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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dynamics of a single polyampholyte chain

Polymers that feature both positive and negative charges along chains, known as polyampholytes, represent a class of materials that hold promise for a new generation of energy storage devices, the design of which will require knowledge of the underlying structure and dynamics. Here, we develop a theory based on the Rouse model for the dynamic structure factor of a single polyampholyte chain in the weak coupling regime (negligible intramolecular electrostatics) or subjected to weak external electric fields (governed by linear response). Neglecting effects of small ions, we find deviations in scaling from the classic Rouse theory and make predictions for scattering experiments performed on polyampholytes. We find that, under weak coupling with arbitrarily strong fields, the dynamics are highly dependent on the charge distribution and consequently look at two representative examples—random charge densities and periodic charge densities—with different scaling properties. Additionally, under weak fields, the dynamics are largely independent of charge distribution. Finally, we investigate the influence of hydrodynamic effects and the implications of including inertial effects in the model.

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

Bioenergy for climate change mitigation: Scale and sustainability

Many global climate change mitigation pathways presented in IPCC assessment reports rely heavily on the deployment of biomass for bioenergy, often used in conjunction with carbon capture and storage (BECCS). We review the literature on bioenergy, including the modelling of bioenergy in integrated assessment models (IAMs) and bottom-up modelling and non-modelling studies on the implications of bioenergy use. We summarise the limitations of existing modelling studies and what is known about the potential co-benefits and adverse side-effects of bioenergy systems. We find that the implications of bioenergy supply on mitigation and other sustainability criteria are context dependent and influenced by feedstock, management regime, climatic region, scale of deployment and the counterfactual land use and energy system. However, due to limitations of the existing models, and uncertainty over the future context with respect to the many variables that influence availability of biomass and land resources, it is not possible to precisely quantify the sustainability implications for different scales of bioenergy implementation. Given these uncertainties, the dependence on large-scale deployment of bioenergy in mitigation scenarios carries risks. The deployment of bioenergy technologies and the evolution of biomass supply chains at a scale that achieves significant mitigation and carbon sequestration requires integrative policies, coordinated institutions and improved governance mechanisms. As a result, bioenergy, and the use of land to produce biomass, is an essential part of many climate mitigation strategies but there are limits to its use due to trade-offs with sustainability.

09 BIOMASS FUELS↗
DOE OSTI2024

Multiscale Normalizing Flows for Gauge Theories

Scale separation is an important physical principle that has previously enabled algorithmic advances such as multigrid solvers. Previous work on normalizing flows has been able to utilize scale separation in the context of scalar field theories, but the principle has been largely unexploited in the context of gauge theories. This work gives an overview of a new method for generating gauge fields using hierarchical normalizing flow models. This method builds gauge fields from the outside in, allowing different parts of the model to focus on different scales of the problem. Numerical results are presented for $U(1)$ and $SU(3)$ gauge theories in 2, 3, and 4 spacetime dimensions.

Abbott, Ryan↗
DOE OSTI2022

Dynamic coevolution of baseflow and multiscale groundwater flow system during prolonged droughts

Field and numerical studies suggest that baseflow is composed of waters from a spectrum of groundwater flow paths termed the Groundwater Flow System (GWFS) – from shallow hillslope contributions to watershed-scale deep circulation originating in headwaters and discharging into lowland rivers. Here, we explore the evolution of the GWFS under prolonged droughts to understand its dynamics and multiscale nature, and to elucidate its role in baseflow generation and recession at the watershed scale. In this work, we consider three drought scenarios of varying severity and simulate groundwater flow in a 2-D cross-section of an idealized watershed with deep permeable bedrock, tracking the evolution of flow paths, baseflow, and residence times during the recession process. We find that baseflow generation at different drainage stages, and within different subwatersheds, is influenced distinctly by flow paths of different scales, depending on the relative strength of the flow paths and the position of the subwatersheds relative to the recharge/discharge zones of the deeper watershed-scale groundwater circulation. Despite having the same local relief, geology, and climate, baseflow from each subwatershed has a distinct recession behavior and time-dependent residence time distribution. Also, the hydraulic and transport characteristics of baseflow generation co-evolve and are strongly affected by the connection state of the water table to subwatersheds. These findings suggest that asynchrony and dissimilarity of baseflow generation from hillslopes under the impact of the watershed-scale groundwater flow, and interactions with local-scale and intermediate-scale groundwater flow, must be taken into account when interpreting baseflow recession data and building conceptual baseflow models at the watershed scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Using Multiscale Ethane/Methane Observations to Attribute Coal Mine Vent Emissions in the San Juan Basin From 2013 to 2021

Abstract Source attribution of natural gas emissions from fossil fuels in New Mexico's San Juan Basin (SJB) is challenging due to source heterogeneity and emissions transience. We demonstrate that ethane (C 2 H 6 ) to methane (CH 4 ) mixing ratios can identify and separate sources over different scales using various measurement techniques. We report simultaneous CH 4 and C 2 H 6 observations near a coal mine vent and oil and gas (O&G) emission sources using ground‐based in situ measurements in 2020/2021. During these campaigns, we observed a stable coal vent C 2 H 6 :CH 4 ratio of 1.28% ± 0.11%, discernibly different than nearby O&G source ratios ranging from 0.9% to 16.8%. We analyze airborne observations of the SJB taken in 2014/2015 that exhibit similar coal vent ratios and further show the region's heterogeneity. We identify episodic O&G sources, including a gas plant source detected in 2014/2015 that is absent in our 2020/2021 data. We examine total column observations of C 2 H 6 and CH 4 made in 2013 with a solar spectrometer and find a C 2 H 6 :CH 4 ratio of 1.3% ± 0.4% for the coal vent. The stable and unique coal vent ratio relative to other O&G sources in the region is used to demonstrate that consistent attribution is possible using various measurement methods at multiple scales across many years. Finally, we demonstrate that using C 2 H 6 as a proxy for fossil CH 4 inversions can inform detailed basin‐scale inversions, provided we understand source specific changes in the C 2 H 6 :CH 4 ratio like we report in the SJB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Combined visualisation of cavitation and vortical structures in a real-size optical diesel injector

A high-speed flow visualisation set-up comprising of combined diffuse backlight illumination (DBI) and schlieren imaging has been developed to illustrate the highly transient, two-phase flow arising in a real-size optical fuel injector. The different illumination nature of the two techniques, diffuse and parallel light respectively, allows for the capturing of refractive-index gradients due to the presence of both interfaces and density gradients within the orifice. Hence, the onset of cavitation and secondary-flow motion within the sac and injector hole can be concurrently visualised. Experiments were conducted utilising a diesel injector fitted with a single-hole transparent tip (ECN spray D) at injection pressures of 700–900 bar and ambient pressures in the range of 1–20 bar. High-speed DBI images obtained at 100,000 fps revealed that the orifice, due to its tapered layout, is mildly cavitating with relatively constant cavity sheets arising mainly in regions of manufacturing imperfections. Nevertheless, schlieren images obtained at the same frame rate demonstrated that a multitude of vortices with short lifetimes arise at different scales in the sac and nozzle regions during the entire duration of the injection cycle but the vortices do not necessarily result in phase change. The magnitude and exact location of coherent vortical structures have a measurable influence on the dynamics of the spray emerging downstream the injector outlet, leading to distinct differences in the variation of its cone angle depending on the injection and ambient pressures examined.

42 ENGINEERING↗
DOE OSTI2020

DECOVALEX-2019 (Task E Final Report)

The DECOVALEX Project is an on-going international research collaboration, established in 1992, to advance the understanding and modeling of coupled Thermal (T), Hydrological (H), Mechanical (M) and Chemical (C) processes in geological in geological systems. DECOVALEX was initially motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. Later it was realized that these processes also play a critical role in other subsurface engineering activities, such as subsurface CO 2 storage, enhanced geothermal systems, and unconventional oil and gas production through hydraulic fracturing. Research teams from many countries (e.g., Canada, China, Czech Republic, Finland, France, Germany, Japan, Republic of Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom, and the United States) various institutions have participated in the DECOVALEX Project over the years, providing a wide range of perspectives and solutions to these complex problems. These institutions represent radioactive waste management organizations, national research institutes, regulatory agencies, universities, as well as industry and consulting groups. This document is the final report of Task E which was proposed and coordinated by Andra, the National Radioactive Waste Management Agency in France, presenting the technical definitions of the problems studied, approaches applied, achievements made and outstanding issues for future research. The purpose of Task E of the DECOVALEX-2019 project is to investigate upscaling THM modelling from small-scale experiments (some cubic meters) to full-scale experiments (some ten cubic meters) and finally to the scale of the waste repository (cubic kilometers). To achieve this aim, the data of two in-situ heating experiments performed by Andra (the French National Radioactive Waste Management Agency) in the Meuse/Haute-Marne Underground Research Laboratory (MHM URL) have formed the basis for the understanding of the THM behavior of the COx at different scales. The first experiment provided the reference values of the THM parameters by means of a calibration exercise and they were used for a blind prediction and an interpretative analysis of the second one.

58 GEOSCIENCES↗
DOE OSTI2023

A deep learning model for automatic analysis of cavities in irradiated materials

Transmission electron microscopy (TEM) is a commonly used technique in materials science for defect investigation. Quantitative analysis of defects is important for understanding the properties of a material, but manual analysis of TEM micrographs can be time-consuming and prone to error, especially when the defects have irregular shapes rather than spherical shapes. Many existing methods or deep learning models do not handle a wide range of sizes for the same object type within a single image. In this work, we present a framework that enables users to train an instance segmentation model called Mask R- CNN on any microstructure dataset, perform multi-detection on the same image at different scales, and obtain properties (e.g., size, area) of the objects based on the desired shape (e.g., circle, ellipse, rectangle). Additionally, we have developed a parallel detection module that uses multiple GPUs to increase the efficiency of the object detection process. We demonstrate the capabilities of our framework using a set of TEM images of cavities with different shapes, size distributions, and background contrasts. Finally, we show that the performance of our model in terms of density, size, and swelling of the cavities is comparable to the human average and that our model achieves the highest recall value compared to existing methods due to the use of image multi-rescaling.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multiscale and Multivariate Transportation System Visualization for Shopping District Traffic and Regional Traffic

In this paper, we present a suite of visualization techniques for sensor-based transportation system data at different scales to facilitate the exploration of interconnected traffic dynamics at intersections and highways. Additionally, these techniques are designed for analyzing multivariate traffic data from radar-based highway sensors and camera-based intersection sensors recording turn movements and vehicle speed, in the Chattanooga Metropolitan Area, with the capability of (a) revealing multiscale mobility patterns using different levels of data aggregation (e.g., individual sensor for microscale, multiple sensors along a corridor for mesoscale, and a larger number of sensors across the region for macroscale visualization) at different intervals (e.g., 5-min intervals, time of day, full day, and day-of-the-week), and (b) exploring the spatial variation of multiple traffic-related variables (e.g., volumes, speeds, turn movements, and traffic light colors) provided by the sensors. We close with a case study to demonstrate the effectiveness of our multiscale and multivariate visualization techniques. At microscale, we focused on intersection data from a shopping district around Shallowford Road in East Chattanooga. For mesoscale visualization, we studied the Shallowford Road corridor and an adjacent stretch of I-75. At macroscale, we included highway data from the Chattanooga Metropolitan Area. All visualizations were integrated into a web-based situational awareness tool to promote user access and interaction. At a minimum, each visualization provides the option for selecting dates for real-time (depending on sensor availability) and historical data, and additional information on hovering, though most provide more detailed information, including different views of the selected data, or interactive highlights.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Entanglement transitions from restricted Boltzmann machines

The search for novel entangled phases of matter has lead to the recent discovery of a new class of “en- tanglement transitions,” exemplified by random tensor networks and monitored quantum circuits. Most known examples can be understood as some classical ordering transitions in an underlying statistical mechanics model, where entanglement maps onto the free-energy cost of inserting a domain wall. In this paper we study the possibility of entanglement transitions driven by physics beyond such statistical mechanics mappings. Motivated by recent applications of neural-network-inspired variational Ansätze, we investigate under what conditions on the variational parameters these Ansätze can capture an entanglement transition. We study the entanglement scaling of short-range restricted Boltzmann machine (RBM) quantum states with random phases. For uncorrelated random phases, we analytically demonstrate the absence of an entanglement transition and reveal subtle finite-size effects in finite-size numerical simulations. Introducing phases with correlations decaying as 1/r α in real space, we observe three regions with a different scaling of entanglement entropy depending on the exponent α. We study the nature of the transition between these regions, finding numerical evidence for critical behavior. Furthermore, our work establishes the presence of long-range correlated phases in RBM-based wave functions as a required ingredient for entanglement transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Fungal drops: a novel approach for macro- and microscopic analyses of fungal mycelial growth

Abstract This study presents an inexpensive approach for the macro- and microscopic observation of fungal mycelial growth. The ‘fungal drops’ method allows to investigate the development of a mycelial network in filamentous microorganisms at the colony and hyphal scales. A heterogeneous environment is created by depositing 15–20 µl drops on a hydrophobic surface at a fixed distance. This system is akin to a two-dimensional (2D) soil-like structure in which aqueous-pockets are intermixed with air-filled pores. The fungus (spores or mycelia) is inoculated into one of the drops, from which hyphal growth and exploration take place. Hyphal structures are assessed at different scales using stereoscopic and microscopic imaging. The former allows to evaluate the local response of regions within the colony (modular behaviour), while the latter can be used for fractal dimension analyses to describe the hyphal network architecture. The method was tested with several species to underpin the transferability to multiple species. In addition, two sets of experiments were carried out to demonstrate its use in fungal biology. First, mycelial reorganization of Fusarium oxysporum was assessed as a response to patches containing different nutrient concentrations. Second, the effect of interactions with the soil bacterium Pseudomonas putida on habitat colonization by the same fungus was assessed. This method appeared as fast and accessible, allowed for a high level of replication, and complements more complex experimental platforms. Coupled with image analysis, the fungal drops method provides new insights into the study of fungal modularity both macroscopically and at a single-hypha level.

Buffi, Matteo↗
DOE OSTI2022

A Dynamic Pore Network Model for Imbibition Simulation Considering Corner Film Flow

Wetting films can develop in the corners of angular pores under strong wetting conditions. Modeling the dynamics of corner film remains elusive using direct numerical simulations because of the significant scale difference between main meniscus and corner film flow. In this paper, the modified interacting capillary bundle model (ICB), developed in our previous work to describe accurately corner film dynamics in a single square tube, is incorporated into a single-pressure dynamic pore network model (DPNM) to simulate imbibition in strongly wetting porous media with corner film flow. The traditional pore network is decomposed into several layers of interacting subpore networks where the 0th layer of subpore network simulates the main meniscus flow and higher layers the corner film flow. The fluid flow between different layers is captured by interlayer throats. In addition, the snap-off mechanism caused by the thickening of wetting corner film is considered. The accuracy of the developed model is validated for four cases: spontaneous imbibition in a single square tube, wetting fluid redistribution through corner films under a capillary pressure difference, snap off in a narrow throat connecting two large pores, and imbibition dynamics in a real microfluidic porous geometry. The validated model is then used to simulate both spontaneous and controlled imbibition in a pore network with random pore size distribution. Finally, the interaction between corner film and main meniscus flow in porous media is analyzed from a pore-scale perspective.

58 GEOSCIENCES↗
DOE OSTI2020

Lignin-derived electrochemical energy materials and systems

Electrochemical energy storage systems such as supercapacitors, rechargeable batteries and fuel cells have been proven the most effective technologies for energy conversion, storage, and management at different scales. Although a large number of electrochemical energy technologies have been developed in the past and they will continue to be optimized in terms of cost, lifetime, and performance, there is a substantial growing demand for advanced electrochemical energy systems. To deploy these advanced systems, the electrode and electrolyte materials with higher performance, longer life, and lower cost, must be developed. Lignin is the second most abundant natural polymer after cellulose, a byproduct from emerging cellulosic biorefineries, and a waste product from pulp and paper industries. Numerous researches have successfully demonstrated that lignin from different sources can be used as precursors or feedstocks for preparing high-performance electrochemical energy materials and components such as electrodes, electrolytes, membrane separators, and additives. Moreover, techno-economic analyses indicate that it is possible to prepare cost-effective carbons from lignin at engineering scales, compared to current carbon products. These facts suggest that scalable conversion of lignin into high-value energy materials will offer a promising pathway to not only promote the utilization and valorization of lignin but also boost the development of the advanced electrochemical energy systems. This review presents state of the arts of renewable energy materials derived from various lignin and their applications in electrochemical energy systems with emphasis on supercapacitors, rechargeable batteries, and fuel cells. Meanwhile, this article also aims to carve out the critical barriers for lignin-derived high-performance materials for energy applications, intending to identify viable approaches for synthesis of sustainable new energy materials.

09 BIOMASS FUELS↗
DOE OSTI2023

Scaling CFB risers: Beyond the data using microstructure similarity

Scaling circulating fluidized bed risers has been a point of contention for nearly a century. There have been numerous attempts to define various methodologies. These have all fallen short of providing a robust approach, primarily due to a lack of maintaining microstructure dynamics – a key factor in maintaining interphase heat and mass transfer. Recent work by the author put forward an approach based upon preserving dynamic similarity at different scales by ensuring that the microstructure remained similar by maintaining statistical and chaotic parameters across the scale. That work relied on a dimensionless regime map in which the x-axis was defined by the ratio of the solids flux to the saturation carrying capacity. This latter property was only good within the range of the data, and it became evident that extrapolation beyond the limits of the data could induce unrealistic conditions. Therefore, literature was reviewed to develop a better correlation for the saturation carrying capacity. In doing so, a critical riser diameter concept was developed and applied to the correlations for both Geldart Group A and B materials. The critical diameter for Geldart Group A and B materials is 0.2 m and 0.3 m, respectively. Here the paper then gives three examples on how to use the scaling approach to maintain dynamic similarity across the scales.

02 PETROLEUM↗
DOE OSTI2023

Maintaining Microstructure – The Path to Successful Technology Maturation in Fluidized Systems

Scaling circulating fluidized bed risers has been a point of contention for nearly a century. There have been numerous attempts to define various methodologies. These have all fallen short of providing a robust approach, primarily due to a lack of maintaining microstructure dynamics – a key factor in maintain interphase heat and mass transfer. Recent work by the author put forward an approach based up maintaining dynamic similarity at different scales by ensuring that the microstructure remained similar by maintaining statistical and chaotic parameters across the scale. That work relied on a dimensionless regime map in which the x-axis was defined by the ratio of the solids flux to the saturation carrying capacity. This latter property was only good within the range of the data and it became evident that extrapolation beyond the limits of the data could induce unrealistic conditions. Therefore, literature was reviewed to develop a better correlation for the saturation carrying capacity. In doing so, a critical diameter concept was developed and applied to the correlations for both Geldart Group A and B materials. The critical diameter for Geldart Group A and B materials is 0.2 m and 0.3 m, respectively. The paper then gives examples on how to use the scaling approach to maintain dynamic similarity across the scales.<br>

Breault, Ronald↗
DOE OSTI2023

Enhanced rare-earth separation with a metal-sensitive lanmodulin dimer

Technologically critical rare-earth elements are notoriously difficult to separate, owing to their subtle differences in ionic radius and coordination number. The natural lanthanide-binding protein lanmodulin (LanM) is a sustainable alternative to conventional solvent-extraction-based separation. Here we characterize a new LanM, from Hansschlegelia quercus (Hans-LanM), with an oligomeric state sensitive to rare-earth ionic radius, the lanthanum(III)-induced dimer being >100-fold tighter than the dysprosium(III)-induced dimer. X-ray crystal structures illustrate how picometre-scale differences in radius between lanthanum(III) and dysprosium(III) are propagated to Hans-LanM’s quaternary structure through a carboxylate shift that rearranges a second-sphere hydrogen-bonding network. Comparison to the prototypal LanM from Methylorubrum extorquens reveals distinct metal coordination strategies, rationalizing Hans-LanM’s greater selectivity within the rare-earth elements. Finally, structure-guided mutagenesis of a key residue at the Hans-LanM dimer interface modulates dimerization in solution and enables single-stage, column-based separation of a neodymium(III)/dysprosium(III) mixture to >98% individual element purities. This work showcases the natural diversity of selective lanthanide recognition motifs, and it reveals rare-earth-sensitive dimerization as a biological principle by which to tune the performance of biomolecule-based separation processes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Testing general relativity on cosmological scales at redshift z ∼ 1.5 with quasar and CMB lensing

ABSTRACT We test general relativity (GR) at the effective redshift $\bar{z} \sim 1.5$ by estimating the statistic EG, a probe of gravity, on cosmological scales $19 - 190\, h^{-1}{\rm Mpc}$. This is the highest redshift and largest scale estimation of EG so far. We use the quasar sample with redshifts 0.8 < z < 2.2 from Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 as the large-scale structure (LSS) tracer, for which the angular power spectrum $C_\ell ^{qq}$ and the redshift-space distortion parameter β are estimated. By cross-correlating with the Planck 2018 cosmic microwave background (CMB) lensing map, we detect the angular cross-power spectrum $C_\ell ^{\kappa q}$ signal at $12\, \sigma$ significance. Both jackknife resampling and simulations are used to estimate the covariance matrix (CM) of EG at five bins covering different scales, with the later preferred for its better constraints on the covariances. We find EG estimates agree with the GR prediction at $1\, \sigma$ level over all these scales. With the CM estimated with 300 simulations, we report a best-fitting scale-averaged estimate of $E_G(\bar{z})=0.30\pm 0.05$, which is in line with the GR prediction $E_G^{\rm GR}(\bar{z})=0.33$ with Planck 2018 CMB + BAO matter density fraction Ωm = 0.31. The statistical errors of EG with future LSS surveys at similar redshifts will be reduced by an order of magnitude, which makes it possible to constrain modified gravity models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

X-Band Radar and Surface-Based Observations of Cold-Season Precipitation in Western Colorado’s Complex Terrain

Abstract Hydrologic processes associated with intermountain cold-season precipitation in the Upper Colorado River basin have important impacts on avalanche forecasting and water resource management. However, traditional weather radar networks struggle with observations in this complex terrain. Data collected during the Study of Precipitation, the Lower Atmosphere, and the Surface for Hydrometeorology (SPLASH) and its sister campaign, Surface Atmosphere Integrated Field Laboratory (SAIL) in the East River watershed of western Colorado, are used to examine a multistorm period from 23 December 2021 to 1 January 2022 that contributed 35% of the total winter precipitation in this watershed. Dual-polarization X-band radar and disdrometer measurements show ∼30-mm differences in precipitation amount at two sites in proximity over four distinct storm events within the period. Wind patterns, synoptic forcings, microphysical characteristics of precipitation, and surface meteorology are analyzed to explain the observed spatial variability of cold-season precipitation in complex mountainous terrain. Analysis shows that differences over time within this event are mainly accounted for by synoptic forcings, such as frontal passages; differences between sites are accounted for by the impact of variations in local wind patterns on precipitation microphysics. Patterns of surface precipitation intensity are compared and found to be correlated with X-band radar signatures; a relationship between a strong dendritic growth stage and intense low-density surface precipitation is reinforced by this study. This relationship demonstrates the importance of particle growth mechanisms on surface snowfall patterns in high-altitude complex terrain, underscoring the importance of realistic microphysical parameterizations. Significance Statement The amount and density of snowpack from western Colorado winter storms have significant impacts on water resources in the Upper Colorado River basin. Snowpack characteristics are affected by small-scale differences in how snow forms in the atmosphere. These differences are hard to study in the complex terrain of the Rockies, but data from the SPLASH and SAIL field campaigns allows us to investigate how snow crystal formation and mountain-driven wind patterns affect snow near the surface. Our study finds that snow crystal growth varies over small space and time scales and is likely controlled by the terrain beneath a given location and resultant local wind patterns. These results imply that predicting snowpack in the Rockies requires properly representing local wind patterns and crystal growth processes in models.

Heflin, Stella↗