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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Method for calculating and observing microwave absorption by a sphere in a single mode rectangular cavity

A new theory of microwave absorption by a lossy dielectric sphere in a single mode rectangular cavity has been recently developed. The absorption was treated in the framework of an electromagnetic scattering problem. That theory is summarized here and calculated results that bear on optimizing the processing of materials are illustrated. Methods for observing power absorption and other results predicted by the scattering model are discussed. Cavity perturbation theory provides a bridge between theoretical calculations and experimental observations, and a special problem that arises when an established version of cavity perturbation theory is applied to spheres is identified, analyzed, and resolved. The direct problem of predicting shifts in frequency and Q from model calculations is discussed for a sphere in a cavity when the sphere's complex dielectric constant is known. Also, the inverse problem of determining the complex dielectric constants from measured values of those shifts is considered. The small sphere limit, where an electrostatic or quasistatic model is valid, is treated in detail, and planned work on parallel problems for larger spheres is described.

Jackson, H. W.↗
NASA NTRS2000

Estimates of Ground Temperature and Atmospheric Moisture from CERES Observations

A method is developed to retrieve surface ground temperature (Tg) and atmospheric moisture using clear sky fluxes (CSF) from CERES-TRMM observations. In general, the clear sky outgoing long-wave radiation (CLR) is sensitive to upper level moisture (q(sub h)) over wet regions and Tg over dry regions The clear sky window flux from 800 to 1200 /cm (RadWn) is sensitive to low level moisture (q(sub j)) and Tg. Combining these two measurements (CLR and RadWn), Tg and q(sub h) can be estimated over land, while q(sub h) and q(sub t) can be estimated over the oceans. The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic CSF data from two different global 4-dimensional data assimilation products. Simple linear regression is used to relate discrepancies in CSF to discrepancies in Tg, q(sub h) and q(sub t). The slopes of the regression lines define sensitivity parameters that can be exploited to help interpret mismatches between satellite observations and model-based estimates of CSF. For illustration, we analyze the discrepancies in the CSF between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) and a recent operational version of the European Center for Medium-Range Weather Prediction data assimilation system. In particular, our analysis of synthetic total and window region SCF differences (computed from two different assimilated data sets) shows that simple linear regression employing (Delta)Tg and broad layer (Delta)q(sub l) from 500 hPa to surface and (Delta)q(sub h) from 200 to 500 hPa provides a good approximation to the full radiative transfer calculations, typically explaining more than 90% of the 6-hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters. Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for (Delta)T to about 20% for (Delta)q(sub t). Our initial application of the methodology employed an early CERES-TRMM data set (CLR and Radwn) to assess the quality of the GEOS2 data. The results showed that over the tropical and subtropical oceans GEOS2 is, in general, too wet in the upper troposphere (mean bias of 0.99 mm) and too dry in the lower troposphere (mean bias of -4.7 mm). We note that these errors, as well as a cold bias in the Tg, have largely been corrected in the current version of GEOS-2 with the introduction of a land surface model, a moist turbulence scheme and the assimilation of SSTM/I total precipitable water.

Wu, Man Li C.↗
NASA NTRS2000

Estimates of Ground Temperature and Atmospheric Moisture from CERES Observations

A method is developed to retrieve surface ground temperature (T(sub g)) and atmospheric moisture using clear sky fluxes (CSF) from CERES-TRMM observations. In general, the clear sky outgoing longwave radiation (CLR) is sensitive to upper level moisture (q(sub l)) over wet regions and (T(sub g)) over dry regions The clear sky window flux from 800 to 1200/cm (RadWn) is sensitive to low level moisture (q(sub t)) and T(sub g). Combining these two measurements (CLR and RadWn), Tg and q(sub h) can be estimated over land, while q(sub h) and q(sub l) can be estimated over the oceans. The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data. The basic methodology employs off-line forward radiative transfer calculations to generate synthetic CSF data from two different global 4-dimensional data assimilation products. Simple linear regression is used to relate discrepancies in CSF to discrepancies in T(sub g), q(sub h) and q(sub l). The slopes of the regression lines define sensitivity parameters that can be exploited to help interpret mismatches between satellite observations and model-based estimates of CSF. For illustration, we analyze the discrepancies in the CSF between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS-DAS) and a recent operational version of the European Center for Medium-Range Weather Prediction data assimilation system. In particular, our analysis of synthetic total and window region SCF differences (computed from two different assimilated data sets) shows that simple linear regression employing Delta(T(sub g)) and broad layer Delta(q(sub l) from .500 hPa to surface and Delta(q(sub h)) from 200 to .300 hPa provides a good approximation to the full radiative transfer calculations. typically explaining more than 90% of the 6-hourly variance in the flux differences. These simple regression relations can be inverted to "retrieve" the errors in the geophysical parameters. Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for Delta(T(sub g)) to about 20% for Delta(q(sub l)). Our initial application of the methodology employed an early CERES-TRMM data set (CLR and Radwn) to assess the quality of the GEOS2 data. The results showed that over the tropical and subtropical oceans GEOS2 is, in general, too wet in the upper troposphere (mean bias of 0.99 mm) and too dry in the lower troposphere (mean bias of -4.7 min). We note that these errors, as well as a cold bias in the T(sub g). have largely been corrected in the current version of GEOS-2 with the introduction of a land surface model, a moist turbulence scheme and the assimilation of SSM/I total precipitable water.

Wu, Man Li C.↗
NASA NTRSDate not supplied

Deriving Essential Climate Variable Data from Multiple Satellite Remote Sensors Using a Consistent Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms can lead to errors in the climate products when fusing data from different satellite sensors. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) data and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Aerosol and Cloud, Convection and Precipitation (ACCP).

Xu Liu↗
NASA NTRS1975

Solar energy microclimate as determined from satellite observations

A method is presented for determining solar insolation at the earth's surface using satellite broadband visible radiance and cloud imagery data, along with conventional in situ measurements. Conventional measurements are used to both tune satellite measurements and to develop empirical relationships between satellite observations and surface solar insolation. Cloudiness is the primary modulator of sunshine. The satellite measurements as applied in this method consider cloudiness both explicitly and implicitly in determining surface solar insolation at space scales smaller than the conventional pyranometer network.

Vonder Haar, T. H.↗
NASA NTRS1977

Computer solutions for studying correlations between solar magnetic fields and Skylab X-ray observations

A method is described which correlates the NASA-Marshall Space Flight Center (MSFC) Image Data Processing System (IDAPS) and MSFC magnetograph data to X-ray and H-alpha observations from the Skylab mission. Solutions of Laplace's equation in three dimensions, based on the magnetograph data, are convolved with observed X-ray and H-alpha regions. Matched filtering (template matching) provides a best fit of the observed X-ray regions to the computed total magnetic vector magnitude between 10,000 and 15,000 km above the photosphere.

Teuber, D.↗
NASA NTRSDate not supplied

Deriving Climate Change Signal from Hyperspectral Sounders Using Spectral Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric temperature, water vapor and trace gas vertical profiles. We have developed a radiometrically consistent spectral fingerprinting method to derive climate change signals from Aqua AIRS/AMSU and S-NPP CrIS/ATMS data. The climate variables include temperature and water vapor profiles, cloud, trace gases, and surface skin temperature. The radiative kernels obtained via a single field of view physical retrieval algorithm under all-sky conditions. A key component to this work is a Principal Component-based Radiative Transfer Model (PCRTM). It is 4 orders of magnitude faster than a line-by-line radiative transfer model while keeping a similar accuracy (0.03 K RMS errors with close to zero bias). The PCRTM includes multiple scattering of clouds and non-thermodynamics equilibrium of CO2 in the RT calculations. Instead of quantifying the radiometric differences between AIRS/AMSU and CrIS/ATMS measurements directly using Simultaneous Nadir Overpass (SNO) or Double Difference Technique (DDT), we use the radiometric consistent fingerprinting scheme to derive two sets of space-time averaged anomalies from the Level 1 data of AIRS/AMSU and CrIS/ATMS. The derived anomalies in geophysical space will form a long-term, stable, and continuous climate data record. We can further infer the causes of any offset or drift by studying the differences between two overlapping data sets. For example, the offset in surface skin temperature anomaly time series will most likely caused by the Blackbody temperature calibration errors of the sounder instruments.

climate↗
NASA NTRS1988

Simulations using a 3D-moment turbulence closure in a two-dimensional cloud model - Comparisons with observations

A method for deep cumulus cloud simulations is presented, in which the plumes or clouds are simulated using a two-dimensional axisymmetric numerical cloud model with third-moment turbulence closure. This method is based on the assumption that the only uncertainty in the turbulence closure is in the turbulent length scale specification. Therefore, the length scale is varied, and, using different length scales, the simulated plumes are compared to the observed ones, making it possible to optimize the length scale prescription.

Krueger, Steven K.↗
NASA NTRS1986

Solution of nonlinear finite difference ocean models by optimization methods with sensitivity and observational strategy analysis

The paper studies with finite difference nonlinear circulation models the uncertainties in interesting flow properties, such as western boundary current transport, potential and kinetic energy, owing to the uncertainty in the driving surface boundary condition. The procedure is based upon nonlinear optimization methods. The same calculations permit quantitative study of the importance of new information as a function of type, region of measurement and accuracy, providing a method to study various observing strategies. Uncertainty in a model parameter, the bottom friction coefficient, is studied in conjunction with uncertain measurements. The model is free to adjust the bottom friction coefficient such that an objective function is minimized while fitting a set of data to within prescribed bounds. The relative importance of the accuracy of the knowledge about the friction coefficient with respect to various kinds of observations is then quantified, and the possible range of the friction coefficients is calculated.

Schroeter, Jens↗
NASA NTRS1990

Estimation of mean rain rate - Application to satellite observations

A method for the estimation of the mean area average rain rate from dependent data is developed and applied to the GARP Atlantic Tropical Experiment data. The method consists of fitting a mixed distribution, containing an atom at zero, by minimum chi-square in combination with certain time-space sampling designs. In modeling the continuous component of the mixed distribution, it is shown that the lognormal distribution provides a very close fit for the nonzero area average rainrates. A comparison with the gamma distribution shows that the lognormal distribution is a better choice as expressed by the minimum chi-square criterion. Some of the time-space sampling designs correspond to satellite sampling. The results indicate that a satellite visiting an area of about 350 x 350 sq km in the tropics approximately every 10 hours over a period can provide a rather close estimate for the mean area average rain rate.

Kedem, Benjamin↗
NASA NTRS1993

Shape optimization for aerodynamic efficiency and low observability

Field methods based on the finite-difference approximations of the time-domain Maxwell's equations and the potential-flow equation have been developed to solve the multidisciplinary problem of airfoil shaping for aerodynamic efficiency and low radar cross section (RCS). A parametric study and an optimization study employing the two analysis methods are presented to illustrate their combined capabilities. The parametric study shows that for frontal radar illumination, the RCS of an airfoil is independent of the chordwise location of maximum thickness but depends strongly on the maximum thickness, leading-edge radius, and leadingedge shape. In addition, this study shows that the RCS of an airfoil can be reduced without significant effects on its transonic aerodynamic efficiency by reducing the leading-edge radius and/or modifying the shape of the leading edge. The optimization study involves the minimization of wave drag for a non-lifting, symmetrical airfoil with constraints on the airfoil maximum thickness and monostatic RCS. This optimization study shows that the two analysis methods can be used effectively to design aerodynamically efficient airfoils with certain desired RCS characteristics.

Vinh, Hoang↗
NASA NTRS1994

Global shortwave energy budget at the earth's surface from ERBE observations

A method is proposed to compute the net solar (shortwave) irradiance at the earth's surface from Earth Radiation Budget Experiment (ERBE) data in the S4 format. The S4 data are monthly averaged broadband planetary albedo collected at selected times during the day. Net surface shortwave irradiance is obtained from the shortwave irradiance incident at the top of the atmosphere (known) by subtracting both the shortwave energy flux reflected by the earth-atmosphere system (measured) and the energy flux absorbed by the atmosphere (modeled). Precalculated atmospheric- and surface-dependent functions that characterize scattering and absorption in the atmosphere are used, which makes the method easily applicable and computationally efficient. Four surface types are distinguished, namely, ocean, vegetation, desert, and snow/ice. Over the tropical Pacific Ocean, the estimates based on ERBE data compare well with those obtained from International Satellite Cloud Climatology Project (ISCCP) B3 data. For the 9 months analyzed the linear correlation coefficient and the standard difference between the two datasets are 0.95 and 14 W/sq m (about 6% of the average shortwave irradiance), respectively, and the bias is 15 W/sq m (higher ERBE values). The bias, a strong function of ISCCP satellite viewing zenith angle, is mostly in the ISCCP-based estimates. Over snow/ice, vegetation, and desert no comparison is made with other satellite-based estimates, but theoretical calculations using the discrete ordinate method suggest that over highly reflective surfaces (snow/ice, desert) the model, which accounts crudely for multiple reflection between the surface and clouds, may substantially overestimate the absorbed solar energy flux at the surface, especially when clouds are optically thick. The monthly surface shortwave irradiance fields produced for 1986 exhibit the main features characteristic of the earth's climate. As found in other studies, our values are generally higher than Esbensen and Kushnir's by as much as 80 W/sq m in the tropical oceans. A cloud parameter, defined as the difference between clear-sky and actual irradiances normalized to top-of-atmosphere clear-sky irradiance, is also examined. This parameter, minimally affected by sun zenith angle, is higher in the midlatitude regions of storm tracks than in the intertropical convergence zone (ITCZ), suggesting that, on average, the higher cloud coverage in midlatitudes is more effective at reducing surface shortwave irradiance than opaque, convective, yet sparser clouds in the ITCZ. Surface albedo estimates are realistic, generally not exceeding 0.06 in the ocean, as high as 0.9 in polar regions, and reaching 0.5 in the Sahara and Arabian deserts.

Breon, Francois-Marie↗
NASA NTRS1991

Meteorological radar methods for validating space observations of precipitation

Meteorological approaches to verification of space measurements of rainfall are examined; validation of Tropical Rainfall Measuring Mission (TRMM) observations is expected to depend significantly on ground-based radars. Two methods of comparison are initially contemplated. TRMM rainfall data over time periods of a month for large areas (500 x 500 km) are averaged and compared with similarly averaged ground truth measurements. Both the rainfall and height distribution data from TRMM are compared with the instantaneous values observed at one or more 'ground truth' stations and from airborne radar and radiometers as available.

Thiele, Otto W.↗
NASA NTRS2016

Benchmark Comparison of Cloud Analytics Methods Applied to Earth Observations

Cloud computing has the potential to bring high performance computing capabilities to the average science researcher. However, in order to take full advantage of cloud capabilities, the science data used in the analysis must often be reorganized. This typically involves sharding the data across multiple nodes to enable relatively fine-grained parallelism. This can be either via cloud-based file systems or cloud-enabled databases such as Cassandra, Rasdaman or SciDB. Since storing an extra copy of data leads to increased cost and data management complexity, NASA is interested in determining the benefits and costs of various cloud analytics methods for real Earth Observation cases. Accordingly, NASA's Earth Science Technology Office and Earth Science Data and Information Systems project have teamed with cloud analytics practitioners to run a benchmark comparison on cloud analytics methods using the same input data and analysis algorithms. We have particularly looked at analysis algorithms that work over long time series, because these are particularly intractable for many Earth Observation datasets which typically store data with one or just a few time steps per file. This post will present side-by-side cost and performance results for several common Earth observation analysis operations.

science data management↗
NASA NTRS1973

Observations of chemical releases from high flying aircraft

Barium and lithium vapors were released from sounding rockets in the thermosphere and observed from aboard the NASA Convair 990 at an altitude of 40,000 ft. The purpose of the releases was to (1) check out observational and operational procedures associated with the large high altitude barium release from a Scout rocket (BIC); (2) develop an all-weather technique for observing chemical releases; (3) evaluate methods of observing daytime releases, and (4) investigate the possibilities of observations from a manned satellite. The initial analysis indicates that the previous limitations on the usage of the vapor release method have been removed by the use of the aircraft and innovative photographic techniques. Methods of analysis and applications to the investigation of the thermosphere are discussed.

Bedinger, J. F.↗
NASA NTRS2013

Analytic Perturbation Method for Estimating Ground Flash Fraction from Satellite Lightning Observations

An analytic perturbation method is introduced for estimating the lightning ground flash fraction in a set of N lightning flashes observed by a satellite lightning mapper. The value of N is large, typically in the thousands, and the observations consist of the maximum optical group area produced by each flash. The method is tested using simulated observations that are based on Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) data. National Lightning Detection NetworkTM (NLDN) data is used to determine the flash‐type (ground or cloud) of the satellite-observed flashes, and provides the ground flash fraction truth for the simulation runs. It is found that the mean ground flash fraction retrieval errors are below 0.04 across the full range 0‐1 under certain simulation conditions. In general, it is demonstrated that the retrieval errors depend on many factors (i.e., the number, N, of satellite observations, the magnitude of random and systematic measurement errors, and the number of samples used to form certain climate distributions employed in the model).

Koshak, William↗
NASA NTRS2005

A Posteriori Correction of Forecast and Observation Error Variances

Proposed method of total observation and forecast error variance correction is based on the assumption about normal distribution of "observed-minus-forecast" residuals (O-F), where O is an observed value and F is usually a short-term model forecast. This assumption can be accepted for several types of observations (except humidity) which are not grossly in error. Degree of nearness to normal distribution can be estimated by the symmetry or skewness (luck of symmetry) a(sub 3) = mu(sub 3)/sigma(sup 3) and kurtosis a(sub 4) = mu(sub 4)/sigma(sup 4) - 3 Here mu(sub i) = i-order moment, sigma is a standard deviation. It is well known that for normal distribution a(sub 3) = a(sub 4) = 0.

Rukhovets, Leonid↗