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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Assessing the representativeness of wind data for wind turbine site evaluation

Once potential wind turbine sites (either for single installations or clusters) are identified through siting procedures, actual evaluation of the sites must commence. This evaluation is needed to obtain estimates of wind turbine performance and to identify hazards to the machine from the turbulence component of the atmosphere. These estimates allow for more detailed project planning and for preliminary financing arrangements to be secured. The site evaluation process can occur in two stages: (1) utilizing existing nearby data, and (2) establishing and monitoring an onsite measurement program. Since step (2) requires a period of at least 1 yr or more from the time a potential site has been identified, step (1) is often an essential stage in the preliminary evaluation process. Both the methods that have been developed and the unknowns that still exist in assessing the representativeness of available data to a nearby wind turbine site are discussed. How the assessment of the representativeness of available data can be used to develop a more effective onsite meteorological measurement program is also discussed.

Renne, D. S.↗
NASA NTRS2002

Microphysics and Radiative Properties of Cirrus: Instrumentation and Analysis

Work under this grant has involved further development of a new aircraft instrument (the cloudscope) for real time characterization of atmospheric particulates together with field observations of such particulates, both in the form of ice and also as nuclei responsible for nucleation of both ice and water cloud particles. Part of the work involving assessment of the frequency of ice crystal shapes has been carried out in collaboration with the Meteorological Service of Canada; part of the work in a field program with the NCAR C-130. Part of the work has been interpreted in terms of laboratory simulation of ice crystal growth under a wide variety of conditions carried out under a grant from Physical Meteorology Program, National Science Foundation.

Hallett, John↗
NASA NTRS2011

A Study on the Potential Applications of Satellite Data in Air Quality Monitoring and Forecasting

In this study we explore the potential applications of MODIS (Moderate Resolution Imaging Spectroradiometer) -like satellite sensors in air quality research for some Asian regions. The MODIS aerosol optical thickness (AOT), NCEP global reanalysis meteorological data, and daily surface PM(sub 10) concentrations over China and Thailand from 2001 to 2009 were analyzed using simple and multiple regression models. The AOT-PM(sub 10) correlation demonstrates substantial seasonal and regional difference, likely reflecting variations in aerosol composition and atmospheric conditions, Meteorological factors, particularly relative humidity, were found to influence the AOT-PM(sub 10) relationship. Their inclusion in regression models leads to more accurate assessment of PM(sub 10) from space borne observations. We further introduced a simple method for employing the satellite data to empirically forecast surface particulate pollution, In general, AOT from the previous day (day 0) is used as a predicator variable, along with the forecasted meteorology for the following day (day 1), to predict the PM(sub 10) level for day 1. The contribution of regional transport is represented by backward trajectories combined with AOT. This method was evaluated through PM(sub 10) hindcasts for 2008-2009, using ohservations from 2005 to 2007 as a training data set to obtain model coefficients. For five big Chinese cities, over 50% of the hindcasts have percentage error less than or equal to 30%. Similar performance was achieved for cities in northern Thailand. The MODIS AOT data are responsible for at least part of the demonstrated forecasting skill. This method can be easily adapted for other regions, but is probably most useful for those having sparse ground monitoring networks or no access to sophisticated deterministic models. We also highlight several existing issues, including some inherent to a regression-based approach as exemplified by a case study for Beijing, Further studies will be necessa1Y before satellite data can see more extensive applications in the operational air quality monitoring and forecasting.

Li, Can↗
DOE OSTI2024

Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S.

Weather data plays a critical role in renewable energy analysis. Compared to using multiple Actual Meteorological Years, simulations using a single typical year require significantly fewer computational resources. Previous efforts to create typical weather datasets for renewable energy analysis either lack justified or optimized strategies for selecting and weighting different weather parameters or are limited to a few specific locations. Here, in this study, we developed a dataset comprising Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for over 2000 locations across the U.S., based on data from NASA's POWER project. The strategies for creating TSYs and TWYs were optimized based on the simulated outputs of various PV systems and wind turbines in 16 representative cities. This dataset provides an efficient means for the rapid evaluation and optimization of renewable energy systems throughout the entire U.S. Additionally, the optimal strategies identified in this study can be directly applied to create near-optimal TSYs and TWYs for most locations worldwide. However, readers can also employ the optimization approach presented in this work to develop optimal strategies tailored for particular regions.

NASA POWER↗
NASA NTRS1992

The role and future of space technology in disaster reduction

Disaster mitigation consists of many activities, including vulnerability assessment, disaster warning and prediction and disaster relief. Various types of satellites can be applied to these endeavors: communications, geophysical, meteorological and Earth resources. The latter two are considered 'remote sensing' satellites. There are many limitations in the design and development of remote sensing satellites; limitations in cost and the acceptable data rate and limitations in our technology. Nevertheless, there are a large number of satellites, both currently in orbit and planned, with capabilities pertinent to disaster mitigation. Some of these are operational and can be relied upon to provide continued data sources. Others are experimental and provide the disaster management community and opportunity to assess the potential usefulness of the techniques and to impact the design of future operational systems. A table lists the operational parameters and potential application in disaster mitigation of 44 current and planned remote sensing satellites and instruments.

Walter, Louis S.↗
DOE OSTI2023

Hyperspectral Infrared Observations of Arctic Snow, Sea Ice, and Non-Frozen Ocean from the RV Polarstern during the MOSAiC Expedition October 2019 to September 2020

This study highlights hyperspectral infrared observations from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) collected as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployment on the icebreaker RV Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The ARM M-AERI directly measures the infrared radiance emission spectrum between 520 cm –1 and 3000 cm –1 (19.2–3.3 μm) at 0.5 cm –1 spectral resolution. These ship-based observations provide a valuable set of radiance data for the modeling of snow/ice infrared emission as well as validation data for the assessment of satellite soundings. Remote sensing using hyperspectral infrared observations provides valuable information on sea surface properties (skin temperature and infrared emissivity), near-surface air temperature, and temperature lapse rate in the lowest kilometer. Comparison of the M-AERI observations with those from the DOE ARM meteorological tower and downlooking infrared thermometer are generally in good agreement with some notable differences. Operational satellite soundings from the NOAA-20 satellite were also assessed using ARM radiosondes launched from the RV Polarstern and measurements of the infrared snow surface emission from the M-AERI showing reasonable agreement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Tools for Assessing Performance (TAP) Project: FY2023 Quarter 2 Report

LANL personnel presented TAP-sponsored work at the 103 rd Annual Meeting of the American Meteorological Society, which was held in Denver, CO in January 2023. There were four different presentations related to TAP-sponsored work that were given by LANL staff and studentsat this meeting: (1) Gloeckler, T., M. Nelson, H. Shah, M. Deshler, L. Wedell, R. Linn, N. Duboc, S. Pol, P. Bieringer, A. Annunzio, B. Martin, and H. Tinnesand, 2023. Testing Validity and Limitations of a Low-Order Diffusive Wake Model. 15 th Symposium on the Urban Environment, January 8-12, 2023, Denver, CO, U.S.A. (2) Nelson, M., H. Shah, T. Gloeckler, M. Deshler, L. Wedell, A. Ortega, R. Linn, N. Duboc, P. Conry, S. Pol, and H. Tinnesand, 2023. The Isolated Building Wake Experiment. Paper 1A.1. 24 th Symposium on Boundary Layers and Turbulence, January 8-12, 2023. Denver, CO, U.S.A. (3) Shah, H., M. Nelson, S. Pol, R. Linn, N. Duboc, and H. Tinnesand, 2023. Detailed Measurement of a Building Wake Under Real-World Atmospheric Conditions. Poster 102. 24 th Symposium on Boundary Layers and Turbulence, January 8-12, 2023, Denver, CO, U.S.A. (4) Wedell, L., M. Nelson, H. Shah, T. Gloeckler, M. Deshler, R. Linn, S. Pol, H. Tinnesand, 2023. The Isolated Building Wake Experiment: Using a Rotating Building to Mulitply the Number of Wake Measurement Locations without Moving the Instruments. Paper 1A.4A. 24 th Symposium on Boundary Layers and Turbulence, January 8-12, 2023, Denver, CO, U.S.A.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Advanced development of atmospheric models

A set of atmospheric analysis and prediction models was developed in support of the SEASAT Program existing objective analysis models which utilize a 125x125 polar stereographic grid of the Northern Hemisphere, which were modified in order to incorporate and assess the impact of (real or simulated) satellite data in the analysis of a two-day meteorological scenario in January 1979. Program/procedural changes included: (1) a provision to utilize winds in the sea level pressure and multi-level height analyses (1000-100 MBS); (2) The capability to perform a pre-analysis at two control levels (1000 MBS and 250 MBS); (3) a greater degree of wind- and mass-field coupling, especially at these controls levels; (4) an improved facility to bogus the analyses based on results of the preanalysis; and (5) a provision to utilize (SIRS) satellite thickness values and cloud motion vectors in the multi-level height analysis.

Kesel, P. G.↗
NASA NTRS1982

Discrimination of growth and water stress in wheat by various vegetation indices through a clear a turbid atmosphere

Reflectance data were obtained over a drought-stressed and a well-watered wheat plot with a hand-held radiometer having bands similar to the MSS bands of the LANDSAT satellites. Data for 48 clear days were interpolated to yield reflectance values for each day of the growing season, from planting until harvest. With an atmospheric path radiance model and LANDSAT-2 calibration data, the reflectance were used to simulate LANDSAT digital counts (not quantized) for the four LANDSAT bands for each day of the growing season, through a clear (approximately 100 km meteorological range) and a turbid (approximately 10 km meteorological range) atmosphere. Several ratios and linear combinations of bands were calculated using the simulated data, then assessed for their relative ability to discriminate vegetative growth and plant stress through the two atmospheres. The results show that water stress was not detected by any of the indices until after growth was retarded, and the sensitivity of the various indices to vegetation depended on plant growth stage and atmospheric path radiance.

Jackson, R. D.↗
NASA NTRS1982

Wind turbine siting: A summary of the state of the art

The process of siting large wind turbines may be divided into two broad steps: site selection, and site evaluation. Site selection is the process of locating windy sites where wind energy development shows promise of economic viability. Site evaluation is the process of determining in detail for a given site the economic potential of the site. The state of the art in the first aspect of siting, site selection is emphasized. Several techniques for assessing the wind resource were explored or developed in the Federal Wind Energy Program. Local topography and meteorology will determine which of the techniques should be used in locating potential sites. None of the techniques can do the job alone, none are foolproof, and all require considerable knowledge and experience to apply correctly. Therefore, efficient siting requires a strategy which is founded on broad based application of several techniques without relying solely on one narrow field of expertise.

Hiester, T. R.↗
NASA NTRS2018

Atmospheric Trace Gas (NO2 and Ozone) Dynamics over Coastal Waters near Polluted Urban Regions

At the interface between the land, oceans, and atmosphere, coastal regions are highly dynamic environments, characterized by strong variability in both water and air quality. Variability in atmospheric composition is associated with highly variable anthropogenic emissions, as well as complex meteorological processes that influence the circulation and accumulation of atmospheric pollutants at the land-ocean interface. Assessing the spatial and temporal dynamics of atmospheric pollutants, aerosols, and absorbing trace gases in coastal areas is critical for improving modeling of coastal tropospheric air quality, developing accurate satellite retrievals of coastal ocean color and biological processes, determining impacts of atmospheric pollution on human health, and assessing the ecological implications of atmospheric pollutant deposition for coastal terrestrial and aquatic ecosystems.Here, we present new measurements of atmospheric trace gas (NO2, and ozone) dynamics across a range of estuarine and coastal waters near urban regions. Measurements were conducted from research vessels using NASA's shipboard Pandora spectrometers, as part of recent multidisciplinary, multiplatform field campaigns, including the 2016 KORUS OC/AQ field campaign in the Yellow Sea and East Sea/Sea of Japan, the 2017/2018 OLWETS field campaign in the Chesapeake Bay estuary, and the 2018 LISTOS field campaign in the Long Island Sound. Shipboard measurements over these coastal waters were integrated with measurements from a ground-based Pandora network to examine differences in air quality over the land and over the ocean. Measurements were combined with air-parcel back-trajectory simulations to determine the origin of air masses over the coastal ocean. Comparisons with satellite retrievals of atmospheric composition reveal the benefits and limitations of polar-orbit satellite observations in capturing variability in atmospheric pollution gradients over land-water boundaries.

Tzortziou, Maria↗
NASA NTRSDate not supplied

Machine learning based noise reduction for satellite products: application to solar-induced fluorescence retrievals using simulated and real data

In the past two decades, global satellite measurements of terrestrial chlorophyll solar-induced fluorescence (SIF) have been used widely for a number of different applications related to physiology, phenology, and productivity of plants. However, SIF retrievals are inherently noisy due to the relatively small SIF spectral signature in comparison with observational noise. In this work, we examine how a spectral-based approach that employs principal component analysis along with a relatively shallow artificial neural network can be used to reduce noise and other artifacts in satellite level 2 (L2) products. We first apply the approach in a controlled environment in which radiance spectra are simulated with a full atmospheric and surface radiative transfer model for different scenarios including various SIF values that are known. Various levels of noise can be added to the simulated spectra. Resulting noisy and noise-reduced SIF retrievals are compared with the true values to assess performance. We then apply the noise reduction approach to real SIF derived from instruments flying on meteorological satellites. The results are evaluated by comparing SIF retrievals from different platforms with each other and with other independent data sets, showing enhanced capability to capture seasonal and interannual variability in SIF.

Chlorophyll fluorescence↗
NASA NTRS2014

Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations

The National Land Cover Database (NLCD) Impervious Surface Area (ISA) and MODIS Land Surface Temperature (LST) are used in a spatial analysis to assess the surface-temperature-based urban heat island's (UHIS) signature on LST amplitude over the continental USA and to make comparisons to local air temperatures. Air-temperature-based UHIs (UHIA), calculated using the Global Historical Climatology Network (GHCN) daily air temperatures, are compared with UHIS for urban areas in different biomes during different seasons. NLCD ISA is used to define urban and rural temperatures and to stratify the sampling for LST and air temperatures. We find that the MODIS LST agrees well with observed air temperature during the nighttime, but tends to overestimate it during the daytime, especially during summer and in nonforested areas. The minimum air temperature analyses show that UHIs in forests have an average UHIA of 1 C during the summer. The UHIS, calculated from nighttime LST, has similar magnitude of 1-2 C. By contrast, the LSTs show a midday summer UHIS of 3-4 C for cities in forests, whereas the average summer UHIA calculated from maximum air temperature is close to 0 C. In addition, the LSTs and air temperatures difference between 2006 and 2011 are in agreement, albeit with different magnitude.

Land Surface Temperature↗
NASA NTRS2016

Estimation of Daily PM(sub 10) Concentrations in Italy (2006-2012) Using Finely Resolved Satellite Data, Land Use Variables and Meteorology

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM10=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM10levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Particulate Matter/analysis↗
DOE OSTI2024

Statistically Resolved Planetary Boundary Layer Height Diurnal Variability Using Spaceborne Lidar Data

The Planetary Boundary Layer Height (PBLH) significantly impacts weather, climate, and air quality. Understanding the global diurnal variation of the PBLH is particularly challenging due to the necessity of extensive observations and suitable retrieval algorithms that can adapt to diverse thermodynamic and dynamic conditions. This study utilized data from the Cloud-Aerosol Transport System (CATS) to analyze the diurnal variation of PBLH in both continental and marine regions. By leveraging CATS data and a modified version of the Different Thermo-Dynamics Stability (DTDS) algorithm, along with machine learning denoising, the study determined the diurnal variation of the PBLH in continental mid-latitude and marine regions. The CATS DTDS-PBLH closely matches ground-based lidar and radiosonde measurements at the continental sites, with correlation coefficients above 0.6 and well-aligned diurnal variability, although slightly overestimated at nighttime. In contrast, PBLH at the marine site was consistently overestimated due to the viewing geometry of CATS and complex cloud structures. The study emphasizes the importance of integrating meteorological data with lidar signals for accurate and robust PBLH estimations, which are essential for effective boundary layer assessment from satellite observations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Estimates of the stratospheric residual circulation using the downward control principle

The transformed Eulerian-mean momentum and continuity equations are used to calculate the residual mean meridional circulations for the lower stratosphere and troposphere. Momentum and temperature fluxes required for the computation are estimated from U.K. Meteorological Office (UKMO) analyzed geopotential heights. National Center for Atmospheric Research (NCAR) CCM2 model output is used to assess the errors associated with the calculation. The model comparisons showed that the method works reasonably well for solstice seasons, but is inadequate for equinox seasons. In addition, it is found that some parameterization of gravity wave drag needs to be included with the planetary wave forcing to accurately estimate the residual mean circulation using this method.

Rosenlof, Karen H.↗
NASA NTRS2000

Delta 2 Explosion Plume Analysis Report

A Delta II rocket exploded seconds after liftoff from Cape Canaveral Air Force Station (CCAFS) on 17 January 1997. The cloud produced by the explosion provided an opportunity to evaluate the models which are used to track potentially toxic dispersing plumes and clouds at CCAFS. The primary goal of this project was to conduct a case study of the dispersing cloud and the models used to predict the dispersion resulting from the explosion. The case study was conducted by comparing mesoscale and dispersion model results with available meteorological and plume observations. This study was funded by KSC under Applied Meteorology Unit (AMU) option hours. The models used in the study are part of the Eastern Range Dispersion Assessment System (ERDAS) and include the Regional Atmospheric Modeling System (RAMS), HYbrid Particle And Concentration Transport (HYPACT), and Rocket Exhaust Effluent Dispersion Model (REEDM). The primary observations used for explosion cloud verification of the study were from the National Weather Service's Weather Surveillance Radar 1988-Doppler (WSR-88D). Radar reflectivity measurements of the resulting cloud provided good estimates of the location and dimensions of the cloud over a four-hour period after the explosion. The results indicated that RAMS and HYPACT models performed reasonably well. Future upgrades to ERDAS are recommended.

Evans, Randolph J.↗
NASA NTRS2008

Comparison of GPCP Monthly and Daily Precipitation Estimates with High-Latitude Gauge Observations

It is very important to know how much rain and snow falls around the world for uses that range from crop forecasting to disaster response, drought monitoring to flood forecasting, and weather analysis to climate research. Precipitation is usually measured with rain gauges, but rain gauges don t exist in areas that are sparsely populated, which tends to be a good portion of the globe. To overcome this, meteorologists use satellite data to estimate global precipitation. However, it is difficult to estimate rain and especially snow in cold climates using most current satellites. The satellite sensors are often "confused" by a snowy or frozen surface and therefore cannot distinguish precipitation. One commonly used satellite-based precipitation data set, the Global Precipitation Climatology Project (GPCP) data, overcomes this frozen-surface problem through the innovative use of two sources of satellite data, the Television Infrared Observation Satellite Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). Though the GPCP estimates are generally considered a very reliable source of precipitation, it has been difficult to assess the quality of these estimates in cold climates due to the lack of gauges. Recently, the Finnish Meteorological Institute (FMI) has provided a 12-year span of high-quality daily rain gauge observations, covering all of Finland, that can be used to compare with the GPCP data to determine how well the satellites estimate cold-climate precipitation. Comparison of the monthly GPCP satellite-based estimates and the FMI gauge observations shows remarkably good agreement, with the GPCP estimates being 6% lower in the amount of precipitation than the FMI observations. Furthermore, the month-to-month correlation between the GPCP and FMI is very high at 0.95 (1.0 is perfect). The daily GPCP estimates replicate the FMI daily occurrences of precipitation with a correlation of 0.55 in the summer and 0.45 in the winter. The winter result indicates the GPCP estimates have skill in "seeing" snowfall, which is the most challenging situation. Thus, the GPCP data set successfully overcomes a current limitation in satellite meteorology, namely the estimation of cold-climate precipitation. The success of the GPCP data set bodes well for future missions, whose instrumentation is specifically designed to give even more information for addressing cold-climate precipitation.

Bolvin, David T.↗