Measurements of the duration of constant reflected-shock temperature in a reflected shock tunnel
Carbon dioxide IR radiation measurements of duration of constant reflected shock temperature in overtailored shock tunnel
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Carbon dioxide IR radiation measurements of duration of constant reflected shock temperature in overtailored shock tunnel
An improved version of the Pionner-Venus orbital data was used for a statistical analysis of global radar roughness and (alpha(0)) (rho) reflectivity. Classification maps of the venusian surface are produced in a supervised manner on the basis of statistical and empirical studies of the individual data sets. The primary objective is to assess the degree of homogeneity of surface radar properties within topographic provinces in order to map possible geologic boundaries. Maps were produced by correlating two data sets at a time. Classification of specific regions, such as Ishtar, has demonstrated that distinct geological units can be identified.
This research demonstrates the use of spectral models and spectral measurements to derive surface snow grain size and liquid water fraction.
The experiments evaluated in this report were conducted at the Health Physics Research Reactor (HPRR), also known as the Fast Burst Reactor. The reactor was designed and built at Oak Ridge National Laboratory (ORNL) in 1961. In this evaluation, a total of 12 experiments were evaluated (6 shield configurations and two responses). Six of them are considered acceptable as benchmark experiments and are thoroughly described: the measurands are bare, steel-shielded and Lucite-shielded neutron fluences and neutron KERMA responses to steady-state operations of the HPRR. It is important to mention that there is a general lack of information in the experimental methodology and neutron spectrum unfolding, and in some cases, unexpected and unexplained discrepancies between calculation and experiment. The HPRR’s unique characteristics were that it is a fast reactor, the use of a Lucite shield as the shielding material, and the use of the neutron fluence as the main benchmark measurand. There are no known, significant correlations between benchmarks in this evaluation and benchmarks in other evaluations.
A study was performed to evaluate the geometrical implication of a Multispectral Resource Sampler; a pointable sensor. Several vegetative targets representative of natural and agricultural canopies were considered in two wavelength bands. All combinations of Sun and view angles between 5 and 85 degrees zenith for a range of azimuths were simulated to examine geometrical dependance arising from seasonal as well as latitudinal variation. The effects of three different atmospheres corresponding to clear, medium and heavy haze conditions are included. An extensive model data base was generated to provide investigators with means for possible further study of atmospheric correction procedures and sensor design questions.
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MISR is scheduled for launch in 1998 on the EOS AM1 platform. The algorithms needed to analyze data from this instrument are currently being tested, using both simulated data and data currently available from the airborne ASAS multi-angle instrument...Results of the retrieval algorithms are presented using simulated MISR data.
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An apparatus for mid-infrared reflectance imaging has been developed as means of inspecting for subsurface damage in thermal-barrier coatings (TBCs). The apparatus is designed, more specifically, for imaging the progression of buried delamination cracks in plasma-sprayed yttria-stabilized zirconia coatings on turbine-engine components. Progression of TBC delamination occurs by the formation of buried cracks that grow and then link together to produce eventual TBC spallation. The mid-infrared reflectance imaging system described here makes it possible to see delamination progression that is invisible to the unaided eye, and therefore give sufficiently advanced warning before delamination progression adversely affects engine performance and safety. The apparatus (see figure) includes a commercial mid-infrared camera that contains a liquid-nitrogen-cooled focal plane indium antimonide photodetector array, and imaging is restricted by a narrow bandpass centered at wavelength of 4 microns. This narrow wavelength range centered at 4 microns was chosen because (1) it enables avoidance of interfering absorptions by atmospheric OH and CO2 at 3 and 4.25 microns, respectively; and (2) the coating material exhibits maximum transparency in this wavelength range. Delamination contrast is produced in the midinfrared reflectance images because the introduction of cracks into the TBC creates an internal TBC/air-gap interface with a high diffuse reflectivity of 0.81, resulting in substantially higher reflectance of mid-infrared radiation in regions that contain buried delamination cracks. The camera is positioned a short distance (.12 cm) from the specimen. The mid-infrared illumination is generated by a 50-watt silicon carbide source positioned to the side of the mid-infrared camera, and the illumination is collimated and reflected onto the specimen by a 6.35-cm-diameter off-axis paraboloidal mirror. Because the collected images are of a steady-state reflected intensity (in contrast to the transient thermal response observed in infrared thermography), collection times can be lengthened to whatever extent needed to achieve desired signal-to-noise ratios. Each image is digitized, and the resulting data are processed in several steps to obtain a true mid-infrared reflectance image. The raw image includes thermal radiation emitted by the specimen in addition to the desired reflected radiation. The thermal-radiation contribution is eliminated by subtracting the image obtained with the illumination off from the image obtained with the illumination on. A flat-field correction is then made to remove the effects of non-uniformities in the illumination level and pixel-to-pixel variations in sensitivity. This correction is performed by normalizing to an image of a standard object that has a known reflectance at a wavelength of 4 microns. After correction, each pixel value is proportional to the reflectance (at a wavelength of 4-microns) at the corresponding location on the specimen. Mid-infrared reflectance imaging of specimens that were thermally cyc led for different numbers of cycles was performed and demonstrated t hat mid-infrared reflectance imaging was able to monitor the gradual delamination progression that occurs with continued thermal cycling . Reproducible values were obtained for the reflectance associated w ith an attached and fully delaminated TBC, so that intermediate refle ctance values could be interpreted to successfully predict the numbe r of thermal cycles to failure.
The spectral variation of canopy reflectance is mostly governed by the absorption properties of the elements, hence the leaves, since their intrinsic scattering properties show very little spectral variation. The relationship between canopy reflectance and leaf reflectance measured at the red edge over sugar beet canopies was used to simulate canopy reflectance from leaf reflectance spectra measured over the whole spectral domain. The results show that the spectral analogies found allows accurate reconstruction of canopy reflectance spectra. Explicit assumptions about the very low spectral variation of leaf intrinsic scattering properties are thus indirectly justified. The sensitivity of canopy reflectance (rho(sub c)) to leaf optical properties can then be investigated from concurrent spectral variations of canopy (delta rho(sub c)/delta lambda) and leaf reflectance (delta rho(sub l)/delta lambda): (delta rho(sub c))/(delta rho(sub l)) = ((delta rho(sub c))/(delta lambda) ((delta rho( sub l))/(delta lambda))(sup -1)). This expression is strictly valid only when the optical properties of the soil background or the other vegetation elements such as bark are either spectrally flat or do not contribute significantly to canopy reflectance. Simulations using the SAIL and PROSPECT models demonstrate that the sensitivity of canopy reflectance to leaf reflectance is significant for large vegetation cover fractions in spectral domains where absorption is low. In these conditions, multiple, scattering enhances the leaf absorption features by a factor that can be greater than 2.0. To override the limitations of the SAIL model for the description of the canopy architecture, we tested the previous findings on experimental data. Concurrent canopy and leaf reflectance spectra were measured for a range of sugar beet canopies. The results show good agreement with the theoretical findings. Conclusions are drawn about the applicability of these findings, with particular attention to the potential detectability of leaf biochemical composition from canopy reflectance sensed from space.
Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types. Using a single common set of parameters across all sites, the calibrated model was able to accurately reproduce surface reflectance for sites with highly varied forest composition and structure. However, the calibrated model's predictions of leaf area index (LAI) were less robust, capturing only 46 % of the variability in the observations. Comparing the ED2 radiative transfer model with another two-stream soil–leaf–canopy radiative transfer model commonly used in remote sensing studies (PRO4SAIL) illustrated structural errors in the ED2 representation of direct radiation backscatter that resulted in systematic underestimation of reflectance. In addition, we also highlight that, to directly compare with a two-stream radiative transfer model like EDR, we had to perform an additional processing step to convert the directional reflectance estimates of AVIRIS to hemispherical reflectance (also known as “albedo”). In future work, we recommend that vegetation models add the capability to predict directional reflectance, to allow them to more directly assimilate a wide range of airborne and satellite reflectance products. We ultimately conclude that despite these challenges, using dynamic vegetation models to predict surface reflectance is a promising avenue for model calibration and validation using remote sensing data.
In remote sensing, the Photochemical Reflectance Index (PRI) provides insight into physiological processes occurring inside the leaves in a stand of plants. Developed by Gamon et al., (1990 and 1992), PRI evolved from laboratory measurements of the reflectance of individual leaves (Bilger et al.,1989). Yet in a remotely sensed image, a pixel measurement may include light from both reflecting and transmitting leaves. We conducted laboratory experiments comparing values of PRI based upon polarized reflectance and transmittance measurements of water and nutrient stressed leaves. We illuminated single detached leaves using a current controlled light source (Oriel model 66881) and measured the leaf weight using an analytical balance (Mettler model AE 260) and the light reflected and transmitted by the leaf during dry down using two Analytical Spectral Devices spectroradiometers. Polarizers on the incident and reflected light beams allowed us to divide the leaf reflectance into two parts: a polarized surface reflectance and a non-polarized 'leaf interior' reflectance. Our results underscore the importance when calculating PRI of removing the leaf surface reflection, which contains no information about physiological processes ongoing in the leaf interior. The results show that the leaf physiology information is in the leaf interior reflectance, not the leaf transmittance. Applied to a plant stand, these results suggest use of polarization measurements in sun-view directions that minimize the number of sunlit transmitting leaves in the sensor field of view.
We have revisited the problem of propagation of toroidal and linear Alfven waves formulated by Heinemann and Olbert (1980) to compare WKB and non-WKB waves and their effects on the solar wind. They considered two solar wind models and showed that reflection is important for Alfven waves with periods of the order of one day and longer, and that non-WKB Alfven waves are no more effective in accelerating the solar wind than WKB waves. There are several recently published papers which seem to indicate that Alfven waves with periods of the order of several minutes should be treated as non-WKB waves and that these non-WKB waves exert a stronger acceleration force than WKB waves. The purpose of this paper is to study the origin of these discrepancies by performing parametric studies of the behavior of the waves under a variety of different conditions. In addition, we want to investigate two problems that have not been addressed by Heinemann and Olbert, namely, calculate the efficiency of Alfven wave reflection by using the reflection coefficient and identify the region of strongest wave reflection in different wind models. To achieve these goals, we investigated the influence of temperature, electron density distribution, wind velocity and magnetic field strength on the waves. The obtained results clearly demonstrate that Alfven wave reflection is strongly model dependent and that the strongest reflection can be expected in models with the base temperatures higher than 10(exp 6) K and with the base densities lower than 7 x 10(exp 7) cm(exp -3). In these models as well as in the models with lower temperatures and higher densities, Alfven waves with periods as short as several minutes have negligible reflection so that they can be treated as WKB waves; however, for Alfven waves with periods of the order of one hour or longer reflection is significant, requiring a non-WKB treatment. We also show that non-WKB, linear Alfven waves are always less effective in accelerating the plasma than WKB Alfven waves. Finally, it is evident from our results that the region of strongest wave reflection is usually located at the base of the models, and hence that interpretation of wave reflection based solely on the reflection coefficient can be misleading.
We have revisited the problem of propagation of toroidal and linear Alfven waves formulated by Heinemann and Olbert (1980) to compare Wentzel-Kramers-Brillouin (WKB) and non-WKB waves and their effects on the solar wind. They considered two solar wind models and showed that reflection is important for Alfven waves with periods of the order of one day and longer and that non-WKB Alfven waves are no more effective in accelerating the solar wind than in WKB waves. There are several recently published papers that seem to indicate that Alfven waves with periods of the order of several minutes should be treated as non-WKB waves and that these non-WKB waves exert a stronger acceleration force than WKB waves. The purposse of this paper is to study the origin of these discrepancies by performing parametric studies of the behavior of the waves under a variety of different conditions. In addition, we want to investigate two problems that have not been addressed by Heinimann and Olbert, namely, calculate the efficieny of Alfven wave reflection by using the reflection coefficient and identfy the region of strongest wave reflection in different wind models. To achieve these goals, we investigate the influence of temperature, electron desity distribution, wind velocity, and magnetic field strength on te waves. The obtained results clearly demonstrate that Alfven wave reflection is strongly model dependent and that the strongest reflection can be expected in models with the base temperatures higher than 10(exp 6) K and with the base densities lower than 7 x 10(exp 7)/cu cm. In these models as well as in the models with lower temperatures and higher densities Alfven waves with periods as short as several minutes have negligible reflection so that they can be treated as WKB waves; however, for Alfven waves with periods of the order of one hour or longer reflection is significant, requiring a non-WKB treatment. We also show that non-WKB, linear Alfven waves are always less effective in accelerating the plasma than WKB Alfven waves. Finally, it is evident from our results that the region of strongest wave reflection is usually located at the base of the models and hence that interpretation of wave reflection based soley on the reflection coefficient can be misleading.
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.
An airborne pointable imaging multispectral linear array sensor has been developed for the multidirectional observation of surface reflectance anisotropy. The sensor design permits observations up to 45 deg off-nadir in three spectral bands (green, red, and near-infrared). Calibration permits the conversion of sensor data to radiance units with an absolute uncertainty of 6 percent. Observations of five field plots from seven view directions are discussed. Calibration and atmospheric corrections are used to derive hemispherical-directional reflectance factors. A three-term reflectance model is fit to the reflectance factors for each plot to represent the continuous distribution of reflectance factors with view direction. The reflectance model is integrated over all view directions to calculate bihemispherical reflectance factors. The calculated bihemispherical factors differed by 1 to 25 percent from values based on an assumption of isotropic reflectance depending on spectral band and field plot. These calculations demonstrate the technologic and scientific capabilities required for the remote characterization of surface reflectance anisotropy. Remote multidirectional observations are both feasible and needed to fully evaluate land reflectance characteristics.
The 380 nm radiance measurements of TOMS (Total Ozone Mapping Spectrometer) have been converted into a global data set of daily (1979 to 1992) Lambert equivalent reflectivities R of the Earth's surface and boundary layer (clouds, aerosols, surface haze, and snow/ice). Since UV surface reflectivity is between 2 and 8% for both land and water during all seasons of the year (except for ice and snow cover), reflectivities larger than the surface value indicates the presence of clouds, haze, or aerosols in the satellite field of view. Statistical analysis of 14 years of daily data show that most snow/ice-free regions of the Earth have their largest fraction of days each year when the reflectivity is low (R less than 10%). The 380 nm reflectivity data shows that the true surface reflectivity is 2 to 3% lower than the most frequently occurring reflectivity value for each TOMS scene. The most likely cause of this could be a combination of frequently occurring boundary-layer water or aerosol haze. For most regions, the observation of extremely clear conditions needed to estimate the surface reflectivity from space is a comparatively rare occurrence. Certain areas (e.g., Australia, southern Africa, portions of northern Africa) are cloud-free more than 80% of the year, which exposes these regions to larger amounts of UV radiation than at comparable latitudes in the Northern Hemisphere. Regions over rain-forests, jungle areas, Europe and Russia, the bands surrounding the Arctic and Antarctic regions, and many ocean areas have significant cloud cover (R greater than 15%) more than half of each year. In the low to middle latitudes, the areas with the heaviest cloud cover (highest reflectivity for most of the year) are the forest areas of northern South America, southern Central America, the jungle areas of equatorial Africa, and high mountain regions such as the Himalayas or the Andes. The TOMS reflectivity data show the presence of large nearly clear ocean areas and the effects of the major ocean currents on cloud production.