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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 NTRS1999

Aerosol Backscatter from Airborne Continuous Wave CO2 Lidars Over Western North America and the Pacific Ocean

Atmospheric aerosol backscatter, beta, variability gives a direct indication of aerosol loading. Since aerosol variability is governed by regional sources and sinks as well as affected by its transport due to meteorological conditions, it is important to characterize this loading at different locations and times. Lidars are sensitive instruments that can effectively provide high-resolution, large-scale sampling of the atmosphere remotely by measuring aerosol beta, thereby capturing detailed temporal and spatial variability of aerosol loading, Although vertical beta profiles are usually obtained by pulsed lidars, airborne-focused CW lidars, with high sensitivity and short time integration, can provide higher resolution sampling in the vertical, thereby revealing detailed structure of aerosol layers. During the 1995 NASA Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission, NASA MSFC airborne-focused CW CO2 Doppler lidars, operating at 9.1 and 10.6-micrometers wavelength, obtained high resolution in situ aerosol beta measurements to characterize aerosol variability. The observed variability in beta at 9.1-micrometers wavelength with altitude is presented as well as comparison with some pulsed lidar profiles.

Jarzembski, Maurice A.↗
NASA NTRS1992

A snow wetness retrieval algorithm for SAR

The objectives of this study are: (1) to evaluate the backscattering signals response to snow wetness; and (2) to develop an algorithm for snow wetness measurement using C-band polarimetric synthetic aperture radar (SAR). In hydrological investigations, modeling and forecasting of snowmelt runoff requires information about snowpack properties and their spatial variability. In particular, timely measurement of snow parameters is needed for operational hydrology. The liquid water content of snowpack is one of the important parameters. Active microwave sensors are highly sensitive to liquid water in the snowpack because of the large dielectric contrast between ice and water in the microwave spectrum. They are not affected by weather and have a spatial resolution compatible with the topographic variation in alpine regions. However, a quantitative algorithm for retrieval snow wetness has not yet been developed.

Shi, Jian-Cheng↗
NASA NTRS1985

Determination of sea ice motion using digital SAR imagery

Precise, densely sampled maps of ice motion have been derived from digital Seasat SAR imagery, in order to determine the small scale spatial variability of ice formation. The SAR images were processed to remove geometric distortions, and then located to an accuracy of about 100 m by means of a spacecraft orbital data/SAR characteristics algorithm, independently of attitude and ground reference point data. Ice features common to an overlapping pair of images yielded vector plots of ice motion that indicate a high degree of spatial deformation, demonstrating the potential value of spaceborne SAR data.

Curlander, J. C.↗
NASA NTRS2004

Global Autocorrelation Scales of the Partial Pressure of Oceanic CO2

A global database of approximately 1.7 million observations of the partial pressure of carbon dioxide in surface ocean waters (pCO2) collected between 1970 and 2003 is used to estimate its spatial autocorrelation structure. The patterns of the lag distance where the autocorrelation exceeds 0.8 is similar to patterns in the spatial distribution of the first baroclinic Rossby radius of deformation indicating that ocean circulation processes play a significant role in determining the spatial variability of pCO2. For example, the global maximum of the distance at which autocorrelations exceed 0.8 averages about 140 km in the equatorial Pacific. Also, the lag distance at which the autocorrelation exceed 0.8 is greater in the vicinity of the Gulf Stream than it is near the Kuroshio, approximately 50 km near the Gulf Stream as opposed to 20 km near the Kuroshio. Separate calculations for times when the sun is north and south of the equator revealed no obvious seasonal dependence of the spatial autocorrelation scales. The pCO2 measurements at Ocean Weather Station (OWS) 'P', in the eastern subarctic Pacific (50 N, 145 W) is the only fixed location where an uninterrupted time series of sufficient length exists to calculate a meaningful temporal autocorrelation function for lags greater than a few days. The estimated temporal autocorrelation function at OWS 'P', is highly variable. A spectral analysis of the longest four pCO2 time series indicates a high level of variability occurring over periods from the atmospheric synoptic to the maximum length of the time series, in this case 42 days. It is likely that a relative peak in variability with a period of 3-6 days is related to atmospheric synoptic period variability and ocean mixing events due to wind stirring. However, the short length of available time series makes identifying temporal relationships between pCO2 and atmospheric or ocean processes problematic.

Li, Zhen↗
NASA NTRS2000

Seven-Year SSM/I-Derived Global Ocean Surface Turbulent Fluxes

A 7.5-year (July 1987-December 1994) dataset of daily surface specific humidity and turbulent fluxes (momentum, latent heat, and sensible heat) over global oceans has been retrieved from the Special Sensor Microwave/Imager (SSM/I) data and other data. It has a spatial resolution of 2.0 deg.x 2.5 deg. latitude-longitude. The retrieved surface specific humidity is generally accurate over global oceans as validated against the collocated radiosonde observations. The retrieved daily wind stresses and latent heat fluxes show useful accuracy as verified by those measured by the RV Moana Wave and IMET buoy in the western equatorial Pacific. The derived turbulent fluxes and input variables are also found to agree generally with the global distributions of annual-and seasonal-means of those based on 4-year (1990-93) comprehensive ocean-atmosphere data set (COADS) with adjustment in wind speeds and other climatological studies. The COADS has collected the most complete surface marine observations, mainly from merchant ships. However, ship measurements generally have poor accuracy, and variable spatial coverages. Significant differences between the retrieved and COADS-based are found in some areas of the tropical and southern extratropical oceans, reflecting the paucity of ship observations outside the northern extratropical oceans. Averaged over the global oceans, the retrieved wind stress is smaller but the latent heat flux is larger than those based on COADS. The former is suggested to be mainly due to overestimation of the adjusted ship-estimated wind speeds (depending on sea states), while the latter is suggested to be mainly due to overestimation of ship-measured dew point temperatures. The study suggests that the SSM/I-derived turbulent fluxes can be used for climate studies and coupled model validations.

Chou, Shu-Hsien↗
NASA NTRS2004

Three dimensional empirical mode decomposition analysis apparatus, method and article manufacture

An apparatus and method of analysis for three-dimensional (3D) physical phenomena. The physical phenomena may include any varying 3D phenomena such as time varying polar ice flows. A repesentation of the 3D phenomena is passed through a Hilbert transform to convert the data into complex form. A spatial variable is separated from the complex representation by producing a time based covariance matrix. The temporal parts of the principal components are produced by applying Singular Value Decomposition (SVD). Based on the rapidity with which the eigenvalues decay, the first 3-10 complex principal components (CPC) are selected for Empirical Mode Decomposition into intrinsic modes. The intrinsic modes produced are filtered in order to reconstruct the spatial part of the CPC. Finally, a filtered time series may be reconstructed from the first 3-10 filtered complex principal components.

Gloersen, Per↗
NASA NTRS2012

Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

Lyapustin, A.↗
NASA NTRS2019

Snow Depth Variability in the Northern Hemisphere Mountains Observed from Space

Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map the snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4,000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change.

Hans Lievens↗
NASA NTRS1993

A study of the influence of satellite data on GLA analyses over the Atlantic Ocean during a period of blocking anticyclone development

This paper presents a statistical diagnosis of the differences between two Goddard Laboratory for Atmospheres analysis representations of temperature and wind speed, one containing satellite data influences (SAT analyses) and one without (NOSAT analyses), for a case of oceanic blocking anticyclone development. Results, obtained using area means and standard deviations of the two fields and correlation coefficients and root-mean-square differences between the two fields, indicate that the inclusion of satellite data can have significant impact on ocean-domain analyses. This is especially evident if one examines higher-order fields that represent gradients in the basic variable fields or contain covariances between two different variables (e.g., advections). More specifically, the inclusion of satellite data resulted in a cold (warm) temperature bias at low (high) levels and weaker temperature gradients, stronger winds, weaker vertical wind shears, and a warm-air advection bias at most levels. The SAT analyses also exhibited larger standard deviations than the NOSAT for wind speed, relative vorticity, vorticity advection, temperature advection, and 500-mb height tendencies, suggesting that for this case the spatial variability of the circulation features were enhanced by the inclusion of satellite data. Even so, since height tendencies forced by vorticity and temperature advection were less sensitive to the addition of satellite data than were the advection quantities themselves, the dynamics of the blocking system was apparently less influenced by the presence of satellite data than was the structure of the system.

Lamberty, Gregory L.↗
NASA NTRS2009

Fully Automated Detection of Cloud and Aerosol Layers in the CALIPSO Lidar Measurements

Accurate knowledge of the vertical and horizontal extent of clouds and aerosols in the earth s atmosphere is critical in assessing the planet s radiation budget and for advancing human understanding of climate change issues. To retrieve this fundamental information from the elastic backscatter lidar data acquired during the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a selective, iterated boundary location (SIBYL) algorithm has been developed and deployed. SIBYL accomplishes its goals by integrating an adaptive context-sensitive profile scanner into an iterated multiresolution spatial averaging scheme. This paper provides an in-depth overview of the architecture and performance of the SIBYL algorithm. It begins with a brief review of the theory of target detection in noise-contaminated signals, and an enumeration of the practical constraints levied on the retrieval scheme by the design of the lidar hardware, the geometry of a space-based remote sensing platform, and the spatial variability of the measurement targets. Detailed descriptions are then provided for both the adaptive threshold algorithm used to detect features of interest within individual lidar profiles and the fully automated multiresolution averaging engine within which this profile scanner functions. The resulting fusion of profile scanner and averaging engine is specifically designed to optimize the trade-offs between the widely varying signal-to-noise ratio of the measurements and the disparate spatial resolutions of the detection targets. Throughout the paper, specific algorithm performance details are illustrated using examples drawn from the existing CALIPSO dataset. Overall performance is established by comparisons to existing layer height distributions obtained by other airborne and space-based lidars.

Vaughan, Mark A.↗
NASA NTRS2012

AgMIP Regional Activities in a Global Framework: The Brazil Experience

Climate variability and change are projected to increate the frequency of extreme high-temperature events, floods, and droughts, which can lead to subsequent changes in soil moister in many locations (Alexandrov and Hoogenboom, 2000). In Brazil, observations reveal a tendency for increasing frequency of extreme rainfall events particularly in south Brazil (Alexander et al., 2006; Carvalho et al., 2014; Groissman et al., 2005), as well as projections for increasing extremes in both maximum and minimum temperatures and high spatial variability for rainfall under the IPCC SRES A2 and B2 scenarios (Marengo et al., 2009).

climate change↗
NASA NTRS1991

Digital array scanned interferometers for astronomy

Investigations are reported of digital array scanned interferometers (DASI) with silicon CCD array detectors to define the operational capabilities of a mapping (polarimetric) spectrometer for astronomical applications based on these instruments. For spectral mapping, spatially resolved spectra using a cylindrical lens to image in the interferometers's redundant coordinate are given. The signal-to-noise characteristics of the Fourier transformed data are demonstrated with regard to the effects of a rectangular sampling function, spectral multiplexing and the pixel-to-pixel variation of the CCD array. These data indicate that DASIs can offer simple, versatile (polarization) mapping spectrometers suitable for spectral mapping observations from the ultraviolet to the infrared of extended sources at variable spatial resolution, particularly where long term stable operation is essential, as for spacecraft instruments.

Smith, Wm. Hayden↗
NASA NTRS1978

Magnetic field measurements from the solar probe

An optical system for the solar probe is described as well as its capability for improvements in spatial resolution. A magnetograph for measuring the elementary flux tube and obtaining vector geometry field geometry offers the possibility of looking for low contrast weak structure. With the probe's orbit passing over the pole, the structure of the polar field can be directly measured. The detector plane of the system receives a telecentric image of the objective. Because there is an aperture in this focal plane that can both move and change size, polarized line profiles can be obtained at arbitrary points with variable spatial resolution. The telescope microprocessor searches for the magnetic elements and then constructs the vector field.

Title, A. M.↗
NASA NTRS2015

An Assessment of Southern Ocean Water Masses and Sea Ice During 1988-2007 in a Suite of Interannual CORE-II Simulations

We characterise the representation of the Southern Ocean water mass structure and sea ice within a suite of 15 global ocean-ice models run with the Coordinated Ocean-ice Reference Experiment Phase II (CORE-II) protocol. The main focus is the representation of the present (1988-2007) mode and intermediate waters, thus framing an analysis of winter and summer mixed layer depths; temperature, salinity, and potential vorticity structure; and temporal variability of sea ice distributions. We also consider the interannual variability over the same 20 year period. Comparisons are made between models as well as to observation-based analyses where available. The CORE-II models exhibit several biases relative to Southern Ocean observations, including an underestimation of the model mean mixed layer depths of mode and intermediate water masses in March (associated with greater ocean surface heat gain), and an overestimation in September (associated with greater high latitude ocean heat loss and a more northward winter sea-ice extent). In addition, the models have cold and fresh/warm and salty water column biases centred near 50 deg S. Over the 1988-2007 period, the CORE-II models consistently simulate spatially variable trends in sea-ice concentration, surface freshwater fluxes, mixed layer depths, and 200-700 m ocean heat content. In particular, sea-ice coverage around most of the Antarctic continental shelf is reduced, leading to a cooling and freshening of the near surface waters. The shoaling of the mixed layer is associated with increased surface buoyancy gain, except in the Pacific where sea ice is also influential. The models are in disagreement, despite the common CORE-II atmospheric state, in their spatial pattern of the 20-year trends in the mixed layer depth and sea-ice.

Sea ice↗
NASA NTRS2003

Spatio-Temporal Distribution of Particulate and Dissolved Organic Matter in the Mississippi River Bight From Optical Measurements

The Mississippi River Bight is a highly dynamic region influenced by the seasonally variable outflow from the Mississippi River. In an effort to characterize the distribution of particulate and dissolved organic matter in the region, we conducted a two-year field program in the spring and fall (high and low flow river discharge) of 2000 and 2002. We collected a comprehensive set of bio-optical measurements consisting of vertical profiles (absorption, scattering, chlorophyll fluorescence and radiometry) and discrete measurements (pigment concentrations, particulate and CDOM absorption) that enabled us to obtain better insight into the seasonal and spatial variability of some important biogeochemical parameters. Our field measurements generally showed higher phytoplankton clorophyll concentrations in the plume waters (associated with lower surface salinities) and confirmed the high biological activity abserved in other studies. The seasonal flow of river discharge and advective currents due to wind forcing exerted a strong influence on the biological and optical properties of the region. An examination of absorption at 440 nm by the algal and non-algal fraction of the particulate pool and of CDOM revealed that at nearshore stations, contributions by the non-algal particles were high (about 40%) and decresed with increasing salinities. While CDOM absorption exhibited conservative mixing, its relative contribution to the total absorption was variable. Surface waters at most stations had lower salinities that generalliy increased with dept. Particulate matter and CDOM also decreased with depth as evidenced by absorption and scattering measurements. Good correlations in surface waters between concentrations of particulate and dissolved matter, the inherent optical properties of absorption and ackscattering and remote sensing reflectance values has allowed the development of robust empirical algorithms for phytoplankton chlorophyll and CDOM absorption.

DSa, E. J.↗
NASA NTRSDate not supplied

Influence of Heat Flow from the Planetary Interior on Surface Habitability

an primordial and/or radiogenic heat flow from a rocky planet’s interior help maintain a surface environment amenable to life?On rocky Earth-like planets with shallow oceans (≤5 km depth) that are on the outer edge of the habitable zone, the additional energy provided might make the difference between a world supporting regional habitat space and a world uninhabitable by any known life-form. To test this hypothesis, we introduce heat flux from the planetary interior as a forcing to the NASA/GISSROCKE-3D exoplanet GCM, and explore whether it can enhance the habitability of marginal terrestrial rocky planets (e.g.,paleo Earth in a “snowball” climate state).GCM simulations of modern Earth have not included geothermal heat flux as a climate forcing, as it is more than an order of magnitude less than the 2.9 W/m heating caused by anthropogenic greenhouse gases [Flanner, GRL 2009]. Modern Earth measurements in the oceans [Downes et al., GRL 2019] and results from ocean GCMs [Barnes et al., Ocean Model. 2017]suggest that localized higher heat flux can have measurable thermodynamic and dynamic impacts, such as weakening deep ocean stratification and increased poleward ocean heat transports. A similar result with ROCKE-3D would be important, since our snowball Earth simulations without heat flux produce features like ocean stratification that should have hampered the survival of life. We have created a set of spatially variable geothermal heat fluxes at varying horizontal resolutions based on modern Earth heat flow patterns [Davies, Geochem. Geophys. Geosys. 2013] to test the sensitivity of the ROCKE-3D GCM initially in a modern Earth context. Preliminary results show that even modest heat fluxes have a measurable impact on deep ocean temperatures (upto +0.9°C locally) and that this heat can be transported at depth along ocean circulation paths. Estimates of heat flux impacts on vertical ocean mixing and surface ocean conditions require long simulations at the higher spatial resolutions needed to express heat flow at the scale of most ocean ridges. Ongoing simulations are focused on testing the impacts of horizontal resolution and flux scaling on surface environments, especially for “snowball” climate scenarios.

Heat flow↗
NASA NTRS1990

A cloud classification scheme applied to the breakup region of marine stratocumulus

A major goal of the marine stratocumulus (MSc) segment of FIRE is to describe and explain the temporal and spatial variability in fractional cloud cover. The challenge from a theoretical standpoint is to correctly represent the mechanisms leading to the transitions between solid stratus, stratocumulus and trade wind cumulus. The development and testing of models accounting for fractional cloudiness require an observational data base that will come primarily from satellites. This, of course, is one of the missions of the ISCCP. There are a number of satellite cloud analysis programs that are being undertaken as part of FIRE. One that has already produced data from the FIRE MSc experiment is the spatial coherence method (COAKLEY and Baldwin, 1984). This method produces information on fractional cloud coverage and cloud heights. It may be possible, however, to extract more information on cloud structure from satellite data that might be of use in describing the transitions in the marine stratocumulus cloud deck. Potential applications are explored of a cloud analysis scheme relying on more detailed analysis of visible and infrared cloud radiance statistics. For this preliminary study, data is examined from three days during the 1987 FIRE MSc field work. These case studies provide a basis for comparison and evaluation of the technique.

Khalsa, Siri Jodha Singh↗
NASA NTRS2003

Soil Sampling Techniques For Alabama Grain Fields

Characterizing the spatial variability of nutrients facilitates precision soil sampling. Questions exist regarding the best technique for directed soil sampling based on a priori knowledge of soil and crop patterns. The objective of this study was to evaluate zone delineation techniques for Alabama grain fields to determine which method best minimized the soil test variability. Site one (25.8 ha) and site three (20.0 ha) were located in the Tennessee Valley region, and site two (24.2 ha) was located in the Coastal Plain region of Alabama. Tennessee Valley soils ranged from well drained Rhodic and Typic Paleudults to somewhat poorly drained Aquic Paleudults and Fluventic Dystrudepts. Coastal Plain s o i l s ranged from coarse-loamy Rhodic Kandiudults to loamy Arenic Kandiudults. Soils were sampled by grid soil sampling methods (grid sizes of 0.40 ha and 1 ha) consisting of: 1) twenty composited cores collected randomly throughout each grid (grid-cell sampling) and, 2) six composited cores collected randomly from a -3x3 m area at the center of each grid (grid-point sampling). Zones were established from 1) an Order 1 Soil Survey, 2) corn (Zea mays L.) yield maps, and 3) airborne remote sensing images. All soil properties were moderately to strongly spatially dependent as per semivariogram analyses. Differences in grid-point and grid-cell soil test values suggested grid-point sampling does not accurately represent grid values. Zones created by soil survey, yield data, and remote sensing images displayed lower coefficient of variations (8CV) for soil test values than overall field values, suggesting these techniques group soil test variability. However, few differences were observed between the three zone delineation techniques. Results suggest directed sampling using zone delineation techniques outlined in this paper would result in more efficient soil sampling for these Alabama grain fields.

Thompson, A. N.↗