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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Exploring Cosmic X-ray Source Polarization

Cosmic X-ray sources are expected to be polarized, either because of their asymmetry and the role of scattering in their emission or the role of magnetic fields. Polarization at other wavelengths has been useful. X-ray polarization will provide a new handle on black hole parameters, in particular the spin, on accretion flows and outflows, on neutron star spin orientations and emission mechanisms, on the quantum mechanical effects of super-strong magnetic fields of magnetars, and on the structure of supernovae shocks. The proposed Gravity and Extreme Magnetism SMEX (GEMS) will use high efficiency polarimeters behind thin foil mirrors. The statistical sensitivity and control of systematics will allow measurement of polarization fractions as small as 1% from many galactic and extragalactic sources. Targets which should be polarized at the level that GEMS can easily measure include stellar black holes, Seyfert galaxies and quasars, blazars, rotation-powered and accretion-powered pulsars, magnetars, shell supernova remnants and pulsar wind nebulae. The polarimeters are Time Projection Chambers that allow reconstruction of images of photoelectron tracks for 2-10 keV Xrays. They can be deep without sacrificing modulation. These polarimeters do not image the sky, but the telescope point spread function and detector collimation allow structure to be resolved at the 10 arcmin level. Rotation of the spacecraft is not needed for the signal measurement in the Time Projection Chambers, but provides for measurement and correction of systematic errors. It also allows a small Bragg reflection soft X-ray experiment to be included that can be used for isolated neutron stars and blazars.

Swank, Jean Hebb↗
NASA NTRS2013

ARM Research in the Equatorial Western Pacific: A Decade and Counting

The tropical western Pacific (TWP) is an important climatic region. Strong solar heating, warm sea surface temperatures, and the annual progression of the intertropical convergence zone (ITCZ) across this region generate abundant convective systems, which through their effects on the heat and water budgets have a profound impact on global climate and precipitation. In order to accurately evaluate tropical cloud systems in models, measurements of tropical clouds, the environment in which they reside, and their impact on the radiation and water budgets are needed. Because of the remote location, ground-based datasets of cloud, atmosphere, and radiation properties from the TWP region have come primarily from short-term field experiments. While providing extremely useful information on physical processes, these short-term datasets are limited in statistical and climatological information. To provide longterm measurements of the surface radiation budget in the tropics and the atmospheric properties that affect it, the Atmospheric Radiation Measurement program established a measurement site on Manus Island, Papua New Guinea, in 1996 and on the island republic of Nauru in late 1998. These sites provide unique datasets now available for more than 10 years on Manus and Nauru. This article presents examples of the scientific use of these datasets including characterization of cloud properties, analysis of cloud radiative forcing, model studies of tropical clouds and processes, and validation of satellite algorithms. New instrumentation recently installed at the Manus site will provide expanded opportunities for tropical atmospheric science.

tropical regions↗
NASA NTRS2017

An Evaluation of Teleconnections Over the United States in an Ensemble of AMIP Simulations with the MERRA-2 Configuration of the GEOS Atmospheric Model

The atmospheric general circulation model that is used in NASA's Modern Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) is evaluated with respect to the relationship between large-scale teleconnection patterns and daily temperature and precipitation over the United States (US) using a ten-member ensemble of simulations, referred to as M2AMIP. A focus is placed on four teleconnection patterns that are known to influence weather and climate in the US: El Nino Southern Oscillation, the Pacific Decadal Oscillation, the North Atlantic Oscillation, and the Pacific-North American Pattern. The monthly and seasonal indices associated with the patterns are correlated with daily temperature and precipitation statistics including: (i) monthly mean 2 m temperature and precipitation, (ii) the frequency of extreme temperature events at the 90th, 95th, and 99th percentiles, and (iii) the frequency and intensity of extreme precipitation events classified at the 90th, 95th, and 99th percentiles.Correlations obtained with M2AMIP data and thus the strength of teleconnections in the free-running model are evaluated through comparison against corresponding correlations computed from observations and from MERRA-2. Overall, the strongest teleconnections in all datasets occur during the winter and coincide with the largest agreement between the observations, MERRA-2, and M2AMIP. When M2AMIP does capture the correlation seen in observations, there is a tendency for the spatial extent to be exaggerated. The weakest agreement between the data sources, for all teleconnection patterns, is in the correlation with extreme precipitation; however there are discrepancies between the datasets in the number of days with at least 1 mm of precipitation: M2AMIP has too few days with precipitation in the Northwest and the Northern Great Plains and too many days in the Northeast. In JJA, M2AMIP has too few days with precipitation in the western two-thirds of the country and too many days with precipitation along the east coast.

JJA↗
NASA NTRS1994

Comparison of Kalman filter and optimal smoother estimates of spacecraft attitude

Given a valid system model and adequate observability, a Kalman filter will converge toward the true system state with error statistics given by the estimated error covariance matrix. The errors generally do not continue to decrease. Rather, a balance is reached between the gain of information from new measurements and the loss of information during propagation. The errors can be further reduced, however, by a second pass through the data with an optimal smoother. This algorithm obtains the optimally weighted average of forward and backward propagating Kalman filters. It roughly halves the error covariance by including future as well as past measurements in each estimate. This paper investigates whether such benefits actually accrue in the application of an optimal smoother to spacecraft attitude determination. Tests are performed both with actual spacecraft data from the Extreme Ultraviolet Explorer (EUVE) and with simulated data for which the true state vector and noise statistics are exactly known.

Sedlak, J.↗
DOE OSTI2025

Climatic controls on erosional efficiency vary with lithology across the Himalaya

Although climate can strongly influence erosional efficiency (i.e., erosion rate for a given topography), demonstrating its impact in tectonically active areas has been challenging due to other confounding controlling factors, such as lithology. Here, we show that 10 Be-derived erosion rates and efficiencies in the Himalayan orogen exhibit distinct relationships with climatic factors depending on lithology. We compile 173 10 Be-derived, basin-averaged erosion rates across the orogen, including 12 newly measured rates from the Dibang and Lohit valleys in the easternmost Himalaya, regions characterized by high precipitation magnitudes and variability. We group basins based on lithologies separated by orogen-scale thrust faults and quantify erosional efficiency coefficients based on the relationships between erosion rates and topographic metrics. Our results show that erosion rates and erosional efficiency from sedimentary and metasedimentary rocks along the Himalayan range front display a positive, nonlinear correlation with climatic factors, such as the number of extreme rainfall events and mean annual precipitation rates. In contrast, erosion rates from crystalline lithologies in the hanging wall of the Main Central thrust show a strong correlation with fluvial topography, whereas erosional efficiency shows no statistically significant correlation with climatic factors. Rapid erosion rates and high erosional efficiencies in the eastern Himalayan range front are likely driven by extreme precipitation on tectonically active, steep slopes composed of mechanically weak metasedimentary rocks. Our findings highlight the importance of the interplay between controlling factors, which include tectonics, lithology, and climate, that drive surface erosion and influence the topographic evolution of orogenic systems.

Channel steepness↗
DOE OSTI2021

Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA

A comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework consists of three major phases: Phase 1—Preliminary raw data sets exploration, including time formatting and combining datasets of different lengths and different time intervals; Phase 2—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme values; and Phase 3—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado) were analyzed. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.The files that are in this data package include one excel file, converted to CSV format (Billy_Barr_raw_qaqc.csv) that contains the raw meteorological data, i.e., input data used for the QA/QC analysis. The second CSV file (Billy_Barr_1hr.csv) is the QA/QC and flagged meteorological data, i.e., output data from the QA/QC analysis. The last file (QAQC_Billy_Barr_2021-03-22.R) is a script written in R that implements the QA/QC and flagging process. The purpose of the CSV data files included in this package is to provide input and output files implemented in the R script.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

Abstract While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Osse Sky Survey Observations for Cycles Three Extreme Red Egret Blazars

The original purpose of this work was to probe EGRET sources of low significance, and to use statistical techniques to construct a log N - log S of sources at greater than 50 MeV. At this writing, the detection significance of EGRET sources is still an issue. Therefore, we shifted our focus to the known EGRET detections. These came in two groups: (a) the known blazars; and (b) the high-Galactic latitude EGRET sources not identified with optical (or radio) counterparts.

Schachter, Jonathan F.↗
DOE OSTI2022

How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections?

Abstract We present an intercomparison of a suite of high‐resolution downscaled climate projections based on a six‐member General Circulation Model (GCM) ensemble from Coupled Models Intercomparison Project (CMIP6). The CMIP6 GCMs have been downscaled using dynamical and statistical downscaling techniques based on two meteorological reference observations over the conterminous United States. We use the regional climate model, RegCM4, for dynamical downscaling, double bias correction constructed analogs method for statistical downscaling, and Daymet and Livneh datasets as the reference observations for statistical training and bias‐correction. We evaluate the performances of downscaled data in both historical and future periods under the SSP585 scenario. While dynamical downscaling improves the simulation of some performance evaluation indices, it adds an extra bias in others, highlighting the need for statistical correction before its use in impact assessments. Downscaled datasets after bias‐correction compare exceptionally well with observations. However, the choice of downscaling techniques and the underlying reference observations influence the hydroclimate characteristics of downscaled data. For instance, the statistical downscaling generally preserves the GCMs climate change signal but overestimates the frequency of hot extremes. Similarly, simulated future changes are sensitive to the choice of reference observations, particularly for precipitation extremes that exhibit a higher projected increase in the ensembles trained and/or corrected by Daymet than Livneh. Overall, these results demonstrate that multiple factors, including downscaling techniques and reference observations, can substantially influence the outcome of downscaled climate projections and stress the need for a comprehensive understanding of such method‐based uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Constraining the Multiscale Structure of Geophysical Fields in Machine Learning: The Case of Precipitation

The use of deep-learning algorithms for estimating the value of geophysical variables from remotely sensed information is rapidly expanding. The typical objective function minimized in such algorithms is the mean square error (MSE), which is known to lead to smooth estimates with compressed dynamical range as compared to the true distribution of the variable of interest. Here, we introduce and evaluate alternative objective functions, focusing on the retrieval of precipitation rates from satellite passive microwave radiometric measurements using a deep convolutional neural network. For this testbed application, the results show that explicitly imposing the preservation of the statistical distribution and spatial wavelet power spectrum of the target variable allows to accurately reproduce extreme values and sharp gradients across multiple scales in this study.

58 GEOSCIENCES↗
DOE OSTI2023

Ocean & Geohazard Analysis Tool

The Ocean & Geohazard Analysis (OGA) software tool is designed to summarize insights into key offshore hazards drawing from a diverse set of approaches, including artificial intelligence, machine learning, probabilistic and statistical, and offshore data sources. The offshore hazards that can be analyzed include submarine landslides, extreme wind/wave/current event probabilities, earthquakes, and metocean pathways (CIAM Climatological Isolation and Attraction Model–Climatological Lagrangian Coherent Structures - Submissions - EDX (doe.gov)). Currently, the tool is developed for use in the Gulf of Mexico. The data underlying the offshore hazard analyses can be found here: https://edx.netl.doe.gov/dataset/gulf-of-mexico-risk-analysis-database-gomrad This work was conducted under the Advanced Offshore Research Portfolio, FWP Number 1022409 at National Energy Technology Laboratory, U.S. Dept. of Energy. Disclaimer This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

AIML↗
NASA NTRS1992

An overview of mesoscale prediction

A development history is presented for techniques used in mesoscale weather prediction over the course of the last 40 years, in which they have undergone a major transition from low-tech to high-tech. Remote sensing satellites and weather radars are now extremely refined tools for mesoscale atmospheric studies. Attention is given to mesocyclones and tornadoes, the statistical prediction of tornadoes, and the status of mesoscale prediction for aviation and space vehicles.

Fujita, T. T.↗
NASA NTRS1994

Radio occultation studies of the Venus atmosphere with the Magellan spacecraft. 1: Experimental description and performance

While primarily designed for radar studies of the Venus surface, the high effective isotropic radiated power (EIRP) from the Magellan spacecraft makes it an ideal transmitter for use in radio occultation measurements of the refractivity and absorptivity of the Venus atmosphere. Such experiments have been conducted involving transmissions at 2.3 GHz and 8.4 GHz (13 cm and 3.6 cm, respectively), during spacecraft ingress. Since the stability of the spacecraft transmitter is critical for accurately determining the Doppler shift and amplitude attenuation created as the ray penetrates the atmosphere, the spacecraft transmitter was locked to a 2.1 GHz uplink from a 70-meter DSN station which also received the signals. Because of the high directivity of the spacecraft antenna, and the significant ray bending in the deep Venus atmosphere, a spacecraft tracking maneuver was designed to keep the spacecraft antenna pointed in the direction of the refracted ray path back to Earth. This tracking maneuver, plus the high EIRP of the Magellan transmitter has yielded 3.6 cm refractivity and absorptivity profiles down to the 35 km altitude and 13 cm profiles down to the altitude of critical refraction (approximately 33 km). The statistical uncertainties in the derived profiles are significantly lower than those previously obtained, resulting in extremely accurate profiles of H2SO4 (g) abundance as discussed in an accompanying paper.

Steffes, Paul G.↗
NASA NTRS1999

Trends in the Vertical Distribution of Ozone

Analyses of satellite, ground-based, and balloon measurements allow updated estimates of trends in the vertical profile of ozone since 1979. The results show overall consistency among several independent measurement systems, particularly for northern hemisphere midlatitudes where most balloon and ground-based measurements are made. Combined trend estimates over these latitudes for the period 1979-96 show statistically significant negative trends at ail attitudes between 10 and 45 km, with two local extremes: -7.4 +/- 2.0% per decade at 40 km and -7.3 +/- 4.6% per decade at 15 km attitude. There is a strong seasonal variation in trends over northern midlatitudes in the altitude range of 10 to 18 km, with the largest ozone loss during winter and spring. The profile trends are in quantitative agreement with independently measured trends in column ozone, the amount of ozone in a column above the surface. The vertical profiles of ozone trends provide a fingerprint for the mechanisms of ozone depletion over the last two decades.

Randel, William J.↗
NASA NTRS1999

Trends in the Vertical Distribution of Ozone

Analyses of satellite, ground-based, and balloon measurements allow updated estimates of trends in the vertical profile of ozone since 1979. The results show overall consistency among several independent measurement systems, particularly for northern hemisphere midlatitudes where most balloon and ground-based measurements are made. Combined trend estimates over these latitudes for the period 1979-96 show statistically significant negative trends at all altitudes between 10 and 45 km, with two local extremes: -7.4 plus or minus 2.0% per decade at 40 km and -7.3 plus or minus -4.6% per decade at 15 km altitude. There is a strong seasonal variation in trends over northern midlatitudes in the attitude range of 10 to 18 km, with the largest ozone loss during winter and spring. The profile trends are in quantitative agreement with independently measured trends in column ozone, the amount of ozone in a column above the surface. The vertical profiles of ozone trends provide a fingerprint for the mechanisms of ozone depletion over the last two decades.

Randel, William J.↗
NASA NTRS2002

Trends in the Vertical Distribution of Ozone

Analyses of satellite, ground-based, and balloon measurements allow updated estimates of trends in the vertical profile of ozone since 1979. The results show overall consistency among several independent measurement systems, particularly for northern hemisphere midlatitudes where most balloon and ground-based measurements are made. Combined trend estimates over these latitudes for the period 1979-96 show statistically significant negative trends at all attitudes between 10 and 45 km, with two local extremes: -7.4 +/- 2.0% per decade at 40 km and -7.3 +/- 4.6% per decade at 15 km attitude. There is a strong seasonal variation in trends over northern midlatitudes in the attitude range of 10 to 18 km. with the largest ozone loss during winter and spring. The profile trends are in quantitative agreement with independently measured trends in column ozone, the amount of ozone in a column above the surface. The vertical profiles of ozone trends provide a fingerprint for the mechanisms of ozone depletion over the last two decades,

Cunnold, Derek M.↗
NASA NTRS2008

Correlations of Prompt and Afterglow Emission in Swift Long and Short Gamma Ray Bursts

Correlation studies of prompt and afterglow emissions from gamma-ray bursts (GRBs) between different spectral bands has been difficult to do in the past because few bursts had comprehensive and intercomparable afterglow measurements. In this paper we present a large and uniform data set for correlation analysis based on bursts detected by the Swift mission. For the first time, short and long bursts can be analyzed and compared. It is found for both classes that the optical, X-ray and gamma-ray emissions are linearly correlated, but with a large spread about the correlation line; stronger bursts tend to have brighter afterglows, and bursts with brighter X-ray afterglow tend to have brighter optical afterglow. Short bursts are, on average, weaker in both prompt and afterglow emissions. No short bursts are seen with extremely low optical to X-ray ratio as occurs for 'dark' long bursts. Although statistics are still poor for short bursts, there is no evidence yet for a subgroup of short bursts with high extinction as there is for long bursts. Long bursts are detected in the dark category at the same fraction as for pre-Swift bursts. Interesting cases are discovered of long bursts that are detected in the optical, and yet have low enough optical to X-ray ratio to be classified as dark. For the prompt emission, short and long bursts have different average tracks on flux vs fluence plots. In Swift, GRB detections tend to be fluence limited for short bursts and flux limited for long events.

Gehrel, Neil↗
NASA NTRS2017

Seasonal Impact of Regional Outdoor Biomass Burning on Air Pollution in Three Indian Cities: Delhi, Bengaluru, and Pune

Air pollution in many of India's cities exceeds national and international standards, and effective pollution control strategies require knowledge of the sources that contribute to air pollution and their spatiotemporal variability. In this study, we examine the influence of a single pollution source, outdoor biomass burning, on particulate matter (PM) concentrations, surface visibility, and aerosol optical depth (AOD) from 2007 to 2013 in three of the most populous Indian cities. We define the upwind regions, or "airsheds," for the cities by using atmospheric back trajectories from the HYSPLIT model. Using satellite fire radiative power (FRP) observations as a measure of fire activity, we target pre-monsoon and post-monsoon fires upwind of the Delhi National Capital Region and pre-monsoon fires surrounding Bengaluru and Pune. We find varying contributions of outdoor fires to different air quality metrics. For the post-monsoon burning season, we find that a subset of local meteorological variables (air temperature, humidity, sea level pressure, wind speed and direction) and FRP as the only pollution source explained 39% of variance in Delhi station PM(sub 10) anomalies, 77% in visibility, and 30% in satellite AOD; additionally, per unit increase in FRP within the daily airshed (1000 MW), PM(sub 10) increases by 16.34 micrograms per cubic meter, visibility decreases by 0.097 km, and satellite AOD increases by 0.07. In contrast, for the pre-monsoon burning season, we find less significant contributions from FRP to air quality in all three cities. Further, we attribute 99% of FRP from post-monsoon outdoor fires within Delhi's average airshed to agricultural burning. Our work suggests that although outdoor fires are not the dominant air pollution source in India throughout the year, post-monsoon fires contribute substantially to regional air pollution and high levels of population exposure around Delhi. During 3-day blocks of extreme PM(sub 2.5) in the 2013 post-monsoon burning season, which coincided with statistically significant high fire activity, concentrations in Delhi averaged 304 micrograms per cubic meter, or more than 1000% above the 24-h PM(sub 2.5) guideline (25 micrograms per cubic meter) of the World Health Organization. These results suggest that providing viable alternatives to agricultural residue burning could help improve post-monsoon air quality for a growing population of 63 million (39% in urban areas) within Delhi's airshed.

Air quality; Outdoor fires; Crop residue burning; ↗