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At least 343 records · Page 19

Resolved gravity waves in the tropical stratosphere: Impact of horizontal resolution and deep convection parametrization

Convectively generated gravity waves (CGGWs) are important for numerical weather prediction due to their effect on the quasi-biennial oscillation (QBO) in the stratosphere. Here, using global ECMWF IFS simulations at TCo7999 (or 1.25 km), TCo2559 (or 3.9 km) and TCo1279 (or 7.8 km) horizontal resolutions, sensitivity of resolved CGGWs to the horizontal resolution and to the explicit versus parametrized representation of deep convection is elucidated during the westerly shear phase of the QBO. Parametrized deep convection is found to inhibit CGGWs, resulting in a twofold reduction in CGGW forcing. When deep convection is explicitly resolved, the total CGGW forcing is almost unchanged across the horizontal resolutions. However, the contribution of long and mesoscale CGGWs (with horizontal wavelengths 100 km ≤ $λ_h$ < $1,900$ km) to the total CGGW forcing decreases and the contribution of smaller-scale CGGWs (with $λ_h$ < $100$ km) increases as the horizontal resolution increases. At the maximum CGGW forcing altitude, at TCo7999 resolution 43% of the total CGGW forcing is due to long and mesoscale waves, whereas at TCo2559 and TCo1279 resolutions their contribution is 70% and 90%, respectively. While CGGW forcing from long and mesoscale waves is similar at TCo7999 resolution with explicit deep convection and at TCo1279 resolution with parametrized deep convection, CGGW forcing from these waves is artificially enhanced at TCo1279 and TCo2559 resolutions with explicit deep convection. This is due to the explicit deep convection being too strong and having too much variance for 100 km ≤ $λ_h$ < $1,900$ km. Therefore, parametrizations of deep convection and CGGWs (to account for forcing from waves with $λ_h$ < $100$ km) are required even at TCo2559 resolution. Additionally, resolved CGGW forcing at TCo7999 resolution is examined for the easterly shear phase of the QBO; similar to the westerly shear phase, the smaller-scale waves contribute 55% to the total CGGW forcing at the maximum CGGW forcing altitude.

54 ENVIRONMENTAL SCIENCES↗

Weak shock compaction on granular salt

This study conducted integrated experiments and computational modeling to investigate the speeds of a developing shock within granular salt and analyzed the effect of various impact velocities up to 245 m/s. Experiments were conducted on table salt utilizing a novel setup with a considerable bore length for the sample, enabling visualization of a moving shock wave. Experimental analysis using particle image velocimetry enabled the characterization of shock velocity and particle velocity histories. Mesoscale simulations further enabled advanced analysis of the shock wave’s substructure. In simulations, the shock front’s precursor was shown to have a heterogeneous nature, which is usually modeled as uniform in continuum analyses. The presence of force chains results in a spread out of the shock precursor over a greater ramp distance. With increasing impact velocity, the shock front thickness reduces, and the precursor of the shock front becomes less heterogeneous. Furthermore, mesoscale modeling suggests the formation of force chains behind the shock front, even under the conditions of weak shock. This study presents novel mesoscale simulation results on salt corroborated with data from experiments, thereby characterizing the compaction front speeds in the weak shock regime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nanostructures for Electrical Energy Storage (NEES) (2020 Final Technical Report)

Nanostructures for Electrical Energy Storage (NEES, www.efrc.umd.edu) was an Energy Frontier Research Center supported by the DOE Office of Science, Basic Energy Sciences, from 8/1/2009 to 7/31/2020. Led by the University of Maryland, NEES enjoyed extensive collaborations with its funded partners, including two DOE Laboratories and six universities. The NEES vision has been to reveal a set of scientific insights and design principles that can underpin a next-generation electrical energy storage approach, building on advances in nanoscale science and technology to achieve simultaneous high power and high energy over extended charge/discharge cycling. The vision is motivated by the recognition that scaling into the nano regime opens the door to new physical phenomena and that the tools enlisted in nanoscale research provide major new opportunities for the synthesis not only of materials at molecular scale but for structures at nano scale and above. NEES has translated this vision into its research program based on two observations. First, while the behavior of ions and electrons in electrolytes and in electrode materials is crucial to electrical energy storage (or more appropriately electrochemical energy storage), it is the transport of ion and electron charge between different structural components of a storage device that ultimately determine its performance. With it well recognized that the choice of electrode materials typically constrain ion transport kinetics as well as maximum ion concentration, the search for better electrode materials has been a primary driver of battery research. At the same time the synthesis of electrodes is typically based on aggregation of particles with varying size, shape, and orientation in the electrode. Together with the presence of additional materials to impart electrical conductivity and cohesion to the composite electrode, change in electrode materials is necessarily accompanied by structural changes at the nano/micro scale that are difficult to categorize and manage. From the beginning, NEES’ vision has been to create and study simpler, highly controlled spatial arrangements of known materials as battery components (electrodes, current collectors, and electrolyte) and to understand how design and structure above the molecular scale determines the energy storage performance available from known materials. Second, advances in nanoscience dramatically expanded the portfolio of synthesis methods, structural motifs, and new phenomena available for research. Some of these gave rapid access to new building blocks at the deep nanoscale (e.g., carbon nanotubes grown by self-assembly, nanoscale arrays formed by electrochemical self-alignment, monolayer films controlled by self-limiting reaction). Such advances served as the enabler for the NEES vision to be pursued experimentally through study of 3D structures created and controlled at the nano, micro, and meso scales. Here, we use meso as in the BES MESO Report, implying not only intermediate or varying length scales, but very much the way behavior is influenced by other factors including aggregation of nanocomponents at different densities and spatial configurations, statistical variations in the aggregates, hierarchical architectures in which they can be assembled, or local 3D configurations that result from the architectures. Over its life cycle, NEES has pursued two overarching goals: (1) to understand the scientific fundamentals of electrochemical storage from the nanoscale to the mesoscale; and (2) to create and learn from innovative, controlled, heterogeneous nanostructures, where such nanostructures can enable the first goal and serve as models for future paradigms in energy storage. Specific goals have included: Synthesize heterogeneous nanostructures comprised of multiple materials arranged in controlled fashion and characterize their behavior; Demonstrate and elucidate design principles for achieving simultaneous high power and high energy; Develop materials processes which enable precision control of thin layers and 3D structures; Investigate the impact of artificial interphases on electrode stability during ion insertion/deinsertion; Create dense arrays of nanostructures to understand how the architecture of these assemblies, along with nanostructure design, influences energy storage behavior at the mesoscale; Identify and understand the consequences of nanoconfinement and local inhomogeneities in 3D mesoscale arrays; Develop and apply computational models to stimulate, guide and interpret experiments.

25 ENERGY STORAGE↗

Influence of Antarctic and Greenland Continental Shelf Circulation on High‐Latitude Oceans in E3SM

The science objectives of this project are to simulate and understand the impacts of both deep-basin warm-water intrusions and land-ice melt on the continental shelf circulations and sea-ice distributions around the margins of Greenland and Antarctica. As well, the role of subsurface ocean heat from the Atlantic on declining sea-ice cover in the Arctic is explored. Mesoscale processes and fine bathymetry are implicated in cross-shelf property transports around both Greenland and Antarctica. Therefore, we configured and ran an atmospheric reanalysis-forced global ocean/sea-ice simulation on a grid that reduces from 8 km at the Equator to 2 km at the poles (UH8to2) with 60 vertical levels. It was produced using the Energy Exascale Earth System Model ‘‘HiLAT’’ code (E3SMv0-HiLAT) that uses the Parallel Ocean Program (POP) and CICE5 as its ocean and sea-ice components, respectively. Two main UH8to2 simulations were carried out: one for 1975-2009 and the other for July 2016-2020 after it was initialized from a 1/25° data-assimilative ocean/sea-ice prediction system ocean/sea-ice state. The UH8to2 is not coupled to an active land-ice model. Rather, land-ice melt is represented by observationally informed freshwater fluxes (FWFs). Short (multi-year) UH8to2 simulations were conducted to understand sensitivities when Greenland ice sheet (GrIS) melt is released only at the ocean surface or when it is distributed over the upper water column in accordance with fjord melt plume behavior; these cases were compared with a no GrIS melt case. West Greenland continental shelf currents were fastest in the vertical distribution case and an increase in baroclinic conversion at the shelf break associated with increased eddy kinetic energy was found relative to the surface release case. Further, salinity is lower and meltwater volume greater in the eastern Labrador Sea in the vertical distribution case. For the Arctic, the veracity of the UH8to2 was evaluated for 2017-2020 using available observations. Simulated seasonal sea-ice thickness and concentration are realistic, but the ice is unrealistically thin in the central and eastern Arctic in the fall. Comparisons of vertical sections of ocean temperature, salinity, and buoyancy collected from Ice-Tethered Profilers (ITPs) in the eastern Arctic in the fall and winter of 2019/2020 and co-located/concurrent UH8to2 fields show the stratification over the top 100 m of the water column is too low in the model, the simulated mixed layer too deep, and the simulated subsurface Atlantic Water (AW) too warm; these biases may contribute to the sea-ice biases. A model intercomparison study using the UH8to2 and a forced 1/25° regional Arctic ocean/sea-ice (uses the HYbrid Coordinate Ocean Model and CICE5) simulation further investigates the relationship between AW and sea-ice in the eastern Arctic. The models show a mesoscale-rich pulse of Atlantic Water extending into the eastern basin that reaches maximum intensity in late winter of 2018, after which it decreases in strength. Concurrent and co-located sea-ice melt or the inhibition of sea-ice growth is seen and is attributed to halocline mesoscale eddies doming into the mixed layer with convection bringing this heat into the vicinity of the sea-ice.

58 GEOSCIENCES↗

Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy

Abstract. The Mesoscale to Microscale Coupling team, part of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative, has studied various important challenges related to coupling mesoscale models to microscale models for the use case of wind energy development and operation. Several coupling methods and techniques for generating turbulence at the microscale that is subgrid to the mesoscale have been evaluated for a variety of cases. Case studies included flat-terrain, complex-terrain, and offshore environments. Methods were developed to bridge the terra incognita, which scales from about 100 m through the depth of the boundary layer. The team used wind-relevant metrics and archived code, case information, and assessment tools and is making those widely available. Lessons learned and discerned best practices are described in the context of the cases studied for the purpose of enabling further deployment of wind energy.

17 WIND ENERGY↗

Tunable Nanoscale Evolution and Topological Phase Transitions of a Polar Vortex Supercrystal

Here, understanding the phase transitions and domain evolutions of mesoscale topological structures in ferroic materials is critical to realizing their potential applications in next-generation high-performance storage devices. Here, the behaviors of a mesoscale supercrystal are studied with 3D nanoscale periodicity and rotational topology phases in a PbTiO 3 /SrTiO 3 (PTO/STO) superlattice under thermal and electrical stimuli using a combination of phase-field simulations and X-ray diffraction experiments. A phase diagram of temperature versus polar state is constructed, showing the formation of the supercrystal from a mixed vortex and α-twin state and a temperature-dependent erasing process of a supercrystal returning to a classical α-twin structure. Under an in-plane electric field bias at room temperature, the vortex topology of the supercrystal irreversibly transforms to a new type of stripe-like supercrystal. Under an out-of-plane electric field, the vortices inside the supercrystal undergo a topological phase transition to polar skyrmions. These results demonstrate the potential for the on-demand manipulation of polar topology and transformations in supercrystals using electric fields. The findings provide a theoretical understanding that may be utilized to guide the design and control of mesoscale polar structures and to explore novel polar structures in other systems and their topological nature.

P=phase-field simulations↗

Orographic enhancement of rainfall over the Congo Basin

Abstract The Congo rainforest located in central equatorial Africa is an important, yet understudied part of the globe surrounded by complex orographic features. A primitive understanding of precipitation processes such as mesoscale convective dynamics magnifies uncertainties in the future climate projections of the hydrological cycle over the Congo. Furthermore, the effects of orography, which is an important forcing for convection and precipitation, are poorly resolved by climate models, and ill‐conceptualized over the Congo. To address this knowledge gap, perturbed orographic forcing experiments are conducted using the Weather Research and Forecasting (WRF) mesoscale numerical model in a high‐resolution convection‐permitting model setup. The model simulated selected dates in November 2014. The thunderstorms and rainfall simulated in the control run for the case study analyzed in this article compared reasonably well to satellite‐derived brightness temperature and rainfall data. The results from this case study show that the dynamical impact of increasing the height of the East African Highlands is the blocking of the lower‐tropospheric tropical easterlies. This weakening of the lower‐tropospheric zonal winds increases the windshear over the Congo Basin resulting in slower propagating, more intense mesoscale convective systems with enhanced rainfall.

54 ENVIRONMENTAL SCIENCES↗

Modeling Arctic boundary layer cloud streets at grey-zone resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds, we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiagvik (formerly Barrow), Alaska on 2 May 2013 and were observed by the Moderate Resolution Imaging Spectroradiometer (MODIS). The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain. We investigated the model-simulated mesoscale environment, horizontal and vertical cloud structures, boundary layer stability, and cloud properties, all of which were subsequently used to interpret the observed roll-cloud case. Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer. The clouds were stratiform-like in the mesoscale domain, but as the model resolution increased, roll-like structures, aligned along the wind field, appeared with ever smaller wavelengths. A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing. With fixed model grid spacing at 0.333 km, changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment, a stronger vertical water vapor gradient below the cloud layers, and the wavelengths of the rolls decreased slightly. In this study, only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Lai, Hui-Wen↗

Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments

The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.

36 MATERIALS SCIENCE↗

A multi-length-scale investigation of the applicability of ductility laws for annealed and work-hardened copper

Small-scale mechanical testing provides unique advantages over conventional testing in investigating the mechanical response of nuclear materials. While small-scale testing enables accelerated materials research, it raises the question of comparability to large-scale properties for engineering design considerations. Among different mechanical properties for structural design considerations such as yield and ultimate tensile stress, ductility is of critical importance with respect to structural component health. The effectiveness of using small-scale mechanical testing for probing these mechanical properties is dictated by understanding how the mechanical responses translate from the microscale to the engineering scale. Therefore, a better understanding of size scaling effects via gathering and analysis of experimental data is required to bridge length-scales. Further, this work builds upon previous reports to provide statistical data on how mechanical response changes as the size of the specimens are reduced from conventional sizes. One hundred twenty mesoscale tensile coupons of oxygen-free high thermal conductivity (OFHC) copper in work-hardened and annealed state have been manufactured using micro-wire electrical discharge machining (EDM) and tested under uniaxial tension. The mesoscale specimens have dimensions dictated by pre-selected geometric ratios (i.e., gauge section length over the square root of the cross-section area) with gauge length dimensions of 3 mm (or less) and sub-millimeter gauge widths and thicknesses. The mesoscale responses were compared to bulkscale properties to reveal the effect of specimen size on the mechanical response as a function of grain size and material state for a single phase face-centered cubic metal.

36 MATERIALS SCIENCE↗

An evaluation of meteorological data prediction over Washington, D.C.: Comparison of DCNet observations and NAM model outputs

This study presents an example of how outputs of operational and readily-available mesoscale numerical models can be adapted to initialize dispersion calculations within the urban surface roughness layer. Three years of urban meteorological observations from central Washington, DC, are compared against forecast outputs of the North American Mesoscale (NAM) model. NAM wind speed predictions underestimate the observations in light winds and overestimate the measurements in high winds. Average wind directions are consistent. However, an adjustment of the predicted direction of the plume by –20° is needed. The uncertainty associated with this adjustment is large in light NAM wind speed with no evident variation by season. The values of the standard deviation of the wind direction, σθ derived from NAM model outputs underestimate the observations by a small amount (about –1.5 to –2.5°). The results presented here indicate that mesoscale numerical model outputs can provide information adequate for dispersion calculations. However, levels of uncertainty associated with implementation of the suggested procedures increase with decreasing wind speed, causing considerable uncertainty in the implementation of adjustments as low wind speed conditions are approached. Results and recommendations reported here should not be extended to other numerical models or other cities without further testing.

54 ENVIRONMENTAL SCIENCES↗

Development of a Filtered CFD-DEM Drag Model with Multiscale Markers Using an Artificial Neural Network and Nonlinear Regression

Here, the accuracy of coarse-grained Euler-Lagrangian simulations of fluidized beds heavily depends on the mesoscale drag models to account for the influences of the unresolved sub-grid structures. Traditional filtered drag models are regressed with mesoscale markers such as voidage and slip velocities. In this research, a filtered drag was regressed with both mesoscale and macro-scale markers using fine grid Computational Fluid Dynamics - Discrete Element Method (CFD-DEM) simulations. The traditional non-linear regression method was compared with machine learning regression using an Artificial Neural Network (ANN) implemented in PyTorch and coupled with MFiX. The new drag showed higher accuracy than the Wen-Yu drag and another filtered drag derived from the two-fluid model. The nonlinear regression shows slightly better results than ANN regression in cases with similar R 2 values. The utilization of the gas inlet velocity as an additional macro-scale marker reduced the errors by up to 55.3% in the tested cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning the Solvation and Solubility Properties of Molecularly Heterogeneous Nonionic Deep Eutectic Solvents via Interface Organization

Common separation techniques, such as liquid− liquid extraction, are usually used for extractions and purifications due to their industrial scalability and affordability. However, these well-established practices are hindered by low selectivity and challenges in recovering solutes and solvents. Deep eutectic solvents (DES), a fairly new type of solvent, have the potential to overcome these issues. DESs are binary mixtures whose physical properties can be tuned by selecting the appropriate precursors to facilitate and/or enhance processes such as extraction. A promising DES for selective separations is formed when lauric acid (LA) is mixed with N-methylacetamide (NMA). This LA-NMA DES has a heterogeneous microscopic structure that can solvate compounds with completely different polarities. This study explores how forming an organized structure on the mesoscale affects the solubility of nonpolar solutes in nonionic DESs. To this end, the molecular and mesoscale structures and their effect on the solubility and solvation properties are evaluated for the LA-NMA DES and two new DESs with slight chemical variations in their precursors. It is observed that the organization of the nonpolar DES domains and, consequently, of their interfaces directly relates to the solubility of nonpolar compounds. Specifically, correctly selecting the DES precursors that form organized nonpolar domains leads to an organized interface in which the nonpolar solutes are solvated, thereby increasing the solubility. Additionally, enhanced dissolution power was observed in a completely different DES with mesoscale order in its molecular structure and composed of menthol and lauric acid. The latter result further validates the proposed tunability of the DES dissolution power through organized interfaces, extending it beyond a specific DES family and opening the possibility of new extraction-tailored designer solvents.

Extraction↗

Structure of Complex Liquid–Liquid Extraction Organic Phases for Rare Earth Separations

Complex, multicomponent liquids with hierarchical structure and phase transitions are encountered in many natural and industrial processes, including in chemical separations. One notable example is aggregation and organic phase splitting in liquid–liquid extraction (LLE) of metal ions. While these two phenomena that have long been closely associated, a mechanistic link between mesoscale structure and the capacity-limiting organic phase splitting remains elusive due to complexity of these systems. Here, in this study, we combine small-angle X-ray scattering (SAXS), X-ray photon correlation spectroscopy (XPCS), and molecular dynamics simulation to reveal a comprehensive picture of structure at the nano- and mesoscale in these complex solutions. For the representative case of rare earth extraction from an acidic aqueous phase by a malonamide extractant in dodecane, we investigate a wide range of process-relevant extractant and acid concentrations to provide a complete picture of how aggregation depends on composition. We decompose organic phase structure from SAXS into two contributions, which together can capture the scattering at all compositions: composition fluctuations described by the Ornstein–Zernike equation at low wavenumber Q, and nanostructure modeled by a “pre-peak” at intermediate Q. The former contains information about the thermodynamics of demixing, while the latter reflects nanoscopic self-assembly of the extractant and extracted solutes. While fluctuations have typically not been considered in the literature, we find they in fact dominate the total structure for nearly all practical conditions. As only the fluctuations have a strong temperature response, we confirm this attribution with temperature-dependent SAXS measurements, including for extracted europium nitrate complexes. SAXS and XPCS measurements near the critical point find static and dynamic scaling consistent with theory. Overall, this new paradigm for understanding LLE organic phases connects composition, nanoscale, and mesoscale structuring to phase behavior, providing both a comprehensive picture of solution structure and a quantitative link between aggregation and third phase formation.

Peroutka, Allison A. [Argonne National Laboratory ↗

Lithium Plating Characteristics in High Areal Capacity Li-Ion Battery Electrodes

Li-ion battery degradation and safety events are often attributed to undesirable metallic lithium plating. Since their release, Li-ion battery electrodes have been made progressively thicker to provide a higher energy density. However, the propensity for plating in these thicker pairings is not well understood. Herein, we combine an experimental plating-prone condition with robust mesoscale modeling to examine electrode pairings with capacities ranging from 2.5 to 6 mAh/cm 2 and negative to positive (N/P) electrode areal capacity ratio from 0.9 to 1.8 without the need for extensive aging tests. Using both experimentation and a mesoscale model, we identify a shift from conventional high state-of-charge (SOC) type plating to high overpotential (OP) type plating as electrode thickness increases. Further, these two plating modes have distinct morphologies, identified by optical microscopy and electrochemical signatures. We demonstrate that under operating conditions where these plating modes converge, a high propensity of plating exists, revealing the importance of predicting and avoiding this overlap for a given electrode pairing. Further, we identify that thicker electrodes, beyond a capacity of 3 mAh/cm 2 or thickness >75 μm, are prone to high OP, limiting negative electrode (NE) utilization and preventing cross-sectional oversizing the NE from mitigating plating. Here, it simply contributes to added mass and volume. The experimental thermal gradient and mesoscale model either combined or independently provide techniques capable of probing performance and safety implications of mild changes to electrode design features.

25 ENERGY STORAGE↗

Pressure Induced Assembly and Coalescence of Lead Chalcogenide Nanocrystals

We report here pressure induced nanocrystal coalescence of ordered lead chalcogenide nanocrystal arrays into one dimensional (1D) and 2D nanostructures. In particular, atomic crystal phase transitions and mesoscale coalescence of PbS and PbSe nanocrystals have been observed and monitored in-situ respectively by wide- and small-angle synchrotron X-ray scattering techniques. At the atomic scale, both nanocrystals underwent reversible structural transformations from cubic to orthorhombic at significantly higher pressures than those for the corresponding bulk materials. At the mesoscale, PbS nanocrystal arrays displayed a superlattice transformation from face-centered cubic to lamellar structures, while no clear mesoscale lattice transformation was observed for PbSe nanocrystal arrays. Intriguingly, transmission electron microscopy (TEM) showed that the applied pressure forced both spherical nanocrystals to coalesce into single crystalline 2D nanosheets and 1D nanorods. Our results confirm that pressure can be used as a straightforward approach to manipulate the interparticle spacing and engineer nanostructures with specific morphologies, and therefore provide insights into the design and functioning of new semiconductor nanocrystal structures under high-pressure conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimization and Evaluation of Stochastic Unified Convection Using Single-Column Model Simulations at Multiple Observation Sites

We extend the previously developed stochastic unified convection scheme (UNICON) for shallow convection to deep convection by parameterizing the impact of mesoscale organized flow on updraft properties. The extended stochastic UNICON parameterizes thermodynamic properties of updrafts at the near-surface as a multivariate Gaussian distribution, where the variances of the distribution are the summation of variances from non-organized turbulence and mesoscale organized flow. The distribution of updraft radius is parameterized as a power-law distribution with a scale break which is parameterized as a linear function of the strength of mesoscale organized flow. The proposed parameterization is validated using a series of large-eddy simulations of deep convection. The free parameters introduced in the formulation of stochastic UNICON are optimized using 10 cases of single-column model simulations over the ocean. Stochastic UNICON with the optimized parameters significantly reduces the biases of thermodynamic profiles and surface precipitation rates simulated in the original UNICON for tropical convection cases. The simulation of the variation in anomalies of temperature and moisture associated with the Madden-Julian oscillation is also improved. The overall improvements in simulated thermodynamic profiles are found to be due to the increased heating and drying tendencies by convective processes in stochastic UNICON. An additional simulation of an idealized deep convection case shows that stochastic UNICON produces enhanced cloud variabilities with dependency on updraft radius, indicating its ability to represent the coexistence of shallow and deep convection.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of a Stochastic Mixing Scheme in the Deep Convective Gray Zone Using a Tropical Oceanic Deep Convection Case Study

Abstract A stochastic horizontal subgrid‐scale mixing scheme is evaluated in ensemble simulations of a tropical oceanic deep convection case using a horizontal grid spacing (Δ h ) of 3 km. The stochastic scheme, which perturbs the horizontal mixing coefficient according to a prescribed spatiotemporal autocorrelation scale, is found to generally increase mesoscale organization and convective intensity relative to a non‐stochastic control simulation. Perturbations applied at relatively short autocorrelation scales induce differences relative to the control that are more systematic than those from perturbations applied at relatively long scales that yield more variable outcomes. A simulation with mixing enhanced by a constant factor of 4 significantly increases mesoscale organization and convective intensity, while turning off horizontal subgrid‐scale mixing decreases both. Total rainfall is modulated by a combination of mesoscale organization, areal coverage of convection, and convective intensity. The stochastic simulations tend to behave more similarly to the constant enhanced mixing simulation owing to greater impacts from enhanced mixing as compared to reduced mixing. The impacts of stochastic mixing are robust, ascertained by comparing the stochastic mixing ensembles with a non‐stochastic mixing ensemble that has grid‐scale noise added to the initial thermodynamic field. Compared to radar observations and a higher resolution Δ h = 1 km simulation, stochastic mixing seemingly degrades the simulation performance. These results imply that stochastic mixing produces non‐negligible impacts on convective system properties and evolution but does not lead to an improved representation of convective cloud characteristics in the case studied here.

54 ENVIRONMENTAL SCIENCES↗