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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Variability of Eastern North Atlantic Summertime Marine Boundary Layer Clouds and Aerosols Across Different Synoptic Regimes Identified With Multiple Conditions

Abstract This study estimates the meteorological covariations of aerosol and marine boundary layer (MBL) cloud properties in the eastern North Atlantic (ENA) region, characterized by diverse synoptic conditions. Using a deep‐learning‐based clustering model with mid‐level and surface daily meteorological data, we identify seven distinct synoptic regimes during the summer from 2016 to 2021. Our analysis, incorporating reanalysis data and satellite retrievals, shows that surface aerosols and MBL clouds exhibit clear regime‐dependent characteristics, whereas lower tropospheric aerosols do not. This discrepancy likely arises from synoptic regimes determined by daily large‐scale conditions, which may overlook air mass histories that predominantly dictate lower tropospheric aerosol conditions. Focusing on three regimes dominated by northerly winds, we analyze the Atmospheric Radiation Measurement Program (ARM) ENA observations on Graciosa Island in the Azores. In the subtropical anticyclone regime, fewer cumulus clouds and more single‐layer stratocumulus clouds with light drizzle are observed, along with the highest cloud droplet number concentration (Nd), surface cloud condensation nuclei (CCN) and surface aerosol levels. The post‐trough regime features more broken or multi‐layer stratocumulus clouds with slightly higher surface rain rate, and lower Nd and surface CCN levels. The weak trough regime is characterized by the deepest MBL clouds, primarily cumulus and broken stratocumulus clouds, with the strongest surface rain rate and the lowest Nd, surface CCN and surface aerosol levels, indicating strong wet scavenging. These findings highlight the importance of considering the covariation of cloud and aerosol properties driven by large‐scale regimes when assessing aerosol indirect effects using observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Trends and controls of terrestrial gross primary productivity of China during 2000–2016

Terrestrial gross primary productivity (GPP) is an important flux that drives the global carbon cycle. However, quantifying the trend and the control factor of GPP from the pixel level to the regional level is still a challenge. We generated monthly GPP dataset using the vegetation photosynthesis model and calculated the interannual linear trend for China during 2000-2016. The Breaks For Additive Seasonal and Trend method was applied to detect the timing of breakpoint and trends shift of monthly GPP, while boosted regression tree analysis was used to identify the most important factor and its relative influence on GPP based on gridded leaf area index (LAI), aerosol optical thickness, and NCEP-DOE Reanalysis II meteorological data. The results show that annual mean GPP was significantly (P < 0.001, R 2 = 0.78) increased, especially in the Loess Plateau and South China, from 2000 to 2016. The change rate of annual mean GPP declined from 18.82 g C m -2 yr -1 in 2000-2008 to 3.48 g C m -2 yr -1 in 2008-2016. About 55.4% of the breakpoints occur between 2009 and 2011 and was mainly distributed in Qinghai-Tibet Plateau, Central China, Southwestern China, and South China, and negative oriented GPP trends variation type still accounts for about 28.76%. LAI and temperature related factors generally had the highest relative influence on GPP in the north part and south part of China, respectively. Our study indicates that the ecological restoration projects and rapid urbanization have respectively induced the most obvious increase and decrease trends of GPP in China. Land cover change and climate change are the main reasons for GPP dynamics in the north and south part of China, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Permafrost thermal conditions are sensitive to shifts in snow timing

Abstract Changes in snow precipitation at high latitudes can significantly affect permafrost thermal conditions and thaw depth, potentially exposing more carbon-laden soil to microbial decomposition. A fully coupled process-based surface/subsurface thermal hydrology model with surface energy balance is used to analyze the impact of intra-annual variability in snow on permafrost thermal regime and the active layer thickness. In the four numerical scenarios considered, simulations were forced by the same meteorological data, except the snow precipitation, which was systematically altered to change timing of snowfall. The scenarios represent subtle shifts in snow timing, but the snow onset/melt days, the end of winter snowpack depth, and total annual snow precipitation are unchanged among scenarios. The simulations show that small shifts in the timing of snow accumulation can have significant effects on subsurface thermal conditions leading to active layer deepening and even talik formation when snowfall arrives earlier in the winter. The shifts in snow timing have a stronger impact on wetter regions, especially soil underneath small ponds, as compared to drained regions. This study highlights the importance of understanding potential changes in winter precipitation patterns for reliable projections of active-layer thickness in a changing Arctic climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Mapping Aedes aegypti (Diptera: Culicidae) and Aedes albopictus Vector Mosquito Distribution in Brownsville, TX

Abstract Aedes mosquitoes are vectors of several emerging diseases and are spreading worldwide. We investigated the spatiotemporal dynamics of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) mosquito trap captures in Brownsville, TX, using high-resolution land cover, socioeconomic, and meteorological data. We modeled mosquito trap counts using a Bayesian hierarchical mixed-effects model with spatially correlated residuals. The models indicated an inverse relationship between temperature and mosquito trap counts for both species, which may be due to the hot and arid climate of southern Texas. The temporal trend in mosquito populations indicated Ae. aegypti populations peaking in the late spring and Ae. albopictus reaching a maximum in winter. Our results indicated that seasonal weather variation, vegetation height, human population, and land cover determine which of the two Aedes species will predominate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Systematic Operating Temperature Differences Between Al-BSF, PERC, and PERT-With-Optimized-Rear-Reflector Solar Mini-Modules Due to Rear Reflectance

Reflecting sub-bandgap light from photovoltaic modules has the potential to improve lifetime energy generation of fielded systems by reducing operating temperature. In this article, the temperature of fielded aluminum back-surface field (Al-BSF) and passivated emitter and rear contact (PERC) mini-modules was monitored every 5 minutes for 75 days along with corresponding meteorological data. Additionally, passivated emitter rear totally diffused (PERT) mini-modules with high-performance sub-bandgap rear reflectors were tested and compared to the state-of-the-art industrial modules. These reflectors consisted of a >300-nm-thick silicon dioxide nanoparticle film with a low refractive index. The impact of reflectance on measured operating temperature was isolated with a previously developed thermal model and quantified as the reflectance-induced median temperature difference between each tested module at representative outdoor conditions (1000 W m -2 , 25 degrees C ambient temperature, and 1.43 m s -1 wind speed). We found that, because of their reflectance differences, PERC modules ran systematically cooler than Al-BSF modules by 1.0 degrees C, whereas the PERT-with-optimized-rear-reflector systematically operated 1.4 degrees C cooler than the Al-BSF module and 0.4 degrees C than the PERC module. We also found that the rear reflector provided the greatest temperature benefit during periods of highest irradiance.

14 SOLAR ENERGY↗
DOE OSTI2024

Impact of Floating PV (FPV) System on Water Evaporation: Case Study of an Open Loop Reservoir in North Carolina

Fresh water scarcity is becoming one of the important concerns worldwide. This situation of water scarcity is further exacerbated by the increase in water evaporation due to climate change. This manuscript will address this concern by considering the impact of floating photovoltaics (FPVs) systems on water evaporation. The installation of PV modules on the water bodies can help reduce the water evaporation rate from reservoirs by reducing the evaporating area of the water surface. This work evaluates the effect of FPV on water evaporation rates in the TuckerTown reservoir located in North Carolina state of United States. Meteorological data, such as mean temperature and dew-point, are used to calculate the rate of the water evaporation by Linacre method. The simulation results for the TuckerTown case study showed that the aggregated avoided evaporated volume for one year is 9 million gallons.

14 SOLAR ENERGY↗
DOE OSTI2023

Emergency Asset Positioning for Resilient Transmission Grid Operation

In this paper we study a problem of hurricane emergency preparedness via placement of emergency storage assets prior to its strike. We present a two-stage stochastic model for choosing locations and quantities of emergency storage to help support the power grid through a hurricane event. The expectation of losses in our two-stage model is estimated using the sample average approximation. We construct damage scenarios for sample average approximation using WIND Toolkit meteorological data and fragility curves of various electric grid components. We demonstrate the efficacy of our two-stage planning model by simulating operations during Hurricane Dolly on the 2000-bus transmission test system. Our model, coupled with our scenario selection strategy, is effective at mitigating loss of load when compared to a model without emergency storage assets placed prior to an extreme event.

emergency preparedness↗
DOE OSTI2016

Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States

Abstract Phenological events, such as bud burst, are strongly linked to ecosystem processes in temperate deciduous forests. However, the exact nature and magnitude of how seasonal and interannual variation in air temperatures influence phenology is poorly understood, and model‐based phenology representations fail to capture local‐ to regional‐scale variability arising from differences in species composition. In this paper, we use a combination of surface meteorological data, species composition maps, remote sensing, and ground‐based observations to estimate models that better represent how community‐level species composition affects the phenological response of deciduous broadleaf forests to climate forcing at spatial scales that are typically used in ecosystem models. Using time series of canopy greenness from repeat digital photography, citizen science data from the USA National Phenology Network, and satellite remote sensing‐based observations of phenology, we estimated and tested models that predict the timing of spring leaf emergence across five different deciduous broadleaf forest types in the eastern United States. Specifically, we evaluated two different approaches: (i) using species‐specific models in combination with species composition information to ‘upscale’ model predictions and (ii) using repeat digital photography of forest canopies that observe and integrate the phenological behavior of multiple representative species at each camera site to calibrate a single model for all deciduous broadleaf forests. Our results demonstrate variability in cumulative forcing requirements and photoperiod cues across species and forest types, and show how community composition influences phenological dynamics over large areas. At the same time, the response of different species to spatial and interannual variation in weather is, under the current climate regime, sufficiently similar that the generic deciduous forest model based on repeat digital photography performed comparably to the upscaled species‐specific models. More generally, results from this analysis demonstrate how in situ observation networks and remote sensing data can be used to synergistically calibrate and assess regional parameterizations of phenology in models.

Melaas, Eli K.↗
DOE OSTI2016

Stomatal response to humidity and CO 2 implicated in recent decline in US evaporation

Abstract Evapotranspiration, defined as the total flux of water from the land surface to the atmosphere, is a major component of the hydrologic cycle and surface energy balance. Although evapotranspiration is expected to intensify with increasing temperatures, long‐term, regional trends in evapotranspiration remain uncertain due to spatially and temporally limited direct measurements. In this study, we utilize an emergent relation between the land surface and atmospheric boundary layer to infer daily evapotranspiration from historical meteorological data collected at 236 weather stations across the United States. Our results suggest a statistically significant ( α = 0.05) decrease in evapotranspiration of approximately 6% from 1961 to 2014, with a significant ( α = 0.05) sharp decline of 13% from 1998 to 2014. We attribute the decrease in evapotranspiration mostly to declines in surface conductance, but also to offsetting changes in longwave radiation, wind speed, and incoming solar radiation. Using an established stomatal conductance model, we explain the changes in inferred surface conductance as a response to increases in carbon dioxide and, more recently, to an abrupt decrease in atmospheric humidity.

Rigden, Angela J.↗
DOE OSTI2016

TRMM Latent Heating Retrieval: Applications and Comparisons with Field Campaigns and Large-Scale Analyses

Yanai et al. (1973) utilized the meteorological data collected from a sounding network to present a pioneering work on thermodynamic budgets, which are referred to as the apparent heat source (Q1) and apparent moisture sink (Q2). Latent heating (LH) is one of the most dominant terms in Q1. Yanai’s paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q1 data have been used to generate the look-up tables in Tropical Rainfall Measuring Mission (TRMM) LH algorithms. A set of algorithms developed for retrieving LH profiles from TRMM-based rainfall profiles are described and evaluated, including details concerning their intrinsic space-time resolutions. Included in the paper are results from a variety of validation analyses that define the uncertainty of the LH profile estimates. Also, examples of how TRMM-retrieved LH profiles have been used to understand the lifecycle of the MJO and improve the predictions of global weather and climate models as well as comparisons with large-scale analyses are provided. Areas for further improvement of the TRMM products are discussed.

field campaigns↗
DOE OSTI2021

Evaluation and Uncertainty of Radioxenon Transport with a Mesoscale Model after the February 2013 Underground Test in North Korea

Abstract The transport of radioxenon released from the February 2013 underground nuclear weapons test in North Korea was analyzed at two receptors—one at the Comprehensive Nuclear Test Ban Treaty site Rn58 in Russia (400 km downwind) and a second at Rn38 in Japan (1000 km downwind). Transport was modeled with two ensembles of mesoscale simulations, one generated with varying initial and lateral boundary conditions taken from the Global Forecasting System uncertainty ensemble, and a second created from different parameterizations and surface conditions. The wind variability was similar for the two ensembles and consistent with observations at 925 mb (1 mb = 1 hPa) but not at the surface. Biases in calculated surface winds and the radioxenon concentration in the ensembles were attributed mainly to poor simulation of the sea breeze at both locations and mountain lee affects at Rn38 in Japan. These wind regimes affected the timing of the surface radioxenon plume at Rn58 and its duration at Rn38. Surface wind variability induced by terrain and land–sea contrast (the sea breeze) also had a significant effect on the surface winds and plume dynamics, including blocking of flow approaching elevated terrain near Vladivostok and the west side of Japan. Increased plume uncertainty was seen at night because of surface wind variability. Measured surface chemical variability was larger than found in the first European Tracer Experiment in central Europe. The study found that horizontal model resolution contributes to uncertainty but not as much as vertical resolution, boundary layer parameterizations, and assimilation of surface meteorological data near the receptor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

ARID Raceway Temperature Model Evaluation

The ARID (Algae Raceway Integrated Design) raceway temperature model, written in Visual Basic for Applications, calculates algae culture temperature in ARID and conventional raceways as a function of meteorological data from agricultural weather stations. The model is an atmospheric boundary layer model and uses energy balance terms from the Penman-Monteith equation. The original model used evapotranspiration, as calculated by the weather station, and assumed an average daily albedo. In this research, equations for albedo and for direct calculation of evaporation from atmospheric parameters were added to the ARID model. Albedo was calculated with the Fresnel equations. The Penman-Monteith model was adjusted for algae raceway evaporation rather than reference evapotranspiration. The new model components were calibrated with data from a 21-day algae growth experiment in the ARID raceway during winter 2011. The model was also adapted to model variable circulation times and heat transfer through a canal cover. In summary, this research improved and calibrated the ARID temperature model for future use.

09 BIOMASS FUELS↗
DOE OSTI2014

Sensitivity of Vadose Zone Water Fluxes to Climate Shifts in Arid Settings

Vadose zone water fluxes in arid settings are investigated regarding their sensitivity to hydraulic soil parameters and meteorological data. The study is based on the inverse modeling of highly defined soil column experiments and subsequent scenario modeling comparing different climate projections for a defined arid region. In arid regions, groundwater resources are prone to depletion due to excessive water use and little recharge potential. Especially in sand dune areas, groundwater recharge is highly dependent on vadose zone properties and corresponding water fluxes. Nevertheless, vadose zone water fluxes under arid conditions are hard to determine owing to, among other reasons, deep vadose zones with generally low fluxes and only sporadic high infiltration events. In this study, we present an inverse model of infiltration experiments accounting for variable saturated nonisothermal water fluxes to estimate effective hydraulic and thermal parameters of dune sands. A subsequent scenario modeling links the results of the inverse model with projections of a global climate model until 2100. The scenario modeling clearly showed the high dependency of groundwater recharge on precipitation amounts and intensities, whereas temperature increases are only of minor importance for deep infiltration. However, simulated precipitation rates are still affected by high uncertainties in the response to the hydrological input data of the climate model. Thus, higher certainty in the prediction of precipitation pattern is a major future goal for climate modeling to constrain future groundwater management strategies in arid regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Alternative Energy for Higher Education

This project provides educational opportunities creating both a teaching facility and center for public outreach. The facility is the largest solar array in Nebraska. It was designed to allow students to experience a variety of technologies and provide the public with opportunities for exposure to the implementation of an alternative energy installation designed for an urban setting. The project integrates products from 5 panel manufacturers (including monocrystalline, polycrystalline and thin film technologies) mounted on both fixed and tracking structures. The facility uses both micro and high power inverters. The majority of the system was constructed to serve as an outdoor classroom where panels can be monitored, tested, removed and replaced by students. As an educational facility it primarily serves students in the Creighton University and Metropolitan Community College, but it also provides broader educational opportunities. The project includes a real-time dashboard and a historical database of the output of individual inverters and the corresponding meteorological data for researcher and student use. This allows the evaluation of both panel types and the feasibility of installation types in a region of the country subject to significant temperature, wind and precipitation variation.

14 SOLAR ENERGY↗
DOE OSTI2012

Roughness Lengths for the Savannah River Site

Surface roughness values for the areas surrounding the H, D and N-Area meteorological towers were computed from archived 2010 meteorological data. These 15-minute-averaged data were measured with cup anemometers and bidirectional wind vanes (bivanes) 61 m above the surface. The results of the roughness calculation using the standard deviation of elevation angle σ E , and applying the simple formula based on tree canopy height, gave consistent estimates for roughness around the H-Area tower in the range of 1.76 to 1.86 m (95% confidence interval) with a mean value of 1.81 m. Application of the σ E method for the 61-m level at D and N-Areas gave mean values of 1.71 and 1.81 with confidence ranges of 1.62-1.81 and 1.73-1.88 meters, respectively. Roughness results are azimuth dependent, and thus are presented as averages over compass sectors spanning 22.5 degrees. Calculated values were compared to other methods of determining roughness, including the standard deviation of the azimuth direction, σ A , and standard deviation of the wind speed, σ U . Additional data was obtained from a sonic anemometer at 61-m on the H-Area tower during a period of a few weeks in 2010. Results from the sonic anemometer support our use of σ E to calculate roughness. Based on the H-Area tower results, a surface roughness of 1.8 m using is recommended for use in dispersion modeling applications that consider the impacts of a contaminant release to individuals along the Site boundary. The canopy surrounding the H-Area tower is relatively uniform (i.e., little variance in roughness by upwind direction), and data supplied by the U.S. Forest Service at Savannah River show that the canopy height and composition surrounding the H-Area tower is reasonably representative of forested areas throughout the SRS reservation. For dispersion modeling analyses requiring assessments of a co-located worker within the respective operations area, recommended area-specific values range from 0.3 m for E Area to 0.7 m for A Area at the Savannah River National Laboratory. These area-specific values, summarized in Table 4-1, were determined using the Environmental Protection Agency's AERSURFACE computer algorithm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Wind Generation Feasibility Study for Sac & Fox Tribe of the Mississippi in Iowa (Meskwaki Nation)

The Meskwaki Nation will obtain an anemometer tower. Install the tower at the site that has been pre-qualified as the site most likely to produce maximum electric power from the wind. It will collect meteorological data from the tower's sensors for a one year period, as required for due diligence to identify the site as appropriate for the installation of a wind turbine to provide electric power for the community. Have the collected data analyzed by a meteorologist and a professionally certified wind engineer to produce the reports of expected power generation at the site, for the specific wind turbine(s) under consideration for installation.

17 WIND ENERGY↗
DOE OSTI2014

Dispersion of Radionuclides and Exposure Assessment in Urban Environments: A Joint CEA and LLNL Report

In the interest of promoting the international exchange of technical expertise, the US Department of Energy’s Office of Emergency Operations (NA-40) and the French Commissariat à l'Energie Atomique et aux énergies alternatives (CEA) requested that the National Atmospheric Release Advisory Center (NARAC) of Lawrence Livermore National Laboratory (LLNL) in Livermore, California host a joint table top exercise with experts in emergency management and atmospheric transport modeling. In this table top exercise, LLNL and CEA compared each other’s flow and dispersion models. The goal of the comparison is to facilitate the exchange of knowledge, capabilities, and practices, and to demonstrate the utility of modeling dispersal at different levels of computational fidelity. Two modeling approaches were examined, a regional scale modeling approach, appropriate for simple terrain and/or very large releases, and an urban scale modeling approach, appropriate for small releases in a city environment. This report is a summary of LLNL and CEA modeling efforts from this exercise. Two different types of LLNL and CEA models were employed in the analysis: urban-scale models (Aeolus CFD at LLNL/NARAC and Parallel- Micro-SWIFT-SPRAY, PMSS, at CEA) for analysis of a 5,000 Ci radiological release and Lagrangian Particle Dispersion Models (LODI at LLNL/NARAC and PSPRAY at CEA) for analysis of a much larger (500,000 Ci) regional radiological release. Two densely-populated urban locations were chosen: Chicago with its high-rise skyline and gridded street network and Paris with its more consistent, lower building height and complex unaligned street network. Each location was considered under early summer daytime and nighttime conditions. Different levels of fidelity were chosen for each scale: (1) lower fidelity mass-consistent diagnostic, intermediate fidelity Navier-Stokes RANS models, and higher fidelity Navier-Stokes LES for urban-scale analysis, and (2) lower-fidelity single-profile meteorology versus higher-fidelity three-dimensional gridded weather forecast for regional-scale analysis. Tradeoffs between computation time and the fidelity of the results are discussed for both scales. LES, for example, requires nearly 100 times more processor time than the mass-consistent diagnostic model or the RANS model, and seems better able to capture flow entrainment behind tall buildings. As anticipated, results obtained by LLNL and CEA at regional scale around Chicago and Paris look very similar in terms of both atmospheric dispersion of the radiological release and total effective dose. Both LLNL and CEA used the same meteorological data, Lagrangian particle dispersion models, and the same dose coefficients. LLNL and CEA urban-scale modeling results show consistent phenomenological behavior and predict similar impacted areas even though the detailed 3D flow patterns differ, particularly for the Chicago cases where differences in vertical entrainment behind tall buildings are particularly notable. Although RANS and LES (LLNL) models incorporate more detailed physics than do mass-consistent diagnostic flow models (CEA), it is not possible to reach definite conclusions about the prediction fidelity of the various models as experimental measurements were not available for comparison. Stronger conclusions about the relative performances of the models involved and evaluation of the tradeoffs involved in model simplification could be made with a systematic benchmarking of urban-scale modeling. This could be the purpose of a future US / French collaborative exercise.

54 ENVIRONMENTAL SCIENCES↗