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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Regional Characteristics of the Relationship Between Columnar AOD and Surface PM2.5: Application of Lidar Aerosol Extinction Profiles over Baltimore-Washington Corridor During DISCOVER-AQ

The first field campaign of DISCOVER-AQ (Deriving Information on Surface conditions from COlumn and VERtically resolved observations relevant to Air Quality) took place in July 2011 over Baltimore-Washington Corridor (BWC). A suite of airborne remote sensing and in-situ sensors was deployed along with ground networks for mapping vertical and horizontal distribution of aerosols. Previous researches were based on a single lidar station because of the lack of regional coverage. This study uses the unique airborne HSRL (High Spectral Resolution Lidar) data to baseline PM2.5 (particulate matter of aerodynamic diameter less than 2.5 μm) estimates and applies to regional air quality with satellite AOD (Aerosol Optical Depth) retrievals over BWC (∼6500 sq. km). The linear approximation takes into account aerosols aloft above AML (Aerosol Mixing Layer) by normalizing AOD with haze layer height (i.e., AOD/HLH). The estimated PM2.5 mass concentrations by HSRL AOD/HLH are shown within 2 RMSE (Root Mean Square Error ∼9.6 μg/cu. m) with correlation ∼0.88 with the observed over BWC. Similar statistics are shown when applying HLH data from a single location over the distance of 100 km. In other words, a single lidar is feasible to cover the range of 100 km with expected uncertainties. The employment of MPLNET-AERONET (MicroPulse Lidar NETwork - AErosol RObotic NETwork) measurements at NASA GSFC produces similar statistics of PM2.5 estimates as those derived by HSRL. The synergy of active and passive remote sensing aerosol measurements provides the foundation for satellite application of air quality on a daily basis. For the optimal range of 10 km, the MODIS-estimated PM2.5 values are found satisfactory at 27 (out of 36) sunphotometer locations with mean RMSE of 1.6-3.3 μg/cu. m relative to PM2.5 estimated by sunphotometers. The remaining 6 of 8 marginal sites are found in the coastal zone, for which associated large RMSE values ∼4.5-7.8 μg/cu. m are most likely due to overestimated AOD because of water-contaminated pixels.

DISCOVER-AQ↗
NASA NTRS1981

Application of maximum-entropy spectral estimation to deconvolution of XPS data

A comparison is made between maximum-entropy spectral estimation and traditional methods of deconvolution used in electron spectroscopy. The maximum-entropy method is found to have higher resolution-enhancement capabilities and, if the broadening function is known, can be used with no adjustable parameters with a high degree of reliability. The method and its use in practice are briefly described, and a criterion is given for choosing the optimal order for the prediction filter based on the prediction-error power sequence. The method is demonstrated on a test case and applied to X-ray photoelectron spectra.

Vasquez, R. P.↗
NASA NTRS1989

Estimations of ABL fluxes and other turbulence parameters from Doppler lidar data

Techniques for extraction boundary layer parameters from measurements of a short-pulse CO2 Doppler lidar are described. The measurements are those collected during the First International Satellites Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE). By continuously operating the lidar for about an hour, stable statistics of the radial velocities can be extracted. Assuming that the turbulence is horizontally homogeneous, the mean wind, its standard deviations, and the momentum fluxes were estimated. Spectral analysis of the radial velocities is also performed from which, by examining the amplitude of the power spectrum at the inertial range, the kinetic energy dissipation was deduced. Finally, using the statistical form of the Navier-Stokes equations, the surface heat flux is derived as the residual balance between the vertical gradient of the third moment of the vertical velocity and the kinetic energy dissipation. Combining many measurements would normally reduce the error provided that, it is unbiased and uncorrelated. The nature of some of the algorithms however, is such that, biased and correlated errors may be generated even though the raw measurements are not. Data processing procedures were developed that eliminate bias and minimize error correlation. Once bias and error correlations are accounted for, the large sample size is shown to reduce the errors substantially. The principal features of the derived turbulence statistics for two case studied are presented.

Gal-Chen, Tzvi↗
NASA NTRS2021

Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States

Light detection and ranging (LiDAR) has become a commonly-used tool for generating remotely-sensed forest inventories. However, LiDAR-derived forest inventories have remained uncommon at a regional scale due to varying parameters among LiDAR data acquisitions and the availability of sufficient calibration data. Here, we present a model using a 3-D convolutional neural network (CNN), a form of deep learning capable of scanning a LiDAR point cloud, combined with coincident satellite data (spectral, phenology, and disturbance history). We compared this approach to traditional modeling used for making forest predictions from LiDAR data (height metrics and random forest) and found that the CNN had consistently lower uncertainty. We then applied the CNN to public data over six New England states in the USA, generating maps of 14 forest attributes at a 10 m resolution over 85% of the region. Aboveground biomass estimates produced a root mean square error of 36 Mg ha−1 (44%) and were within the 97.5% confidence of independent county-level estimates for 33 of 38 or 86.8% of the counties examined. CNN predictions for stem density and percentage of conifer attributes were moderately successful, while predictions for detailed species groupings were less successful. The approach shows promise for improving the prediction of forest attributes from regional LiDAR data and for combining disparate LiDAR datasets into a common framework for large-scale estimation.

Elias Ayrey↗
NASA NTRS1973

Utilization of ERTS-1 data to monitor and classify eutrophication of inland lakes

The author has identified the following significant results. Significant findings are: (1) one-acre lakes and one-acre islands are detectable; (2)removal of atmospheric parameters derived from RPMI measurements show test lakes to have reflectances of 3.1 to 5.5% in band 4 and 0.3 to 2.3% in band 5; (3) failure to remove reflectance caused by atmosphere results in errors up to 500% in computing lake reflectance from ERTS-1 data; (4) in band 4, up to seven reflectance levels were observed in test lakes; (5) reflectance patterns have been displayed on a color-coded TV monitor and on computer-generated gray scales; (6) deep and shallow water can be separated by a trained photointerpreter and automatic machine processing, with estimates of water depth possible in some cases; (7) RPMI provides direct spectral signature measurements of lakes and lake features such as algal scums and floating plants; (8) a method is reported for obtaining lake color, as estimated by Forel-Ule standards, from ERTS-1 data; (9) a strong correlation between browner water color, diminishing water transparency; and (10) classifying lake eutrophication by observation of surface scums or macrophytes in shallow water seems straightforward.

Rogers, R. H.↗
NASA NTRS1979

A structural model of the adaptive human pilot

A compensatory tracking model of the human pilot is offered which attempts to provide a more realistic representation of the human's signal processing structure than that which is exhibited by pilot models currently in use. Two features of the model distinguish it from other representations of the human pilot. First, proprioceptive information from the control stick or manipulator constitutes one of the major feedback paths in the model, providing feedback of vehicle output rate due to control activity. Implicit in this feedback loop is a model of the vehicle dynamics which is valid in and beyond the region of crossover. Second, error-rate information is continuously derived and independently but intermittently controlled. An output injected remnant model is offered and qualitatively justified on the basis of providing a measure of the effect of inaccuracies such as time variations in the pilot's internal model of the controlled element dynamics. The data from experimental tracking tasks involving five different controlled element dynamics and one nonideal viewing condition were matched with model generated describing functions and remnant power spectral densities.

Hess, R. A.↗
NASA NTRS1981

Cylindrical Crystal Imaging Spectrometer (CCIS) for cosmic X-ray spectroscopy

A "stigmatic" focusing, Bragg crystal spectrometer was developed and used for high spectral resolution X-ray emission line diagnostics on hot laboratory plasmas. The concept be applied at the focal plane of an orbiting X-ray telescope where it offers several advantages over conventional spectrometers, i.e., mechanical simplicity, high resolving power and sensitivity, simultaneous measurement of an extended segment of spectrum, and good imaging properties. The instrument features a simple, unambiguous, non-scanning spectrum readout that is not adversely affected by either spacecraft pointing error or source extent. The performance of the instrument is estimated in the context of the Advanced X-Ray Astrophysical Facility mission.

Schnopper, H. W.↗
NASA NTRS2012

Water Vapor in Titan's Stratosphere from Cassini CIRS Far-Infrared Spectra

Here we report the measurement of water vapor in Titan's stratosphere using the Cassini Composite Infrared Spectrometer (CIRS). CIRS senses water emissions in the far infrared spectral region near 50 micron, which we have modeled using two independent radiative transfer codes. From the analysis of nadir spectra we have derived a mixing ratio of 0.14 +/- 0.05 ppb at an altitude of 97 km, which corresponds to an integrated (from 0 to 600 km) surface normalized column abundance of 3.7 +/- 1.3 1014 molecules/cm2. In the latitude range 80S to 30N we see no evidence for latitudinal variations in these abundances within the error bars. Using limb observations, we obtained mixing ratios of 0.13 +/- 0.04 ppb at an altitude of 115 km and 0.45 +/- 0.15 ppb at an altitude of 230 km, confirming that the water abundance has a positive vertical gradient as predicted by photochemical models. We have also fitted our data using scaling factors of 0.1-0.6 to these photochemical model profiles, indicating that the models over-predict the water abundance in Titan's lower stratosphere.

composition↗
NASA NTRS2018

Reflectance-Based Imaging Spectrometer Error Budget Field Practicum at the Railroad Valley Test Site, Nevada

Calibration and validation determine the quality and integrity of the data provided by sensors and have enormous downstream impacts on the accuracy and reliabilityof the products generated by these sensors. With the imminent launch of the next generation of space borne imaging spectroscopy sensors, the IEEE Geoscience and Remote Sensing Society's (GRSS's) Geoscience Spaceborne Imaging Spectroscopy Technical Committee (GSIS TC) initiated a calibration and validation initiative.This article reports on a recent reflectance-based imaging spectrometer error budget field practicum focused on radiometric calibration of spaceborne imaging spectroscopy sensors. The field exercise, conducted at Railroad Valley in Nevada, provided valuable training for personnel in a variety of Earth observation (EO) areas, from engineers developing future sensors to calibration scientists actively working in the field. Future work in this area will focus on analyzing the data acquired as part of the training to answer numerous scientific questions, e.g., understanding the spatial and spectral homogeneity of the site being measured, identifying the optimal sampling to characterize the site, and optimizating the sampling techniques, including looking into the automation of some measurement protocol aspects. The training exercise was recorded to ensure that the knowledge can be disseminated across the GRSS and wider imaging spectroscopy community.

Ong, Cindy↗
NASA NTRS1972

Photometry of late type stars

Broad band filter photometry for 57 bright stars of spectral type A2 discussed with peak instrument responses at 3320, 2980, 2460 and 1910 A. The data include nearly all usable filter observations of G, K and M types. Sampling is nearly complete for A and F giants and supergiants, with the exception of Cepheid variables. The basic results presented are relative digital counting rates obtained with a field-stop aperture of 10 minutes of arc. Characteristics of the four filter-photometer combinations and errors are discussed. Some observations require substantial correction if they are to represent the visually brightest star in the field. These corrections and the effects of interstellar reddening are discussed. The adjusted counts are then used to construct color-color diagrams and are compared to the recent SAO grid of model atmospheres.

Doherty, L. R.↗
NASA NTRS1984

Validation of water vapor results measured by the Limb Infrared Monitor of the Stratosphere experiment on Nimbus 7

In the LIMS experiment using thermal IR limb scanning to sound the composition and structure of the upper atmosphere, one of the LIMS channels was spectrally centered at 6.9 micrometers to measure the vertical profile and global distribution of stratospheric water vapor. This channel's characteristics, the data from it, and the steps taken to validate results are described. The mean difference between the LIMS measurements and data from 13 balloon underflights is about 0.6 ppmv with LIMS mixing ratios biased high; this difference is of about the same order as estimated LIMS accuracy and less than the sum of the errors for LIMS and the balloon techniques. In-orbit precision is 0.2-0.3 ppmv and accuracy is estimated at 20-30 percent from 50 mbar to the stratopause. An unexplained diurnal variation exists in the vertical profile data which is largest at the 1-mbar level and virtually nonexistent at 10 mbar; day values are higher than night. More confidence is placed in zonal mean distributions averaged over several days than in single profiles. A zonal mean pressure-latitude cross section is described for January 5-9, 1979.

Russell, J. M., III↗
NASA NTRS1992

Evaluation of a technique for satellite-derived area estimation of forest fires

The advanced very high resolution radiometer (AVHRR), has been found useful for the location and monitoring of both smoke and fires because of the daily observations, the large geographical coverage of the imagery, the spectral characteristics of the instrument, and the spatial resolution of the instrument. This paper will discuss the application of AVHRR data to assess the geographical extent of burning. Methods have been developed to estimate the surface area of burning by analyzing the surface area effected by fire with AVHRR imagery. Characteristics of the AVHRR instrument, its orbit, field of view, and archived data sets are discussed relative to the unique surface area of each pixel. The errors associated with this surface area estimation technique are determined using AVHRR-derived area estimates of target regions with known sizes. This technique is used to evaluate the area burned during the Yellowstone fires of 1988.

Cahoon, Donald R., Jr.↗
NASA NTRS1997

Rainfall Estimation Over Tropical Oceans: Area Average Rain Rate - 1

Multichannel dual polarization microwave radiometer SSM/I observations over oceans do not contain sufficient information to differentiate quantitatively the rain from other hydrometeors on a scale comparable to the radiometer field of view (approx. 30 km). For this reason we have developed a method to retrieve average rain rate over a mesoscale grid box of approx. 300 x 300 sq km area over the TOGA COARE region where simultaneous radiometer and radar observations are available for four months (Nov. 92 to Feb. 93). The rain area in the grid box, inferred from the scattering depression due to hydrometeors in the 85 Ghz brightness temperature, constitutes a key parameter in this method. Then the spectral and polarization information contained in all the channels of the SSM/I is utilized to deduce a second parameter. This is the ratio S/E of scattering index S, and emission index E calculated from the SSM/I data. The rain rate retrieved from this method over the mesoscale area can reproduce the radar observed rain rate with a correlation coefficient of about 0.85. Furthermore monthly total rainfall estimated from this method over that area has an average error of about 15%.

Cuddapah, Prabhakara↗
NASA NTRS2021

Retrievals of Aerosol Optical Depth and Spectral Absorption from DSCOVR EPIC

A new algorithm is described for joint retrievals of the aerosol optical depth and spectral absorption from EPIC observations in the UV—Vis spectral range. The retrievals are illustrated on examples of the wildfire smoke events over North America, and dust storms over greater Sahara region in 2018. An initial evaluation of single scattering albedo (SSA) at 443 nm over these regions shows a good agreement with AERONET data, generally within the uncertainty of AERONET SSA of ± 0.03. A particularly good agreement is achieved for dust with R∼0.62, rmse∼0.02, negligible bias, and 85% points within the expected error. This new capability is part of version 2 MAIAC EPIC algorithm. The v2 algorithm has recently completed reprocessing of the EPIC record covering the period of 2015–2020.

EPIC↗
NASA NTRS1985

Near infrared leaf reflectance modeling

Near infrared leaf reflectance modeling using Fresnel's equation (Kumar and Silva, 1973) and Snell's Law successfully approximated the spectral curve for a 0.25-mm turgid oak leaf lying on a Halon background. Calculations were made for ten interfaces, air-wax, wax-cellulose, cellulose-water, cellulose-air, air-water, and their inverses. A water path of 0.5 mm yielded acceptable results, and it was found that assignment of more weight to those interfaces involving air versus water or cellulose, and less to those involving wax, decreased the standard deviation of the error for all wavelengths. Data suggest that the air-cell interface is not the only important contributor to the overall reflectance of a leaf. Results also argue against the assertion that the near infrared plateau is a function of cell structure within the leaf.

Parrish, J. B.↗
NASA NTRS2021

Observing System Simulation Experiments Investigating Atmospheric Motion Vectors and Radiances from a Constellation of 4–5-μm Infrared Sounders

A set of observing system simulation experiments (OSSEs) was performed to investigate the utility of a constellation of passive infrared spectrometers, strategically designed with the aim of deriving the three-dimensional retrievals of the horizontal wind via atmospheric motion vectors (AMVs) from instruments with the spectral resolution of an infrared sounder. The instrument and constellation designs were performed in the context of the Midwave Infrared Sounding of Temperature and humidity in a Constellation for Winds (MISTiC Winds). The Global Modeling and Assimilation Office OSSE system, which includes a full suite of operational meteorological observations, served as the control. To illustrate the potential impact of this observing strategy, two experiments were performed by adding the new simulated observations to the control. First, perfect (error free) simulated AMVs and radiances were assimilated. Second, the data were made imperfect by adding realistic modeled errors to the AMVs and radiances that were assimilated. The experimentation showed beneficial impacts on both the mass and wind fields, as based on analysis verification, forecast verification, and the assessment of the observations using the forecast sensitivity to observation impact (FSOI) metric. In all variables and metrics, the impacts of the imperfect observations were smaller than those of the perfect observations, although much of the positive benefit was retained. The FSOI metric illustrated two key points. First, the largest impacts were seen in the middle troposphere AMVs, which is a targeted capability of the constellation strategy. Second, the addition of modeled errors showed that the assimilation system was unable to fully exploit the 4.3-μm carbon dioxide absorption radiances.

Will McCarty↗
NASA NTRSDate not supplied

Mapping the seasonal variability of Titan’s upper atmospheric gases using ALMA

We present a study of the impact of seasonal effects on the spatial distribution of Titan’s atmospheric gases HNC, CH3CN, and HC3N over a timescale of less than a Titan month (9 Earth months). These molecules are synthesized primarily in the upper and middle atmosphere as a result of CH4 and N2 photochemistry, and are redistributed around Titan’s globe as a result of diffusion and zonal and meridional circulation. With observations from the Atacama Large Millimeter/submillimeter Array (ALMA) obtained in August 2016 [1] and May 2017 [2], we produced high-resolution, spectrally and spatially resolved maps of the emission from these gases. These observations are contemporaneous with the end of the Cassini mission (around the time of the northern summer solstice), allowing for studies of seasonal variations in Titan’s organic chemistry through analysis of the production, destruction, and transport of complex molecules. We observed a strong reduction of 41% ± 4% in the HC3N flux coming from the north pole, while CH3CN and HNC remained relatively stable (within errors) over the 9 month period of our observations. In the south pole, CH3CN presented a 31% ± 10% increase, while HNC saw a reduction of 20% ± 8%, and HC3N remained fairly stable (within errors). The HNC emission comes primarily from the highest (thermospheric) altitudes, and is distributed more uniformly about Titan’s limb than HC3N and CH3CN; the latter two molecules show strong polar enhancements due to meridional circulation. The steep decline in the HC3N north polar concentration is consistent its short photochemical lifetime (compared to HNC and CH3CN), combined with a reduction in meridional transport of gases produced at lower latitudes, towards the northern (summer) pole. The loss of emission of HC3N in the northern hemisphere is also consistent with the breakdown of Titan’s northern polar vortex during the onset of the northern summer, leading to a loss of confinement of these species [3].

Titan↗
NASA NTRSDate not supplied

Velocity and Temperature Measurements in High-speed Flows with Naturally Present Dust Particles Using Rayleigh and Mie Scattering

Dust particles and occasional moisture condensations are unavoidable reality of all wind tunnels. On the path to pursue a goal of velocity and temperature measurements in high-speed wind tunnels we have created a tabletop, spectrally resolved, Rayleigh-Mie scattering setup around a small jet fed by ambient and air with different particle concentration to determine the accuracy of the technique. The other reality of a wind tunnel setup is the spurious reflection and scattering of the incident laser beam by solid surfaces (flare light), which contaminates the Rayleigh-Mie scattered light. This is simulated by backgrounds with different reflectivity towards the collection optics. Light from a CW laser is delivered via an optical fiber and the scattered light from a point on the laser path is spectrally resolved using a stabilized Fabry-Perot interferometer, followed by imaging on an EMCCD camera. A model of the combined background glare, Mie scattering, and the Rayleigh spectrum was fitted to the camera image using maximum likelihood estimation. It was observed that the present modeling approach can extract velocity and temperature with reasonable accuracy when the intensity of the Mie scattered light is less than or comparable to that of the Rayleigh scattered light; beyond that error in velocity measurement remains reasonable ±12m/s but the temperature measurement becomes progressively more inaccurate. Increasingly the flare light is found to cause a bias error in velocity. Similar trend is observed in the presence of both the flare light and the Mie scattered light. The setup has provided a set of data for the future improvement of the modeling procedure, and demonstrated that even in the case of large amount of dust particles and large flare light the present technique can provide measurement of velocity with reasonable accuracy.

Rayleigh scattering↗