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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Polarimetric Radar Analysis of Ice Microphysical Processes in Melting Layers of Winter Storms Using S-Band Quasi-Vertical Profiles

Quasi-vertical profiles (QVPs) obtained from a database of U.S. WSR-88D data are used to document polarimetric characteristics of the melting layer (ML) in cold-season storms with high vertical resolution and accuracy. A polarimetric technique to define the top and bottom of the ML is first introduced. Using the QVPs, statistical relationships are developed to gain insight into the evolution of microphysical processes above, within, and below the ML, leading to a statistical polarimetric model of the ML that reveals characteristics that reflectivity data alone are not able to provide, particularly in regions of weak reflectivity factor at horizontal polarization Z H . QVP ML statistics are examined for two regimes in the ML data: Z H ≥ 20 dB Z and Z H < 20 dB Z . Regions of Z H ≥ 20 dB Z indicate locations of MLs collocated with enhanced differential reflectivity Z DR and reduced copolar correlation coefficient ρ hv , while for Z H < 20 dB Z a well-defined ML is difficult to discern using Z H alone. Evidence of large Z DR up to 4 dB, backscatter differential phase δ up to 8°, and low ρ hv down to 0.80 associated with lower Z H (from -10 to 20 dB Z ) in the ML is observed when pristine, nonaggregated ice falls through it. Positive correlation is documented between maximum specific differential phase K DP and maximum Z H in the ML; these are the first QVP observations of K DP in MLs documented at S band. Negative correlation occurs between minimum ρ hv in the ML and ML depth and between minimum ρ hv in the ML and the corresponding enhancement of Z H (Δ Z H = Z H max - Z H rain ).

Meteorology & Atmospheric Sciences↗
DOE OSTI2019

Investigation of Hydrometeor Distributions in Continental and Maritime Storm Systems: Application of Cloud-Resolving Simulations, a Polarimetric Scanning Radar Simulator and Polarimetric Radar Observations

Detailed observations from DOE ARM field campaigns were used to evaluate and improve microphysical and dynamic fields simulated by 3D Cloud Resolving Models (CRMs), employing both bulk and size-resolved bin microphysics. One of the main challenges in bridging the gap between observations and models is placing the analysis in a common framework. To address this, a polarimetric radar simulator was built, consisting of a forward operator to calculate model-consistent polarimetric radar fields, and an analysis package to calculate microphysical and dynamic fields from radar data in a self-consistent manner. The assumptions required for the transformation from model output to radar parameters were carefully considered and tested. It was found that although rain is fairly well captured by the forward model, ice characteristics are difficult to constrain. This polarimetric radar simulator, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), was then applied to WRF simulations and polarimetric C-band radar observations from Darwin, Australia and the SGP site in Oklahoma. These two locations contrast maritime and mid-latitude continental convection respectively. POLARRIS was used with NASA Unified WRF simulations of the same storms in order to compare the observed land and ocean contrasts in microphysics and dynamics. An improved model framework for dynamic downscaling of large-scale aerosol products was also developed and applied to the NASA Unified WRF (NU-WRF) cloud resolving model. This improved framework was used to explore the effects of thermodynamic and aerosol invigoration in deep land and ocean convection through a series of sensitivity studies by perturbating aerosol (CCN) and convective available potential energy (CAPE). It was found that increases in aerosol concentrations yielded increases in low-density graupel in the maritime case and high-density hail in the continental case through riming by increased supercooled water. This result implies that native differences in aerosol concentrations may enhance the inherent contrast in riming effects between deep convective systems in the maritime and continental conditions. Formal publications were generated describing this research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Debris Disk Results from the Gemini Planet Imager Exoplanet Survey's Polarimetric Imaging Campaign

We report the results of a ∼4 yr direct imaging survey of 104 stars to resolve and characterize circumstellar debris disks in scattered light as part of the Gemini Planet Imager (GPI) Exoplanet Survey. We targeted nearby (≲150 pc), young (≲500 Myr) stars with high infrared (IR) excesses (L {sub IR}/L {sub ⋆} > 10{sup −5}), including 38 with previously resolved disks. Observations were made using the GPI high-contrast integral field spectrograph in H-band (1.6 μm) coronagraphic polarimetry mode to measure both polarized and total intensities. We resolved 26 debris disks and 3 protoplanetary/transitional disks. Seven debris disks were resolved in scattered light for the first time, including newly presented HD 117214 and HD 156623, and we quantified basic morphologies of five of them using radiative transfer models. All of our detected debris disks except HD 156623 have dust-poor inner holes, and their scattered-light radii are generally larger than corresponding radii measured from resolved thermal emission and those inferred from spectral energy distributions. To assess sensitivity, we report contrasts and consider causes of nondetections. Detections were strongly correlated with high IR excess and high inclination, although polarimetry outperformed total intensity angular differential imaging for detecting low-inclination disks (≲70°). Based on postsurvey statistics, we improved upon our presurvey target prioritization metric predicting polarimetric disk detectability. We also examined scattered-light disks in the contexts of gas, far-IR, and millimeter detections. Comparing H-band and ALMA fluxes for two disks revealed tentative evidence for differing grain properties. Finally, we found no preference for debris disks to be detected in scattered light if wide-separation substellar companions were present.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Multiband Polarimetric Imaging of HR 4796A with the Gemini Planet Imager

HR4796A hosts a well-studied debris disk with a long history due to its high fractional luminosity and favorable inclination, which facilitate both unresolved and resolved observations. We present new J- and K {sub 1}-band images of the resolved debris disk HR4796A taken in the polarimetric mode of the Gemini Planet Imager (GPI). The polarized intensity features a strongly forward-scattered brightness distribution and is undetected at the far side of the disk. The total intensity is detected at all scattering angles and also exhibits a strong forward-scattering peak. We use a forward-modeled geometric disk in order to extract geometric parameters, polarized fraction, and total intensity scattering phase functions for these data as well as H-band data previously taken by GPI. We find the polarized phase function becomes increasingly more forward-scattering as wavelength increases. We fit Mie and distribution of hollow spheres (DHS) grain models to the extracted functions. We find that it is possible to generate a satisfactory model for the total intensity using a DHS model, but not with a Mie model. We find that no single grain population of DHS or Mie grains of arbitrary composition can simultaneously reproduce the polarized fraction and total intensity scattering phase functions, indicating the need for more sophisticated grain models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Toward Autonomous Field Inspection of CSP Collectors With a Polarimetric Imaging Drone

We developed a polarimetric imaging drone to perform field inspections of heliostats and carried out field tests at Sandia’s National Solar Thermal Test Facility (NSTTF). The preliminary results show that Degree of Linear Polarization (DOLP) and Angle of Polarization (AOP) images greatly enhanced the edge detection results compared with the conventional visible images, supporting fast and accurate detection of heliostat mirror edges and cracks. The system holds the promise to enable future automated detection of heliostats optical errors and mirror defects.

14 SOLAR ENERGY↗
DOE OSTI2016

Development and Validation of a Polarimetric-MCScene 3D Atmospheric Radiation Model

Polarimetric measurements can substantially enhance the ability of both spectrally resolved and single band imagery to detect the proliferation of weapons of mass destruction, providing data for locating and identifying facilities, materials, and processes of undeclared and proliferant nuclear weapons programs worldwide. Unfortunately, models do not exist that efficiently and accurately predict spectral polarized signatures for the materials of interest embedded in complex 3D environments. Having such a model would enable one to test hypotheses and optimize both the enhancement of scene contrast and the signal processing for spectral signature extraction. The Phase I set the groundwork for development of fully validated polarimetric spectral signature and scene simulation models. This has been accomplished 1. by (a) identifying and downloading state-of-the-art surface and atmospheric polarimetric data sources, (b) implementing tools for generating custom polarimetric data, and (c) identifying and requesting US Government funded field measurement data for use in validation; 2. by formulating an approach for upgrading the radiometric spectral signature model MODTRAN to generate polarimetric intensities through (a) ingestion of the polarimetric data, (b) polarimetric vectorization of existing MODTRAN modules, and (c) integration of a newly developed algorithm for computing polarimetric multiple scattering contributions; 3. by generating an initial polarimetric model that demonstrates calculation of polarimetric solar and lunar single scatter intensities arising from the interaction of incoming irradiances with molecules and aerosols; 4. by developing a design and implementation plan to (a) automate polarimetric scene construction and (b) efficiently sample polarimetric scattering and reflection events, for use in a to be developed polarimetric version of the existing first-principles synthetic scene simulation model, MCScene; and 5. by planning a validation field measurement program in collaboration with the Remote Sensing and Exploitation group at Sandia National Laboratories (SNL) in which data from their ongoing polarimetric field and laboratory measurement program will be shared and, to the extent allowed, tailored for model validation in exchange for model predictions under conditions and for geometries outside of their measurement domain.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1992

Unsupervised segmentation of polarimetric SAR data using the covariance matrix

A method for unsupervised segmentation of polarimetric synthetic aperture radar (SAR) data into classes of homogeneous microwave polarimetric backscatter characteristics is presented. Classes of polarimetric backscatter are selected on the basis of a multidimensional fuzzy clustering of the logarithm of the parameters composing the polarimetric covariance matrix. The clustering procedure uses both polarimetric amplitude and phase information, is adapted to the presence of image speckle, and does not require an arbitrary weighting of the different polarimetric channels; it also provides a partitioning of each data sample used for clustering into multiple clusters. Given the classes of polarimetric backscatter, the entire image is classified using a maximum a posteriori polarimetric classifier. Four-look polarimetric SAR complex data of lava flows and of sea ice acquired by the NASA/JPL airborne polarimetric radar (AIRSAR) are segmented using this technique. The results are discussed and compared with those obtained using supervised techniques.

Rignot, Eric J. M.↗
NASA NTRS1996

Performance of Polarimetric Processing Techniques using NAWC P-3 SAR Imagery

The use of synthetic aperture radar (SAR) polarimetric processing for enhancing the detection, classification, and/or identification of scene scattering features is described. This paper describes and compares the results obtained from applying the polarimetric techniques that have been developed and/or advanced by researchers at MIT Lincoln Laboratory, and basic polarimetric match filter (PMF) techniques that have been modified to treat distributed scatterers. The paper describes the individual polarimetric processing techniques and the formulation used fro their application to polarimetric imagery obtained from the NAWC P-3 SAR. In all cases, the polarimetric techniques have been applied to enhance the detection of distributed scatterers in clutter The emphasis arises from considering most complex scatterers of interest (either man made or natural) as distributed scatterers consisting of multiple scattering centers, and many modern polarimetric radar systems have the resolution performance to resolve the multiple scattering centers. Furthermore, the individual scattering centers of a distributed target can often exhibit different polarimetric scattering characteristics, and consequently do not respond favorably to polarimetric processing techniques derived for individual point scatterers. The treatment of distributed scatterers also includes concepts for tuning the polarimetric ensemble response of individual scattering centers.

Teti, J. G., Jr.↗
NASA NTRS2015

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

Radar↗
NASA NTRS2000

Polarimetric Ku-Band Scatterometer for High Accuracy, Large Swath Global Wind Vector Measurements

In the past, wind measurements from space using fan-beam antennas, such as Seasat Scatterometer (SASS-1), ERS-1 &2, and NASA scatterometer (NSCAT), required up to six large stick-like antennas and suffered a nadir gap of up to 400 km. In the near future, a spinning pencil-beam scatterometer system is to be used for the SeaWinds scatterometer on QuikSCAT (QSCAT) and on ADEOS-2 (SeaWinds). This scatterometer, though offering wind measurements in the nadir region, still suffers from degraded performance in the nadir and outer swath. The purpose of this paper is to present an advanced polarimetric spinning pencil-beam scatterometer system, which can significantly improve the wind performance across the entire swath. The polarimetric scatterometer simultaneously measures co-polarized backscatter and the polarimetric correlation of co- and cross-polarized radar returns from the ocean surface. The advantage over the conventional scatterometer system is that, while the co-polarization radar returns are even function of the wind direction, the polarimetric correlation is an odd function of wind direction due to the reflection symmetry of the wind roughened surface. Therefore, this polarimetric scatterometer system can provide additional, equivalent measurements at azimuth angle 45degree away from the corresponding co-polarization measurements. The combined co-polarization and correlation measurements enable good wind performance across the whole swath to be obtained. In this paper, we will first present the theoretical formulation of all of the key components required for designing a polarimetric scatterometer. Then, we show that good wind performance can be achieved by a slight improvement in the signal-to-noise ratio of the current QSCAT/SeaWinds design. We then present the predicated wind performance using computer simulation based on a model function for the co-polarized backscatter obtained from actual spaceborne scatterometer data and an estimated model function for the polarimetric correlation based on the asymmetry observed in backscatter data. Finally, we will show that, aside from ocean applications, this polarimetric scatterometer can also be used for ice and land applications.

Tsai, Wu-Yang↗
DOE OSTI2018

Monitoring Surface Phenomena Created by an Underground Chemical Explosion Using Fully Polarimetric VideoSAR

Sandia National Laboratories flew its Facility for Advanced RF and Algorithm Development X-Band (9.6-GHz center frequency), fully polarimetric synthetic aperture radar (PolSAR) in VideoSAR mode to collect complex-valued SAR imagery before, during, and after the sixth Source Physics Experiment's (SPE-6) underground explosion. The VideoSAR products generated from the data sets include "movies'' of single- and quad-polarization coherence maps, magnitude imagery, and polarimetric decompositions. Residual defocus, due to platform motion during data acquisition, was corrected with a digital elevation model-based autofocus algorithm. We generated and exploited the VideoSAR image products to characterize the surface movement effects caused by the underground explosion. Unlike seismic sensors, which measure local area seismic waves using sparse spacing and subterranean positioning, these VideoSAR products captured high-spatial resolution, 2-D, time-varying surface movement. The results from the fifth SPE (SPE-5) used single-polarimetric VideoSAR data. In this paper, we present single-polarimetric and fully polarimetric VideoSAR results while monitoring the SPE-6 underground chemical explosion. We show that fully polarimetric VideoSAR imaging provides a unique, coherent, time-varying measure of the surface expression of the SPE-6 underground chemical explosion. As a result, we include new surface characterization results from the measured PolSAR SPE-6 data via H/A/α polarimetric decomposition.

47 OTHER INSTRUMENTATION↗
NASA NTRS1991

Unsupervised segmentation of polarimetric SAR data using the covariance matrix

An unsupervised selection of polarimetric features useful for the segmentation and analysis of polarimetric synthetic aperture radar (SAR) data is presented. The technique is based on multidimensional clustering of the parameters composing the polarimetric covariance matrix of the data. Clustering is performed on the logarithm of these quantities. Once the polarimetric cluster centers have been determined, segmentation of the polarimetric data into regions is performed using a maximum likelihood polarimetric classifier. Segmentation maps are further improved using a Markov random field to describe the statistics of the regions and computing the maximum of the product of the local conditional densities. Examples with real polarimetric SAR imagery are given to illustrate the potential of this method.

Rignot, Eric↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES-Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗