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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Threshold progressions in covering and packing contexts

Here, using standard methods (due to Janson, Stein–Chen, and Talagrand) from probabilistic combinatorics, we explore the following general theme: As one progresses from each member of a family of objects $\mathcal{A}$ being “covered” by at most one object in a random collection $\mathcal{C}$, to being covered at most λ times, to being covered at least once, to being covered at least λ times, a hierarchy of thresholds emerge. We will use examples from extremal set theory, combinatorics, and additive number theory to see how these results vary according to the context, and level of dependence introduced.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Diffusion energy barrier of Au on Bi 2 Se 3 : theory and experiment

The stability and diffusion of ultra-thin thermally deposited Au films on Bi 2 Se 3 was studied using scanning tunneling microscopy and density functional theory calculations. The Au/Bi 2 Se 3 interface is of interest as gold is predicted to provide excellent electrical contact while maintaining the spin-polarized characteristics of the electronic states in Bi 2 Se 3 that make the material attractive for spintronic applications. When deposited at room temperature, Au 10 covers the surface with tightly packed islands of nanometer scale dimension. The surface morphology is stable up to 400K. At this annealing temperature, Au atoms have sufficient energy to diffuse across the surface and aggregate into larger nanostructures. At 550K, the Bi 2 Se 3 surface is only sparsely covered, and the Au has formed clusters with length scales 5-10 times larger than the original islands formed at room temperature. Comparison of the experiment and first principle calculation lead to the conclusion that the diffusion energy barrier for Au on Bi 2 Se 3 is as high as 0.47 eV, 15 which is much larger than diffusion barriers on other van der Waals materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Angularly resolved spectral reconstruction of x rays via filter pack attenuation

We have designed a new filter pack array to measure angular variations in x-ray spectra during a single shot. The filter pack was composed of repeating identical columns of aluminum and copper filters of varying thicknesses. These columns were located at different positions to measure the spectrum at each corresponding angle. This array was utilized in an experiment to measure the energy evolution of betatron x rays in a laser wakefield accelerator by curving the wakefield with a transverse density gradient, streaking the x rays across the array in front of an x-ray charge-coupled device (CCD) camera. After subtracting the background and “flattening” the image to remove spatial nonuniformities, a critical energy was calculated for each position that produced the best agreement with the measured signal. There was a clear change in critical energy with angle, shedding light on the dynamics of the electrons that traveled through the accelerator. Furthermore, these angles correspond to distinct emission times, covering a timescale of tens of picoseconds. The filter pack was capable of recovering these angular details without the impact of errors introduced by shot-to-shot variability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Overview of the MOSAiC expedition: Snow and sea ice

Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Average Shape of Sea Ice Ridge Keels

Through analysis of over 64,000 ridge profiles identified from moored upward-looking sonars, we identify a well-defined average shape of pressure ridge keels that is concave or cusped, not triangular as widely assumed in other literature. On the basis of this average shape, we put forward a new, dimensional-definition, of a pressure ridge cross-section that follows a negative exponential form and allows an average pressure ridge cross section to be constructed with knowledge or choice of a single parameter. The horizonal asymptote of the profile represents the draft of the “background” ice in which the ridge is embedded. The draft of this background ice scales with keel depth and is typically greater than can be accounted through thermodynamic growth, indicating that ridges tend to be embedded in fields of mechanically thickened rubble. Using a variational ridge model we simulated keel shapes for a range of ridge building conditions. Here, the model results agree well with the observations and indicate the cusped shape of an average ridge profile arises from the varying angle of horizontal shear in the ice cover when ridges form. The modeling results also explain the elongated tail of the area draft distribution of the pack.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Lipid Droplets: Packing Hydrophobic Molecules Within the Aqueous Cytoplasm

Lipid droplets, also known as oil bodies or lipid bodies, are plant organelles that compartmentalize neutral lipids as a hydrophobic matrix covered by proteins embedded in a phospholipid monolayer. Some of these proteins have been known for decades, such as oleosins, caleosins, and steroleosins, whereas a host of others have been discovered more recently with various levels of abundance on lipid droplets, depending on the tissue and developmental stage. In addition to a growing inventory of lipid droplet proteins, the subcellular machinery that contributes to the biogenesis and degradation of lipid droplets is being identified and attention is turning to more mechanistic questions regarding lipid droplet dynamics. While lipid droplets are mostly regarded as storage deposits for carbon and energy in lipid-rich plant tissues such as seeds, these organelles are present in essentially all plant cells, where they display additional functions in signaling, membrane remodeling, and the compartmentalization of a variety of hydrophobic components. Remarkable metabolic engineering efforts have demonstrated the plasticity of vegetative tissues such as leaves to synthesize and package large amounts of storage lipids, which enable future applications in bioenergy and the engineering of high-value lipophilic compounds. Here, we review the growing body of knowledge about lipid droplets in plant cells, describe the evolutionary similarity and divergence in their associated subcellular machinery, and point to gaps that deserve future attention.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Performance Evaluation of a Prototype Moving Packed-Bed Particle/sCO 2 Heat Exchanger

Particle heat exchangers are a critical enabling technology for next generation concentrating solar power (CSP) plants that use supercritical carbon dioxide (sCO 2 ) as a working fluid. This report covers the design, manufacturing and testing of a prototype particle-to-sCO 2 heat exchanger targeting thermal performance levels required to meet commercial scale cost targets. In addition, the the design and assembly of integrated particle and sCO 2 flow loops for heat exchanger performance testing are detailed. The prototype heat exchanger was tested to particle inlet temperatures of 500 °C at 17 MPa which resulted in overall heat transfer coefficients of approximately 300 W/m 2 -K at the design point and cases using high approach temperature with peak values as high as 400 W/m 2 -K

14 SOLAR ENERGY↗
DOE OSTI2021

Modulating Interactions between Molten Polystyrene and Porous Solids Using Atomic Layer Deposition

Understanding and modulating the interactions between molten polymers and porous solids is important for numerous processes and phenomena including catalytic conversion of polymers and fabrication of nanocomposites and nanostructured materials. Although changing the surface composition of pores would enable modulation of interactions between polymer and nanoporous solids, it is challenging to achieve such a control without inducing significant changes to the size and structure of nanopores. In this work, we demonstrate that the interactions between molten polystyrene (PS) and disordered packings of SiO 2 nanoparticles (NPs) can be modulated by changing the surface composition of the NPs using atomic layer deposition (ALD). A disordered packing of silica NPs is modified with varying surface coverages of TiO 2 , WO 3 and CaCO 3 , with coverages estimated by the mass gain and the refractive index change of NP packings. Based on the time required to fully infiltrate these ALD-modified NP packings via capillarity, the contact angles for PS on different surfaces prepared via ALD are determined. The contact angle gradually changes from that of pure SiO 2 to that of the fully covered surfaces. The contact angles for PS on SiO 2 , TiO 2 , WO 3 and CaCO 3 are found to be 20°, 62°, 70° and 10°, respectively. Interestingly, the contact angles and interfacial energies between PS and the ALD-modified surfaces do not correlate strongly with the water contact angle of these surfaces; thus, caution must be exercised in predicting how a polymer would wet or interact with porous solids solely based on their hydrophilicity. Furthermore, the method presented in this work can be extended to study the interactions between a wide range of polymers and surfaces in porous media, which will have important implications for designing new catalytic materials for polymer upcycling reactions as well as novel NP-polymer composite films and membranes with enhanced mechanical and transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-resolution x-ray spectrometer for x-ray absorption fine structure spectroscopy

Two extended x-ray absorption fine structure flat crystal x-ray spectrometers (EFX’s) were designed and built for high-resolution x-ray spectroscopy over a large energy range with flexible, on-shot energy dispersion calibration capabilities. The EFX uses a flat silicon [111] crystal in the reflection geometry as the energy dispersive optic covering the energy range of 6.3–11.4 keV and achieving a spectral resolution of 4.5 eV with a source size of 50 μm at 7.2 keV. A shot-to-shot configurable calibration filter pack and Bayesian inference routine were used to constrain the energy dispersion relation to within ±3 eV. The EFX was primarily designed for x-ray absorption fine structure (XAFS) spectroscopy and provides significant improvement to the Laboratory for Laser Energetics’ OMEGA-60 XAFS experimental platform. The EFX is capable of performing extended XAFS measurements of multiple absorption edges simultaneously on metal alloys and x-ray absorption near-edge spectroscopy to measure the electron structure of compressed 3d transition metals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

First-Principles Insights into the Thermocatalytic Cracking of Ammonia-Hydrogen Blends on Fe(110): 1. Thermodynamics

Ammonia (NH 3 ) is being considered as a practical means to transport hydrogen (H 2 ) because of its higher volumetric energy density for the same temperature and pressure. Thermodynamics suggest high temperature is needed to decompose NH 3 to nitrogen (N 2 ) and H 2 . Furthermore, overcoming decomposition kinetic barriers requires a catalyst. Via density functional theory, we study this reaction on a model catalyst: the close-packed (110) facet of α-Fe. Specifically, we predict detailed in-operando temperature- and pressure-dependent surface phase diagrams on this benchmark catalyst that offer insights for the design of optimal NH 3 decomposition catalysts. Here, we explore the equilibrium composition(s) of the Fe(110) surface when exposed to NH 3 –H 2 mixtures. Further, we predict that both N and NH partially cover the Fe(110) surface at 300–400 °C (far above the NH 3 decomposition-formation coexistence temperature at standard partial pressures of 1 bar: ~ 180 °C) and 2–4 bar of total reactor pressure. At the equilibrium N/NH coverage, these species inhibit coadsorption of H, indicating that direct H 2 production may occur. However, from thermodynamics alone, removal of N/NH as N 2 (g) is extremely unfavorable even at these elevated temperatures–effectively deactivating the surface toward further NH 3 decomposition. Thus, catalysts that remain active toward N–H bond breaking but with weakened N binding relative to Fe are needed to enable high-turnover catalytic NH 3 decomposition to release H 2 .

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

Probing the solidification of quasicrystals via joint experiment and simulation (Final Report)

Quasicrystals (QCs) possess long-range positional order but non-crystallographic orientational order. Their classically ‘forbidden’ symmetry has long attracted the interest of scientists worldwide. Despite their frequent observation in both metal alloys and soft matter structures in the 35 years since their discovery, little is known about how QCs evolve from a liquid, amorphous, or crystalline precursor. In this project, we sought to resolve the enigma of QC self-assembly through a combined experimental and computational program. The Shahani group employed in situ electron and synchrotron X ray imaging to peer into the growth dynamics of QCs in a liquid, covering a broad range of length scales and solidification pathways. Glotzer's team developed new simulation models incorporating phasonic defects — which are unique to quasicrystals — and used this model to investigate two grains growing together, closely mimicking the experimental conditions. While QCs remain exceptional structures, most compounds in the realm of intermetallics adopt non-trivial geometries. In fact, only around 6% of phases are comprised of the simplest sphere packings that researchers so readily associate with metals. State-of-the-art knowledge of phase transformations at the outset of this collaborative project did not encompass the remaining 94% of intermetallic compounds that possess complex and aperiodic structure types. Therefore, we expect that outcomes from this project will have immediate and profound impact on synthesis and processing science: our efforts will be used to not only explain the growth dynamics of QCs but also complex intermetallics more broadly.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Automatic Generation of High-Performance Convolution Kernels on ARM CPUs for Deep Learning

In this work, we present FastConv, a template-based code auto-generation open source library that can automatically generate high-performance deep learning convolution kernels of arbitrary matrices/tensors shapes. FastConv is based on the Winograd algorithm, which is reportedly the highest performing algorithm for the time-consuming convolution layers of convolutional neural networks. ARM CPUs cover a wide range designs and specifications, from embedded devices to HPC-grade CPUs. The leads to the dilemma of how to consistently optimize Winograd-based convolution solvers for convolution layers of different shapes. FastConv addresses this problem by using templates to auto-generate multiple shapes of tuned kernels variants suitable for skinny tall matrices. As a performance portable library, FastConv transparently searches for the best combination of kernel shapes, cache tiles, scheduling of loop orders, packing strategies, access patterns, and online/offline computations. Auto-tuning is used to search the parameter configuration space for the best performance for a given target architecture and problem size. The experiments with layer-wise evaluation on the VGG--16 model confirms a 1.25x performance gains is got by tuning the Winograd library. Integrated comparison results shows 1.02x to 1.40x, 1.14x to 2.17x, and 1.22x and 2.48x speedup is achieved over NNPACK, Arm NN, and FeatherCNN on the Kunpeng 920 beside few cases. Furthermore, problem size performance portability experiments with various convolution shapes shows that FastConv achieves 1.2x to 1.7x speedup and 2x to 22x speedup over NNPACK and ARM NN inference engine using Winograd on Kunpeng 920 . CPU performance portability evaluation on the VGG--16 show an average speedup over NNPACK of 1.42x, 1.21x, 1.26x, 1.37x, 2.26x, and 11.02x is observed on Kunpeng 920, Snapdragon 835, 855, 888, Apple M1, and AWS Graviton2, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Recent Advances in Scalable, High‐Mass Loaded Electrodes for Grid‐Scale Energy Storage

Abstract The increasing electrification of daily life as well as the intermittent characteristic of renewable energy sources require viable solutions for grid‐scale energy storage. Critical considerations for grid storage applications are electrode mass loading and electrode thickness as these features govern battery pack energy density, an important factor in determining manufacturing costs. For this reason, there is increased interest in finding new ways of creating electrodes with high mass loading. In this review, various high‐mass loading fabrication approaches are considered for positive electrode materials used in batteries. The benchmark used for high mass loading is above 20 mg cm −2 , which is higher than the practical limit of conventional tape‐cast electrodes. Several different electrode approaches are described including templating, laser patterning, direct ink writing, and electrodeposition. A variety of materials are covered with the most prominent being LiFe(PO 4 ) (LFP), LiCoO 2 (LCO), and MnO 2 . In research to date, scalable electrochemical performance has been achieved with mass loadings over 100 mg cm −2 . Areal capacities as high as 14.7 mAh cm −2 at 1.82 mA cm −2 have been achieved in non‐aqueous electrolytes and 9.8 mAh cm −2 at 10 mA cm −2 in aqueous electrolytes. These results establish that the mass loading of electrodes can be scaled up without compromising their electrochemical properties.

White, Makena [Department of Materials Science and↗
DOE OSTI2021

Learning electric vehicle driver range anxiety with an initial state of charge-oriented gradient boosting approach

This manuscript focuses on the modeling of electric vehicle (EV) driver’s range anxiety, a fear that a vehicle does not have sufficient range, or state of charge (SOC) of the battery pack, to reach its destination and would strand its occupants. Despite numerous research studies on the modeling of charging behaviors, modeling efforts to understand at what battery percentages do EV drivers charge their vehicles, and what are the associated contributing factors, are rather limited. To this end, an ensemble learning model based on gradient boosting is developed. The model sequentially fits new predictors to new residuals of the previous prediction and, then, minimizes the loss when adding the latest prediction. A total of 18 features are defined and extracted from the multisource data, which cover information on driver, vehicles, stations, traffic conditions, as well as spatial-temporal context information of the charging events. The analyzed dataset includes 4.5-year’s charging event log data from 3,096 users and 468 public charging stations in Kansas City Missouri, and the macroscopic travel demand model maintained by the metropolitan planning organization. Here, the result shows the proposed model achieved a satisfactory result with a R square value of 0.54 and root mean square error of 0.14, both better than multiple linear regression model and random forest model. To reduce range anxiety, it is suggested that the priorities of deploying new charging facilities should be given to the areas with higher daily traffic prediction, with more conservative EV users or that are further from residential areas.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Development of a Techno-Economic Analysis Framework for a Solar Thermochemical Fuel Production Process

Synthetic liquid fuels can provide a drop-in substitute for fossil-based fuels in sectors such as aviation and maritime, where electrification is not a viable option due to the need for high specific energy density. However, for these alternative fuels to be adopted at a commercial scale, their price must be competitive compared to their fossil-based counterparts. The reverse water-gas shift (RWGS) reaction offers a promising pathway, using hydrogen (sourced from electrolysis) and carbon dioxide as the feed and reacting to produce syngas - a mixture of H2 and CO at a specific ratio. Syngas is a useful precursor that can be converted into fuels and chemicals via known downstream processes, such as liquid transportation fuels via Fischer-Tropsch (FT) synthesis. The RWGS reaction is currently not applied in commercial scale, unlike the rest of the components in the process chain (electrolyzers and syngas-to-fuel synthesis units). The RWGS reaction poses several challenges due to its restrictive thermodynamics. Being an equimolar reaction, high temperatures and a large excess of H2 are needed to achieve reasonable CO2 conversion at equilibrium. This has detrimental effects on practical process implementation and the quality of syngas that can be produced, with direct effect on the energy and capital requirements, as well as the need for expensive downstream separation. In this work, we are proposing to develop a new concentrating solar thermal (CST) compatible RWGS reactor, performing the reaction in a 2-step chemical looping process using metal oxide at a temperature range of 600-800 degrees Celsius. By decoupling the reactor from the solar receiver, the Generation 3 (Gen3) CST technology could be utilized, together with its proposed thermal energy storage (TES) technology, benefitting from a good match to the required temperatures. CST technology is a viable option for supplying the heat that could be rapidly deployed in scale, thus being a good match to the gas-to-liquid (GTL) process which requires a large minimal scale to be commercially viable. The integration of TES with CST also allows operating the plant at large annual capacity factors and avoids multiple shutdown/startup cycles, thus fitting into the steady-state operation mode that most GTL processes require. The main innovation in the proposed design hinges on a countercurrent reaction design using a packed bed reactor. In 2019 Metcalfe et al. showed the benefits of countercurrent species exchange could be realized in a redox chemical-looping processes, by storing the favorable countercurrent chemical potential profiles in a packed bed of non-stoichiometric oxide. Metcalfe et al. applied this breakthrough concept to the WGS reaction, which is conventionally a co-feed catalytic process, showing a dramatic improvement. Bulfin et al. (2023) performed a similar proof-of-concept demonstration for the RWGS reaction using CeO2, achieving cumulative and peak CO2 conversions of 88% and 95%, respectively, compared to a thermodynamic limit of 58% for the co-feed catalytic process at the same conditions. In our new REGENLOOP project, we are developing a reactor prototype from the heat-exchange packed bed reactor-type, a commonly used reactor in the chemical industry. The endothermic heat of reduction will be supplied to the reactor using CST, while the same heat transfer fluid (HTF) mechanism will be used to extract the exothermic heat of oxidation. An array of multiple reactors is used to supply constant high-purity CO stream, that is then mixed with H2 from electrolysis to produce a high-purity syngas at the required composition. By removing the CO-CO2 separation after the RWGS process, significant energy and cost reduction can be achieved. A physics-based TEA framework is currently being developed, covering all the major plant processes, from the solar collection through storage, chemical looping RWGS, GTL, and auxiliary unit operations, up to the liquid hydrocarbon product. This modeling framework will utilize reduced-order models for the chemical looping RWGS and TES, CST modeling using SolarPILOT, and Aspen Plus for the GTL. By using this combined physics-based approach, the effects of design/operating parameters on the performance and cost can be elucidated. In our presentation, the modeling framework will be presented in detail, including preliminary cost predictions of using this plant configuration under a few selected relevant case studies. This study will be used to identify the major cost drivers, informing further system design and optimization needed to chart the way for a commercially viable pathway.

14 SOLAR ENERGY↗
DOE OSTI2021

The effect of water on colloidal quantum dot solar cells

Almost all surfaces sensitive to the ambient environment are covered by water, whereas the impacts of water on surface-dominated colloidal quantum dot (CQD) semiconductor electronics have rarely been explored. Here, strongly hydrogen-bonded water on hydroxylated lead sulfide (PbS) CQD is identified. The water could pilot the thermally induced evolution of surface chemical environment, which significantly influences the nanostructures, carrier dynamics, and trap behaviors in CQD solar cells. The aggravation of surface hydroxylation and water adsorption triggers epitaxial CQD fusion during device fabrication under humid ambient, giving rise to the inter-band traps and deficiency in solar cells. To address this problem, meniscus-guided-coating technique is introduced to achieve dense-packed CQD solids and extrude ambient water, improving device performance and thermal stability. Our works not only elucidate the water involved PbS CQD surface chemistry, but may also achieve a comprehensive understanding of the impact of ambient water on CQD based electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluating fine-resolution, regional outputs of a variable resolution global climate model

Climate models have been used to study water resources and regional hydrologic responses to climate change, but climate model outputs must be downscaled to provide relevant regional data. However, the accuracy of this regional data is limited by uncertainties across and within downscaling methods, uncertainty across global outputs, and discontinuities at downscaled boundaries. A new alternative to traditional downscaling is a variable resolution model that incorporates fine-resolution regions directly into a coarse-resolution, global climate simulation in order to capture contiguous dynamics across resolution boundaries. In this study, we used the Variable-Resolution Community Earth System Model (VR-CESM) to generate one-eighth degree (14 km) fine-resolution outputs for the western U.S. and eastern China from 1970-2006. We focus our evaluation on precipitaiton, temperature, snow pack, solar radiation, and wind. We compare the model outputs with remote-sensing-based precipitation data, and both reanalysis and gridded weather station data for precipitation and temperature. VR-CESM generally has a cold bias in winter and a warm bias in summer in the western U.S., which compensate each other to reduce the annual bias. In eastern China, however, the sign of temperature biases are more consistent throughout the year with cold biases in the higher mountains and warm biases throughout most of the rest of the region. Precipitation biases are dependent upon reference data, and show slight overestimation in high mountain regions in both the U.S. and China with respect to gridded weather station data. Simulated snow cover in the western U.S. is reasonable compared to remote sensing data, but snow cover and snow water equivalent have larger biases when compared to reanalysis data. In eastern China there are widespread snow cover biases compared to remote sensing data. VR-CESM underestimates downward shortwave radiation to a greater degree in summer than in winter, and underestimates surface layer windspeed over mountains to a greater degree than in other areas. Comparison between VR-CESM and a coarser simulation (1-degree Beijing Climate Center model) shows reduced precipitation biases in the mountainous regions with finer resolution, indicating the value of variable-resolution modeling for reigonal studies.

Di Vittorio, Alan↗