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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

A research program in determination of heavy metals in sediments and benthic species in relation to nuclear power plant operation

Heavy metals in the estuarine environment can be toxic to fish and shellfish early life history stages and concentrations build up to levels of concern in marketable shellfish. The present survey was begun just before startup in 1974 of the 1900 megawatt Calvert Cliffs Nuclear Power Plant on the Chesapeake Bay in order to assess and understand factors relating to heavy metal accumulation in estuarine biota. Oysters were collected in large numbers at test and reference sites in June 1974 to 77 and individually analyzed for copper and zinc. Oyster copper and zinc concentrations were correlated with salinity read at time of collection. The relationship of oyster age to metal concentration was examined with two sets of oysters of known age and genetic origin (laboratory spawned). Copper sorption by typical mid Bay sediments, and field studies on cadmium concentrations in sediments were examined.

Phelps, H. L.↗
NASA NTRS1995

Error modeling for differential GPS

Differential Global Positioning System (DGPS) positioning is used to accurately locate a GPS receiver based upon the well-known position of a reference site. In utilizing this technique, several error sources contribute to position inaccuracy. This thesis investigates the error in DGPS operation and attempts to develop a statistical model for the behavior of this error. The model for DGPS error is developed using GPS data collected by Draper Laboratory. The Marquardt method for nonlinear curve-fitting is used to find the parameters of a first order Markov process that models the average errors from the collected data. The results show that a first order Markov process can be used to model the DGPS error as a function of baseline distance and time delay. The model's time correlation constant is 3847.1 seconds (1.07 hours) for the mean square error. The distance correlation constant is 122.8 kilometers. The total process variance for the DGPS model is 3.73 sq meters.

Blerman, Gregory S.↗
NASA NTRS2000

Space Solar Power Satellite Technology Development at the Glenn Research Center: An Overview

NASA Glenn Research Center (GRC). is participating in the Space Solar Power Exploratory Research and Technology program (SERT) for the development of a solar power satellite concept. The aim of the program is to provide electrical power to Earth by converting the Sun's energy and beaming it to the surface. This paper will give an overall view of the technologies being pursued at GRC including thin film photovoltaics, solar dynamic power systems, space environmental effects, power management and distribution, and electric propulsion. The developmental path not only provides solutions to gigawatt sized space power systems for the future, but provides synergistic opportunities for contemporary space power architectures. More details of Space Solar Power can be found by reading the references sited in this paper and by connecting to the web site http://moonbase.msfc.nasa.gov/ and accessing the "Space Solar Power" section "Public Access" area.

Dudenhoefer, James E.↗
NASA NTRS2004

Implementation of Coupled Skin Temperature Analysis and Bias Correction in a Global Atmospheric Data Assimilation System

The NASA/NCAR Finite Volume GCM (fvGCM) with the NCAR CLM (Community Land Model) version 2.0 was integrated into the NASA/GMAO Finite Volume Data Assimilation System (fvDAS). A new method was developed for coupled skin temperature assimilation and bias correction where the analysis increment and bias correction term is passed into the CLM2 and considered a forcing term in the solution to the energy balance. For our purposes, the fvDAS CLM2 was run at 1 deg. x 1.25 deg. horizontal resolution with 55 vertical levels. We assimilate the ISCCP-DX (30 km resolution) surface temperature product. The atmospheric analysis was performed 6-hourly, while the skin temperature analysis was performed 3-hourly. The bias correction term, which was updated at the analysis times, was added to the skin temperature tendency equation at every timestep. In this presentation, we focus on the validation of the surface energy budget at the in situ reference sites for the Coordinated Enhanced Observation Period (CEOP). We will concentrate on sites that include independent skin temperature measurements and complete energy budget observations for the month of July 2001. In addition, MODIS skin temperature will be used for validation. Several assimilations were conducted and preliminary results will be presented.

Radakovich, Jon↗
NASA NTRS2003

The CEOP Inter-Monsoon Studies (CIMS)

Prediction of climate relies on models, and better model prediction depends on good model physics. Improving model physics requires the maximal utilization of climate data of the past, present and future. CEOP provides the first example of a comprehensive, integrated global and regional data set, consisting of globally gridded data, reference site in-situ observations, model location time series (MOLTS), and integrated satellite data for a two-year period covering two complete annual cycles of 2003-2004. The monsoon regions are the most important socio-economically in terms of devastation by floods and droughts, and potential impacts from climate change md fluctuatinns nf the hydrologic cyc!e. Scientifically, it is most challenging, because of complex interactions of atmosphere, land and oceans, local vs. remote forcings in contributing to climate variability and change in the region. Given that many common features, and physical teleconnection exist among different monsoon regions, an international research focus on monsoon must be coordinated and sustained. Current models of the monsoon are grossly inadequate for regional predictions. For improvement, models must be confronted with relevant observations, and model physic developers must be made to be aware of the wealth of information from existing climate data, field measurements, and satellite data that can be used to improve models. Model transferability studles must be conducted. CIMS is a major initiative under CEOP to engage the modeling and the observational communities to join in a coordinated effort to study the monsoons. The objectives of CIMS are (a) To provide a better understanding of fundamental physical processes (diurnal cycle, annual cycle, and intraseasonal oscillations) in monsoon regions around the world and (b) To demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. In this talk, I will present the basic concepts of CIMS and the key scientific problems facing monsoon climates and provide examples of common monsoon features, and possible monsoon induced teleconnections linking different parts of the world.

Lau, William K. M.↗
NASA NTRS2007

The Joint Aerosol-Monsoon Experiment (JAMEX): A Core Element for the Asian Monsoon Year (2008-2009)

The objective of the Joint Aerosol-Monsoon Experiment (JAMEX) is to unravel the physical mechanisms and multi-scale interactions associated with aerosol-monsoon water cycle in the Asian Indo-Pacific region towards improved prediction of rainfall in land regions of the Asian monsoon. JAMEX will be planned as a five-year (2007-201 1) multi-national aerosol-monsoon research project, aimed at promoting collaboration, partnership and alignment of ongoing and planned national and international programs. Two coordinated special observing periods (SOP), covering the pre-monsoon (April-May) and the monsoon (June-August) periods is tentatively targeted for 2008 and 2009. The major work on validation and reference site coordination will take place in 2007 through the spring of 2008. A major science workshop is planned after SOP-I1 in 2010. Modeling and satellite data utilization studies will continue throughout the entire period to help in design of the observation arrays and measurement platforms for SOPS. The tentative time schedule, including milestones and research activities is shown in Fig. 1. One of the unique aspects of JAMEX is that it stems from grass-root scientific and societal imperatives, and it bridges a gap in existing national and international research programs. Currently we have identified 10 major national and international projects/programs separately for aerosols and monsoon research planned in the next five years in China, India, Japan, Italy, and the US, that could be potential contributors or partners with JAMEX. These include the Asian-Indo- Pacific Ocean (AIPO) Project and Aerosol Research Project from China, Monsoon Asian Hydro- Atmospheric Science Research and predication Initiative (MAHASRI) from Japan, Continental Tropical Convergence Zone (CTCZ) and Severe Thunderstorm: Observations and Regional Modeling (STORM) from India, Share-Asia from Italy, Atmospheric Brown Cloud (ABC), Pacific Aerosol-Cloud-Dust Experiment (PACDEX), East Asia Study of Tropospheric Aerosol: an International Regional Experiment (East-AIRE), and Radiation Aerosol Joint Observations - Monsoon Experiments over the Gangetic Himalayas Area (Rajo-Megha: dust cloud in Sanskrit) from the US, and Monsoon Asia Integrated Regional Study (MAIR) under the Earth Systems I Science Partnership (ESSP) and WCRP. For JAMEX to succeed, it is crucial for an international body, such as CEOP or an organization under WCRP to provide the science oversight, data policy and stewardship, and to promote collaboration and partnership among national programs. It makes eminent sense for WCRP to expand the concept and the prototype proposed by JAMEX to include all monsoon countries to expand AMY08-09 into an International Monsoon Era (2008- 2013). Such an establishment followed by establishment of an international body for science oversight, and data stewardship will go a long way in promoting coordination and connection among various existing monsoon research programs within WCRP, and with burgeoning national programs on monsoon and aerosol research.

Lau, William K.M.↗
NASA NTRS2007

The Joint Aerosol-Monsoon Experiment (JAMEX): A Core Element for the Asian Monsoon Year (2008-2009)

The objective of the Joint Aerosol-Monsoon Experiment (JAMEX) is to unravel the physical mechanisms and multi-scale interactions associated with aerosol-monsoon water cycle in the Asian Indo-Paczj?c region towards improved prediction of rainfall in land regions of the Asian monsoon. JAMEX will be planned as a five-year (2007-201 1) multi-national aerosol-monsoon research project, aimed at promoting collaboration, partnership and alignment of ongoing and planned national and international programs. Two coordinated special observing periods (SOP), covering the pre-monsoon (April-May) and the monsoon (June-August) periods is tentatively targeted for 2008 and 2009. The major work on validation and reference site coordination will take place in 2007 through the spring of 2008. A major science workshop is planned after SOP-I1 in 2010. Modeling and satellite data utilization studies will continue throughout the entire period to help in design of the observation arrays and measurement platforms for SOPS. The tentative time schedule, including milestones and research activities is shown in Fig. 1. One of the unique aspects of JAMEX is that it stems from grass-root scientific and societal imperatives, and it bridges a gap in existing national and international research programs. Currently we have identified 10 major national and international projects/programs separately for aerosols and monsoon research planned in the next five years in China, India, Japan, Italy, and the US, that could be potential contributors or partners with JAMEX. These include the Asian-Indo- Pacific Ocean (AIPO) Project and Aerosol Research Project from China, Monsoon Asian Hydro- Atmospheric Science Research and predication Initiative (MAHASRI) from Japan, Continental Tropical Convergence Zone (CTCZ) and Severe Thunderstorm: Observations and Regional Modeling (STORM) from India, Share-Asia from Italy, Atmospheric Brown Cloud (ABC), Pacific Aerosol-Cloud-Dust Experiment (PACDEX), East Asia Study of Tropospheric Aerosol: an International Regional Experiment (East-AIRE), and Radiation Aerosol Joint Observations - Monsoon Experiments over the Gangetic Himalayas Area (Rajo-Megha: dust cloud in Sanskrit) from the US, and Monsoon Asia Integrated Regional Study (MAIR) under the Earth Systems Science Partnership (ESSP) and WCRP. For JAMEX to succeed, it is crucial for an international body, such as CEOP or an organization under WCRP to provide the science oversight, data policy and stewardship, and to promote collaboration and partnership among national programs. It makes eminent sense for WCRP to expand the concept and the prototype proposed by JAMEX to include all monsoon countries to expand AMY08-09 into an International Monsoon Era (2008- 2013). Such an establishment followed by establishment of an international body for science oversight, and data stewardship will go a long way in promoting coordination and connection among various existing monsoon research programs within WCRP, and with burgeoning national programs on monsoon and aerosol research.

Lau, WIlliam K. M.↗
NASA NTRS2012

A Regional CO2 Observing System Simulation Experiment Using ASCENDS Observations and WRF-STILT Footprints

Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments.

Wang, James S.↗
NASA NTRS2015

Reductions in Productivity Due to Land Degradation in the Drylands of the Southwestern United States

Dryland degradation has long been recognized at regional, national, and global scales, yet there are no objective assessments of its location and severity. An assessment of reductions in net primary production (NPP) due to dryland degradation in the southwestern United States is reported. The local NPP scaling (LNS) approach was applied to map the extent and magnitude of degradation. LNS seeks to identify reference sites in which there is no degradation that can be used as a standard for comparison with other sites that share the same environment, except for degradation. Twelve years were analyzed (2000–2011), using Normalized Difference Vegetation Index (NDVI) data (250 m) from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite‐borne multispectral sensor. The results indicated that the total NPP reductions in the study area were about 35.9 ± 4.7 Tg C/yr, which equates to 0.31 ± 0.04 Mg C/ha·y. The NPP reductions in grassland‐savanna and livestock grazing areas were large and mostly consistent between years in spite of large variations in overall NPP caused by differences in land‐use, interannual variations in rainfall, and other aspects of weather. In comparison with other cover types, forested land generally had higher NPP reduction per unit area. The maps also enable attribution of degradation from the finest management units to entire agencies, such as the Bureau of Land Management, which had 50% less production per unit area than the U.S. Forest Service. The degradation within Native American land was low with total NPP reduction of about 2.41 ± 0.24 Tg C/yr and unit area reduction of productivity of just 0.21 ± 0.02 Mg C/ha·yr, yet the percent reduction from potential was in equivalence with other land management agencies.

Noojipady, Praveen↗
NASA NTRS2022

Satellite Soil Moisture Data Assimilation Impacts on Modeling Weather Variables and Ozone in the Southeastern US – Part 2: Sensitivity to Dry-Deposition Parameterizations

Ozone (O3) dry deposition is a major O3 sink. As a follow-up study of Huang et al. (2021), we quantify the impact of satellite soil moisture (SM) on model representations of this process when different dry-deposition parameterizations are implemented, based on which the implications for interpreting O3 air pollution levels and assessing the O3 impacts on human and ecosystem health are provided. The SM data from NASA's Soil Moisture Active Passive mission are assimilated into the Noah-Multiparameterization (Noah-MP) land surface model within the NASA Land Information System framework, semicoupled with Weather Research and Forecasting model with online Chemistry (WRF-Chem) regional-scale simulations covering the southeastern US. Major changes in the modeling system used include enabling the dynamic vegetation option, adding the irrigation process, and updating the scheme for the surface exchange coefficient. Two dry-deposition schemes are implemented, i.e., the Wesely scheme and a “dynamic” scheme, in the latter of which dry-deposition parameterization is coupled with photosynthesis and vegetation dynamics. It is demonstrated that, when the dynamic scheme is applied, the simulated O3 dry-deposition velocities vd and their stomatal and cuticular portions, as well as the total O3 fluxes Ft, are larger overall; vd and Ft are 2–3 times more sensitive to the SM changes due to the data assimilation (DA). Further, through case studies at two forested sites with different soil types and hydrological regimes, we highlight that, applying the Community Land Model type of SM factor controlling stomatal resistance (i.e., β factor) scheme in replacement of the Noah-type β factor scheme reduced the v(d) sensitivity to SM changes by ∼75 % at one site, while it doubled this sensitivity at the other site. Referring to multiple evaluation datasets, which may be associated with variable extents of uncertainty, the model performance of vegetation, surface fluxes, weather, and surface O3 concentrations shows mixed responses to the DA, some of which display land cover dependency. Finally, using model-derived concentration- and flux-based policy-relevant O3 metrics as well as their matching exposure–response functions, the relative biomass/crop yield losses for several types of vegetation/crops are estimated to be within a wide range of 1 %–17 %. Their sensitivities to the model's dry-deposition scheme and the implementation of SM DA are discussed.

Min Huang↗
DOE OSTI2020

Assessing Cost-Optimal Battery Energy and Solar-Plus-Storage Systems for Federal Customers: A Nationwide Assessment: Preprint

Prior research has identified that the financial viability of behind-the-meter battery energy storage systems is heavily dependent on technology cost, utility rate structure, energy consumption patterns, and co-deployment with synergistic technologies like solar photovoltaics (PV), among other factors. This study builds on existing research by comprehensively evaluating the economics of battery energy storage systems (BESS) and solar-plus-storage systems for a reference office building at 755 reference sites under 834 utility rates, and four storage capital cost scenarios. Results indicate that even with dramatic cost reductions, BESS is likely to be cost-effective only under utility rates that include demand charges, and possibly include time-of-use (TOU) pricing as well. Even under these utility rates, BESS systems provide marginal savings, and office building operators are unlikely to deploy the technology for cost savings alone. Solar-plus-storage systems provide more savings than BESS and allow for larger economic storage capacities. Solar-plus-storage provides compelling savings opportunities at baseline prices, and even at capital costs 25% higher than baseline. Solar-plus-storage is most effective where there are demand charges and energy pricing schemes include TOU pricing, or where electricity is expensive (at least $0.30/kWh). Our case studies illustrate that the presence of demand charges, even at similar energy costs, can be the deciding factor in BESS and solar-plus-storage viability. The findings and maps from this assessment may be of use to planners, building owners, and developers looking for potentially economic storage opportunities.

battery energy storage systems↗
DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Scaling Wind Power Innovation Assessment for Rapid Energy Transition with Artificial Intelligence

Planning for energy system decarbonization requires new insights into the potential of renewable technologies, deployed at unprecedented scale, to meet urgent sustainability goals. However, limited scalability of current wind energy research tools restricts characterization of innovation impacts to isolated reference sites, challenging investment and decision making under rapid growth. We demonstrate the transformative potential of artificial intelligence (AI) to inform future technology advancement and energy systems design by leveraging a state-of-the-art surrogate model to conduct a series of fleet-wide wind plant layout optimizations for greater than 6,800 projected U.S. onshore buildout locations. We show how innovative wake steering technology can address an array of barriers to large-scale deployment and integration of wind power. Specifically, wake steering reduces required plant area by an average of 18% and could preserve upwards of 13,000 km2 for future greenfield deployment, potentially easing siting challenges associated with wind energy infrastructure. Further, by enabling reduced turbine spacing and increased energy production, flexible operations of wake steering improve levelized cost of energy, particularly for large plants and in land-constrained settings. Finally, optimizations that consider dynamic energy prices can deliver increased power production and revenue capture during high-value (often low-wind) periods, further bolstering plant economics. Our computationally efficient approach offers a pathway to accelerate nationwide geographic evaluation of innovative technologies.

graph neural networks↗
NASA NTRS2009

Recent Progress on Cross-Comparison of Terra and Aqua MODIS Calibration Using Dome C

For the past few years, the MODIS Characterization Support Team (MCST) at NASA/GSFC has continued to evaluate the Terra and Aqua MODIS calibration long-term stability and their calibration consistency using sensor observations over the Dome Concordia, Antarctica. Early results from Dome C observations show that the calibration of bands I and 2 (0.65 and 0.86 micron) is consistent within 1-2% and bands 31 and 32 (11 and 12 micron) differences are less than a couple of tenths of Kelvin, demonstrating that this site can provide a useful calibration reference for a wide range of Earth-observing sensors from visible (VIS) to long-wave infrared (LWIR). Recently, the Dome C area has been endorsed by the CEOS as a reference standard site for sensor cross-comparison. This, as a result, has led to an invitation to the broad community to participate in a CEOS comparison of top-of-atmosphere (TOA) spectral radiance/reflectance over Dome C. In this paper, we provide a brief description of the methodologies and report our recent progress on cross-comparison of Terra and Aqua MODIS spectral bands using observations over this area, including data provided in support of the upcoming CEOS comparison. Emphasis of this paper is on the long-term data records of MODIS instruments, their calibration consistency, and challenging issues.

Xiong, X.↗
DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) southern great plains (SGP) site at Oklahoma, USA has become a reference research site for meteorological studies. Due to an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, SGP instrumentations, the site and some site-specific atmospheric conditions which potentially effect wind turbines within the region. As the atmospheric boundary layer is bounded and influenced by the surface, observations of surface radiation components and heat fluxes are crucial in understanding land-atmosphere interactions. The entrainment of air, updrafts, downdrafts and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both surface in-situ and remote sensing observations at SGP provide an overall climatology and their interactions from surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at SGP central facility were analyzed. All the measurements were generally within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in-situ and remote sensing instrumentation used in the report; provides mathematical equations to analyze fluxes, turbulence and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site specific atmospheric conditions, such as nocturnal low-level jets. Diurnal, seasonal and yearly variations of surface, sub-surface and boundary layer quantities, such as wind speed, direction, temperature, atmospheric stability, soil temperature, and various atmospheric fluxes at SGP showed distinct trends useful for focused modeling studies. The applicability of surface similarity theory on ARM SGP data is also evaluated, which showed northerly flows are aligned with MO theory estimates compared to southerly flows. Boundary layer winds and direction profiles for several years from a Doppler lidar shows a consistent presence of a nocturnal low-level jet and predominant southerly wind directions through the boundary layer at SGP. The inter-annual variability at SGP is low (<3.5%), with a mean annual wind speed of approximately 7 m s -1 at 100 m above ground level. Boundary layer turbulence and moisture transport from Doppler and Raman lidars are evaluated, which provides evidence of increased water vapor mass flux into the great plains during nocturnal low-level jets. The moisture flux from nocturnal low-level jets is observed to be maximum during summer periods. A novel machine learning algorithm is implemented to accurately estimate the planetary boundary layer height, providing further insights into growth and destruction of the convective boundary layer height during various seasons and land-atmosphere conditions. The high frequency of low-level clouds during winter, spring and fall seasons is validated using the multi-sensor array and satellite estimates of cloud top height. Satellite vegetative fraction data provides insight into seasonal surface roughness and vegetation variability around SGP site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, USA, has become a reference research site for meteorological studies. Because of an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, the SGP instrumentation, the site and some site-specific atmospheric conditions, which potentially affect wind turbines in the region. Because the atmospheric boundary layer is bounded and influenced by the land surface, observations of surface radiation components and heat fluxes are crucial to understanding land–atmosphere interactions. The entrainment of air, updrafts, downdrafts, and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both ground surface in situ and remote-sensing observations at the SGP site provide an overall climatology and their interactions from ground surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at the SGP central facility were analyzed. All the measurements were generally made within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at the SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in situ and remotesensing instrumentation used in the report; mathematical equations to analyze fluxes, turbulence, and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory (MOST); an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site-specific atmospheric conditions, such as nocturnal low-level jets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

First-principles modeling of chemistry in mixed solvents: Where to go from here?

Mixed solvents (i.e., binary or higher order mixtures of ionic or nonionic liquids) play crucial roles in chemical syntheses, separations, and electrochemical devices because they can be tuned for specific reactions and applications. Apart from fully explicit solvation treatments that can be difficult to parameterize or computationally expensive, there is currently no well-established first-principles regimen for reliably modeling atomic-scale chemistry in mixed solvent environments. We offer our perspective on how this process could be achieved in the near future as mixed solvent systems become more explored using theoretical and computational chemistry. We first outline what makes mixed solvent systems far more complex compared to single-component solvents. An overview of current and promising techniques for modeling mixed solvent environments is provided. We focus on so-called hybrid solvation treatments such as the conductor-like screening model for real solvents and the reference interaction site model, which are far less computationally demanding than explicit simulations. We also propose that cluster-continuum approaches rooted in physically rigorous quasi-chemical theory provide a robust, yet practical, route for studying chemical processes in mixed solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗