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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cloud forensics and incident response platform

A system, method, and device for cloud forensics and incident response is provided. In an embodiment, a computer-implemented method for performing cloud forensics and incident response includes intercepting, by a cloud incident response module (CIRM), communication between a virtual machine (VM) and a hypervisor. The method also includes extracting, by the CIRM, data from the communication between the VM and the hypervisor according to a forensic policy. Intercepting and extracting the data are transparent to the VM and to the hypervisor. Intercepting and extracting the data are independent of the VM and the hypervisor.

Urias, Vincent↗
DOE OSTI2021

Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM

Abstract Mesoscale convective systems (MCSs) are one of the most climatically significant forms of convection because of their large role in water and energy cycles. The mesoscale features associated with MCS are difficult to represent in climate models because the relevant dynamics and physics are absent or poorly represented with coarse model resolution (∼100 km). Using a regionally refined model (RRM) with 0.25° grid spacing embedded in the Energy Exascale Earth System Model (E3SM), we explore the impact of cloud microphysics parameterizations on the simulation of precipitation, particularly MCS precipitation over the contiguous United States. The Predicted Particle Properties (P3) cloud microphysics scheme has been modified and implemented into E3SM to overcome the limitations of the default Morrison and Gettelman (MG2) scheme in which rimed precipitating ice particles (graupel/hail) are absent and frozen particles are artificially partitioned into cloud ice and snow. We show that P3 improves the simulation of precipitation statistics including frequency distribution compared with MG2 with a limited effect on the diurnal cycle. P3 predicts higher hourly rain rates, resulting in 20% more MCSs and a higher total MCS precipitation (4.4%) compared to MG2, agreeing better with observations. The improvements with P3 mainly result from improved representations of ice microphysics, which not only produces higher rain rates through melting but also leads to a stronger large‐scale ascending motion by releasing more latent heating. This study suggests that improving microphysics parameterization is important for simulating MCS precipitation as future climate model resolutions continue to increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Important ice processes are missed by the Community Earth System Model (CESM) in Southern Ocean mixed–phase clouds: Bridging SOCRATES observations to model developments

Global climate models (GCMs) are challenged by difficulties in simulating cloud phase and cloud radiative effect over the Southern Ocean (SO). Some of the new generation GCMs predict too much liquid and too little ice in mixed-phase clouds. This misrepresentation of cloud phase in GCMs results in weaker negative cloud feedback over the SO and a higher climate sensitivity. Based on a model comparison with observational data obtained during the Southern Ocean Cloud Radiation and Aerosol Transport Experimental Study (SOCRATES), this study addresses a key uncertainty in the Community Earth System Model version 2 (CESM2) related to cloud phase, namely ice formation in pristine remote SO clouds. It is found that sea spray organic aerosols (SSOA) are the most important type of ice nucleating particles (INPs) over the SO with concentrations one order of magnitude higher than those of dust INPs based on measurements and CESM2 simulations. Secondary ice production (SIP) which includes riming splintering, rain droplet shattering, and ice-ice collisional fragmentation as implemented in CESM2 is the dominant ice production process in moderately cold clouds with cloud temperatures greater than –20°C. SIP enhances the in-cloud ice number concentrations (Ni) by 1-3 orders of magnitude and predicts more mixed-phase (with percentage occurrence increased from 15% to 21%), in better agreement with the observations. Finally, this study highlights the importance of accurately representing cloud phase over the pristine remote SO by considering the ice nucleation of SSOA and SIP processes, which are currently missing in most GCM cloud microphysics parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Automated Production of Optimization-Based Control Logics for Dynamic Facade Systems, with Experimental Application to Two-Zone External Venetian Blinds

The primary goal of this research is to devise a system that produces controllers for complex fenestration systems that perform nearly as well as Model Predictive Control but at a level of cost and implementation complexity that rivals simple heuristic controls. To this end, a cloud-based automated controller production system has been set up for a motorized external Venetian blind device, with a simple web interface that can be used by non-experts. The computation cost per controller is in the range of a few dollars, and the control logic is simple enough to be implemented on small and cheap distributed controllers. The web interface allows the user to specify some details of their particular building and window configuration, including orientation, latitude, interior geometries, and lighting and HVAC system parameters. Upon submittal, a cloud-based system configures the necessary files and commands, and then runs thousands of optimizations with them. Once the calculations are finished, the system produces a lookup table and interpolation-based controller scripts that can be used on a simple and cheap distributed controller. This paper describes the underlying models and optimization processes. It also describes the resulting control logics for two cases tested at Lawrence Berkeley National Laboratory’s Advanced Windows Testbed Facility: illuminance maximization subject to glare constraints; and lighting + HVAC energy minimization. The performance of the model-based controllers produced by the automated web-based system are compared to a heuristic ‘block beam’ controller in physical experiments at the Testbed. The experimental results are supplemented by simulation experiments with the same configuration as the Testbed. The results show the illuminance maximizing controller significantly outperforms the heuristic controller in terms of glare avoidance, and also outperforms it in terms of hours of daylight autonomy. The energy minimizing controller also outperforms the heuristic controller. This paper also discusses how the web-based system may be extended to consider other configurations, such as electrochromic windows and thermally massive HVAC systems. Potential roles for this type of system within the building design and construction industry are discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Search for a Cloud Phase Feedback in the Arctic Climate System

This project was motivated by a hypothesis involving the transition in lower troposphere temperatures across the freezing point of water. Specifically, at temperatures just below to about ten degrees below freezing, Arctic clouds should be in a mixed-phase, with strong influences from secondary ice production (e.g., the Hallett-Mossop process). At temperatures just above freezing, clouds should become entirely deglaciated. We hypothesized that, with multiple years of ARM data, a statistically significant change could be detected in cloud radiative properties and surface radiative fluxes that could be directly attributed to this phase change. Furthermore, in a gradually warming climate, these phase change-related responses in surface radiation would represent a cloud phase feedback as part of Arctic amplification. We designed this research project to coincide with a new ARM Arctic cloud radar product developed by Ed Luke and collaborators at BNL (Luke et al., 2021: PNAS, doi:10.1073/pnas.2021387118) that explicitly contains SIP cloud properties retrieved from radar data. This research project has successfully concluded after analysis of a much larger North Slope of Alaska (NSA) data sample than originally anticipated, and the results are quite different than originally hypothesized.

58 GEOSCIENCES↗
DOE OSTI2025

Data Management in the Continuum: Cross-facility Object-based Data Transfers

Scientific workflows are evolving from relying on a monolithic storage subsystem at a single High-Performance Computing (HPC) facility to using geographically distributed file systems, repositories, and cloud storage. As a result, storing, accessing, transferring, and managing scientific data have become highly complex and prone to performance inefficiencies. This paper delves into these challenges by exploring an optimized end-to-end interface designed to seamlessly connect various local and remote storage systems, enabling efficient data movement of objects across HPC–Cloud and HPC–HPC environments. We showcase this capability through an object-focused data management runtime system, discuss the effects of relaxed consistency semantics in distributed object scenarios, and illustrate its application in an earthquake simulation workflow. Besides reducing the amount of data by selectively transferring regions of interest, our facility-local results achieved a speedup of 45 × over an optimized HDF5 usage and 15 × over the HDF5 with caching by using the new interface in PDC-XF.

Bez, Jean Luca↗
DOE OSTI2022

Framework for idealized climate simulations with spatiotemporal stochastic clouds and planetary-scale circulations

In climate predictions, clouds are the leading source of uncertainty. This is partly because, to simulate the fluid dynamics of climate over the entire globe, a large grid spacing must be used, so clouds are a subgrid-scale parametrization rather than a resolved feature. Here, a framework is investigated with finer grid spacing of O(1) or O(10)km so that some clouds are not subgrid-scale; instead, clouds evolve on the numerical grid. This cloud evolution is achieved using stochastic modeling. Hence, the framework is idealized in the sense that the full fluid dynamics of cloud circulations is still not resolved, and simplified vertical structures are used. Nevertheless, the fluid dynamics model includes evolving clouds that interactively adjust in size, shape, lifetime, and regional coverage. In addition, different cloud types are included with different roles in the climate system, including deep convective clouds and also boundary-layer clouds such as shallow cumulus and stratocumulus clouds. Other basic aspects of the idealized climate system are planetary-scale circulations (e.g., Walker circulation) and radiation. With these ingredients (evolving clouds, planetary-scale circulations, and radiation), the framework has the potential for idealized investigations of climate change with interactive cloud–radiative feedback of individual clouds. Here, the formulation of the model equations is presented, and numerical simulations are shown to illustrate the model dynamics and climate change.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Micropulse Lidar Cloud Mask (MPLCMASK) Value-Added Product for the Fast-Switching Polarized Micropulse Lidar Technical Report

Lidar backscattered signal is a useful tool for identifying vertical cloud structure in the atmosphere in optically thin clouds. Cloud boundaries derived from lidar signals are a necessary input for popular ARM data products, such as the Active Remote Sensing of Clouds (ARSCL) product. An operational cloud boundary algorithm (Wang and Sassen 2001) has been implemented for use with the ARM Micropulse Lidar (MPL) systems. In addition to retrieving cloud boundaries above 500 m, the value-added product (VAP) named Micropulse Lidar Cloud Mask (MPLCMASK) applies lidar-specific corrections (i.e., range-square, background, deadtime, and overlap) as described in Campbell et al. (2002) to the measured backscattered lidar. Depolarization ratio is computed using the methodology developed by Flynn et al. (2007) for polarization-capable MPL systems. The cloud boundaries output from MPLCMASK will be the primary lidar cloud mask for input to the ARSCL product and will be applied to all MPL systems, including historical data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vertical Variations of Cloud Microphysical Relationships in Marine Stratocumulus Clouds Observed During the ACE‐ENA Campaign

Abstract This study examines the vertical variations of cloud microphysical relationships and their implications to cloud microphysical processes in marine stratocumulus clouds using in‐situ aircraft observations during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE‐ENA) field campaign. A new diagram with a coordinate system based on cloud droplet liquid water content (L c ) and phase relaxation time scale is proposed to investigate mixing mechanisms. This new diagram analysis shows that the inhomogeneous mixing trait is dominant near the cloud top, but homogeneous mixing trait is stronger at lower altitudes. The relevant scale parameters (i.e., transition length scale and transition scale number) also indicate a high likelihood of inhomogeneous mixing. The relationship between L c and standard deviation of droplet radius (σ R ) clearly shows the vertical transition: the correlation between L c and σ R is positive at lower cloud altitudes, but it becomes negative as altitude increases. Such a vertical transition is consistent with the vertical circulation mixing, modulating the cloud microphysical relationships to suggest homogeneous mixing at a significant depth from the cloud top.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE)

Convective clouds play an important role in Earth’s climate system and are a known source of extreme weather. Gaps in our understanding of convective vertical motions, microphysics, and precipitation across a full range of aerosol and meteorological regimes continue to limit our ability to predict the occurrence and intensity of these cloud systems. To improve predictability, the National Science Foundation (NSF) sponsored a large field experiment entitled “Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE).” ESCAPE took place between 30 May and 30 September 2022 in the vicinity of Houston, Texas, because this area frequently experiences isolated deep convection that interacts with the region’s mesoscale circulations and its range of aerosol conditions. ESCAPE focused on collecting observations of isolated deep convection through innovative sampling and developing novel analysis techniques. This included the deployment of two research aircraft, the National Research Council of Canada Convair-580 and the Stratton Park Engineering Company Learjet, which combined conducted 24 research flights from 30 May to 17 June. On the ground, three mobile X-band radars and one mobile Doppler lidar truck equipped with soundings were deployed from 30 May to 28 June. From 1 August to 30 September 2022, a dual-polarization C-band radar was deployed and operated using a novel, multisensor agile adaptive sampling strategy to track the entire life cycle of isolated convective clouds. Analysis of the ESCAPE observations has already yielded preliminary findings on how aerosols and environmental conditions impact the convective life cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System

We present an efficient and performance portable implementation of the Simple Cloud Resolving E3SM Atmosphere Model (SCREAM). SCREAM is a full featured atmospheric global circulation model with a nonhydrostatic dynamical core and state-of-the-art parameterizations for microphysics, moist turbulence and radiation. It has been written from scratch in C++ with the Kokkos library used to abstract the on-node execution model for both CPUs and GPUs. SCREAM is one of only a few global atmosphere models to be ported to GPUs. As far as we know, SCREAM is the first such model to run on both AMD GPUs and NVIDIA GPUs, as well as the first to run on nearly an entire Exascale system (Frontier). On Frontier, we obtained a record setting performance of 1.26 simulated years per day for a realistic cloud resolving simulation.

Taylor, Mark↗
DOE OSTI2021

Retrieving microphysical properties of concurrent pristine ice and snow using polarimetric radar observations

Abstract. Ice and mixed-phase clouds play a key role in our climate system because of their strong controls on global precipitation and radiation budget. Their microphysical properties have been characterized commonly by polarimetric radar measurements. However, there remains a lack of robust estimates of microphysical properties of concurrent pristine ice and aggregates because larger snow aggregates often dominate the radar signal and mask contributions of smaller pristine ice crystals. This paper presents a new method that separates the scattering signals of pristine ice embedded in snow aggregates in scanning polarimetric radar observations and retrieves their respective abundances and sizes for the first time. This method, dubbed ENCORE-ice, is built on an iterative stochastic ensemble retrieval framework. It provides the number concentration, ice water content, and effective mean diameter of pristine ice and snow aggregates with uncertainty estimates. Evaluations against synthetic observations show that the overall retrieval biases in the combined total microphysical properties are within 5 % and that the errors with respect to the truth are well within the retrieval uncertainty. The partitioning between pristine ice and snow aggregates also agrees well with the truth. Additional evaluations against in situ cloud probe measurements from a recent campaign for a stratiform cloud system are promising. Our median retrievals have a bias of 98 % in the total ice number concentration and 44 % in the total ice water content. This performance is generally better than the retrieval from empirical relationships. The ability to separate signals of different ice species and to provide their quantitative microphysical properties will open up many research opportunities, such as secondary ice production studies and model evaluations for ice microphysical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Cybersecurity Platform and Certification Framework Development for Extreme Fast Charging (XFC)-Integrated Charging Ecosystem (Final Project Report)

This report summarizes a pioneering effort in Electric Vehicle charging infrastructure ecosystem cybersecurity requirements, assessment methodologies, functional verification, as well as embodiment of the key technologies in the form of hardware and software tools being made available to the public. EPRI led a team of experts, as well as a stakeholder coalition encompassing all key actors in the EV charging infrastructure ecosystem that includes eXtreme Fast Charging (XFC) equipment (defined as 200kW or above). EV charging infrastructure in the United States is a patchwork of networks that have continued to grow organically and have been designed to serve the charging needs of the EV owners, who are their customers. In doing so, each network provider, as well as their connected entities such as the cloud Electric Vehicle Service Providers or EVSPs, utility back office, utility AMI networks, payment networks, as well as Original Equipment Manufacturer (EV manufacturer) telematics networks, have designed systems that may work well individually, but no single entity is responsible for the entire ecosystem to be secure in terms of data exchange. Furthermore, there is no uniformity in how each actor has implemented the cybersecurity requirements since no system-wide cybersecurity requirements existed prior to this project. The final project report describes the technical approach guided by the EV charging infrastructure cybersecurity working group, convened specifically for this project. The technical approach included definition of requirements at the ecosystem level, treated as a ‘system of systems’, and then passed down to individual systems (EVSE, EV, cloud EVSP, utility, and the payment networks), followed by developing the cybersecurity risk and vulnerability assessment methods, that were later applied to real-world cyber-physical systems at EPRI, ANL, and NREL laboratories, to validate both the process and the results. Finally, in a spotlight over the most vulnerable equipment, which is the EV charge station (AC or DC), the team developed a multi-layer cybersecurity implementation in the embedded domain embodied by the open-source Secure Network Interface Card (SNIC) demonstrating the various ways in which the infrastructure can be secured protecting against the identified attack surfaces. Finally, the entire process of EV infrastructure cybersecurity assessment was encapsulated in the Electric Vehicle Charging Cybersecurity Management (EVC2M) online GUI-based tool, that is expected to be released to the public. The report presents the objectives, the technical approach, the key results, and recommendations for future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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↗
DOE OSTI2022

A review of coarse mineral dust in the Earth system

Mineral dust particles suspended in the atmosphere span more than three orders of magnitude in diameter, from <0.1 µm to more than 100 µm. This wide size range makes dust a unique aerosol species with the ability to interact with many aspects of the Earth system, including radiation, clouds, hydrology, atmospheric chemistry, and biogeochemistry. This review focuses on coarse and super-coarse dust aerosols, which we respectively define as dust particles with a diameter of 2.5–10 µm and 10–62.5 µm. We review several lines of observational evidence indicating that coarse and super-coarse dust particles are transported farther than previously expected and that the abundance of these particles is substantially underestimated in current global models. We synthesize previous studies that used observations, theories, and model simulations to highlight the impacts of coarse and super-coarse dust aerosols on the Earth system, including their effects on dust-radiation interactions, dust-cloud interactions, atmospheric chemistry, and biogeochemistry. Specifically, coarse and super-coarse dust aerosols produce a net positive direct radiative effect (warming) at the top of the atmosphere and can modify temperature and water vapor profiles, influencing the distribution of clouds and precipitation. In addition, coarse and super-coarse dust aerosols contribute a substantial fraction of ice-nucleating particles, especially at temperatures above –23 °C. They also contribute a substantial fraction to the available reactive surfaces for atmospheric processing and the dust deposition flux that impacts land and ocean biogeochemistry by supplying important nutrients such as iron and phosphorus. Furthermore, we examine several limitations in the representation of coarse and super-coarse dust aerosols in current model simulations and remote-sensing retrievals. Because these limitations substantially contribute to the uncertainties in simulating the abundance and impacts of coarse and super-coarse dust aerosols, we offer some recommendations to facilitate future studies. Overall, we conclude that an accurate representation of coarse and super-coarse properties is critical in understanding the impacts of dust aerosols on the Earth system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Regime-based aerosol–cloud interactions from CALIPSO-MODIS and the Energy Exascale Earth System Model version 2 (E3SMv2) over the Eastern North Atlantic

This study investigates aerosol-cloud interactions in marine boundary layer (MBL) clouds using an advanced deep-learning-driven synoptic-regime-based framework, combining satellite data (CALIPSO vertically resolved aerosol extinction and MODIS cloud properties) with 1° nudged Energy Exascale Earth System Model version 2 (E3SMv2) simulation over the Eastern North Atlantic (ENA; ∼10°×10°, 2006–2014). The E3SMv2 captures observed seasonal variations in cloud droplet number concentrations (N d ) and liquid water path (LWP), though it systematically underestimates N d . We then partition ENA meteorology into four synoptic regimes (Pre-Trough, Post-Trough, Ridge, Trough) via a deep-learning clustering of ERA5 reanalysis fields, enabling regime-dependent aerosol-cloud interactions analyses. Both satellite and E3SMv2 exhibit an inverted-V LWP-N d relationship. In Post-Trough and Ridge regimes, the satellite shows stronger negative LWP-N d sensitivities than in Pre-Trough regime. The Trough regime displays a muted satellite LWP response. In comparison, the model predicts more exaggerated LWP responses across regimes, with LWP increasing too quickly at low N d and decreasing more sharply at high N d , especially in Pre-Trough and Trough regimes. These exaggerated model LWP sensitivities may stem from uncertainties in representing drizzle processes, entrainment, and turbulent mixing. As for N d susceptibility to aerosols, N d increases with MBL aerosol extinction in both datasets, but the simulated aerosol-cloud interactions appear oversensitive to meteorological conditions. Overall, E3SMv2 better captures aerosol effects under regimes that favor stratiform clouds (Post-Trough, Ridge), but performance deteriorates for regimes with deeper, dynamically complex clouds (Trough), highlighting the need for improved representations of those cloud processes in climate models.

Environmental sciences↗
DOE OSTI2023

A Novel Method for Diagnosing Land–Atmosphere Coupling Sensitivity in a Single-Column Model

The response of boundary layer properties and cloudiness to changes in surface evaporative fraction (EF) is investigated in a single-column model to quantify the locally coupled impact of subgrid surface variations on the atmosphere during summer. Sensitive coupling days are defined when the model atmosphere exhibits large variations across a range of EFs centered on the analyzed value. Coupling sensitivity exists as both positive feedback (cloudiness increases with EF) and negative feedback (clouds increase with decreasing EF) regimes. The positive regime manifests in shallow convection situations, which are capped by a strengthened inversion and subsidence, restricting the vertical extent of convection to just above the boundary layer. Surfaces with larger EF (greater surface latent heat flux) can inject more moisture into the vertically confined system, lowering the cloud base and an increasing cloud liquid water path (LWP). Negative feedback regimes tend to manifest when large-scale deep convection, such as from mesoscale convective systems and fronts, is advected through the domain, where convection strengthens over surfaces with a lower EF (greater surface sensible heat flux). The invigoration of these systems by the land surface leads to an increase in LWP through strengthened updrafts and stronger coupling between the boundary layer and the free atmosphere. These results apply in the absence of heterogeneity-induced mesoscale circulations, providing a one-dimensional dynamical perspective on the effect of surface heterogeneity. Finally, this study provides a framework of intermediate complexity, lying between parcel theory and high-resolution coupled land–atmosphere modeling, and therefore isolates the relevant first-order processes in land–atmosphere interactions.

54 ENVIRONMENTAL SCIENCES↗