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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Real-Time Radiological Source Term Estimation for Multiple Sources in Cluttered Environments

A particle filter algorithm is presented to estimate the position, strength, and cardinality of an unknown number of radioactive point sources in an obstacle-rich environment using count measurements. The algorithm addresses gaps in the prior literature by incorporating two novel elements. The first is a precomputation step in which local terrain and obstacle data is processed to compute attenuation kernels throughout the search area. This enables rapid estimation performance in obstacle-rich environments as measurements are gathered. The second novel feature is a dynamic particle allocation technique in which the number of particles is adjusted in real time to meet convergence goals. This feature allows the algorithm to scale more efficiently to scenarios with a larger number of sources. Furthermore, a series of computational experiments using simulated data demonstrates the algorithm’s performance in a cluttered environment with up to eight sources.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Self-Supervised Cloud Classification

Abstract Low-level marine clouds play a pivotal role in Earth’s weather and climate through their interactions with radiation, heat and moisture transport, and the hydrological cycle. These interactions depend on a range of dynamical and microphysical processes that result in a broad diversity of cloud types and spatial structures, and a comprehensive understanding of cloud morphology is critical for continued improvement of our atmospheric modeling and prediction capabilities moving forward. Deep learning has recently accelerated our ability to study clouds using satellite remote sensing, and machine learning classifiers have enabled detailed studies of cloud morphology. A major limitation of deep learning approaches to this problem, however, is the large number of hand-labeled samples that are required for training. This work applies a recently developed self-supervised learning scheme to train a deep convolutional neural network (CNN) to map marine cloud imagery to vector embeddings that capture information about mesoscale cloud morphology and can be used for satellite image classification. The model is evaluated against existing cloud classification datasets and several use cases are demonstrated, including training cloud classifiers with very few labeled samples, interrogation of the CNN’s learned internal feature representations, cross-instrument application, and resilience against sensor calibration drift and changing scene brightness. The self-supervised approach learns meaningful internal representations of cloud structures and achieves comparable classification accuracy to supervised deep learning methods without the expense of creating large hand-annotated training datasets. Significance Statement Marine clouds heavily influence Earth’s weather and climate, and improved understanding of marine clouds is required to improve our atmospheric modeling capabilities and physical understanding of the atmosphere. Recently, deep learning has emerged as a powerful research tool that can be used to identify and study specific marine cloud types in the vast number of images collected by Earth-observing satellites. While powerful, these approaches require hand-labeling of training data, which is prohibitively time intensive. This study evaluates a recently developed self-supervised deep learning method that does not require human-labeled training data for processing images of clouds. We show that the trained algorithm performs competitively with algorithms trained on hand-labeled data for image classification tasks. We also discuss potential downstream uses and demonstrate some exciting features of the approach including application to multiple satellite instruments, resilience against changing image brightness, and its learned internal representations of cloud types. The self-supervised technique removes one of the major hurdles for applying deep learning to very large atmospheric datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Intermodel Spread in the Pattern Effect and Its Contribution to Climate Sensitivity in CMIP5 and CMIP6 Models

Radiative feedbacks depend on the spatial patterns of sea surface temperature (SST) and thus can change over time as SST patterns evolve—the so-called pattern effect. In this study, we investigate intermodel differences in the magnitude of the pattern effect and how these differences contribute to the spread in effective equilibrium climate sensitivity (ECS) within CMIP5 and CMIP6 models. Effective ECS in CMIP5 estimated from 150-yr-long abrupt4×CO2 simulations is on average 10% higher than that estimated from the early portion (first 50 years) of those simulations, which serves as an analog for historical warming; this difference is reduced to 7% on average in CMIP6. The (negative) net radiative feedback weakens over the course of the abrupt4×CO2 simulations in the vast majority of CMIP5 and CMIP6 models, but this weakening is less dramatic on average in CMIP6. For both ensembles, the total variance in the effective ECS is found to be dominated by the spread in radiative response on fast time scales, rather than the spread in feedback changes. Using Green’s functions derived from two AGCMs shows that the spread in feedbacks on fast time scales may be primarily due to differences in atmospheric model physics, whereas the spread in feedback evolution is primarily governed by differences in SST patterns. Intermodel spread in feedback evolution is well explained by differences in the relative warming in the West Pacific warm-pool regions for the CMIP5 models, but this relation fails to explain differences across the CMIP6 models, suggesting that a stronger sensitivity of extratropical clouds to surface warming may also contribute to feedback changes in CMIP6.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluation of Mesoscale Convective Systems in Climate Simulations: Methodological Development and Results from MPAS-CAM over the U.S.

In this study, a process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the U.S. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation feature at 12, 25 and 50 km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 km and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency and intensity are found to be consistently underestimated in the Central U.S., particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while MCS precipitation area is too large and intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Arctic Aerosol Sources and Mixing States Field Campaign Report

The Arctic is warming at a faster rate than anywhere else on Earth, with rapidly shrinking sea ice extent transforming the region. Depending on chemical and physical properties, atmospheric aerosols directly scatter and/or absorb radiation, serve as cloud droplet and/or ice crystal nuclei, and/or reduce the reflectiveness of the snow surface, thereby altering the atmospheric energy budget. There is a wide spread in the magnitude of simulated arctic aerosol radiative forcing, and significant differences in aerosol concentration levels and seasonal cycles often exist between models and observations. Increasing local natural and anthropogenic emissions are significant, with uncertain climate impacts due to complex feedbacks. Model evaluations, however, are limited by the dearth of arctic aerosol observations available and an inadequate understanding of arctic aerosol processes. The majority of previous arctic aerosol observations have been made through intensive spring/summer field campaigns, with few intensive measurement studies focused on the fall-winter transition, a period when freeze-up is occurring later and thinning sea ice is resulting in wintertime ice fracturing. Aerosol monitoring at arctic coastal stations has provided knowledge of long-term seasonal trends in aerosol concentrations. The completed ARM field campaign addresses observational and knowledge gaps through detailed aerosol size and chemical composition measurements during the fall-winter transition in the coastal Arctic and through the entire annual cycle in the central Arctic. The observations are improving our understanding of the sources and processes controlling the aerosol population in the rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Physics of the solar system

Solar system, solar physics, planetary atmospheres and structure, and origin of planets and moon - conference

Rasool, S. I.↗
NASA NTRS1977

Experiments on atmospheric processes

Spacelab technology is examined as applied to the observation of the earth's weather patterns, composition, thermodynamics, and kinematics. An atmospheric cloud physics laboratory and a geophysical fluid flow cell are individually outlined as planned payload experiment efforts.

Vaughan, W. W.↗
NASA NTRS1978

Modification of the continuous flow diffusion chamber for use in zero-gravity

The design philosophy and performance characteristics of the continuous flow diffusion chamber developed for use in ground-based simulation of some of the experiments planned for the atmospheric cloud physics laboratory during the first Spacelab flight are discussed. Topics covered include principle of operation, thermal control, temperature measurement, tem-powered heat exchangers, wettable metal surfaces, sample injection system, and control electronics.

Keyser, G.↗
NASA NTRS1978

Making clouds in Spacelab

Improvements in the accuracy of weather predictions and possibilities for changing the weather might depend on a better understanding of the microphysical processes which take place within clouds. A study of these processes on the surface of the earth is difficult in connection with gravitational disturbances. An Atmospheric Cloud Physics Laboratory (ACPL), which is currently being developed, is to be carried into space in the Spacelab in the early 1980's. This facility will provide scientists, for the first time, with the opportunity to study cloud physics without the disturbing gravitational effects. In the ACPL facility, a microscopic element can be suspended without support. The processes of freezing, thawing, collision, electric charging, and temperature changes can be observed and photographed as many times and for as long as necessary.

Duncan, C.↗
NASA NTRS1979

Warm/cold cloud processes

Technical assistance continued in support of the Atmospheric Cloud Physics Laboratory is discussed. A study of factors affecting warm cloud formation showed that the time of formation during an arbitrary expansion is independent of carrier gas composition for ideal gases and independent of aerosol concentration for low concentrations of very small aerosols. Equipment and procedures for gravimetric evaluation of a precision saturator were laboratory tested. A numerical feasibility study was conducted for the stable levitation of charged solution droplets by an electric field in a one-g static diffusion chamber. The concept, operating principles, applications, limits, and sensitivity of the levitation technique are discussed.

Bowdle, D. A.↗
NASA NTRS1981

Atmospheric noise temperature measurements

Radiometric microwave noise temperature measurements were used to estimate atmospheric transmission loss. The following lumped element model expression is used for the noise temperature contribution, T double prime = T sub p (1 - 1/L). This relationship is used to estimate the transmission loss L in terms of T double prime and the atmosphere effective physical temperature T sub p. This report evaluates T sub p in terms of assumed distributed loss and temperature models. Simplified expressions are presented for low loss applications. For these applications L was determined directly and accurately without integration or iteration.

Stelzried, C.↗
NASA NTRS1978

Preliminary design of the cryogenic cooled limb scanning interferometer radiometer (CLIR)

The preliminary design of the cryogenic cooling system for the Cryogenic Cooled Limb Scanning Interferometer Radiometer (CLIR) instrument to be flown on the Atmospheric Magnetospheric Physics Satellite (AMPS) was studied. The top level trade studies were extensive due to the instrument requirement for cooling at three temperature levels as opposed to the two levels initially described for the instrument. Approximately 12 different combinations of cryogens were investigated. The basic lifetime requirement for the instrument was 30 days. However, studies were also conducted for a follow-up mission requiring a 1 year lifetime. The top level trades led to the selection of a single stage supercritical helium baseline.

Sherman, A.↗
NASA NTRS1982

Rayleigh, Raman and particulate scattering

Analysis of the visible and near infrared spectra of planetary atmospheres and the multiple scattering of photons within the atmosphere are discussed. Photons detected within the spectral region are solar photons which were scattered by the gas and particles in the planetary atmosphere. An example is given for the incident and emitted fluxes for a hypothetical planet with an effective temperature of 100 K. The absorption spectrum of the planetary atmosphere is discussed in terms of the various scattering processes photons undergo within the atmosphere. Three different physical processes are considered. Rayleigh scattering and Raman scattering by the gas molecules, and scattering by any cloud or dust aerosol particles in the atmosphere. The physics of each of these processes is examined.

Cochran, W. D.↗
NASA NTRS1993

Subsonic Airplane For High-Altitude Research

Report discusses engineering issues considered in design of conceptual subsonic airplane intended to cruise at altitudes of 100,000 ft or higher. Airplane would carry scientific instruments for research in chemistry and physics of atmosphere, particularly, for studies of ozone hole, greenhouse gases, and climatic effects.

Chambers, Alan↗
NASA NTRS1995

Evaluation of HFC 245ca and HFC 236ea as foam blowing agents

Hydrochlorofluorocarbon (HCFC) 141b has been selected as the interim blowing agent for use in urethane insulations on NASA's Space Shuttle External Tank. Due to the expected limited commercial lifetime of this material, research efforts at the NASA Thermal Protection Systems Materials Research Laboratory at the Marshall Space Flight Center are now being devoted to the identification and development of alternatives with zero ozone depletion potential. Physical blowing agents identified to date have included hydrocarbons, fluorocarbons, hydrofluoroethers, and more predominantly, hydrofluorocarbons (HFCs). The majority of the HFC evaluations in industry have focused on the more readily available, low boiling candidates such as HFC 134a. Higher boiling HFC candidates that could be handled at ambient conditions and use current processing equipment would be more desirable. This paper will describe results from a research program of two such candidate HFC's performed as a cooperative effort between Martin Marietta Manned Space Systems, the U.S. Environmental Protection Agency, and Oak Ridge National Laboratories. The purpose of this effort was to perform a cursory evaluation of the developmental HFC's 245ca and 236ea as blowing agents in urethane based insulations. These two materials were selected from screening tests of 37 C2, C3, and C4 isomers based on physical properties, atmospheric lifetime, flammability, estimated toxicity, difficulty of synthesis, suitability for dual use as a refrigerant, and other factors. Solubility of the two materials in typical foam components was tested, pour foaming trials were performed, and preliminary data were gathered regarding foam insulation performance.

Sharpe, Jon↗
NASA NTRS1998

Global Change Research Related to the Earth's Energy and Hydrologic Cycle

The Institute for Global Change Research and Education (IGCRE) is a joint initiative of the Universities Space Research Association (USRA) and the University of Alabama in Huntsville (UAH) for coordinating and facilitating research and education relevant to global environmental change. Created in 1992 with primary support from the National Aeronautics and Space Administration (NASA), IGCRE fosters participation by university, private sector and government scientists who seek to develop long-term collaborative research in global change science, focusing on the role of water and energy in the Earth's atmosphere and physical climate system. IGCRE is also chartered to address educational needs of Earth system and global change science, including the preparation of future scientists and training of primary and secondary education teachers.

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