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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The global energy budget and satellite observations

During the last 30 years, space observations have provided new information about (a) the energy from our Sun, (b) the radiative exchange between our earth-atmosphere system and space, (c) required poleward energy transports by our atmosphere and oceans, (d) seasonal and interannual variations of (b) and (c), (e) the role of clouds in the global energy budget, and (f) preliminary information about the role of water vapor in the global energy budget. After a review of what we now know about these topics, the paper concludes with a discussion of major unknowns including the vertical variation of cloud forcing, the 'CO2 fingerprint,' the 'missing petawatt' of energy transport, and the role of non-cloud aerosols and surface features in the global budget.

Vonder Haar, Thomas H.↗
NASA NTRS2002

New Results from Space and Field Observations on the Aerosol Direct and Indirect Radiative Forcing

New space observations from the MODIS instrument on board the Terra satellite and analysis of POLDER data flown on the ADEOS satellite, show in great details the spatial and seasonal variability of the global aerosol system. These spaceborne instruments distinguish fine aerosol from man-made regional pollution and biomass burning from mostly natural coarse dust and sea salt aerosol. E.g. fine regional pollution in and around the Indian sub-continent, Europe and North America; smoke from biomass burning in Southern Africa and Southern America; coarse dust from West Africa and mixed dust pollution and smoke from West and central Africa and East Asia. These regions were also studied extensively in focused field experiments and by the distributed AERONET network. The results generate the first climatologies of the aerosol system, are used to derive the aerosol radiative effects and to estimate the anthropogenic component. The measurements are also used to evaluate each other and constrain aerosol transport models.

Kaufman, Yoram J.↗
NASA NTRS2022

Precision Measurement of a Brown Dwarf Mass in A Binary System in the Microlensing Event OGLE-2019-BLG-0033/MOA-2019-BLG-035

Context. Brown dwarfs are transition objects between stars and planets that are still poorly understood, for which several competing mechanisms have been proposed to describe their formation. Mass measurements are generally difficult to carry out for isolated objects as well as for brown dwarfs orbiting low-mass stars, which are often too faint for a spectroscopic follow-up. Aims. Microlensing provides an alternative tool for the discovery and investigation of such faint systems. Here, we present an analysis of the microlensing event OGLE-2019-BLG-0033/MOA-2019-BLG-035, which is caused by a binary system composed of a brown dwarf orbiting a red dwarf. Methods. Thanks to extensive ground observations and the availability of space observations from Spitzer, it has been possible to obtain accurate estimates of all microlensing parameters, including the parallax, source radius, and orbital motion of the binary lens. Results. Following an accurate modeling process, we found that the lens is composed of a red dwarf with a mass of M(1) = 0:149 ± 0.010 M⊙ and a brown dwarf with a mass of M(2) = 0:0463 ± 0:0031 M at a projected separation of a⊥ = 0:585 au. The system has a peculiar velocity that is typical of old metal-poor populations in the thick disk. A percent-level precision in the mass measurement of brown dwarfs has been achieved only in a few microlensing events up to now, but will likely become more common in the future thanks to the Roman space telescope.

gravitational lensing↗
NASA NTRS1987

Least squares linear lags and limited memory filters

Pure autoregressive (AR) models which are linear in the short term, that is when a variable can be predicted by linear regression on a limited number of past observations, are discussed. When evenly spaced observations are available, a fixed set of AR coefficients can be calculated independent of the data. For filtering purposes, such a lag structure can be implemented recursively with an efficient algorithm. The method of computing variance recursively is also derived. A complete algorithm is presented in the appendix.

Discenza, Joseph H.↗
NASA NTRS2000

The Spacelab Accomplishments Forum

This document is a record of the Spacelab Accomplishments Forum held in March 1999. Presentations made at the Forum covered the design, engineering, utilization, and science associated with Spacelab, as well as the international associations and impact of Spacelab and its use in the design and utilization of the International Space Station. Topics included Earth observations, space science, life science, commercial uses, microgravity science, and international participation.

Emond, J.↗
NASA NTRS2012

What Properties of CMEs are Most Important for Space Weather?

Severe space weather is characterized by intense particle radiation from the Sun and major geomagnetic storm caused by magnetized solar plasmas arriving at Earth. Coronal mass ejections (CMEs) are key players in both these aspects. CMEs traveling at super-Alfv nic speeds drive fast-mode MHD shocks that create the high levels of particle radiation. When a CME arrives at Earth, the CME-associated magnetic fields reconnect with Earth s magnetopause fields resulting in solar plasma entry into the magnetosphere and a geomagnetic storm depending on the magnetic structure of the CME. Particle radiation starts affecting geospace as soon as the CMEs leave the Sun and the geospace may be immersed in the radiation for several days. On the other hand, the geomagnetic storm happens only upon CME arrival at Earth. The requirements for the production of particles and magnetic storms by CMEs are different in a number of respects: solar source location, CME magnetic structure, conditions in the ambient solar wind, and shock-driving ability of CMEs. Intense shocks arriving at Earth have additional space weather effects such as sudden impulse that shrinks the magnetosphere often exposing satellites in geosynchronous orbit to the solar wind and energetic storm particle events. This paper highlights these space weather effects using CME observations space and ground based instruments during of solar cycles 23 and 24.

Gopalswamy, Nat↗
NASA NTRS1984

Space America's commercial space program

Space America prepared a private sector land observing space system which includes a sensor system with eight spectral channels configured for stereoscopic data acquisition of four stereo pairs, a spacecraft bus with active three-axis stabilization, a ground station for data acquisition, preprocessing and retransmission. The land observing system is a component of Space America's end-to-end system for Earth resources management, monitoring and exploration. In the context of the Federal Government's program of commercialization of the US land remote sensing program, Space America's space system is characteristic of US industry's use of advanced technology and of commercial, entrepreneurial management. Well before the issuance of the Request for Proposals for Transfer of the United States Land Remote Sensing Program to the Private Sector by the US Department of Commerce, Space Services, Inc., the managing venturer of Space America, used private funds to develop and manage its sub-orbital launch of its Conestoga launch vehicle.

Macleod, N. H.↗
NASA NTRS2015

Dealing with Uncertainties in Initial Orbit Determination

A method to deal with uncertainties in initial orbit determination (IOD) is presented. This is based on the use of Taylor differential algebra (DA) to nonlinearly map the observation uncertainties from the observation space to the state space. When a minimum set of observations is available DA is used to expand the solution of the IOD problem in Taylor series with respect to measurement errors. When more observations are available high order inversion tools are exploited to obtain full state pseudo-observations at a common epoch. The mean and covariance of these pseudo-observations are nonlinearly computed by evaluating the expectation of high order Taylor polynomials. Finally, a linear scheme is employed to update the current knowledge of the orbit. Angles-only observations are considered and simplified Keplerian dynamics adopted to ease the explanation. Three test cases of orbit determination of artificial satellites in different orbital regimes are presented to discuss the feature and performances of the proposed methodology.

Armellin, Roberto↗
NASA NTRS2019

Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia

Snow is an important component of the terrestrial freshwater budget in high mountainAsia (HMA) and contributes to the runoff in Himalayan rivers through snowmelt. Despitethe importance of snow in HMA, considerable spatiotemporal uncertainty exists across the different estimates of snow water equivalent for this region. In order to better estimate snow water equivalent, radiative transfer models are often used in conjunction with microwave brightness temperature measurements. In this study, the efficacy of support vector machines (SVMs), a machine learning technique, to predict passive microwave brightness temperature spectral difference (1Tb) as a function of geophysical variables (snow water equivalent, snow depth, snow temperature, and snow density) is explored through a sensitivity analysis. The use of machine learning (as opposed to radiative transfer models) is a relatively new and novel approach for improving snow water equivalent estimates. The Noah-MP land surface model within the NASALand Information System framework is used to simulate the hydrologic cycle over HMA and model geophysical variables that are then used for SVM training. The SVMsserve as a nonlinear map between the geophysical space (modeled in Noah-MP) andthe observation space (1Tb as measured by the radiometer). Advanced MicrowaveScanning Radiometer-Earth Observing System measured passive microwave brightness temperatures over snow-covered locations in the HMA region are used as training data during the SVM training phase. Sensitivity of well-trained SVMs to each Noah-MP modeled state variable is assessed by computing normalized sensitivity coefficients. Sensitivity analysis results generally conform with the known first-order physics. Input states that increase volume scattering of microwave radiation, such as snow density and snow water equivalent, exhibit a plurality of positive normalized sensitivity coefficients. In general, snow temperature was the most sensitive input to the SVM predictions. The sensitivity of each state is location and time dependent. The signs of normalized sensitivity coefficients that indicate physical irrationality are ascribed to significant cross-correlation between Noah-MP simulated states and decreased SVM prediction capability at specific locations due to insufficient training data. SVM prediction pitfalls do exist that serve to highlight the limitations of this particular machine learning algorithm.

high mountain Asia↗
NASA NTRS2012

Validation of Atmosphere/Ionosphere Signals Associated with Major Earthquakes by Multi-Instrument Space-Borne and Ground Observations

The latest catastrophic earthquake in Japan (March 2011) has renewed interest in the important question of the existence of pre-earthquake anomalous signals related to strong earthquakes. Recent studies have shown that there were precursory atmospheric/ionospheric signals observed in space associated with major earthquakes. The critical question, still widely debated in the scientific community, is whether such ionospheric/atmospheric signals systematically precede large earthquakes. To address this problem we have started to investigate anomalous ionospheric / atmospheric signals occurring prior to large earthquakes. We are studying the Earth's atmospheric electromagnetic environment by developing a multisensor model for monitoring the signals related to active tectonic faulting and earthquake processes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (thermal infrared radiation, electron concentration in the ionosphere, lineament analysis, radon/ion activities, air temperature and seismicity) that were found to be associated with earthquakes. A physical link between these parameters and earthquake processes has been provided by the recent version of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model. Our experimental measurements have supported the new theoretical estimates of LAIC hypothesis for an increase in the surface latent heat flux, integrated variability of outgoing long wave radiation (OLR) and anomalous variations of the total electron content (TEC) registered over the epicenters. Some of the major earthquakes are accompanied by an intensification of gas migration to the surface, thermodynamic and hydrodynamic processes of transformation of latent heat into thermal energy and with vertical transport of charged aerosols in the lower atmosphere. These processes lead to the generation of external electric currents in specific regions of the atmosphere and the modifications, by dc electric fields, in the ionosphere-atmosphere electric circuit. We retrospectively analyzed temporal and spatial variations of four different physical parameters (gas/radon counting rate, lineaments change, long-wave radiation transitions and ionospheric electron density/plasma variations) characterizing the state of the lithosphere/atmosphere coupling several days before the onset of the earthquakes. Validation processes consist in two phases: A. Case studies for seven recent major earthquakes: Japan (M9.0, 2011), China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and, Chile (M8.8, 2010) and B. A continuous retrospective analysis was preformed over two different regions with high seismicity- Taiwan and Japan for 2003-2009. Satellite, ground surface, and troposphere data were obtained from Terra/ASTER, Aqua/AIRS, POES and ionospheric variations from DEMETER and COSMIC-I data. Radon and GPS/TEC were obtaining from monitoring sites in Taiwan, Japan and Italy and from global ionosphere maps (GIM) respectively. Our analysis of ground and satellite data during the occurrence of 7 global earthquakes has shown the presence of anomalies in the atmosphere. Our results for Tohoku M9.0 earthquake show that on March 7th, 2011 (4 days before the main shock and 1 day before the M7.2 foreshock of March 8, 2011) a rapid increase of emitted infrared radiation was observed by the satellite data and an anomaly was developed near the epicenter. The GPS/TEC data indicate an increase and variation in electron density reaching a maximum value on March 8. From March 3 to 11 a large increase in electron concentration was recorded at all four Japanese ground-based ionosondes, which returned to normal after the main earthquake. Similar approach for analyzing atmospheric and ionospheric parameters has been applied for China (M7.9, 2008), Italy (M6.3, 2009), Samoa (M7, 2009), Haiti (M7.0, 2010) and Chile (M8.8, 2010) eahquakes. Results have revealed the presence of related variations of these parameters implying their connection with the earthquake process. The second phase (B) of this validation included 102 major earthquakes (M>5.9) in Taiwan and Japan. We have found anomalous behavior before all of these events with no false negatives. False alarm ratio for false positives is less then 10% and has been calculated for the same month of the earthquake occurrence for the entire period of analysis (2003-2009). The commonalities for detecting atmospheric/ionospheric anomalies are: i.) Regularly appearance over regions of maximum stress (i.e., along plate boundaries); ii.) Anomaly existence over land and sea; and iii) association with M>5.9 earthquakes not deeper than 100km. Due to their long duration over the same region these anomalies are not consistent with a meteorological origin. Our initial results from the ISTF validation of multi-instrument space-borne and ground observations show a systematic appearance of atmospheric anomalies near the epicentral area, one to seven (average) days prior to the largest earthquakes, and suggest that it could be explained by a coupling process between the observed physical parameters and the pre-earthquake preparation processes.

Ouzounov, Dimitar↗