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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Descriptor: High Temporal Resolution Meteorological Data at Oak Ridge Reservation (ORR-HiResMet)

Access to continuous, quality assessed meteorological data is critical for understanding the climatology and atmospheric dynamics of a region. Research facilities like Oak Ridge National Laboratory (ORNL) rely on such data to assess site-specific climatology, model potential emissions, establish safety baselines, and prepare for emergency scenarios. To meet these needs, on-site towers at ORNL collect meteorological data at 15-minute and hourly intervals. However, data measurements from meteorological towers are affected by sensor sensitivity, degradation, lightning strikes, power fluctuations, glitching, and sensor failures, all of which can affect data quality. To address these challenges, we conducted a comprehensive quality assessment and processing of five years of meteorological data collected from ORNL at 15-minute intervals, including measurements of temperature, pressure, humidity, wind, and solar radiation. The time series of each variable was pre-processed and gap-filled using established meteorological data collection and cleaning techniques, i.e., the time series were subjected to structural standardization, data integrity testing, automated and manual outlier detection, and gap-filling. The data product and highly generalizable processing workflow developed in Python Jupyter notebooks are publicly accessible online. As a key contribution of this study, the evaluated 5-year data will be used to train atmospheric dispersion models that simulate dispersion dynamics across the complex ridge-and-valley topography of the Oak Ridge Reservation in East Tennessee.

Steckler, Morgan R. [Oak Ridge National Laboratory↗
NASA NTRS1976

Analysis of high resolution satellite data for cosmic gamma ray bursts

Cosmic gamma ray bursts detected a germanium spectrometer on the low altitude satellite 1972-076B were surveyed. Several bursts with durations ranging from approximately 0.032 to 15 seconds were found and are tabulated. The frequency of occurrence/intensity distribution of these events was compared with the S to the -3/2 power curve of confirmed events. The longer duration events fall above the S to the -3/2 power curve of confirmed events, suggesting they are perhaps not all true cosmic gamma-ray bursts. The narrow duration events fall closely on the S to the -3/2 power curve. The survey also revealed several counting rate spikes, with durations comparable to confirmed gamma-ray bursts, which were shown to be of magnetospheric origin. Confirmation that energetic electrons were responsible for these bursts was achieved from analysis of all data from the complete payload of gamma-ray and energetic particle detectors on board the satellite. The analyses also revealed that the narrowness of the spikes was primarily spatial rather than temporal in character.

Imhof, W. L.↗
NASA NTRS1989

The use of high-resolution terrain data in gravity field prediction

Different types of gravity prediction methods for local and regional gravity evaluation are developed, tested, and compared. Four different test areas were particularly selected in view of different prediction requirements. Also different parts of the spectrum of the gravity field were considered.

Groten, E.↗
NASA NTRS1990

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Key, J.↗
NASA NTRS1990

Automated cloud base height determination from high resolution Landsat data - A Hough transform approach

A direct method for determining the cloud base height derived from the displacement of the shadow from the cloud, and the solar azimuth and zenith angle is presented. Cumulus cloud scenes over land from Landsat MSS imagery are considered. The clouds are first matched with the corresponding shadows; the pixel distance of a reference point in the cloud is computed from the corresponding reference point in the shadow; and then the solar zenith angle is used to compute the cloud base height. Observations indicate that the cloud base height appears to be size-dependent with larger clouds generally associated with higher cloud bases and that clouds within the same size range and within the same scene region are approximately of the same height.

Sengupta, S. K.↗
NASA NTRS2012

Method and system for near-field spectroscopy using targeted deposition of nanoparticles

There is provided in one embodiment of the invention a method for analyzing a sample material using surface enhanced spectroscopy. The method comprises the steps of imaging the sample material with an atomic force microscope (AFM) to select an area of interest for analysis, depositing nanoparticles onto the area of interest with an AFM tip, illuminating the deposited nanoparticles with a spectrometer excitation beam, and disengaging the AFM tip and acquiring a localized surface enhanced spectrum. The method may further comprise the step of using the AFM tip to modulate the spectrometer excitation beam above the deposited nanoparticles to obtain improved sensitivity data and higher spatial resolution data from the sample material. The invention further comprises in one embodiment a system for analyzing a sample material using surface enhanced spectroscopy.

Anderson, Mark S.↗
DOE OSTI2019

DeepClimGAN: A High-Resolution Climate Data Generator

Earth system models (ESMs), which simulate the physics and chemistry of the global atmosphere, land, and ocean, are often used to generate future projections of climate change scenarios. These models are far too computationally inten- sive to run repeatedly, but limited sets of runs are insufficient for some important applications, like adequately sampling distribution tails to characterize extreme events. As a com- promise, emulators are substantially less expensive but may not have all of the complexity of an ESM. Here we demon- strate the use of a conditional generative adversarial network (GAN) to act as an ESM emulator. In doing so, we gain the ability to produce daily weather data that is consistent with what ESM might output over any chosen scenario. In particular, the GAN is aimed at representing a joint proba- bility distribution over space, time, and climate variables, enabling the study of correlated extreme events, such as floods, droughts, or heatwaves.

Extreme events, Machine Learning, deep learning↗
DOE OSTI2022

Improving Simulations of Vegetation Dynamics over the Tibetan Plateau: Role of Atmospheric Forcing Data and Spatial Resolution

The efficacy of vegetation dynamics simulations in offline land surface models (LSMs) largely depends on the quality and spatial resolution of meteorological forcing data. In this study, the Princeton Global Meteorological Forcing Data (PMFD) and the high spatial resolution and upscaled China Meteorological Forcing Data (CMFD) were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics (SSiB4/TRIFFID) and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau (TP), a region with complex topography and sparse observations. By comparing the monthly Leaf Area Index (LAI) and Gross Primary Production (GPP) against observations, we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP, reducing RMSEs by 24.3% and 20.5%, respectively. The multi-year averaged GPP decreased from 364.68 gC m –2 yr –1 to 241.21 gC m –2 yr –1 with the percentage bias dropping from 50.2% to –1.7%. When using the high spatial resolution CMFD, the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5% and 9.5%, respectively. This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

AMM: Adaptive Multilinear Meshes

Adaptive representations are increasingly indispensable for reducing the in-memory and on-disk footprints of large-scale data. Usual solutions are designed broadly along two themes: reducing data precision, e.g., through compression, or adapting data resolution, e.g., using spatial hierarchies. Additionally, recent research suggests that combining the two approaches, i.e., adapting both resolution and precision simultaneously, can offer significant gains over using them individually. However, there currently exist no practical solutions to creating and evaluating such representations at scale. In this work, we present a new resolution-precision-adaptive representation to support hybrid data reduction schemes and offer an interface to existing tools and algorithms. Through novelties in spatial hierarchy, our representation, Adaptive Multilinear Meshes (AMM), provides considerable reduction in the mesh size. AMM creates a piecewise multilinear representation of uniformly sampled scalar data and can selectively relax or enforce constraints on conformity, continuity, and coverage, delivering a flexible adaptive representation. AMM also supports representing the function using mixed-precision values to further the achievable gains in data reduction. We describe a practical approach to creating AMM incrementally using arbitrary orderings of data and demonstrate AMM on six types of resolution and precision datastreams. By interfacing with state-of-the-art rendering tools through VTK, we demonstrate the practical and computational advantages of our representation for visualization techniques. With an open-source release of our tool to create AMM, we make such evaluation of data reduction accessible to the community, which we hope will foster new opportunities and future data reduction schemes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

High resolution atmospheric and surface variability from combined MAMS and VAS radiances

Measuring of the variation of atmospheric and surface quantities such as moisture and stability at small scales is an important step to monitoring, understanding and forecasting mesoscale processes. For instance, moisture and stability products from the geostationary platform VISSR Atmospheric Sounder (VAS) exhibit interesting detail at the meso B (20-200 km) level (Chesters et al., 1986; Smith et al., 1985). However, variations at the meso C scale (2-20 km) and at the lower end of the meso B scale (20-100 km) suffer from the effects of noise. Noise can be greatly reduced by using a high resolution data collection system. The Multispectral Atmospheric Mapping Sensor (MAMS), with its 100-m resolution over a 36km swath, is well suited to provide high resolution mesoscale information about the atmosphere and surface of the earth. A more complete depiction of the atmospheric state at the smaller scales is possible through the combination of the high horizontal resolution MAMS data with the vertical sounding data of the VAS. This paper demonstrates a procedure for combining MAMS and VAS data in a physical retrieval to produce high resolution derived products of precipitable water (PW), lifted index (LI), and skin temperature (TS). The variability of these products is evaluated in a structure function analysis similar to that of Hillger and Vonder Haar (1979). Results for 19 June 1986 from the Cooperative Hunstville Meteorological Experiment (COHMEX) are presented.

Moeller, Christopher C.↗