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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Contaminated Solar Array Handrail Samples Retrieved From Mir Analyzed

In January 1998 during the shuttle STS 89 mission, an eight-section Russian solar array panel was retrieved after more than 10 years of exposure to the orbital space environment on Mir. The array was deployed June 16, 1987, and removed on November 3, 1997. It had been actively used as a source of electrical power for 8 years. This operational array had been located on the Mir core module, located directly above the Kvant-2 module. Its retrieval provided a unique opportunity to study the effects of the low-Earth-orbit environment on a functional solar array. The intact solar array underwent scientific inspections and preliminary tests by a joint team of U.S. and Russian investigators to evaluate the effects of long-term space exposure. Upon initial examination, significant contamination was observed over most components of the array. One panel, panel 8, was provided to the U.S. scientists for further evaluation. As part of the U.S. investigations, two solar array handrail samples from panel 8 were evaluated for contamination at the NASA Glenn Research Center at Lewis Field. One is a section of a rigid handrail, and the other is a section of woven fabric tape that was overwrapped around a flexible handhold. Both the flexible handhold woven fabric and the rigid handrail were significantly darkened after 10 years of space exposure. They were evaluated with optical microscopy, field emission scanning electron microscopy (FESEM), and energy-dispersive spectroscopy. Solar absorptance and room-temperature emittance values also were obtained. The returned contaminated solar array segment is very similar in design to the solar arrays being supplied by the Russians for the International Space Station. Therefore, it was desirable to determine what the contaminants on various surfaces are and what the sources of the contamination were.

deGroh, Kim K.↗
NASA NTRS2002

Physical and Thermal Properties Evaluated of Teflon FEP Retrieved From the Hubble Space Telescope During Three Servicing Missions

Mechanical properties of aluminized Teflon fluorinated ethylene propylene (FEP) thermal control materials on the Hubble Space Telescope (HST) exposed to low Earth orbit for up to 9.7 years have significantly degraded, with extensive cracking occurring on orbit. The NASA Glenn Research Center and the NASA Goddard Space Flight Center have collaborated on analyzing the physical and thermal properties of aluminized FEP (FEP-Al, DuPont) materials retrieved in December 1999 during HST's third servicing mission (SM3A). Comparisons have been made to properties of FEP-Al retrieved during the first and second HST servicing missions, SM1 and SM2, in order to determine degradation processes for FEP on HST.

Dever, Joyce A.↗
NASA NTRS2005

Retrieving Storm Electric Fields From Aircraft Field Mill Data. Part I: Theory

It is shown that the problem of retrieving storm electric fields from an aircraft instrumented with several electric field mill sensors can be expressed in terms of a standard Lagrange multiplier optimization problem. The method naturally removes aircraft charge from the retrieval process without having to use a high voltage stinger and linearly combined mill data values. It also allows a variety of user-supplied physical constraints (the so-called side constraints in the theory of Lagrange multipliers). Additionally, this paper introduces a novel way of performing the absolute calibration of an aircraft that has several benefits over conventional analyses. In the new approach, absolute calibration is completed by inspecting the time derivatives of mill and pitch data for a pitch down maneuver performed at high (greater than 1 km) altitude. In Part II of this study, the above methods are tested and then applied to complete a full calibration of a Citation aircraft.

Koshak, W. J.↗
NASA NTRS2006

Variational Assimilation of Global Microwave Rainfall Retrievals: Physical and Dynamical Impact on GEOS Analyses and Forecasts

Global microwave rainfall retrievals from a 5-satellite constellation, including TMI from TRMM, SSWI from DMSP F13, F14 and F15, and AMSR-E from EOS-AQUA, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) using a 1-D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses and forecasts is examined at various temporal and spatial scales. This study demonstrates that the 1-D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over the land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly-mean and 6-hour time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1-D VCA algorithm, by compensating for errors in the model s moist time-tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall-assimilation m especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicates that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity are more realistically captured across the front. Short-term forecasts using initial conditions assimilated with rainfall data also show slight improvements. 1

Lin, Xin↗
NASA NTRS1995

(abstract) Using an Inversion Algorithm to Retrieve Parameters and Monitor Changes over Forested Areas from SAR Data

In this work, the application of an inversion algorithm based on a nonlinear opimization technique to retrieve forest parameters from multifrequency polarimetric SAR data is discussed. The approach discussed here allows for retrieving and monitoring changes in forest parameters in a quantative and systematic fashion using SAR data. The parameters to be inverted directly from the data are the electromagnetic scattering properties of the forest components such as their dielectric constants and size characteristics. Once these are known, attributes such as canopy moisture content can be obtained, which are useful in the ecosystem models.

forest canopy SAR data algorithm radar scattering ↗
NASA NTRS1994

Development of an Aerosol Opacity Retrieval Algorithm for Use with Multi-Angle Land Surface Images

In 1998, the Multi-angle Imaging SpectroRadiometer (MISR) will fly aboard the EOS-AM1 spacecraft. MISR will enable unique methods for retrieving the properties of atmospheric aerosols, by providing global imagery of the Earth at nine viewing angles in four visible and near-IR spectral bands. As part of the MISR algorithm development, theoretical methods of analyzing multi-angle, multi-spectral data are being tested using images acquired by the airborne Advanced Solid-State Array Spectroradiometer (ASAS). In this paper we derive a method to be used over land surfaces for retrieving the change in opacity between spectral bands, which can then be used in conjunction with an aerosol model to derive a bound on absolute opacity.

Advanced Solid-State Array Spectroradiometer ASAS ↗
NASA NTRS2006

Retrieved Surface Emissivity Impact of New Cloud-Clearing Channel Set

A viewgraph presentation on a proposed new cloud clearing channel set to improve land products and validate surface emissivity is given. The topics include: 1) Methodology; 2) Channel Selection; 3) Temperature Statistics; 4) 850 hPa Temperature Variability; 5) Status of Surface Retrieval; 6) Emissivity at 9 micrometers; 7) Emissivity Spectra; 8) Ha Megev (Israel); 9) Egypt One; 10) Salonga National Park, Zaire; 11) HaGolan (Israel/Syria); 12) Emissivity at 3.75 micrometers; 13) Improving Surface Retrieval; 14) Work Needed for V5 Delivery; 15) Effects of MODIS Emissivity; 16) Channel Selection; 17) 500 hPa Temperature Variability; 18) 850 hPa Temperature Variability; and 19) 850 hPa Temperature Differences;

Atmospheric Infrared Sounder (AIRS)↗
NASA NTRS2006

Retrieving Storm Electric Fields from Aircraft Field Mill Data: Theory - Part 1

It is shown that the problem of retrieving storm electric fields from an aircraft instrumented with several electric field mill sensors can be expressed in terms of a standard Lagrange multiplier optimization problem. The method naturally removes aircraft charge from the retrieval process without having to use a high voltage stinger and linearly combined mill data values. It allows a variety of user-supplied physical constraints (the so-called side constraints in the theory of Lagrange multipliers) and also helps improve absolute calibration. Additionally, this paper introduces an alternate way of performing the absolute calibration of an aircraft that has some benefits over conventional analyses. It is accomplished by using the time derivatives of mill and pitch data for a pitch down maneuver performed at high (greater than 1 km) altitude. In Part II of this study, the above methods are tested and then applied to complete a full calibration of a Citation aircraft.

Koshak, W. J.↗
NASA NTRS2007

Retrieval Lesson Learned from NAST-I Hyperspectral Data

The retrieval lesson learned is important to many current and future hyperspectral remote sensors. Validated retrieval algorithms demonstrate the advancement of hyperspectral remote sensing capabilities to be achieved with current and future satellite instruments.

Zhou, Daniel K.↗
NASA NTRS2007

Global Aerosol Optical Models and Lookup Tables for the New MODIS Aerosol Retrieval over Land

Since 2000, MODIS has been deriving aerosol properties over land from MODIS observed spectral reflectance, by matching the observed reflectance with that simulated for selected aerosol optical models, aerosol loadings, wavelengths and geometrical conditions (that are contained in a lookup table or 'LUT'). Validation exercises have showed that MODIS tends to under-predict aerosol optical depth (tau) in cases of large tau (tau greater than 1.0), signaling errors in the assumed aerosol optical properties. Using the climatology of almucantur retrievals from the hundreds of global AERONET sunphotometer sites, we found that three spherical-derived models (describing fine-sized dominated aerosol), and one spheroid-derived model (describing coarse-sized dominated aerosol, presumably dust) generally described the range of observed global aerosol properties. The fine dominated models were separated mainly by their single scattering albedo (omega(sub 0)), ranging from non-absorbing aerosol (omega(sub 0) approx. 0.95) in developed urban/industrial regions, to neutrally absorbing aerosol (omega(sub 0) approx.90) in forest fire burning and developing industrial regions, to absorbing aerosol (omega(sub 0) approx. 0.85) in regions of savanna/grassland burning. We determined the dominant model type in each region and season, to create a 1 deg. x 1 deg. grid of assumed aerosol type. We used vector radiative transfer code to create a new LUT, simulating the four aerosol models, in four MODIS channels. Independent AERONET observations of spectral tau agree with the new models, indicating that the new models are suitable for use by the MODIS aerosol retrieval.

Levy, Robert C.↗
NASA NTRS2007

Utility of AIRS Retrievals for Climate Studies

Satellites provide an ideal platform to study the Earth-atmosphere system on practically all spatial and temporal scales. Thus, one may expect that their rapidly growing datasets could provide crucial insights not only for short-term weather processes/predictions but into ongoing and future climate change processes as well. Though Earth-observing satellites have been around for decades, extracting climatically reliable information from their widely varying datasets faces rather formidable challenges. AIRS/AMSU is a state of the art infrared/microwave sounding system that was launched on the EOS Aqua platform on May 4, 2002, and has been providing operational quality measurements since September 2002. In addition to temperature and atmospheric constituent profiles, outgoing longwave radiation and basic cloud parameters are also derived from the AIRS/AMSU observations. However, so far the AIRS products have not been rigorously evaluated and/or validated on a large scale. Here we present preliminary assessments of monthly and 8-day mean AIRS "Version 4.0" retrieved products (available to the public through the DAAC at NASA/GSFC) to assess their utility for climate studies. First we present "consistency checks" by evaluating the time series of means, and "anomalies" (relative to the first 4 full years' worth of AIRS "climate statistics") of several climatically important retrieved parameters. Finally, we also present preliminary results regarding interrelationships of some of these geophysical variables, to assess to what extent they are consistent with the known physics of climate variability/change. In particular, we find at least one observed relationship which contradicts current general circulation climate (GCM) model results: the global water vapor climate feedback which is expected to be strongly positive is deduced to be slightly negative (shades of the "Lindzen effect"?). Though the current AIRS climatology covers only -4.5 years, it will hopefully extend much further into the future.

Molnar, Guyla I.↗
NASA NTRS2006

Algorithm for NO2 Vertical Column Retrieval from the Ozone Monitoring Instrument

We describe the operational algorithm for the retrieval of stratospheric, tropospheric, and total column densities of nitrogen dioxide NO2 from earthshine radiances measured by the Ozone Monitoring Instrument (OMI), aboard the EOS-Aura satellite. The algorithm uses the DOAS method for the retrieval of slant column NO densities. Air mass factors (AMFs) calculated from a stratospheric NO2 profile are used to make initial estimates of the vertical column density. Using data collected over a 24-h period, a smooth estimate of the global stratospheric field is constructed. Where the initial vertical column densities exceed the estimated stratospheric field, we infer the presence of tropospheric NO2, and recalculate the vertical column density (VCD) using an AMF calculated from an assumed tropospheric NO2 profile. The parameters that control the operational algorithm were selected with the aid of a set of data assembled from stratospheric and tropospheric chemical transport models. We apply the optimized algorithm to OMI data and present global maps of NO2 VCDs for the first time.

Bucsela, Eric J.↗
NASA NTRS2007

Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

This study compares cirrus particle effective radius retrieved by a CALIPSO-like method with two similar methods using MODIS, MODI Airborne Simulator (MAS), and GOES imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-micrometer, 11.15-micrometer and 12.05-micrometer bands to infer the microphysical properties of cirrus clouds. The two other methods, sing passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the CERES team at LaRC (Langley Research Center) in support of CERES algorithms; the two algorithms will be referred to as MOD06- and LaRC-method, respectively. The three techniques are compared at two different latitudes: (i) the mid-latitude ice clouds study uses 18 days of observations at the Palaiseau ground-based site in France (SIRTA: Site Instrumental de Recherche par Teledetection Atmospherique) including a ground-based 532 nm lidar and the Moderate Resolution Imaging Spectrometer (MODIS) overpasses on the Terra Platform, (ii) the tropical ice clouds study uses 14 different flight legs of observations collected in Florida, during the intensive field experiment CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers-Florida Area Cirrus Experiment), including the airborne Cloud Physics Lidar (CPL) and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness, but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote-sensing method (CALIPSO-like) for the study of sub-visible ice clouds, in both mid-latitudes and tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds.

Chiriaco, M.↗
NASA NTRS2008

1D-VAR Retrieval Using Superchannels

Since modern ultra-spectral remote sensors have thousands of channels, it is difficult to include all of them in a 1D-var retrieval system. We will describe a physical inversion algorithm, which includes all available channels for the atmospheric temperature, moisture, cloud, and surface parameter retrievals. Both the forward model and the inversion algorithm compress the channel radiances into super channels. These super channels are obtained by projecting the radiance spectra onto a set of pre-calculated eigenvectors. The forward model provides both super channel properties and jacobian in EOF space directly. For ultra-spectral sensors such as Infrared Atmospheric Sounding Interferometer (IASI) and the NPOESS Airborne Sounder Testbed Interferometer (NAST), a compression ratio of more than 80 can be achieved, leading to a significant reduction in computations involved in an inversion process. Results will be shown applying the algorithm to real IASI and NAST data.

Liu, Xu↗
NASA NTRS2007

Ross Sea Polynyas: Response of Ice Concentration Retrievals to Large Areas of Thin Ice

For a 3-month period between May and July of 2005, we examine the response of the Advanced Microwave Scanning Radiometer (AMSR-E) Enhanced NASA Team 2 (NT2) and AMSR-E Bootstrap (ABA) ice concentration algorithms to large areas of thin ice of the Ross Sea polynyas. Coincident Envisat Synthetic Aperture Radar (SAR) coverage of the region during this period offers a detailed look at the development of the polynyas within several hundred kilometers of the ice front. The high-resolution imagery and derived ice motion fields show bands of polynya ice, covering up to approximately 105 km(sup 2) of the Ross Sea, that are associated with wind-forced advection. In this study, ice thickness from AMSR-E 36 GHz polarization information serves as the basis for examination of the response. The quality of the thickness of newly formed sea ice (<10 cm) from AMSR-E is first assessed with thickness estimates derived from ice surface temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The effect of large areas of thin ice in lowering the ice concentration estimates from both NT2/ABA approaches is clearly demonstrated. Results show relatively robust relationships between retrieved ice concentrations and thin ice thickness estimates that differ between the two algorithms. These relationships define the approximate spatial coincidence of ice concentration and thickness isopleths. Using the 83% (ABA) and 91% (NT2) isopleths as polynya boundaries, we show that the computed coverage compares well with that using the estimated 10-cm thickness contour. The thin ice response characterized here suggests that in regions with polynyas, the retrieval results could be used to provide useful geophysical information, namely thickness and coverage.

algorithms↗
NASA NTRS2008

Mesospheric H2O Concentrations Retrieved from SABER/TIMED Measurements

The SABER instrument on board the TIMED Satellite is a limb scanning infrared radiometer designed to measure temperature and minor constituent vertical profiles and energetics parameters in the mesosphere and lower thermosphere (MLT). The H2O concentrations are retrieved from 6.3 micron band radiances. The populations of H2O(v2) vibrational levels are in non-Local Thermodynamic Equilibrium (non-LTE) above approximately 55 km altitude and the interpretation of 6.3 micron radiance requires utilizing non-LTE H2O model that includes various energy exchange processes in the system of H2O vibrational levels coupled with O2, N2, and CO2 vibrational levels. We incorporated these processes including kinetics of O2/O3 photolysis products to our research non-LTE H2O model and applied it for the development and optimization of SABER operational model. The latter has been validated using simultaneous SCISAT1/ACE occultation measurements. This helped us to estimate CO2(020)-O2(X,v=I), O2(X,v=I)- H2O(010), and O2(X,v=1) O rates at mesopause temperatures that is critical for an adequate interpretation of non-LTE H2O radiances in the MLT. The first distributions of seasonal and meridional H2O concentrations retrieved from SABER 6.3 micron radiances applying an updated non-LTE H2O model are demonstrated and discussed.

Feofilov, A. G.↗
NASA NTRS2006

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

Retrieving surface longwave radiation from space has been a difficult task since the surface downwelling longwave radiation (SDLW) are integrations from radiation emitted by the entire atmosphere, while those emitted from the upper atmosphere are absorbed before reaching the surface. It is particularly problematic when thick clouds are present since thick clouds will virtually block all the longwave radiation from above, while satellites observe atmosphere emissions mostly from above the clouds. Zhou and Cess developed an algorithm for retrieving SDLW based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for areas that were covered with ice clouds. An improved version of the algorithm was developed that prevents the large errors in the SDLW at low water vapor amounts. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths measured from the Cloud and the Earth's Radiant Energy System (CERES) satellites to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for the Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing. It will be incorporated in the CERES project as one of the empirical surface radiation algorithms.

Zhou, Yaping↗
NASA NTRS2007

Impact of Uncertainty in the Drop Size Distribution on Oceanic Rainfall Retrievals From Passive Microwave Observations

The variability of the drop size distribution (DSD) is one of the factors that must be considered in understanding the uncertainties in the retrieval of oceanic precipitation from passive microwave observations. Here, we have used observations from the Precipitation Radar on the Tropical Rainfall Measuring Mission spacecraft to infer the relationship between the DSD and the rain rate and the variability in this relationship. The impact on passive microwave rain rate retrievals varies with the frequency and rain rate. The total uncertainty for a given pixel can be slightly larger than 10% at the low end (ca. 10 GHz) of frequencies commonly used for this purpose and smaller at higher frequencies (up to 37 GHz). Since the error is not totally random, averaging many pixels, as in a monthly rainfall total, should roughly halve this uncertainty. The uncertainty may be lower at rain rates less than about 30 mm/h, but the lack of sensitivity of the surface reference technique to low rain rates makes it impossible to tell from the present data set.

Wilheit, Thomas T.↗