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At least 1,117 records · Page 62

Spectral Radiative Properties of Polydispersed SiO 2 Particle Beds

The focus of this work is on the measurement and analysis of the radiative properties of polycrystalline SiO 2 particle beds with various layer thicknesses. The particles are polydispersed with average diameters of 222, 150, and 40 μm . The spectral, directional–hemispherical reflectance and transmittance of the particle bed are measured at wavelengths from 0.4 to 1.8 μm using a monochromator, and the reflectance measurement is extended to 15 μm using a Fourier-transform infrared spectrometer. Particles are closely packed between two transparent windows for measuring the radiative properties. In the visible and near-infrared region up to 1.8 μm, the inverse adding–doubling method yields the effective absorption and scattering coefficients. The results suggest that short wavelength absorption needs to be included in modeling the behavior of particle beds due to multiple scattering. A discrete-scale Monte Carlo ray-tracing method is developed to model the radiative properties by assuming monodispersed spherical particles, and the simulated results compare well with measurements. The effective absorption and scattering coefficients of the particle beds obtained from the independent scattering theory are compared to those from the inverse method. As a result, the impact of dependent scattering on the packed beds is observed for smaller-sized particles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-resolution Spectra of Earth-like Planets Orbiting Red Giant Host Stars

In the near future we will have ground- and space-based telescopes that are designed to observe and characterize Earth-like planets. While attention is focused on exoplanets orbiting main-sequence stars, more than 150 exoplanets have already been detected orbiting red giants, opening the intriguing question of what rocky worlds orbiting in the habitable zone (HZ) of red giants would be like and how to characterize them. We present a high-resolution spectral database of reflection and emission spectra for nominal Earth-like planets orbiting in the red giant HZ from the visible to infrared (0.4–20 μm) for planets orbiting at the Earth-equivalent distance. We also show the change of such planetary spectra through the evolution of their red giant hosts. While the luminosity of the host increases the contrast ratio between star and planet, the increased orbital distance of the HZ for red giant hosts relaxes the light suppression requirements close to the star, which could make such planets interesting targets to characterize and search for signs of life, if new coronagraph designs with higher suppression at larger orbital separations could be developed. We assess the feasibility of characterizing atmospheric features including biosignatures for such planets with the proposed mission concept Large UV/Optical/IR Surveyor (LUVOIR).

79 ASTRONOMY AND ASTROPHYSICS↗

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗

Landsat near-infrared (NIR) band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon

Forest disturbance and regrowth are key processes in forest dynamics, but detailed information on these processes is difficult to obtain in remote forests such as the Amazon. We used chronosequences of Landsat satellite imagery (Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus) to determine the sensitivity of surface reflectance from all spectral bands to windthrow, clear-cut, and clear-cut and burned (cut + burn) and their successional pathways of forest regrowth in the Central Amazon. We also assessed whether the forest demography model Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, accurately represents the changes for windthrow and clear-cut. The results show that all spectral bands from the Landsat satellites were sensitive to the disturbances but after 3 to 6 years only the near-infrared (NIR) band had significant changes associated with the successional pathways of forest regrowth for all the disturbances considered. In general, the NIR values decreased immediately after disturbance, increased to maximum values with the establishment of pioneers and early successional tree species, and then decreased slowly and almost linearly to pre-disturbance conditions with the dynamics of forest succession. Statistical methods predict that NIR values will return to pre-disturbance values in about 39, 36, and 56 years for windthrow, clear-cut, and cut + burn disturbances, respectively. The NIR band captured the observed, and different, successional pathways of forest regrowth after windthrow, clear-cut, and cut + burn. Consistent with inferences from the NIR observations, ELM-FATES predicted higher peaks of biomass and stem density after clear-cuts than after windthrows. ELM-FATES also predicted recovery of forest structure and canopy coverage back to pre-disturbance conditions in 38 years after windthrows and 41 years after clear-cut. The similarity of ELM-FATES predictions of regrowth patterns after windthrow and clear-cut to those of the NIR results suggests the NIR band can be used to benchmark forest regrowth in ecosystem models. Our results show the potential of Landsat imagery data for mapping forest regrowth from different types of disturbances, benchmarking, and the improvement of forest regrowth models.

54 ENVIRONMENTAL SCIENCES↗

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗

High-efficiency graded band-gap Al/x/Ga/1-x/As-GaAs solar cell

A detailed theoretical analysis of an n-on-p graded band-gap Al(x)Ga(1-x)As-GaAs solar cell yields a maximum air mass zero power conversion efficiency of 17% compared to 9% for a similar GaAs cell. The analysis includes surface and bulk minority carrier recombination, junction recombination current, spectrally varying surface reflection, and series resistance loss. The maximum efficiency is determined for a surface recombination velocity of 10,000 cm/sec and hole and electron diffusion lengths of 2.1 and 7.6 microns, respectively. The improved efficiency is primarily due to a built-in electric field, caused by the band-gap gradation, accelerating photogenerated holes toward the p-n junction. This field reduces the surface and bulk recombination of the holes, and thereby enhances their collection.

Hutchby, J. A.↗

Development of Surfaces Optically Suitable for Flat Solar Panels

Three areas of research in the development of flat solar panels are described. (1) A reflectometer which can separately evaluate the spectral and diffuse reflectivities of surfaces was developed. The reflectometer has a phase locked detection system. (2) A coating composed of strongly bound copper oxide that is formed by an etching process performed on an aluminum alloy with high copper content was also developed. Because of this one step fabrication process, fabrication costs are expected to be small. (3) A literature search was conducted and conclusions on the required optical properties of flat plate solar collectors are presented.

Desmet, D.↗

Development of Surfaces Optically Suitable for Flat Solar Panels

A reflectometer which can separately evaluate the spectral and diffuse reflectivities of surfaces is described. A phase locked detection system for the reflectometer is also described. A selective coating on aluminum potentially useful for flat plate solar collector applications is presented. The coating is composed of strongly bound copper oxide (divalent) and is formed by an etching process performed on an aluminum alloy with high copper content. Fabrication costs are expected to be small due to the one stop fabrication process. A number of conclusions gathered from the literature as to the required optical properties of flat plate solar collectors are discussed.

Source record↗

Methods of editing cloud and atmospheric layer affected pixels from satellite data

Practical methods of computer screening cloud-contaminated pixels from data of various satellite systems are proposed. Examples are given of the location of clouds and representative landscape features in HCMM spectral space of reflectance (VIS) vs emission (IR). Methods of screening out cloud affected HCMM are discussed. The character of subvisible absorbing-emitting atmospheric layers (subvisible cirrus or SCi) in HCMM data is considered and radiosonde soundings are examined in relation to the presence of SCi. The statistical characteristics of multispectral meteorological satellite data in clear and SCi affected areas are discussed. Examples in TIROS-N and NOAA-7 data from several states and Mexico are presented. The VIS-IR cluster screening method for removing clouds is applied to a 262, 144 pixel HCMM scene from south Texas and northeast Mexico. The SCi that remain after cluster screening are sited out by applying a statistically determined IR limit.

Nixon, P. R.↗

Specular reflectance of optical-black coatings in the far infrared

Far-infrared specular reflectance spectra of seven optically black coatings near normal incidence are presented. Seven photometric spectra were obtained using eleven bandpass transmission filters in the wavelength range between 12 and 500 microns, and three interferometric spectra were obtained for corroboration. Data on the construction, thickness, and rms surface roughness of the coatings are also presented. The chemical composition of three coatings can be distinguished from that of the others by a strong absorption feature between 20 and 40 microns, which can be largely attributed to amorphous silicate material. At 100 microns, the most and least reflective coatings differ by nearly 3 orders of magnitude. Inverse relationships observed between the spectra and the roughness and thickness of the coatings led to development of a reflecting-layer model for the measured reflectance. The model successfully describes the spectra at wavelengths outside the silicate absorption, and optical constants are deduced from a nonlinear least squares fit to the data. Parametric errors are estimated by chi-square analysis, and sensitivity tests are performed to determine which parameters control reflectance in different spectral regions.

Smith, S. M.↗

Venus topography - A harmonic analysis

A model of Venusian global topography has been obtained by fitting an eighteenth-degree harmonic series to Pioneer Venus orbiter radar altimeter data. The mean radius is (6051.45 + or - 0.04) km. The corresponding mean density is (5244.8 + or 0.5) kg/cu m. The center of figure is displaced from the center of mass by (0.339 + or - 0.088) km towards (6.6 + or 10.1) deg N, (148. 8 + or - 7.7) deg. The figure of Venus is distinctly triaxial, but the orientation and magnitudes of the principal topographic axes correlate rather poorly with the gravitational principal axes. However, the higher-degree harmonics of topography and gravity are significantly correlated. The topographic variance spectrum of Venus is very similar in form to those of the moon, Mars, and especially earth. It is suggested that this spectral similarity simply reflects a statistical balance between constructional and degradational geomorphic proceses. Venus and earth are particularly similar (and differ from the moon and Mars) in that the larger bodies both exhibit a significant low degree deficit (relative to the extrapolated trend of the higher harmonics).

Bills, B. G.↗

NIMBUS-7 CZCS. Coastal Zone Color Scanner Imagery for Selected Coastal Regions. North America - Europe. South America - Africa - Antarctica. Level 2 Photographic Product

The Nimbus-7 Coastal Zone Color Scanner (CZCS) is the first spacecraft instrument devoted to the measurement of ocean color. Although instruments on other satellites have sensed ocean color, their spectral bands, spatial resolution, and dynamic range were optimized for geographical or meteorological use. In the CZCS, every parameter is optimized for use over water to the exclusion of any other type of sensing. The signal-to-noise ratios in the spectral channels sensing reflected solar radiance are higher than those required in the past. These ratios need to be high because the ocean is such a poor reflecting surface that the majority of the signal seen by the reflected energy channels at spacecraft altitudes is backscattered solar radiation from the atmosphere rather than reflected solar energy from the ocean. The CZCS is a conventional multichannel scanning radiometer utilizing a rotating plane mirror at a 45 deg angle to the optic axis of a Cassegrain telescope. The mirror scans 360 deg; however, only 80 deg of data centered on the spacecraft nadir is collected for ocean color measurements. Spatial resolution at spacecraft nadir is 825x825 m with some degradation at the edges of the scan swath. The useful swath width from a spacecraft altitude of 955 km is 1600 km.

Source record↗

Vegetation reflectance features in AVIRIS data

Equations for converting Airborne Visible-IR Imaging Spectrometer (AVIRIS) digital numbers to percent reflectance were developed using a set of three calibration targets. When converted to reflectance the following spectral features of vegetation can be observed in AVIRIS data: details in the pigment absorption region, the red edge, the NIR plateau, leaf water absorptions on the NIR plateau, leaf water absorptions, and lignocellulose absorptions. These results indicate that AVIRIS data will be quite useful in geobotanical remote sensing.

Elvidge, Christopher D.↗

A validation tool for the Earth Radiation Budget Experiment nonscanning radiometers

Two data sets for one geographical scene are used as a comparative validation tool to verify the quality of radiometer measurements taken for NASA's Earth Radiation Budget Experiment (ERBE). The measurements are taken from four independent nonscanning radiometers installed on the Earth Radiation Budget Satellite and two NOAA spacecraft. Two radiometers measure radiation in the 0.2-50-micron range, and two measure solar reflected energy in spectral band ranging from 0.2 to 5 microns. Calculated top-of-atmosphere flux-value measurements for day and night demonstrate significant correlation as well as consistency and stability over a three-year period. It is concluded that intercomparisons of intersections between the satellites are necessary over varied geographical scenes to utilize the subject method in validating the measurements of the ERBE nonscanning radiometer.

Bolden, William C.↗

Infrared (2.08-14 micron) spectra of powered stony meteorites

Infrared biconical reflectance spectra of 60 powdered meteorite samples, representing 50 different stony meteorites, were measured as analogues of asteroidal regolith. Representative samples were measured in directional hemispherical reflectance to assure that Kirchhoff's Law can be used to predict relative emissivity from the reflectance spectra. These spectral data confirm that the O-H fundamental absorption band near 2.9 microns is an extremely sensitive indicator of incipient alteration, which often has taken place in powdered meteorite samples exposed only to water vapor in the air. Such non-carbonaceous samples typically contain less than 1 percent water by weight. Likewise, the C-H fundamental absorption bands near 3.4 and 3.5 microns are equally sensitive indicators of contamination with volatile hydrocarbons, which can also be absorbed from the air. The heavy, macromolecular hydrocarbons native to chondrites do not display such heavy bands, making detection of these bands in remote sensing of asteroids unlikely. Despite the spectral artifacts introduced by alteration and hydrocarbon contamination, powdered stony meteorites display a wide variety of real spectral features that can be used for their identification, including residual reststrahlen bands, absorption bands, and the Christiansen feature. Researchers found that the wavelengths of the peaks or troughs of each of these spectral features can be used independently to infer meteorite composition, but the best results are obtained when the entire spectral curve is used, or at least the portion of it encompassed by the 8 to 14 micron atmospheric window, in a digital search library.

Salisbury, J. W.↗

Next generation optical instruments and space experiments based on the LDEF thermal control surfaces experiment (S0069)

The Thermal Control Surfaces Experiment (TCSE) on the Long Duration Exposure Facility (LDEF) was a very effective experiment to study the effects of the space environment on thermal control surfaces. Three current programs have benefitted from the TCSE experiment and are the: Optical Properties Monitor (OPM); Laboratory Portable Spectroreflectometer (LPSR); and Space Portable Spectroreflectometer. The OPM expands the TCSE optical measurement and environmental monitoring capability. The LPSR is a hand held instrument developed to measure the spectral total hemispherical reflectance of small and larger surfaces in the field. The SPSR is a space application of the LPSR and TCSE technologies with the same measurement capabilities. The SPSR will be able to characterize the external surfaces of operational spacecraft such as Space Station Freedom.

Wilkes, Donald R.↗