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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Spatial resolution and cloud optical thickness retrievals

The impact of sensor spatial resolution and accurate cloud pixel identification on cloud property retrievals was investigated. Twelve fair weather cumulus (FWC) scenes of high spectral and spatial resolution Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data are analyzed. A variation of the 3-band ratio technique of Gao and Goetz is used to discriminate clouds from the background, and then a discrete ordinate radiative transfer model is used to obtain optical thickness of cloudy regions for each scene. To study the effect of spatial resolution upon retrieved optical thickness, the 20 m AVIRIS data was spatially degraded to spatial resolutions ranging from 40 to 960 m. Cloud area, scene average optical thickness, and distribution of retrieved optical thickness are determined at each spatial resolution. Finally, a comparison between the 3-band ratio technique and monospectral reflectance thresholding, using 20 m spatial resolution data, is presented.

Feind, Rand E.↗
NASA NTRS1990

Forecast model applications of retrieved three dimensional liquid water fields

Forecasts are made for tropical storm Emily using heating rates derived from the SSM/I physical retrievals described in chapters 2 and 3. Average values of the latent heating rates from the convective and stratiform cloud simulations, used in the physical retrieval, are obtained for individual 1.1 km thick vertical layers. Then, the layer-mean latent heating rates are regressed against the slant path-integrated liquid and ice precipitation water contents to determine the best fit two parameter regression coefficients for each layer. The regression formulae and retrieved precipitation water contents are utilized to infer the vertical distribution of heating rates for forecast model applications. In the forecast model, diabatic temperature contributions are calculated and used in a diabatic initialization, or in a diabatic initialization combined with a diabatic forcing procedure. Our forecasts show that the time needed to spin-up precipitation processes in tropical storm Emily is greatly accelerated through the application of the data.

Raymond, William H.↗
NASA NTRS1993

Retrieval of ice thickness from polarimetric SAR data

We describe a potential procedure for retrieving ice thickness from multi-frequency polarimetric SAR data for thin ice. This procedure includes first masking out the thicker ice types with a simple classifier and then deriving the thickness of the remaining pixels using a model-inversion technique. The technique used to derive ice thickness from polarimetric observations is provided by a numerical estimator or neural network. A three-layer perceptron implemented with the backpropagation algorithm is used in this investigation with several improved aspects for a faster convergence rate and a better accuracy of the neural network. These improvements include weight initialization, normalization of the output range, the selection of offset constant, and a heuristic learning algorithm. The performance of the neural network is demonstrated by using training data generated by a theoretical scattering model for sea ice matched to the database of interest. The training data are comprised of the polarimetric backscattering coefficients of thin ice and the corresponding input ice parameters to the scattering model. The retrieved ice thickness from the theoretical backscattering coefficients is compare with the input ice thickness to the scattering model to illustrate the accuracy of the inversion method. Results indicate that the network convergence rate and accuracy are higher when multi-frequency training sets are presented. In addition, the dominant backscattering coefficients in retrieving ice thickness are found by comparing the behavior of the network trained backscattering data at various incidence angels. After the neural network is trained with the theoretical backscattering data at various incidence anges, the interconnection weights between nodes are saved and applied to the experimental data to be investigated. In this paper, we illustrate the effectiveness of this technique using polarimetric SAR data collected by the JPL DC-8 radar over a sea ice scene.

Kwok, R.↗
NASA NTRS1994

Ozone profile retrievals from the ESA GOME instrument

The potential of the ESA Global Ozone Monitoring Experiment (GOME) to produce ozone profile information has been examined by carrying out two sample retrievals using simulated GOME data. The first retrieval examines the potential of the GOME instrument to produce stratospheric ozone profiles using the traditional back-scatter ultraviolet technique, while the second examines the possibility of obtaining tropospheric profile information, and improving the quality of the stratospheric profile retrievals, by exploiting the temperature dependence of the ozone Huggins bands.

Munro, Rosemary↗
NASA NTRS1995

A diagnostic analysis of the VVP single-doppler retrieval technique

A diagnostic analysis of the VVP (volume velocity processing) retrieval method is presented, with emphasis on understanding the technique as a linear, multivariate regression. Similarities and differences to the velocity-azimuth display and extended velocity-azimuth display retrieval techniques are discussed, using this framework. Conventional regression diagnostics are then employed to quantitatively determine situations in which the VVP technique is likely to fail. An algorithm for preparation and analysis of a robust VVP retrieval is developed and applied to synthetic and actual datasets with high temporal and spatial resolution. A fundamental (but quantifiable) limitation to some forms of VVP analysis is inadequate sampling dispersion in the n space of the multivariate regression, manifest as a collinearity between the basis functions of some fitted parameters. Such collinearity may be present either in the definition of these basis functions or in their realization in a given sampling configuration. This nonorthogonality may cause numerical instability, variance inflation (decrease in robustness), and increased sensitivity to bias from neglected wind components. It is shown that these effects prevent the application of VVP to small azimuthal sectors of data. The behavior of the VVP regression is further diagnosed over a wide range of sampling constraints, and reasonable sector limits are established.

Boccippio, Dennis J.↗
NASA NTRS1995

Retrieval of water vapor mixing ratios from a laser-based sensor

Langley Research Center has developed a novel external path sensor which monitors water vapor along an optical path between an airplane window and reflective material on the plane's engine. An infrared tunable diode laser is wavelength modulated across a water vapor absorption line at a frequency f. The 2f and DC signals are measured by a detector mounted adjacent to the laser. The 2f/DC ratio depends on the amount of wavelength modulation, the water vapor absorption line being observed, and the temperature, pressure, and water vapor content of the atmosphere. The present work concerns efforts to quantify the contributions of these factors and to derive a method for extracting the water vapor mixing ratio from the measurements. A 3 m cell was fabricated in order to perform laboratory tests of the sensor. Measurements of 2f/DC were made for a series of pressures and modulation amplitudes. During my 1994 faculty fellowship, a computer program was created which allowed 2f/DC to be calculated for any combination of the variables which effect it. This code was used to generate 2f/DC values for the conditions measured in the laboratory. The experimental and theoretical values agreed to within a few percent. As a result, the laser modulation amplitude can now be set in the field by comparing the response of the instrument to the calculated response as a function of modulation amplitude. Once the validity of the computer code was established, it was used to investigate possible candidate absorption lines. 2f/DC values were calculated for pressures, temperatures, and water vapor mixing ratios expected to be encountered in future missions. The results have been incorporated into a database which will be used to select the best line for a particular mission. The database will also be used to select a retrieval technique. For examples under some circumstances there is little temperature dependence in 2f/DC so temperature can be neglected. In other cases, there is a dependence with temperature for a particular pressure, requiring a more complicated retrieval algorithm. Future experimental work is necessary to test agreement with the theoretical values over a range of temperatures and mixing ratios. Additionally, retrieval algorithms for forthcoming missions must be incorporated into the software package which controls the instrument.

Tucker, George F.↗
NASA NTRS1997

HARV ANSER Flight Test Data Retrieval and Processing Procedures

Under the NASA High-Alpha Technology Program the High Alpha Research Vehicle (HARV) was used to conduct flight tests of advanced control effectors, advanced control laws, and high-alpha design guidelines for future super-maneuverable fighters. The High-Alpha Research Vehicle is a pre-production F/A-18 airplane modified with a multi-axis thrust-vectoring system for augmented pitch and yaw control power and Actuated Nose Strakes for Enhanced Rolling (ANSER) to augment body-axis yaw control power. Flight testing at the Dryden Flight Research Center (DFRC) began in July 1995 and continued until May 1996. Flight data will be utilized to evaluate control law performance and aircraft dynamics, determine aircraft control and stability derivatives using parameter identification techniques, and validate design guidelines. To accomplish these purposes, essential flight data parameters were retrieved from the DFRC data system and stored on the Dynamics and Control Branch (DCB) computer complex at Langley. This report describes the multi-step task used to retrieve and process this data and documents the results of these tasks. Documentation includes software listings, flight information, maneuver information, time intervals for which data were retrieved, lists of data parameters and definitions, and example data plots.

Yeager, Jessie C.↗
NASA NTRS1997

Comparison of Ice Cloud Particle Sizes Retrieved From Satellite Data Derived From In Situ Measurements

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al. 1994), there is no comparable study for cirrus ice crystals. In this paper a near-global survey of cirrus ice crystal sizes is conducted using ISCCP satellite data analysis. The retrieval scheme uses phase functions based upon hexagonal crystals calculated by a ray tracing technique. The results show that global mean values of D(e) are about 60 micro-m. This study also investigates the possible reasons for the significant difference between satellite retrieved effective radii (approx. 60 micro-m) and aircraft measured particle sizes (approx. 200 micro-m) during the FIRE I IFO experiment. They are (1) vertical inhomogeneity of cirrus particle sizes; (2) lower limit of the instrument used in aircraft measurements; (3) different definitions of effective particle sizes; and (4) possible inappropriate phase functions used in satellite retrieval.

Han, Qingyuan↗
NASA NTRS1996

Atmospheric Pre-Corrected Differential Absorption Techniques to Retrieve Columnar Water Vapor: Theory and Simulations

Two different approaches exist to retrieve columnar water vapor from imaging spectrometer data: (1) Differential absorption techniques based on: (a) Narrow-Wide (N/W) ratio between overlapping spectrally wide and narrow channels; (b) Continuum Interpolated Band Ratio (CIBR) between a measurement channel and the weighted sum of two reference channels. (2) Non-linear fitting techniques which are based on spectral radiative transfer calculations. The advantage of the first approach is computational speed and of the second, improved retrieval accuracy. Our goal was to improve the accuracy of the first technique using physics based on radiative transfer. Using a modified version of the Duntley equation, we derived an "Atmospheric Pre-corrected Differential Absorption" (APDA) technique and described an iterative scheme to retrieve water vapor on a pixel-by-pixel basis. Next we compared both, the CIBR and the APDA using the Duntley equation for MODTRAN3 computed irradiances, transmissions and path radiance (using the DISORT option). This simulation showed that the CIBR is very sensitive to reflectance effects and that the APDA performs much better. An extensive data set was created with the radiative transfer code 6S over 379 different ground reflectance spectra. The calculated relative water vapor error was reduced significantly for the APDA. The APDA technique had about 8% (vs. over 35% for the CIBR) of the 379 spectra with a relative water vapor error of greater than +5%. The APDA has been applied to 1991 and 1995 AVIRIS scenes which visually demonstrate the improvement over the CIBR technique.

Borel, Christoph C.↗
NASA NTRS1999

The Role of Metadata Standards in EOSDIS Search and Retrieval Applications

Metadata standards play a critical role in data search and retrieval systems. Metadata tie software to data so the data can be processed, stored, searched, retrieved and distributed. Without metadata these actions are not possible. The process of populating metadata to describe science data is an important service to the end user community so that a user who is unfamiliar with the data, can easily find and learn about a particular dataset before an order decision is made. Once a good set of standards are in place, the accuracy with which data search can be performed depends on the degree to which metadata standards are adhered during product definition. NASA's Earth Observing System Data and Information System (EOSDIS) provides examples of how metadata standards are used in data search and retrieval.

Pfister, Robin↗
NASA NTRS1999

A Spherical Earth Solution for TOA Lightning Location Retrieval

With the advent of high-speed digital computers, the method of chi square minimization is a highly practical means for analyzing a wide variety of (otherwise intractable) nonlinear inversion problems in applied mathematical physics. Little thought or effort is required to apply the chi square method to obtain quick and reasonable estimates of a solution, and the method offers a means to assess retrieval errors. Because the method is simple and practical it is sometimes hastily applied to problems that can be solved by formal analytic or quasi-analytic means. Presently, Global Atmospherics Inc. (GAI) finds the minimum of a chi square function to analyze time-of-arrival (TOA) and magnetic bearing data derived from the National Lightning Detection Network (NLDN); ellipsoidal Earth geometry is assumed. An analytic solution to this problem has not yet been attained, but the consideration and solving of less general problem statements might eventually lead to a final solution. In the present study, the problem of retrieving lightning ground-strike location on a spherical Earth surface using a network of 4 or more time-of-arrival (TOA) sensors is considered. It is shown that this problem has an analytic solution and therefore does not require the use of nonlinear estimation theory (such as the chi square method mentioned above). The mathematical robustness of the analytic solution is tested using computer-generated lightning sources and simulated TOA measurement errors. A quasi-analytic extension of the spherical Earth solution for an oblate spheroidal Earth geometry is considered in a related study. The incorporation of magnetic bearing information into these analytic solutions would lead to a general and elegant analytic retrieval scheme that would most likely replace the chi square estimation theory currently employed by Global Atmospherics Inc. (GAI).

Koshak, William J,↗
NASA NTRS1999

Improving Pixel Level Cloud Optical Property Retrieval using Monte Carlo Simulations

The accurate pixel-by-pixel retrieval of cloud optical properties from space is influenced by radiative smoothing due to high order photon scattering and radiative roughening due to low order scattering events. Both are caused by cloud heterogeneity and the three-dimensional nature of radiative transfer and can be studied with the aid of computer simulations. We use Monte Carlo simulations on variable 1-D and 2-D model cloud fields to seek for dependencies of smoothing and roughening phenomena on single scattering albedo, solar zenith angle, and cloud characteristics. The results are discussed in the context of high resolution satellite (such as Landsat) retrieval applications. The current work extends the investigation on the inverse NIPA (Non-local Independent Pixel Approximation) as a tool for removing smoothing and improving retrievals of cloud optical depth. This is accomplished by: (1) Delineating the limits of NIPA applicability; (2) Exploring NIPA parameter dependences on cloud macrostructural features, such as mean cloud optical depth and geometrical thickness, degree of extinction and cloud top height variability. We also compare parameter values from empirical and theoretical considerations; (3) Examining the differences between applying NIPA on radiation quantities vs direct application on optical properties; (4) Studying the radiation budget importance of the NIPA corrections as a function of scale. Finally, we discuss fundamental adjustments that need to be considered for successful radiance inversion at non-conservative wavelengths and oblique Sun angles. These adjustments are necessary to remove roughening signatures which become more prominent with increasing absorption and solar zenith angle.

Oreopoulos, Lazaros↗
NASA NTRS1999

Cloud Power Spectra-Dependence on Solar Zenith Angle and Wavelength, Implications for Cloud Optical Property Retrievals

Scale breaks (spatial scales at which power-law exponent changes occur) observed in Landsat radiances have proven to be useful indicators of radiative interactions, and have aided the development of improved techniques in the remote sensing of clouds. This work extends previous theoretical studies to absorbing wavelengths by using both Landsat Thematic Mapper (TM) observations and Monte Carlo (MC) simulations to infer the systematic dependencies of power spectral shape on cloud characteristics, illumination conditions, and wavelength. We show that MC simulations operating on a simple fractal model of horizontally inhomogeneous clouds produce power spectra that qualitatively resemble observed spectra. We also show that the decrease in the spectra power-law exponent seen at intermediate scales (referred to as "roughening") as the Sun becomes more oblique is more pronounced at absorbing wavelengths. An automated procedure designed to detect the small scale break location is unable to find systematic differences between TM Band 4 and Band 7, despite the fact that MC simulations point to systematic differences in horizontal fluxes. The effect of these qualitative characteristics of the spatial spectra on the retrieval of cloud optical properties is examined by comparing power spectra of nadir radiances with power spectra of optical properties retrieved using either traditional Independent Pixel Approximation approaches or modifications based on normalized radiance indices and the inverse Non-local Independent Pixel Approximation. Assuming that the actual cloud properties follow perfect scaling behavior at all scales, we show the improvement of the proposed retrieval modifications.

Oreopoulos, Lazaros↗
NASA NTRS1999

Current Status of Aerosol Retrievals from TOMS

Properties of atmospheric aerosols over all land and water surfaces are retrieved from TOMS measurements of backscattered radiances. The TOMS technique, uses observations at two wavelengths. In the near ultraviolet (330-380 nm) range, where the effects of gaseous absorption are negligible. The retrieved properties are optical depth and a measure of aerosol absorptivity, generally expressed as single scattering albedo. The main sources of error of the TOMS aerosol products are sub-pixel cloud contamination and uncertainty on the height above the surface of UV-absorbing aerosol layers. The first error source is related to the large footprint (50 x 50 km at nadir) of the sensor, and the lack of detection capability of sub-pixel size clouds. The uncertainty associated with the height of the absorbing aerosol layers, on the other hand, is related to the pressure dependence of the molecular scattering process, which is the basis of the near-UV method of absorbing aerosol detection. The detection of non-absorbing aerosols is not sensitive to aerosol layer height. We will report on the ongoing work to overcome both of these difficulties. Coincident measurements of high spatial resolution thermal infrared radiances are used to address the cloud contamination issue. Mostly clear scenes for aerosol retrieval are selected by examining the spatial homogeneity of the IR radiance measurements within a TOMS pixel. The approach to reduce the uncertainty associated with the height of the aerosol layer by making use of a chemical transport model will also be discussed.

Torres, O.↗
NASA NTRS1999

Two-Channel Satellite Retrievals of Aerosol Properties: An Overview

In order to reduce current uncertainties in the evaluation of the direct and indirect effects of tropospheric aerosols on climate on the global scale, it has been suggested to apply multi-channel retrieval algorithms to the full period of existing satellite data. This talk will outline the methodology of interpreting two-channel satellite radiance data over the ocean and describe a detailed analysis of the sensitivity of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. We will specifically address the calibration and cloud screening issues, consider the suitability of existing satellite data sets to detecting short- and long-term regional and global changes, compare preliminary results obtained by several research groups, and discuss the prospects of creating an advanced retroactive climatology of aerosol optical thickness and size over the oceans.

Mishchenko, Michael I.↗
NASA NTRS1997

Estimating the Uncertainty in Passive-Microwave Rain-Retrievals

Current passive-microwave rain-retrieval methods are largely based on databases built off-line using cloud models. The vertical distribution of hydrometeors within the cloud has a large impact on upwelling brightness temperatures ([31,[5]). Thus, a forward radiative transfer model can predict off-line the radiance associated with different rain scenarios. To estimate the rain from measured brightness temperatures, one simply looks for the rain scenario whose associated radiances are closest to the measurements. To understand the uncertainties in this process, we first study the dependence of the simulated brightness temperatures on different hydrometeor size distribution (DSD) models. We then analyze the marginal and joint distributions of the radiances observed by the Tropical Rainfall Measuring Mission satellite and of those in the databases used in the TRMM rain retrievals. We finally calculate the covariances of the rain profiles and brightness temperatures in the TRMM passive-microwave database and derive a simple parametric model for the conditional uncertainty, given measured radiances. These results are used to characterize the uncertainty inherent in the passive-microwave retrieval.

Coppens, Dorothee↗
NASA NTRS2001

Intercomparison of GOES-8 Imager and Sounder Land Surface Temperature Retrievals

Recent studies at the Global Hydrology and Climate Center (GHCC) have shown that the assimilation of land skin temperature (LST) tendencies into a mesoscale model can significantly improve short term forecasts of near surface temperature and moisture. The high spatial and temporal resolution of GOES derived land surface products provide valuable information about the spatial and temporal variability of the land surface forcing simulated in the model. In the GHCC studies LST was derived using a split window technique requiring at least two longwave infrared window channels and thus, utilized the 11 and 12 micron channels found on the GOES-8 Imager with a nadir spatial resolution of 4km. However, beginning with the launch of GOES-M (scheduled for mid 2001 ) and subsequent satellites the 12 micron channel will be removed from the Imager leaving only one longwave window channel. The GOES Sounder will continue to have more than one longwave infrared window channel (including a 12 micron channel) but, with a spatial resolution of 10 km nadir. LST retrievals from the newer GOES satellites will thus be derived from Sounder measurements at a reduced spatial resolution. This paper intercompares the LST retrievals from the GOES-8 Imager and Sounder. The effects on the LST retrievals due to the Sounder's reduced resolution from that of the Imager and its different longwave infrared channel characteristics are examined. The effects of transitioning from Imager to Sounder LST products on the results from model assimilation of these products are also examined.

Suggs, Ronnie J.↗
NASA NTRS2001

A Comparison of Seasonal and Interannual Variability of Soil Dust Aerosols Over the Atlantic Ocean as Inferred by the Toms AI and AVHRR AOT Retrievals

The seasonal cycle and interannual variability of two estimates of soil (or 'mineral') dust aerosols are compared: Advanced Very High Resolution Radiometer (AVHRR) aerosol optical thickness (AOT) and Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI), Both data sets, comprising more than a decade of global, daily images, are commonly used to evaluate aerosol transport models. The present comparison is based upon monthly averages, constructed from daily images of each data set for the period between 1984 and 1990, a period that excludes contamination from volcanic eruptions. The comparison focuses upon the Northern Hemisphere subtropical Atlantic Ocean, where soil dust aerosols make the largest contribution to the aerosol load, and are assumed to dominate the variability of each data set. While each retrieval is sensitive to a different aerosol radiative property - absorption for the TOMS AI versus reflectance for the AVHRR AOT - the seasonal cycles of dust loading implied by each retrieval are consistent, if seasonal variations in the height of the aerosol layer are taken into account when interpreting the TOMS AI. On interannual time scales, the correlation is low at most locations. It is suggested that the poor interannual correlation is at least partly a consequence of data availability. When the monthly averages are constructed using only days common to both data sets, the correlation is substantially increased: this consistency suggests that both TOMS and AVHRR accurately measure the aerosol load in any given scene. However, the two retrievals have only a few days in common per month so that these restricted monthly averages have a large uncertainty. Calculations suggest that at least 7 to 10 daily images are needed to estimate reliably the average dust load during any particular month, a threshold that is rarely satisfied by the AVHRR AOT due to the presence of clouds in the domain. By rebinning each data set onto a coarser grid, the availability of the AVHRR AOT is increased during any particular month, along with its interannual correlation with the TOMS AI The latter easily exceeds the sampling threshold due to its greater ability to infer the aerosol load in the presence of clouds. Whether the TOMS AI should be regarded as a more reliable indicator of interannual variability depends upon the extent of contamination by sub-pixel clouds.

Cakmur, R. V.↗