examine their evolution and causality, in terms of forced versus natural variability. The limited weather station and remotely sensed sea ice data are analyzed combining with output from the fully coupled Regional Arctic System Model (RASM), including one hindcast and two ensemble simulations. We found that neither the accompanying anomalous warm surface air intrusion nor the ocean below had an impact (i.e., no significant ice melting) on the evolution of the observed winter open-water episodes in the region. Instead, the extreme atmospheric wind forcing resulted in greater sea ice deformation and transport offshore, accounting for the majority of sea ice loss in all four polynyas. Our analysis suggests that strong southerly winds (i.e., northward wind with speeds greater than 10 m s –1 ) blowing persistently over the study region for at least 2 d or more were required over the study region to mechanically redistribute some of the thickest Arctic sea ice out of the region and thus to create open-water areas (i.e., a latent heat polynya). To assess the role of internal variability versus external forcing of such events, we carried out and examined results from the two RASM ensembles dynamically downscaled with output from the Community Earth System Model (CESM) Decadal Prediction Large Ensemble (DPLE) simulations. Out of 100 winters in each of the two ensembles (initialized 30 years apart: one in December 1985 and another in December 2015), 17 and 16 winter polynyas were produced north of Greenland, respectively. The frequency of polynya occurrence had no apparent sensitivity to the initial sea ice thickness in the study area pointing to internal variability of atmospheric forcing as a dominant cause of winter polynyas north of Greenland. We assert that dynamical downscaling using a high-resolution regional climate model offers a robust tool for process-level examination in space and time, synthesis with limited observations, and probabilistic forecasts of Arctic events, such as the ones being investigated here and elsewhere.

54 ENVIRONMENTAL SCIENCES↗