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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Numerical case study of the aerosol–cloud interactions in warm boundary layer clouds over the eastern North Atlantic with an interactive chemistry module

The presence of warm boundary layer stratiform clouds over the eastern North Atlantic (ENA) region is commonly influenced by the Azores High, especially during the summer season. To investigate comprehensive aerosol–cloud interactions, this study employs the Weather Research and Forecasting model coupled with a chemistry component (WRF-Chem), incorporating aerosol chemical components that are relevant to the formation of cloud condensation nuclei (CCN) and accounting for aerosol spatiotemporal variation. This study focuses on aerosol indirect effects, particularly the long-range transport of aerosols, in the ENA region under three different weather regimes: a ridge with a surface high-pressure system, a post-trough with a surface high-pressure system, and a weak trough. The WRF-Chem simulations conducted at a near-large-eddy scale offer valuable insights into the model's performance, especially in terms of its ability to use high spatial resolution to capture mesoscale cloud features across various weather regimes. Our result shows that introducing 5 times more aerosols to either non-precipitating or precipitating clouds significantly increases ambient CCN numbers, resulting in, to varying degrees, higher liquid water path (LWP) values. The substantial aerosol–cloud interaction especially occurs in the precipitating clouds and demonstrates the susceptibility of the LWP to changes in CCN under different regimes. Conversely, thin, non-rain clouds at the edges of a cloud system are prone to evaporation, exhibiting an aerosol drying effect. The aerosols released during this process transition back to the accumulation mode, facilitating future activation. This dynamic behavior is not adequately represented in prescribed-aerosol simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Drizzle, Turbulence, and Density Currents Below Post Cold Frontal Open Cellular Marine Stratocumulus Clouds

Nine cases of postcold frontal marine stratocumulus clouds exhibiting open cellular mesoscale organization are analyzed to characterize the drizzle, turbulence, and density currents below them. Data collected by the vertically pointing Doppler cloud radar and multiple lidars part of the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site are used in these analyses. A total of 251 drizzle shafts passed over the site with 76 shafts sampled for more than 15 min by the vertically pointing instruments. On average the drizzle shafts were ~18 km wide with below-cloud drizzle water path of ~40 g m −2 , cloud base rain rate of 7.78 mm day −1 , and cloud base drizzle modal diameter of 393 μm. The widths of the drizzle shafts did not exhibit any relationship with the cloud base rain rate, below-cloud drizzle water path, and the total water removed from the cloud. The downdrafts in the lowest 500 m within the drizzle cells strengthened with increasing cloud base rain rates, while the updrafts within drizzle cells did not exhibit this behavior. On average, the surface air density, pressure, water vapor mixing ratio, and wind speed along the background wind during the drizzle shaft were higher by 1.88 g m −3 , 8.60 Pa, 0.24 g kg −1 , and 1.22 m s −1 , respectively, from their background values. On the other hand, the surface air temperature was lower by 0.43 K during the drizzle shaft than its background value. The coincident measurements highlight the drizzle-turbulence-surface coupling in these cloud systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Resolving Mesoscale Convective Systems: Grid Spacing Sensitivity in the Tropics and Midlatitudes

Abstract Mesoscale convective systems (MCSs) are a critical global water cycle component and drive extreme precipitation events in tropical and midlatitude regions. However, simulating deep convection remains challenging for modern numerical weather and climate models due to the complex interactions of processes from microscales to synoptic scales. Recent models with kilometer‐scale horizontal grid spacings offer notable improvements in simulating deep convection compared to coarser‐resolution models. Still, deficiencies in representing key physical processes, such as entrainment, lead to systematic biases. Additionally, evaluating model outputs using process‐oriented observational data remain difficult. This study presents an ensemble of MCS simulations with spanning the deep convective gray zone ( from 12 km to 125 m) in the Southern Great Plains of the U.S. and the Amazon Basin. Comparing these simulations with Atmospheric Radiation Measurement (ARM) wind profiler observations, we find greater sensitivity in the Amazon Basin compared to the Great Plains. Convective drafts converge structurally at sub‐kilometer scales, but some deficiencies remain. In both regions, simulated up and downdrafts are too deep and extreme downdrafts are not strong enough. Furthermore, Amazonian updrafts are too strong. Overall, we observe higher sensitivity in the tropics, including an artificial buildup in vertical kinetic energy at scales of , suggesting a need for 250 m in this region. Nevertheless, bulk convergence—agreement of storm‐average statistics—is achievable with kilometer‐scale simulations within a 10% error margin with 1 km providing a good balance between accuracy and computational cost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The GFDL Variable-Resolution Global Chemistry-Climate Model for Research at the Nexus of US Climate and Air Quality Extremes

We present a variable-resolution global chemistry-climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban-to-rural chemical regimes, mesoscale convective systems, and land-surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi-decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25-km uniform-resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal-to-diurnal cycles and extremes, notably reducing the central US dry-and-warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process-level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land-biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Efficacy of the Cell Perturbation Method in Large-Eddy Simulations of Boundary Layer Flow over Complex Terrain

A challenge to simulating turbulent flow in multiscale atmospheric applications is the efficient generation of resolved turbulence motions over an area of interest. One approach is to apply small perturbations to flow variables near the inflow planes of turbulence-resolving simulation domains nested within larger mesoscale domains. While this approach has been examined in numerous idealized and simple terrain cases, its efficacy in complex terrain environments has not yet been fully explored. Here, we examine the benefits of the stochastic cell perturbation method (CPM) over real complex terrain using data from the 2017 Perdigão field campaign, conducted in an approximately 2-km wide valley situated between two nearly parallel ridges. Following a typical configuration for multiscale simulation using nested domains within the Weather Research and Forecasting (WRF) model to downscale from the mesoscale to a large-eddy simulation (LES), we apply the CPM on a domain with horizontal grid spacing of 150 m. At this resolution, spurious coherent structures are often observed under unstable atmospheric conditions with moderate mean wind speeds. Results from such an intermediate resolution grid are often nested down for finer, more detailed LES, where these spurious structures adversely affect the development of turbulence on the subsequent finer grid nest. We therefore examine the impacts of the CPM on the representation of turbulence within the nested LES domain under moderate mean flow conditions in three different stability regimes: weakly convective, strongly convective, and weakly stable. In addition, two different resolutions of the underlying terrain are used to explore the role of the complex topography itself in generating turbulent structures. We demonstrate that the CPM improves the representation of turbulence within the LES domain, relative to the use of high-resolution complex terrain alone. During the convective conditions, the CPM improves the rate at which smaller-scales of turbulence form, while also accelerating the attenuation of the spurious numerically generated roll structures near the inflow boundary. During stable conditions, the coarse mesh spacing of the intermediate LES domain used herein was insufficient to maintain resolved turbulence using CPM as the flow develops downstream, highlighting the need for yet higher resolution under even weakly stable conditions, and the importance of accurate representation of flow on intermediate LES grids.

17 WIND ENERGY↗
DOE OSTI2022

Novel fabrication tools for dynamic compression targets with engineered voids using photolithography methods

Mesoscale imperfections, such as pores and voids, can strongly modify the properties and the mechanical response of materials under extreme conditions. Tracking the material response and microstructure evolution during void collapse is crucial for understanding its performance. In particular, imperfections in the ablator materials, such as voids, can limit the efficiency of the fusion reaction and ultimately hinder ignition. To characterize how voids influence the response of materials during dynamic loading and seed hydrodynamic instabilities, we, in this paper, have developed a tailored fabrication procedure for designer targets with voids at specific locations. Our procedure uses SU-8 as a proxy for the ablator materials and hollow silica microspheres as a proxy for voids and pores. By using photolithography to design the targets’ geometry, we demonstrate precise and highly reproducible placement of a single void within the sample, which is key for a detailed understanding of its behavior under shock compression. This fabrication technique will benefit high-repetition rate experiments at x-ray and laser facilities. Insight from shock compression experiments will provide benchmarks for the next generation of microphysics modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

FY2020 Fourth Quarter Performance Metric: Evaluate Improvement in Simulations of Mesoscale Convective Systems from New Parameterization Developments in E3SM

Mesoscale convective systems (MCSs) consist of an assembly of cumulonimbus clouds on scales of 100 km or more and produce mesoscale circulations (Houze, 2004, 2018). As the largest form of deep convective storms, MCSs contribute to 30% – 70% of annual and warm season rainfall in the U.S. and in the global tropics (Houze 2018; Stevenson & Schumacher, 2014; Feng et al., 2019; Haberlie & Ashley, 2019). Since MCSs contribute importantly to mean and extreme precipitation in the U.S. and many other regions around the world, understanding how well they are simulated by E3SM may guide future development towards more skillful modeling of convective storms and associated hydrologic impacts. The FY2020 Second Quarter Performance Metric Report documented comparisons of MCSs in the central and eastern U.S. in a high-resolution simulation produced by E3SM v1 at 25 km resolution (Caldwell et al. 2019) with observations. MCSs in the simulation occur less frequently and produce less intense precipitation, resulting in large underestimation of MCS volumetric rain-rate compared to observations. The first and third quarter performance metric report indicated that these model biases in simulating MCSs can be attributed to model limitations in parameterizing convection, clouds, and other related processes, as well as model biases in simulating the MCS large-scale environment. In the current FY2020 Fourth Quarter Performance Metric Report, we evaluate MCSs simulated in E3SM with several new developments in convection parameterizations that are being developed for its next generation. The goal is to summarize what have been improved with the new developments and highlight what need more work in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Convection-Permitting Ensembles of an Isolated Mountain Thunderstorm during RELAMPAGO/CACTI

Abstract The north–south-oriented Sierras de Córdoba (SDC) ridge in central Argentina is noted for initiating thunderstorms that may grow into intense mesoscale convective systems (MCSs). It also initiates more isolated, shorter-lived cells under weaker synoptic forcing. These cells are less impactful than MCSs but may be difficult to predict in convective-scale numerical weather prediction (NWP) due to their strong sensitivities to subgrid and partially resolved processes. To study the mechanisms and predictability of such cells, convection-permitting ensemble simulations were conducted of an isolated, diurnally forced SDC thunderstorm during Cloud, Aerosol, and Complex Terrain Interactions (CACTI)/Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO). The rich observational data facilitated detailed ensemble verification, where dry biases in the surface energy balance and soil moisture were identified. These biases promoted rapid removal of convective inhibition and an early onset of precipitating cells over the SDC that were shallower and weaker than the observed cell. Correction, and then overcorrection, of the soil moisture bias in two successive ensembles was required to rectify the surface energy balance and improve the representation of the SDC cell. Nevertheless, substantial ensemble variability in convective precipitation was found, with some members producing more widespread convection than observed and others producing no deep convection at all. This variability was largely explained by a combination of thermodynamic and dynamic mechanisms, dominated by a positive sensitivity of convective precipitation to preconvective moist instability over the ridge. Secondary sensitivities were found to low-level upward mass flux and midlevel cross-barrier winds, the latter of which caused gravity waves with elevated downdrafts that tended to suppress incipient clouds.

Lopez, Andres [Department of Atmospheric and Ocean↗
DOE OSTI2024

Characterizing Mesoscale Cellular Convection in Marine Cold Air Outbreaks With a Machine Learning Approach

Abstract During marine cold‐air outbreaks (MCAOs), when cold polar air moves over warmer ocean, a well‐recognized cloud pattern develops, with open or closed mesoscale cellular convection (MCC) at larger fetch over open water. The Cold‐Air Outbreaks in the Marine Boundary Layer Experiment provided a comprehensive set of ground‐based in situ and remote sensing observations of MCAOs at a coastal location in northern Norway. MCAO periods that unambiguously exhibit open or closed MCC are determined. Individual cells observed with a profiling Ka‐band radar are identified using a watershed segmentation method. Using self‐organizing maps (SOMs), these cells are then objectively classified based on the variability in their vertical structure. The SOM nodes contain some information about the location of the cell transect relative to the center of the MCC. This adds classification noise, requiring numerous cell transects to isolate cell dynamical information. The SOM‐based classification shows that comparatively intense convection occurs only in open MCC. This convection undergoes an apparent lifecycle. Developing cells are associated with stronger updrafts, large spectrum width, larger amounts of liquid water, lower surface precipitation rates, and lower cloud tops than mature and weakening cells. The weakening of these cells is associated with the development of precipitation‐induced cold pools. The SOM classification also reveals less intense convection, with a similar lifecycle. More stratiform vertical cloud structures with weak vertical motions are common during closed MCC periods and are separated into precipitating and non‐precipitating stratiform cores. Convection is observed only occasionally in the closed MCC environment.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Assessing turbulence and mixing parameterizations in the gray-zone of multiscale simulations over mountainous terrain during the METEX21 field experiment

Multiscale numerical weather prediction models transition from mesoscale, where turbulence is fully parameterized, to microscale, where the majority of highly energetic scales of turbulence are resolved. The turbulence gray-zone is situated between these two regimes and multiscale models must downscale through these resolutions. Here, we compare three multiscale simulations which vary by the parameterization used for turbulence and mixing within the gray-zone. The three parameterizations analyzed are the Mellor-Yamada Nakanishi and Niino (MYNN) Level 2.5 planetary boundary layer scheme, the TKE-1.5 large eddy simulation (LES) closure scheme, and a recently developed three-dimensional planetary boundary layer scheme based on the Mellor-Yamada model. The simulation domain includes complex (i.e., mountainous) terrain in Nevada that was instrumented with meteorological towers, profiling and scanning lidars, a tethered balloon, and a surface flux tower. Simulations are compared to each other and to observations, with assessment of model skill at predicting wind speed, wind direction and TKE, and qualitative evaluations of transport and dispersion of smoke from controlled releases. This analysis demonstrates that microscale predictions of transport and dispersion can be significantly influenced by the choice of turbulence and mixing parameterization in the terra incognita , particularly over regions of complex terrain and with strong local forcing. This influence may not be apparent in the analysis of model skill, and motivates future field campaigns involving controlled tracer releases and corresponding modeling studies of the turbulence gray-zone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A derecho climatology (2004–2021) in the United States based on machine learning identification of bow echoes

Due to their persistent widespread severe winds, derechos pose significant threats to human safety and property, with impacts comparable to many tornadoes and hurricanes. Yet, automated detection of derechos remains challenging due to the absence of spatiotemporally continuous observations and the complex criteria employed to define the phenomenon. This study presents an objective derecho detection approach capable of automatically identifying derechos through both observations and model results. The approach is grounded in a physically based definition of derechos and integrates three algorithms: (1) the Python Flexible Object Tracker (PyFLEXTRKR) algorithm to track mesoscale convective systems (MCSs), (2) a semantic segmentation convolutional neural network to identify bow echoes, and (3) a comprehensive classification algorithm to detect derechos within MCS life cycles and distinguish derecho-producing from non-derecho-producing MCSs. Using this approach, we developed a novel high-resolution (4 km and hourly) observational dataset of derechos and accompanying derecho-producing MCSs over the United States east of the Rocky Mountains from 2004 to 2021. The dataset consists of two subsets based on different gust speed data sources and is analyzed to document the climatology of derechos in the United States. On average, 12–15 derechos are identified per year, aligning with previous estimations (∼6–21 events annually). The spatial distribution and seasonal variation patterns are consistent with prior studies, showing peak occurrences in the Great Plains and the Midwest during the warm season. Additionally, during the study period, derechos account for approximately 3.1 % of measured damaging gusts (≥25.93 m s−1) over the eastern United States. The dataset is publicly available at https://doi.org/10.5281/zenodo.14835362 (Li et al., 2025).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Atmospheric Constraints on Landing Site Selection

The Martian atmosphere is a significant part of the environment that the Mars Exploration Rovers (MER) will encounter. As such, it imposes important constraints on where the rovers can and cannot land. Unfortunately, as there are no meteorological instruments on the rovers, there is little atmospheric science that can be accomplished, and no scientific preference for landing sites. The atmosphere constrains landing site selection in two main areas, the entry descent and landing (EDL) process and the survivability of the rovers on the surface. EDL is influenced by the density profile and boundary layer winds (up to altitudes of 5 to 10 km). Surface survivability involves atmospheric dust, temperatures and winds. During EDL, the atmosphere is used to slow the lander down, both ballistically and on the parachute. This limits the maximum elevation of the landing site to -1.3 km below the MOLA reference aeroid. The landers need to encounter a sufficiently dense atmosphere to be able to stop, and the deeper the landing site, the more column integrated atmosphere the lander can pass through before reaching the surface. The current limit was determined both by a desire to be able to reach the hematite region and by a set of atmosphere models we developed for EDL simulations. These are based on Thermal Emission Spectrometer (TES) atmospheric profile measurements, Ames Mars General Circulation Model (MGCM) results, and the 1-D Ames GCM radiative/convective model by J. Murphy. The latter is used for the near surface diurnal cycle. The current version of our model encompasses representative latitude bands, but we intend to make specific models for the final candidate landing sites to insure that they fall within the general envelope. The second constraint imposed on potential landing sites through the EDL process is the near surface wind. The wind in the lower approximately 5 km determines the horizontal velocity that the landers have when they land. Due to the mechanics of the landing process, the total velocity (including both the horizontal and vertical components) determines whether or not the landers are successful. Unfortunately, the landing system has no easy way to nullify any horizontal velocity imparted by the wind, so the landing sites selected need to have as little wind as possible. In addition to the mean wind velocity, the landing system is sensitive to vertical wind shear in the lowest kilometer or so. Wind shear can deflect the retro rockets (RADs) from their nominal vertical orientation producing unwanted horizontal spacecraft velocities. Both mean velocity and wind shear are dominated by the the local topography and other surface properties (in particular albedo and thermal inertia which control the surface temperature). This is seen even in simplified 2-D mesoscale models. The effects in a fully 3-D model are expected to he even more topographically dependent. In particular there is potential for wind channeling in canyons and other terrain features. Boundary layer winds and wind shear are currently being modeled based on terrestrial data and boundary layer scaling laws modified for Martian conditions. We hope to supplement this with mesoscale model results (from several sources) once the number of landing sites is reduced to a manageable number.

Kass, David M.↗
DOE OSTI2026

Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation

The performance of rechargeable batteries is fundamentally influenced by the physicochemical properties and microstructural features of their key material components. Recent experimental advancements have highlighted the potential of single-crystal (SC) morphologies to address inherent limitations of polycrystalline (PC) electrodes and solid-state electrolytes, offering tunable charge transport kinetics and improved cell cycling performance. Here, this review examines how state-of-the-art computational modeling, from atomistic and mesoscale to continuum-level approaches, including machine learning methodologies, has been utilized to investigate the critical factors governing the electrochemical behavior of SC battery materials. We explore how predictive modeling can elucidate the processing–structure–property–performance relationships of SC cathodes, anodes, and solid-state electrolytes, with a focus on unique SC characteristics such as crystallographic anisotropy, size effects, and facet-dependent properties. Additionally, we identify limitations in commonly used modeling techniques and discuss strategies to address these challenges. By integrating high-fidelity simulations with experimental insights, this review aims to outline a clear path for the rational design and optimization of SC battery components, paving the way for accelerated advancements in energy storage technologies.

Materials science↗
DOE OSTI2025

Effectiveness of street trees in reducing air temperature and outdoor heat exposure in Las Vegas

Urban greening and especially tree planting strategies are being widely planned and implemented to mitigate urban overheating and thermal stress in many urban areas. However, the effectiveness of these strategies depends on multiple factors, including urban morphology, environmental conditions, and tree characteristics. This study investigates the effects of street tree planting strategies on air temperature and outdoor heat exposure in Las Vegas by combining an urbanized mesoscale climate model coupled to a multi-layer street tree model (Weather Research and Forecasting-BEP-Tree; Δ x = 900 m) with a microscale pedestrian heat exposure model (Temperatures of Urban Facets for Pedestrian; Δ x = 1 m). A series of simulations are conducted for July and August 2022. Large city-wide increases of a drought tolerant tree species cool air temperature mainly during the nighttime (up to 1.5 °C), with daytime effects being limited due to leaves shedding sensible instead of latent heat as stomata close in response to high vapor pressure deficits. Increased evaporative cooling is achieved with a different tree species (double at night, and reaching 0.4 °C during the day), but water requirements increase threefold. Despite their relatively small effect on air temperature during the day, trees provide significant shade by intercepting solar radiation, reducing mean radiant temperature (up to 16 °C) and enhancing outdoor thermal comfort, a major benefit of street trees in hot arid climates. The nighttime cooling of trees and the daytime reduction of radiant loading show potential to reduce the heat-related health impacts. Our results highlight the need to evaluate the effects of street trees on a case-by-case basis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sensitivity of organized convective storms to model grid spacing in current and future climates

Mesoscale convective systems (MCSs) are complexes of thunderstorms that become organized and cover hundreds of kilometres over several hours. MCSs are prolific rain producers in the tropics and mid-latitudes and are the major cause of warm-season flooding. Traditionally, climate models have difficulties in simulating MCSs partly due to the misrepresentation of complex process interactions that operate across a large range of scales. Significant improvements in simulating MCSs have been found in kilometre-scale models that explicitly simulate deep convection. However, these models operate in the grey zone of turbulent motion and have known deficiencies in simulating small-scale processes (e.g. entrainment, vertical mass transport). Here, we perform mid-latitude idealized ensemble MCS simulations under current and future climate conditions in three atmospheric regimes: hydrostatic (12 km horizontal grid spacing; Δx), non-hydrostatic (Δx = 4, 2 and 1 km) and large eddy scale (Δx = 500 m and 250 m). Our results show a dramatic improvement in simulating MCS precipitation, movement, cold pools, and cloud properties when transitioning from 12 km to 4 km Δx. Decreasing Δx beyond 4 km results in modest improvements except for up- and downdraft sizes, average vertical mass fluxes, and cloud top height and temperature, which continue to change. Most important for climate modelling is that Δx = 4 km simulations reliably capture most MCS climate change signals compared to those of the Δx = 250 m runs. Significantly different climate change signals are found in Δx = 12 km runs that overestimate extreme precipitation changes by up to 100%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Encoding hierarchical 3D architecture through inverse design of programmable bonds

The ability to fabricate materials and devices at small scales by design has resulted in tremendous technological progress. However, the need for engineered three-dimensional (3D) nanoscale materials requires new strategies for organizing nanocomponents. Here we demonstrate an inverse design approach for the assembly of nanoparticles into hierarchically ordered 3D organizations using DNA voxels with directional, addressable bonds. By identifying intrinsic symmetries in repeating mesoscale structural motifs, we prescribe a set of voxels, termed a mesovoxel, that are assembled into target 3D crystals. The relationship between different degrees of encoded information used for voxel bonds and the fidelity of assembly is investigated using experimental and computational methods. We apply this assembly strategy to create periodic 3D nanoparticle ordered organizations, including structures with low-dimensional elements, helical motifs, a nanoscale analogue of a face-centred perovskite crystal and a distributed Bragg reflector based on a crystal with plasmonic and photonic length-scale regimes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mesoscale Convective Systems Simulated by a High–Resolution Global Nonhydrostatic Model Over the United States and China

Mesoscale convective systems (MCSs) contribute a large fraction of warm-season precipitation and generate hazardous weather with substantial socio-economic impacts. Uncertainties in convection parameterizations in climate models limit our understanding of MCS characteristics and reliability of future projection. We examine the MCS simulation from the global 14-km Nonhydrostatic ICosahedral Atmospheric Model (NICAM) without cumulus parameterization against satellite observation from Global Precipitation Measurement (GPM) during 2001-2008. We focus on MCSs over the central U.S. and eastern China where MCSs prevail from March to August. A process-oriented tracking method incorporating both cloud and precipitation criteria is used to identify and track MCSs. About 140/100 MCSs initiate in the central U.S./eastern China per warm season and most of them initiate east of high mountains and in coastal regions. The frequency distribution of MCS lifetime is well captured in NICAM. But the simulated MCSs have stronger precipitation, smaller precipitation area, and larger cold cloud system than observed in both regions, which may be caused by weak entrainment as it is not well resolved at 14 km resolution. Here, the simulated MCS number is also underestimated in summer. By examining the climatological and MCS large-scale environments, the significant underestimation of MCS number in summer over the central U.S. may be attributed to the large climatological dry bias in the atmosphere. For China, mean moisture in summer is well simulated but deficiency in capturing the dynamic condition related to the coastal topography for triggering convection may have contributed to underestimation of MCS even in a sufficiently moist environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains

Abstract In this study, the mesoscale convective systems (MCSs) are tracked using high-resolution radar and satellite observations over the U.S. Great Plains during April–August from 2010 to 2012. The spatiotemporal variability of MCS precipitation is then characterized using the Stage IV product. We found that the spatial variability and nocturnal peaks of MCS precipitation are primarily driven by the MCS occurrence rather than the precipitation intensity. The tracked MCSs are further classified into convective core (CC), stratiform rain (SR), and anvil clouds regions. The spatial variability and diurnal cycle of precipitation in the SR regions of MCSs are not as significant as those of MCS precipitation. In the SR regions, the high-resolution, long-term ice cloud microphysical properties [ice water content (IWC) and ice water paths (IWPs)] are provided. The IWCs generally decrease with height. Spatially, the IWC, IWP, and precipitation are all higher over the southern Great Plains than over the northern Great Plains. Seasonally, those ice and precipitation properties are all higher in summer than in spring. Comparing the peak timings of MCS precipitation and IWPs from the diurnal cycles and their composite evolutions, it is found that when using the peak timing of IWPSR as a reference, the heaviest precipitation in the MCS convective core occurs earlier, while the strongest SR precipitation occurs later. The shift of peak timings could be explained by the stratiform precipitation formation process. The IWP and precipitation relationships are different at MCS genesis, mature, and decay stages. The relationships and the transition processes from ice particles to precipitation also depend on the low-level humidity.

54 ENVIRONMENTAL SCIENCES↗