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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Space-Based Remote Sensing of Atmospheric Aerosols: The Multi-Angle Spectro-Polarimetric Frontier

The review of optical instrumentation, forward modeling, and inverse problem solution for the polarimetric aerosol remote sensing from space is presented. The special emphasis is given to the description of current airborne and satellite imaging polarimeters and also to modern satellite aerosol retrieval algorithms based on the measurements of the Stokes vector of reflected solar light as detected on a satellite. Various underlying surface reflectance models are discussed and evaluated.

polarimetry↗
NASA NTRS2003

A Study of the Non-Thermal X-Ray Emission of Shell-Type Supernova Remnants

We present an analysis of the X-ray spectrum of the Galactic shell-type SNR G347.3-0.5 (RX 51713.7-3946). This SNR is a member of a growing class of SNRs which are dynamically young, shell-type sources that emit non-thermal X-rays from specific regions on their outer shells. By performing a joint spectral analysis of data from observations made of G347.3-0.5 using the ROSAT PSPC, the ASCA GIS and the RXTE PCA, we have fit the spectra of particular regions of this SNR (including the bright northwestern and southwestern rims, the northeast rim and the interior diffuse emission) over the approximate energy range of 0.5 through 30 keV. We find that fits to the spectra of this SNR over this energy range using the SRCUT model were superior to a simple power law model or the SRESC model. We find that the inclusion of a thermal model with the SRCUT model helps to improve the fit to the observed X-ray spectrum: this represents the first detection of thermal X-ray emission from G347.3-0.5. Thermal emission appears to be more clearly associated with the diffuse emission in the interior of the SNR than with the bright X-ray emitting rims. A weak emission feature seen near 6.4 keV in the RXTE PCA spectrum most likely originates from diffuse X-ray emission from the surrounding Galactic Ridge rather than from G347.3-0.5 itself. We have analyzed our RXTE PCA data to search for pulsations from a recently discovered radio pulsar (PSR 51713-3949) which may be associated with G347.3-0.5, and we do not detect any X-ray pulsations at the measured radio period of 392 ms. Using the best-fit parameters obtained from the SRCUT model, we estimate the maximum energy of cosmic-ray electrons accelerated by the rims of G347.3-0.5 to be 19-25 TeV (assuming a magnetic field strength of B = 10muG), consistent with the results of Ellison et al. We present a broadband (radio to gamma ray) photon energy-flux spectrum for the northwestern rim of G347.3-0.5, where we have fit the spectrum using a more sophisticated synchrotron-inverse Compton model with a variable magnetic field strength. Our fit derived from this model yields a maximum energy of only 8.8 (+4.1) (-3.4) TeV for the accelerated cosmic-ray electrons and a much greater magnetic field strength of 150 (+250) (-80). Finally, we compare the gross properties of G347.3-0.5 with other SNRs known to possess X-ray spectra dominated by non-thermal emission.

Allen, Glenn E.↗
NASA NTRS2014

A Decade of Volcanic Observations from Aura and the A-Train

Aura observations have made many seminal contributions to volcanology. Prior to the Aura launch, satellite observations of volcanic degassing (e.g., from TOMS) were mostly restricted to large eruptions. However, the vast majority of volcanic gases are released during quiescent 'passive' degassing between eruptions. The improved sensitivity of Aura OMI permitted the first daily, space-borne measurements of passive volcanic SO2 degassing, providing improved constraints on the source locations and magnitude of global SO2 emissions for input to atmospheric chemistry and climate models. As a result of this unique sensitivity to volcanic activity, OMI data were also the first satellite SO2 measurements to be routinely used for volcano monitoring at several volcano observatories worldwide. Furthermore, the Aura OMI SO2 data also offer unprecedented sensitivity to volcanic clouds in the UTLS, elucidating the transport, fate and lifetime of volcanic SO2 and providing critical input to aviation hazard mitigation efforts. Another major advance has been the improved vertical resolution of volcanic clouds made possible by synergy between Aura and other A-Train instruments (e.g., AIRS, CALIPSO, CloudSat), advanced UV SO2 altitude retrievals, and inverse trajectory modeling of detailed SO2 cloud maps. This altitude information is crucial for climate models and aviation hazards. We will review some of the highlights of a decade of Aura observations of volcanic activity and look ahead to the future of volcanic observations from space.

Aura↗
NASA NTRS1982

High-resolution X-ray observations of M87 - Nucleus, jet and radio halo

X-ray observations of M87 made using the Einstein Observatory HRI show the presence of four components. A broad, diffuse component associated with hot gas in the galaxy follows an approximate inverse power law; the pressure of the gas could be sufficient to confine the inner and outer radio lobes. A diffuse, asymmetrical X-ray distribution to the east and southwest appears similar to the radio morphology and is consistent with an inverse Compton model. An X-ray source centered on the nucleus of the galaxy is extended by 2-3 arcsec and may be due to thermal bremsstrahlung; a possible compact source of less than 10 to the 41st ergs/sec is weak compared with other active galaxies, and its implications for the presence of a massive black hole are discussed. A structure correlated with the radio-optical jet is also seen; the X-ray flux is consistent with an extrapolation of the optical synchrotron spectrum. The four components suggest that all three canonical astrophysical X-ray emission mechanisms are present in M87: thermal bremsstrahlung, inverse Compton scattering, and synchrotron radiation.

Schreier, E. J.↗
NASA NTRS2013

Analyzing Carbon Dioxide and Methane Emissions in California Using Airborne Measurements and Model Simulations

Greenhouse gas (GHG) concentrations have increased over the past decades and are linked to global temperature increases and climate change. These changes in climate have been suggested to have varying effects, and uncertain consequences, on agriculture, water supply, weather, sea-level rise, the economy, and energy. To counteract the trend of increasing atmospheric concentrations of GHGs, the state of California has passed the California Global Warming Act of 2006 (AB-32). This requires that by the year 2020, GHG (e.g., carbon dioxide (CO2) and methane (CH4)) emissions will be reduced to 1990 levels. To quantify GHG fluxes, emission inventories are routinely compiled for the State of California (e.g., CH4 emissions from the California Greenhouse Gas Emissions Measurement (CALGEM) Project). The major sources of CO2 and CH4 in the state of California are: transportation, electricity production, oil and gas extraction, cement plants, agriculture, landfills/waste, livestock, and wetlands. However, uncertainties remain in these emission inventories because many factors contributing to these processes are poorly quantified. To alleviate these uncertainties, a synergistic approach of applying air-borne measurements and chemical transport modeling (CTM) efforts to provide a method of quantifying local and regional GHG emissions will be performed during this study. Additionally, in order to further understand the temporal and spatial distributions of GHG fluxes in California and the impact these species have on regional climate, CTM simulations of daily variations and seasonality of total column CO2 and CH4 will be analyzed. To assess the magnitude and spatial variation of GHG emissions and to identify local “hot spots”, airborne measurements of CH4 and CO2 were made by the Alpha Jet Atmospheric eXperiment (AJAX) over the San Francisco Bay Area (SFBA) and San Joaquin Valley (SJV) in January and February 2013 during the Discover-AQ-CA study. High mixing ratios of GHGs were observed in-flight with a high degree of spatial variability. To provide an additional method to quantify GHG emissions, and analyze AJAX measurement data, the GEOS-Chem CTM is used to simulate SFBA/SJV GHG measurements. A nested-grid version of GEOS-Chem will be applied and utilizes varying emission inventories and model parameterizations to simulate GHG fluxes/emissions. The model considers CO2 fluxes from fossil fuel use, biomass/biofuel burning, terrestrial and oceanic biosphere exchanges, shipping and aviation, and production from the oxidation of carbon monoxide, CH4, and non-methane volatile organic carbons. The major sources of CH4 simulated in GEOS-Chem are domesticated animals, rice fields, natural gas leakage, natural gas venting/flaring (oil production), coal mining, wetlands, and biomass burning. Preliminary results from the comparison between available observations (e.g., AJAX and CALGEM CH4 emission maps) and GEOS-Chem results will be presented, along with a discussion of CO2 and CH4 source apportionment and the use of the GEOS-Chem-adjoint to perform inverse GHG modeling.

Johnson, Matthew S.↗
NASA NTRS2011

Using High-Resolution Forward Model Simulations of Ideal Atmospheric Tracers to Assess the Spatial Information Content of Inverse CO2 Flux Estimates

Attribution of observed atmospheric carbon concentrations to emissions on the country, state or city level is often inferred using "inversion" techniques. Such computations are often performed using advanced mathematical techniques, such as synthesis inversion or four-dimensional variational analysis, that invoke tracing observed atmospheric concentrations backwards through a transport model to a source region. It is, to date, not well understood how well such techniques can represent fine spatial (and temporal) structure in the inverted flux fields. This question is addressed using forward-model computations with idealized tracers emitted at the surface in a large number of grid boxes over selected regions and examining how distinctly these emitted tracers can be detected downstream. Initial results show that tracers emitted in half-degree grid boxes over a large region of the Eastern USA cannot be distinguished from each other, even at short distances over the Atlantic Ocean, when they are emitted in grid boxes separated by less than five degrees of latitude - especially when only total-column observations are available. A large number of forward model simulations, with varying meteorological conditions, are used to assess how distinctly three types observations (total column, upper tropospheric column, and surface mixing ratio) can separate emissions from different sources. Inferences inverse modeling and source attribution will be drawn.

Pawson, Steven↗
NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗
NASA NTRS1994

Visible-infrared remote-sensing model and applications for ocean waters

Remote sensing has become important in the ocean sciences, especially for research involving large spatial scales. To estimate the in-water constituents through remote sensing, whether carried out by satellite or airplane, the signal emitted from beneath the sea surface, the so called water-leaving radiance (L(w)), is of prime importance. The magnitude of L(w) depends on two terms: one is the intensity of the solar input, and the other is the reflectance of the in-water constituents. The ratio of the water-leaving radiance to the downwelling irradiance (E(d)) above the sear surface (remote-sensing reflectance, R(sub rs)) is independent of the intensity of the irradiance input, and is largely a function of the optical properties of the in-water constituents. In this work, a model is developed to interpret r(sub rs) for ocean water in the visible-infrared range. In addition to terms for the radiance scattered from molecules and particles, the model includes terms that describe contributions from bottom reflectance, fluorescence of gelbstoff or colored dissolved organic matter (CDOM), and water Raman scattering. By using this model, the measured R(sub rs) of waters from the West Florida Shelf to the Mississippi River plume, which covered a (concentration of chlorophyll a) range of 0.07 - 50 mg/cu m, were well interpreted. The average percentage difference (a.p.d.) between the measured and modeled R(sub rs) is 3.4%, and, for the shallow waters, the model-required water depth is within 10% of the chart depth. Simple mathematical simulations for the phytoplankton pigment absorption coefficient (a(sub theta)) are suggested for using the R(sub rs) model. The inverse problem of R(sub rs), which is to analytically derive the in-water constituents from R(sub rs) data alone, can be solved using the a(sub theta) functions without prior knowledge of the in-water optical properties. More importantly, this method avoids problems associated with a need for knowledge of the shape and value of the chlorophyll-specific absorption coefficient. The simulation was tested for a wide range of water types, including waters from Monterey Bay, the West Florida Shelf, and the Mississippi River plume. Using the simulation, the R(sub rs)-derived in-water absorption coefficients were consistent with the values from in-water measurements (r(exp 2) greater than 0.94, slope approximately 1.0). In the remote-sensing applications, a new approach is suggested for the estimation of primary production based on remote sensing. Using this approach, the calculated primary production (PP) values based upon remotely sensed data were very close to the measured values for the euphotic zone (r(exp 2) = 0.95, slope 1.26, and 32% average difference), while traditional, pigment-based PP model provided values only one-third the size of the measured data. This indicates a potential to significantly improve the accuracy of the estimation of primary production based upon remote sensing.

Lee, Zhongping↗
NASA NTRS1981

Solar wind electron densities from Viking dual-frequency radio measurements

Simultaneous phase coherent, two-frequency measurements of the time delay between the earth station and the Viking spacecraft have been analyzed in terms of the electron density profiles from 4 solar radii to 200 solar radii. The measurements were made during a period of solar activity minimum (1976-1977) and show a strong solar latitude effect. The data were analyzed with both a model independent, direct numerical inversion technique and with model fitting, yielding essentially the same results. It is shown that the solar wind density can be represented by two power laws near the solar equator proportional to r exp -2.7 and r exp -2.04. However, the more rapidly falling term quickly disappears at moderate latitudes (approximately 20 deg) leaving only the inverse-square behavior.

Muhleman, D. O.↗
NASA NTRSDate not supplied

FORWARD AND INVERSE L-BAND RADIATIVE TRANSFER MODELING OVER THE DRY CHACO, USING SMOS OBSERVATIONS, LAND SURFACE MODELING AND IN SITU DATA

Passive microwave L-band remote sensing is well known for its sensitivity to surface soil moisture over land.The signal is also affected by other dynamic variables such as vegetation and soil salinity. In this research, L-band microwave observations of the Soil Moisture Ocean Salinity (SMOS) mission are used to explore soil surface salinity, moisture and vegetation, in the Argentinean Dry Chaco, an area with possible emerging dryland salinity. A Radiative Transfer Model (RTM) with inclusion of a correction to the soil’s dielectric constant for salinity was used in forward and inverse mode, using either in situ data or Catchment Land Surface Model (CLSM) simulations as RTM input. The forward analysis pointed out shortcomings in the modeled soil moisture and soil surface temperature estimates. The impact of salinity on forward simulations over the Dry Chaco was limited.The RTM inversion using 10 years of SMOS brightness temperature observations resulted in realistic estimates of vegetation and roughness, both with and withouto ptimizing a correction term for the dielectric constant in terms of salinity equivalents. However,the retrieval of the correction term to the dielectric constant was very uncertain and not representative of soil surface salinity, but rather of open water, texture uncertainty or soil moisture bias.

L-band↗
NASA NTRS1972

The X-ray spectrum of NGC 5128.

Evaluation of the X-ray spectrum of NGC 5128 (Cen A) obtained by sounding rocket and balloon observations in the range from 1 to 180 keV. NGC 5128 may be fitted by a power law with a photon index -2 less than or equal to n less than or equal to -1.45. Inverse Compton models are presented, and constraints on their parameters are discussed. In all such models, the electrons and magnetic field have not yet equilibrated. Alternatively, the X rays may originate in a compact central core source.

Lampton, M.↗
NASA NTRS1978

Remote sensing of the boundary layer over the oceans

The paper explores the possibility of remotely sensing the boundary layer structure over the oceans by means of the Nimbus 4 IR Interferometric Spectrometer (IRIS) measurements in the water vapor bands. It is found from theoretical considerations that the moderately strong spectral lines in the 9-micron water vapor window region contain useful information about the lowest layers in the atmosphere. The difference between the observed line strength and the theoretically predicted line strength provides information about the departure in the atmospheric temperature and water vapor profiles from standard conditions. The observations of METEOR oceanographic expedition over the North and South Atlantic, and the Indian Ocean expedition make it possible to model the inversion conditions. It is concluded that significant characteristics of the temperature and water vapor profiles in the boundary layer of the atmosphere can be remotely sensed using the water vapor spectral measurements over the oceans.

Prabhakara, C.↗
NASA NTRS1982

Contrast reduction by the atmosphere and retrieval of nonuniform surface reflectance

A radiative transfer model is developed which gives the upward radiance at nadir for any 1-D Lambertian surface reflectance. This model is used to depict the atmospheric effect on the transmittance of contrast for any 1-D surface reflectance. Here by contrast we mean a general variation of the radiation field across the image. With the aid of this model an inversion algorithm is developed for retrieval of true surface reflectance from high resolution satellite data (e.g., Landsat). This inversion technique can be a useful tool for extraction of surface reflectance from satellite data in the case of a surface reflectance variable in one dimension only (e.g., seashore or near borders of big fields). A sensitivity study of the inversion procedure on the knowledge of atmospheric parameters and sensor calibration was performed. It is shown that this inversion technique is stable even in the presence of errors in the sensor calibration and the atmospheric parameters. The method was applied to Landsat data in two wavelengths. The results show reasonable dependence of the derived surface reflectance on the distance from the seashore.

Mekler, Y.↗
NASA NTRS1984

Inversion of vegetation canopy reflectance models for estimating agronomic variables. II - Use of angle transforms and error analysis as illustrated by Suits' model

The technique for inverting a vegetation canopy reflectance model described earlier (Goel and Strebel, 1983) is investigated further. The novel concept of an 'angle transform' is introduced. This concept allows the formation of functions of reflectances at different view zenith and azimuth angles, which are either sensitive or insensitive to a certain agronomic parameter. A proper combination of these functions can allow determination of all the important agronomic and spectral parameters from measured canopy reflectance data. The technique is demonstrated using Suits' (1972) model for homogeneous canopies. It is shown that leaf area index, leaf reflectance and transmittance, and average leaf angle all can be determined from the canopy reflectance at a set of selected view zenith and azimuth angles. A sensitivity analysis of the calculated values to the errors in the data is also carried out. Guidelines are formulated for the number and types of observations required to obtain the values of a particular canopy variable to within a given degree of accuracy for a given level of error in the measurement of canopy reflectance.

Goel, N. S.↗
NASA NTRS1984

Cygnus X-1 revisited

The X- and gamma-ray observations of Cygnus X-1 and their theoretical interpretations are reviewed, with emphasis on new developments since the mid-1970s. The overall data base at present is most consistent with the inverse Compton model by hot thermal electrons of T(e) of about 10 billion K, for the hard X-ray luminosity (10-200 keV). However, the origin of the soft X-rays (not greater than 10 keV) in high states and gamma rays (greater than 200 keV) remain unsettled.

Liang, E. P.↗