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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Wheat yield forecasts using Landsat data

Leaf area index and percentage of vegetative cover, two indices of crop yield developed from Landsat multispectral scanning data, are discussed. Studies demonstrate that the Landsat indicators may be as highly correlated with winter wheat yield as estimates based on traditional field sampling methods; in addition, the Landsat indicators may account for variations in individual field yield which are not explainable by meteorological data. A simple technique employing early-season Landsat data to make wheat yield predictions is also considered.

Colwell, J. E.↗
DOE OSTI2019

Spectral and Microclimate Measurements in Relation to Gold-Standard Methods Field Campaign Report

Arable is an agricultural data and analytics company offering an Internet of things (IOT)-enabled irrigation management tool, weather station, and crop monitor: the Arable Mark. The device synthesizes both climate and plant data to produce actionable insights on natural resource management, mainly commercial agriculture at any scale. Arable collected 11 months of microclimate and radiometric data at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory to compare measurements of the Arable Mark to the ARM-SGP gold-standard sensors, and for demonstrating the ease of installation and system value to stakeholders. A member from Arable labs installed the device on January 10, 2018, at the ARM facilities and the site managers were in charge of maintaining the sensors in a clean state until the unit’s removal on January 15, 2019. The sampling was positively uneventful, except for a period during the winter when the device stopped posting data for about one week. The verdict was that the equipment required an external solar panel to stay powered through the shorter days of winter. A solar panel was shipped to the SGP, and the unit came back to full charge to continue sending data for the rest of the sampling period. The main goal of the project is to use the data collected by the Arable Mark and build a model that can establish a close relationship with the current methodologies applied to measure ecosystem response to environmental changes. During the sampling period, our team discovered that there was a drift in some of the meteorological data and also in the radiometry, so all efforts are focused into the development of models that would reduce the errors in the reported values.

Southern Great Plains, evapotranspiration, photosy↗
NASA NTRS1979

Case studies of gravity waves associated with isolated tornadic storms on January 13, 1976

Penetrative convection, thunderstorms, squall lines, etc., all generate atmospheric gravity waves which can be observed by a ground-based ionospheric Doppler sounder array. Sources of these waves can be determined from reverse ray tracing computations. Case studies of gravity waves associated with isolated tornadic storms on January 13, 1976 were summarized to establish the minimum data sampling time required for correct spectral analysis and ray tracing computations. It was concluded that the data sampling time can be reduced to two to three times the wave period while still obtaining a reasonably good power spectral density. It was also demonstrated that the data sampling time can be reduced to two to three times the time delay of the wave arrival between two station pairs while still obtaining a justifiably good cross-spectral analysis. Computed source locations of the observed gravity waves are compared with conventional and satellite meteorological data.

Hung, R. J.↗
DOE OSTI2025

Multi-seasonal measurements of the ground-level atmospheric ice-nucleating particle abundance on the North Slope of Alaska

Atmospheric ice-nucleating particles (INPs) are an important subset of aerosol particles that are responsible for the heterogeneous formation of ice crystals. INPs modulate the arctic cloud phase (liquid vs. ice), resulting in implications for radiative feedbacks. The number of arctic INP studies investigating specific INP episodes or sources increased recently. However, existing studies are based on short-duration field data, and long-term datasets are lacking. Continuous, long-term measurements are key to determining the abundance and variability of ambient arctic INPs and constraining aerosol–cloud interactions, e.g., to verify and/or improve simulations of mixed-phase clouds. Here, we present a new long-duration INP dataset from the Arctic: 2 years of predominantly immersion-mode INP concentrations (n INP ) measured continuously at the National Oceanic and Atmospheric Administration's Barrow Atmospheric Baseline Observatory (BRW) on the North Slope of Alaska. A portable ice nucleation experiment chamber (PINE-03), which simulates adiabatic expansion cooling, was used to directly measure the ground-level INP abundance with an approximately 12 min time resolution from October 2021 to December 2023. We document PINE-03 n INP measurements as well as estimated ice nucleation active surface site density (n s ) over a wide range of heterogeneous freezing temperatures from −16 to −31 °C from which we introduce new season-specific parameterizations suitable for modeling mixed-phase clouds. Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient n INP , air mass origin region, and meteorological variability. Our findings suggest (1) very high freezing efficiency of INPs across the measured temperatures (n s ≈ 2×10 8 –10 10 m −2 for −16 to −31 °C), which is a factor of 10–1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in fall using the same instrument; (2) surprisingly high n INP (≥ 1 L −1 at −25 °C) for the examined temperatures throughout the year that were not measured by PINE-03 at other sites; and (3) high n INP in spring, possibly related to arctic haze episodes. Relatively low concentrations of aerosol surface area and contrasting high-INP concentrations at BRW relative to mid-latitude sites are the possible reasons for the observed high freezing efficiency.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Modeling the terrestrial hydrology for the global atmosphere - The future role of satellite data

A global terrestrial hydrology model has been developed for the transport and storage of moisture and heat in the ground surface layer where the hydrological parameters react to diurnal and seasonal changes in the atmosphere. The spatial and temporal variability of land surface features is considered in the model by means of large scale parameterizations. The model can be either forced by the atmosphere using conventional meteorological data or coupled to an atmospheric general circulation model (GCM) for interactive studies. The global surface is divided into 4 deg longitude by 5 deg latitude cells while the ground is represented by a thin surface layer, a bulk layer (the root zone), and a deep layer (the ground water zone). Results are presented from a seven-day global experiment which was conducted utilizing the GLAS GCM (NASA Goddard Laboratory for Atmospheric Sciences). The model has demonstrated its capability to predict, over a large region, the overall soil moisture storage and major flux exchanges with the atmosphere above and the ground water below.

Lin, J. D.↗
DOE OSTI2019

Timing and duration of hydrological transitions in Arctic polygonal ground from stable isotopes

Land surface models and Earth system models that include Arctic landscapes must capture the abrupt hydrological transitions that occur during the annual thaw and deepening of the active layer. In this work, stable water isotopes (δ 2 H and δ 18 O) are used to appraise hydrologically significant transitions during annual landscape thaw at the Barrow Environmental Observatory (Utqia&#289vik, Alaska). These hydrologically significant periods are then linked to annual shifts in the landscape energy balance, deduced from meteorological data and described by the microclimatic periods: Winter, Pre-Melt, Melt, Post-Melt, Summer, and Freeze-Up. The tight coupling of the microclimatic periods with the hydrological transitions supports the use of microclimatic periods as a means of linking polygonal surface water hydrology to meteorological datasets, which provides a mechanism for improving the representation of polygonal surface water hydrology in process-based models. Rayleigh process reconstruction of the isotopic changes revealed that 19% of winter precipitation was lost to sublimation prior to melting and that 23% of surface water was lost to evaporation during the first 10 days post-melt. This agrees with evaporation rates reported in a separate study using an eddy covariance flux tower located nearby. An additional 17% was lost to evaporation during the next 33 days. Stable water isotopes are also used to identify the dominant sources of surface water to various hydrogeomorphological features prevalent in polygonal terrain (a lake, a low centre polygon centre, troughs within the rims of low centre polygons, flat centre polygon troughs, a high centre polygon trough, and drainages). Hydrogeomorphologies that retained significant old water or acted as snow drifts are isotopically distinct during the Melt Period and therefore are easily distinguished. Finally, biogeochemical changes related to the annual thaw are also reported and coupled to the hydrological transitions, which provides insight into the sources and sinks of these ions to and from the landscape.

stable water isotopes↗
NASA NTRS1981

A study of model parameters associated with the urban climate using HCMM data

The use of infrared and visible data from the Heat Capacity Mapping Mission (HCMM) and in situ data to study the intensity of the urban heat island of Saint Louis is described. Analysis of HCMM data shows that an urban heat island exists day and night in all seasons when clear skies prevail. The lower albedo value of the urban region during the day suggests that the higher temperatures are due to more absorption of solar radiation. Preliminary analysis of in situ meteorological data was performed after merging with HCMM data, and surface roughness, the exchange coefficient, and the soil moisture were calculated.

Source record↗
NASA NTRS1999

The GEOS Ozone Data Assimilation System: Design and Validation

An ozone data assimilation system has been developed at the Data Assimilation Office of the NASA/Goddard Space Flight Center to provide global three-dimensional analyzed ozone mixing ratio and total column ozone. The Total Ozone Mapping Spectrometer (TOMS) total column ozone and the Solar Backscatter Ultraviolet (SBUV) or SBUV/2 partial ozone profile data are assimilated. The analyzed winds from the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) drive the ozone transport. Following every transport model timestep, the model prediction is combined with the observations using a global, physical-space based, statistical analysis scheme. Due to the smaller size of the ozone system than that of a global meteorological data assimilation system, new statistical analysis methodology, including anisotropic and flow-dependent forecast error correlation models, can be implemented and tested in the ozone system more easily. Sample results from the winter 1992 validation period are presented. There is a close agreement between the analyzed fields and the independent observations from ozone sondes and the Halogen Occultation Experiment (HALOE).

Stajner, I.↗
NASA NTRS2000

Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations

Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.

Owe, Manfred↗
NASA NTRS2010

The Wettzell System Monitoring Concept and First Realizations

Automated monitoring of operational system parameters for the geodetic space techniques is becoming more important in order to improve the geodetic data and to ensure the safety and stability of automatic and remote-controlled observations. Therefore, the Wettzell group has developed the system monitoring software, SysMon, which is based on a reliable, remotely-controllable hardware/software realization. A multi-layered data logging system based on a fanless, robust industrial PC with an internal database system is used to collect data from several external, serial, bus, or PCI-based sensors. The internal communication is realized with Remote Procedure Calls (RPC) and uses generative programming with the interface software generator idl2rpc.pl developed at Wettzell. Each data monitoring stream can be configured individually via configuration files to define the logging rates or analog-digital-conversion parameters. First realizations are currently installed at the new laser ranging system at Wettzell to address safety issues and at the VLBI station O Higgins as a meteorological data logger. The system monitoring concept should be realized for the Wettzell radio telescope in the near future.

Ettl, Martin↗
DOE OSTI2026

Assessing Photovoltaic Capacity Factor Variability Using Long-Term Satellite Derived Solar Resource Data Under Brazilian Climate

Accurate estimation of photovoltaic (PV) energy yield and its variability is essential for reducing financial risk and supporting reliable system planning for rapidly expanding PV markets. In Brazil, high solar adoption and increasing levels of distributed energy resources are beginning to introduce operational challenges such as curtailment and evolving grid requirements. Understanding how natural variability in solar resource propagates into PV system performance is therefore increasingly important for both project design and grid integration. Modern PV yield assessments commonly rely on multi-year meteorological datasets and probabilistic exceedance metrics (e.g., P50/P90) to quantify energy yield uncertainty for project financing. However, the implications of long-term solar resource variability for PV system design choices and high-adoption grid conditions remain less well characterized for rapidly expanding markets such as Brazil. In particular, understanding how weather-driven variability propagates into PV production distributions and capacity factor expectations is important for evaluating curtailment exposure, deployment strategies, and storage requirements in regions experiencing rapid growth of distributed and utility-scale PV. Seasonal and interannual variability in atmospheric conditions can produce substantial fluctuations in monthly PV energy production, which propagate into uncertainty in annual energy yield and capacity factor expectations. Characterizing this variability using long-term meteorological datasets allows probabilistic estimation of PV system performance and provides improved insight into the range of expected PV energy outcomes. This study explores the use of long-term satellite-derived meteorological data from the National Solar Radiation Database (NSRDB) to evaluate the variability of photovoltaic system performance across multiple locations in Brazil. Using a 27-year dataset (1998-2024), PV system simulations are performed to characterize the distribution of annual and seasonal capacity factors and energy yield outcomes, while propagating key sources of meteorological variability and model uncertainty through the PV modeling chain. The analysis also investigates the sensitivity of PV performance outcomes to key system design assumptions within the PV modeling chain, including tracking configuration and system sizing parameters. The resulting probabilistic performance characterization provides insight into how weather-driven variability influences PV production expectations and capacity factor distributions. These results provide a foundation for evaluating how weather-driven variability interacts with high PV adoption and potential storage or curtailment mitigation strategies.

14 SOLAR ENERGY↗
DOE OSTI2025

U.S. Agrivoltaics Irradiance Database

This is a foundational data set for research and deployment of agrivoltaics, which is the co-location of agriculture and solar power plants on the same land. This irradiance and shading dataset can be utilized to determine the suitability of agrivoltaics configurations for a given region and crop-type. The data is hourly, 4x4 km resolution across the contiguous United States and Hawaii. It is calculated from the National Solar Radiation Database sites, using the System Advisor Model (SAM) to simulate the shading patterns for 10 common agrivoltaics configurations. Sunlight availability data is reported for 10 locations on the ground between adjacent rows of solar panels, as well as averaged across areas of interest such as the average irradiance in the edge-to-edge open area or across 3-6 planting beds. Other available metrics include the input meteorological data from the NSRDB (e.g. global horizontal irradiance, wind speed, etc.) and estimates for comparing energy and agricultural characteristic across the 10 configurations, including power output per acre or per kW installed capacity and farmable land area per acre.

14 SOLAR ENERGY↗
NASA NTRS1978

Users' instructions for the NASA/MSFC cloud-rise preprocessor program, version 6, and the NASA/MSFC multilayer diffusion program, version 6: Research version for Univac 1108 system

The cloud-rise preprocessor and multilayer diffusion computer programs were used by NASA in predicting concentrations and dosages downwind from normal and abnormal launches of rocket vehicles. These programs incorporated: (1) the latest data for the heat content and chemistry of rocket exhaust clouds; (2) provision for the automated calculation of surface water pH due to deposition of HCl from precipitation scavenging; (3) provision for automated calculation of concentration and dosage parameters at any level within the vertical grounds for which meteorological inputs have been specified; and (4) provision for execution of multiple cases of meteorological data. Procedures used to automatically calculate wind direction shear in a layer were updated.

Bjorklund, J. R.↗
DOE OSTI2022

Watershed Workflow: A toolset for parameterizing data-intensive, integrated hydrologic models

Integrated, distributed hydrologic models leverage advances in computational power and data accessibility to improve predictive understanding of the water cycle. While impressive advances in this area of environmental modeling have been accomplished, such models are still rarely used, partially because of difficulty integrating model and data. This research describes the release of Watershed Workflow version 1.2, a new library aiming to automate and enable complex workflows defining inputs to high resolution, integrated, distributed hydrologic models. Watershed Workflow provides tools enabling the discovery, acquisition, mapping, and coordination of watershed geometry, land cover, soil properties, and meteorological data. It enables the construction of unstructured meshes that incorporate this data, and provides tools for automating a “first” simulation on any watershed in the United States. We present the design of the workflow tool, and describe best practices for its usage, culminating in a final example from watershed specification to simulation at the Coweeta Hydrologic Laboratory.

Integrated hydrologic modeling↗
NASA NTRS1972

Application of ERTS-A data to the protection and management of New Jersey's coastal environment

The author has identified the following significant results. Apparent sewage sludge disposal by barge has been detected approximately 12 miles offshore in an area with an approximate radius of 2.5 nautical miles. Verification is underway to determine whether this dumping is within one of the approved dump sites in the Bight. Analysis of all available historical and routine meteorological data in correlation with the observed phenomenon is necessary before final conclusions can be reached with respect to the effects of currents on the disposal of dumped wastes. Four effluent plumes emanating from the shoreline just south of Sandy Hook were observed and are moving in a southerly direction. Another plume is evident north of Barnegat Inlet and is moving almost directly offshore. This suggests that the more northerly plumes are under the influence of the tidal regime around New York Harbor much more than are the plumes further south along the New Jersey coast. Of further interest are what appear to be an internal wave phenomena approximately 75 miles east of the New Jersey coast. This same sort of phenomena has been observed repetitively off the coast of Oregon.

Yunghans, R. S.↗
NASA NTRS2005

Improvements in the estimates of ice thickness and production in the Chukchi Sea polynyas derived from AMSR-E

For January-March 2003, we use 12.5-km resolution Advanced Microwave Scanning Radiometer (AMSR) data for the first time in a comparison with Synthetic Aperture Radar (SAR) and Special Sensor Microwave/Imager (SSM/I) data to study two Chukchi coast polynyas, one consisting of many, the other of only a few 25-km SSM/I pixels. Within these polynyas, the ice thicknesses are derived separately from the SMM/I 37-GHz and AMSR 36-GHz channels; the heat fluxes are derived by combining thicknesses with meteorological data. Comparison with ScanSAR data shows that for the large polynya, because AMSR provides better resolution of the surrounding coastline and first-year ice, the AMSR heat losses are greater than the SSM/I; for the small polynya, AMSR measures its variability even when its area is order of a single SSM/I pixel. This means that AMSR permits more accurate calculation of polynya heat losses, yielding the potential of improved estimates of Arctic polynya productivity.

ice thicknesses↗
NASA NTRS2005

Improvements in the estimates of ice thickness and production in the Chukchi Sea polynyas derived from AMSR-E

For January-March 2003, we use 12.5-km resolution Advanced Microwave Scanning Radiometer (AMSR) data for the first time in a comparison with Synthetic Aperture Radar (SAR) and Special Sensor Microwave/Imager (SSM/I) data to study two Chukchi coast polynyas, one consisting of many, the other of only a few 25-km SSM/I pixels. Within these polynyas, the ice thicknesses are derived separately from the SMM/I 37-GHz and AMSR 36-GHz channels; the heat fluxes are derived by combining thicknesses with meteorological data. Comparison with ScanSAR data shows that for the large polynya, because AMSR provides better resolution of the surrounding coastline and first-year ice, the AMSR heat losses are greater than the SSM/I; for the small polynya, AMSR measures its variability even when its area is order of a single SSM/I pixel. This means that AMSR permits more accurate calculation of polynya heat losses, yielding the potential of improved estimates of Arctic polynya productivity.

Chukchi coast polynyas↗
NASA NTRS2005

Improvements in the estimates of ice thickness and production in the Chukchi Sea polynyas derived from AMSR-E

For January-March 2003, we use 12.5-km resolution Advanced Microwave Scanning Radiometer (AMSR) data for the first time in a comparison with Synthetic Aperture Radar (SAR) and Special Sensor Microwave/Imager (SSM/I) data to study two Chukchi coast polynyas, one consisting of many, the other of only a few 25-km SSM/I pixels. Within these polynyas, the ice thicknesses are derived separately from the SMM/I 37-GHz and AMSR 36-GHz channels; the heat fluxes are derived by combining thicknesses with meteorological data. Comparison with ScanSAR data shows that for the large polynya, because AMSR provides better resolution of the surrounding coastline and first-year ice, the AMSR heat losses are greater than the SSM/I; for the small polynya, AMSR measures its variability even when its area is order of a single SSM/I pixel. This means that AMSR permits more accurate calculation of polynya heat losses, yielding the potential of improved estimates of Arctic polynya productivity.

Advanced Microwave Scanning Radiometer (AMSR)↗