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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Status of the Signals of Opportunity Airborne Demonstrator (SoOp-AD)

Root zone soil moisture (RZSM) is not directly measured by any current satellite instrument, despite its importance as a key link between surface hydrology and deeper processes. Presently, model assimilation of surface measurements or indirect estimates using other methods must be used to estimate this value. Signals of Opportunity (SoOp) methods, exploiting reflected P- and S-band communication satellite signals, have many of the benefits of both active and passive microwave remote sensing. Reutilization of active transmitters, with forward-scattering geometry, presents a strong reflected signal even at orbital altitudes. Microwave radiometry is advantageous as it measures emissivity, which is directly related to dielectric constant and sensitive to water content of soil. Synthetic aperture radar (SAR) is used in P-band (400 MHz) for soil moisture and biomass, but faces issues in obtaining permission to transmit due to spectrum regulations, particularly over North America and Europe. A primary advantage of SAR is excellent spatial resolution. Signals-of-opportunity (SoOp) reflectometry provides a good compromise between radiometry and SAR by providing decent sensitivity and special resolution for RZSM measurements without issues of spectrum access. Further, a SoOp instrument would not be limited to operating in only a few protected frequencies and is also expected to have less susceptibility to radio-frequency interference (RFI). Although advantageous if available, SoOp techniques do not require the ability to demodulate or decode the communication signals. The SoOp instrument is receive only and therefore requires much less electrical power than a SAR and is more similar to a radiometer in receiver architecture. These unique features of SoOp circumvent past obstacles to a spaceborne P-band remote sensing mission and have the potential to enable new RZSM measurements that are not possible with present technology. We will present the latest development status of a SoOp reflectometer airborne demonstrator (SoOp-AD) operating at 250 MHz to take advantage of existing communication satellite. The instrument is currently in laboratory integration and test.

Reflectometers↗
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.↗
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 (50m) 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.↗
NASA NTRS2016

Far-Infrared Room-Temperature Focal Plane Modules for Radiation Budget Instrument

This work presents focal plane modules for a Radiation Budget Instrument, a passive remote-sensing instrument that follows the legacy of the Clouds and Earth’s Radiant Energy System (CERES) to measure short and longwave Earth’s radiation budget. The focal plane arrays are micromachined at JPL (Jet Propulsion Laboratory) and integrated into sub-assembly modules to be mounted on the optical telescope of the instrument.

Mariani, Giacomo↗
NASA NTRS2017

CERES S’COOL Project Update: The Evolution and Value of a Long-Running Education Project With a Foundation in NASA Earth Science Missions

In January 1997, the Students’ Cloud Observations On-Line (S’COOL; http://scool.larc.nasa.gov) Project began with NASA scientists visiting rural Gloucester, Virginia to observe clouds with middle school students. In the 19 years since, this educational outreach component of NASA’s Clouds and the Earth’s Radiant Energy System (CERES) mission has collected ~141,000 observations from every continent and ocean basin around the world. Thousands of students and teachers have directly engaged in S’COOL. Beginning in 2008 we invited citizen scientists to participate as well. Over time S’COOL has added more components that engage participants directly with science data analysis, continuing direct ties to CERES research. Whenever possible, the S’COOL team extracts corresponding subsets of CERES data, which are sent to the participant to analyze. Observations can now be matched to images and cloud retrievals from MODIS and measurements from CALIPSO. To date, more than half of S'COOL observation reports correspond to one (or more) CERES overpasses. Comparisons with CERES geostationary satellite cloud retrievals were recently added, making cloud observations at almost any time of day over non-polar regions useful for validation. A thorough analysis of co-located S’COOL and satellite data was conducted during summer 2015. Results show that the S’COOL community provides high quality observations offering useful insights on the strengths and shortcomings of passive cloud remote sensing from space. This reconfirmed the utility of S’COOL observations to the scientific community and provides observers with deeper insight into the challenges associated with validation of space-based cloud property retrievals.

Lin H Chambers↗
NASA NTRS2019

Far-infrared room-temperature focal plane modules for polar radiant energy in the Far InfraRed experiment

This work presents focal plane modules for Polar Radiant Energy in the Far InfraRed Experiment, a passive remote-sensing instrument aimed to determine errors in the estimated outgoing longwave radiation in the Earth’s polar regions to reduce uncertainties in surface emissivity, mass balance, and ice flux. The focal plane arrays are micromachined at JPL and integrated into sub-assembly modules to be mounted on the optical telescope of the instrument.

White, Mary↗
NASA NTRS2021

Revisiting the Global Patterns of Seasonal Cycle in Sea Surface Salinity

Argo profiling floats and L-band passive microwave remote sensing have significantly improved the global sampling of sea surface salinity (SSS) in the past 15 years, allowing the study of the range of SSS seasonal variability using concurrent satellite and in situ platforms. Here, harmonic analysis was applied to four 0.25° satellite products and two 1° in situ products between 2016 and 2018 to determine seasonal harmonic patterns. The 0.25° World Ocean Atlas (WOA) version 2018 was referenced to help assess the harmonic patterns from a long-term perspective based on the 3-year period. The results show that annual harmonic is the most characteristic signal of the seasonal cycle, and semiannual harmonic is important in regions influenced by monsoon and major rivers. The percentage of the observed variance that can be explained by harmonic modes varies with products, with values ranging between 50% and 72% for annual harmonic and between 15% and 19% for semiannual harmonic. The large spread in the explained variance by the annual harmonic reflects the large disparity in nonseasonal variance (or noise) in the different products. Satellite products are capable of capturing sharp SSS features on meso- and frontal scales and the patterns agree well with the WOA 2018. These products are, however, subject to the impacts of radiometric noises and are algorithm dependent. The coarser-resolution in situ products may underrepresent the full range of high-frequency small scale SSS variability when data record is short, which may have enlarged the explained SSS variance by the annual harmonic.

L-band↗
NASA NTRS2023

Radiative interaction of atmosphere and surface: write up with elements of code

In passive satellite remote sensing of the Earth, separation of the path radiance (atmosphere-only contribution) from the surface reflection remains a “significant challenge”. Recent literature names it among the gaps in radiative transfer (RT) topics that “require continued research in the near future”. The challenge comes from multiple reflections (bouncing) between the atmosphere and surface – radiative interaction. In this paper we use a known RT technique, the matrix-operator method (MOM), and a new modification of the monochromatic vector RT (vRT) code IPOL (Intensity and POLarization) to simulate the interaction of a plane-parallel atmosphere and a few widely used surface reflection models. Following the idea of the Green’s function method, IPOL no longer takes the surface model parameters on input. Instead, it provides the path radiance, and the atmospheric reflection and transmission matrices as output. Despite many RT codes use the MOM formalism, this output does not seem common. The surface reflection matrix is computed externally. Therefore, this paper extends the Green’s function atmospheric correction technique to the case of polarized light. Aiming clarity rather than performance, we explain in Python the structure of the surface matrices for the isotropic (Lambertian), directional unpolarized, and polarized ocean reflection models. We then combine these surface matrices and the precomputed IPOL output to get numerically accurate signal at the top of atmosphere (TOA) and test it vs. published benchmarks. Then, for each benchmark scenario we show how to get the surface from the TOA signal, i.e. perform the RT-based atmospheric correction.

radiative transfer↗
NASA NTRS2023

A SmallSat Concept to Resolve Diurnal and Vertical Variations of Aerosols, Clouds, and Boundary Layer Height

A SmallSat mission concept is formulated here to carry out Time-varying Optical Measurements of Clouds and Aerosol Transport (TOMCAT) from space while embracing low-cost opportunities enabled by the revolution in Earth science observation technologies. TOMCAT’s “around-the-clock” measurements will provide needed insights and strong synergy with existing Earth observation satellites to 1) statistically resolve diurnal and vertical variation of cirrus cloud properties (key to Earth’s radiation budget), 2) determine the impacts of regional and seasonal planetary boundary layer (PBL) diurnal variation on surface air quality and low-level cloud distributions, and 3) characterize smoke and dust emission processes impacting their long-range transport on the subseasonal to seasonal time scales. Clouds, aerosol particles, and the PBL play critical roles in Earth’s climate system at multiple spatiotemporal scales. Yet their vertical variations as a function of local time are poorly measured from space. Active sensors for profiling the atmosphere typically utilize sun-synchronous low-Earth orbits (LEO) with rather limited temporal and spatial coverage, inhibiting the characterization of spatiotemporal variability. Pairing compact active lidar and passive multiangle remote sensing technologies from an inclined LEO platform enables measurements of the diurnal and vertical variability of aerosols, clouds, and aerosol-mixing-layer (or PBL) height in tropical-to-midlatitude regions where most of the world’s population resides. TOMCAT is conceived to bring potential societal benefits by delivering its data products in near–real time and offering on-demand hazard-monitoring capabilities to profile fire injection of smoke particles, the frontal lofting of dust particles, and the eruptive rise of volcanic plumes.

John E. Yorks↗
NASA NTRS2017

NASA's SnowEx Campaign: Observing Seasonal Snow in a Forested Environment

SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earth's terrestrial snow-covered regions? Year 1(2016-17) focused on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site was Grand Mesa and the secondary site was the Senator Beck Basin, both in western Colorado, USA. Nine sensors on five aircraft made observations using a broad range of sensing techniques - active and passive microwave, and active and passive optical/infrared - to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also included an extensive range of ground truth measurements - in-situ manual samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some preliminary results will be presented.

cryosphere↗
DOE OSTI2024

Frequency‐Locked Wireless Multifunctional Surface Acoustic Wave Sensors

Abstract Surface acoustic waves (SAWs) have shown great potential for developing sensors for structural health monitoring (SHM) and lab‐on‐a‐chip (LOC) applications. Existing SAW sensors mainly rely on measuring the frequency shifts of high‐frequency (e.g., >0.1 GHz) resonance peaks. This study presents frequency‐locked wireless multifunctional SAW sensors that enable multiple wireless sensing functions, including strain sensing, temperature measurement, water presence detection, and vibration sensing. These sensors leverage SAW resonators on piezoelectric chips, inductive coupling‐based wireless power transmission, and, particularly, a frequency‐locked wireless sensing mechanism that works at low frequencies (e.g., <0.1 GHz). This mechanism locks the input frequency on the slope of a sensor's reflection spectrum and monitors the reflection signal's amplitude change induced by the changes of sensing parameters. The proof‐of‐concept experiments show that these wireless sensors can operate in a low‐power active mode for on‐demand wireless strain measurement, temperature sensing, and water presence detection. Moreover, these sensors can operate in a power‐free passive mode for vibration sensing, with results that agree well with laser vibrometer measurements. It is anticipated that the designs and mechanisms of the frequency‐locked wireless SAW sensors will inspire researchers to develop future wireless multifunctional sensors for SHM and LOC applications.

Bo, Luyu↗
NASA NTRS2017

Overview of SnowEx Year 1 Activities

SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earths terrestrial snow-covered regions? Year 1 (2016-17) focused on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site was Grand Mesa and the secondary site was the Senator Beck Basin, both in western, Colorado, USA. Nine sensors on five aircraft made observations using a broad range of sensing techniques, active and passive microwave, and active and passive optical infrared to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also included an extensive range of ground truth measurements in-situ manual samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some preliminary results will be presented.

snow↗
NASA NTRS1976

Remote sensing of soil moisture by a 21-cm passive radiometer

Microwave sensors on Skylab collected data as part of the Earth Resources Experiment Package. An investigation was designed to obtain field observations of soil moisture content for comparison with data from Skylab. The 21-cm radiometer has been shown to be highly responsive to the moisture content of the upper 2.5-cm layer of soil. A composite relationship between the radiometric temperature and soil moisture content has been determined from five data sets obtained over Kansas and Texas. This relationship, having a correlation index of -0.96, has been used as a basis for calculating the soil moisture content of large areas across the United States.

Eagleman, J. R.↗
NASA NTRS2000

BOREAS HYD-4 Areal Snow Course Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-4 team focused on collecting data during the 1994 winter focused field campaign (FFCW) to improve the understanding of winter processes within the boreal forest. Knowledge of snow cover and its variability in the boreal forest is fundamental if BOREAS is to achieve its goals of understanding the processes and states involved in the exchange of energy and water. The development and validation of remote sensing algorithms will provide the means to extend the knowledge of these processes and states from the local to the regional scale. A specific thrust of the hydrology research is the development and validation of snow cover algorithms from airborne passive microwave measurements. Airborne remote sensing data (gamma, passive microwave) were acquired along a series of flight lines established in the vicinity of the BOREAS study areas. Ground snow surveys were conducted along selected sections of these aircraft flight lines. These calibration segments were typically 10-20 km in length, and ground data were collected at one to two kilometer intervals. The data are provided in tabular ASCII files. The HYD-04 areal snow course data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗
NASA NTRS1983

Passive Magnetic Bearing

Magnetic bearing for limited rotation devices requires no feedback control system to sense and correct shaft position. Passive Magnetic Torsion Bearing requires no power supply and has no rubbing parts. Torsion wire restrains against axial instability. Magnetic flux geometry chosen to assure lateral stability with radial restoring force that maintains alignment.

Studer, P. A.↗
NASA NTRS1992

SAYANI'91 - A joint United States/Commonwealth of Independent States field campaign to investigate forest decline damage in the Krasnoyarsk region of southcentral Siberia

The field experiment described took place in the Sayani Mountains of Siberia. The purpose of the joint field campaign was to observe and exchange methodologies with Russian scientists with regard to the development of remote sensing techniques for the early detection and assessment of forest decline damage believed to be associated with atmospheric deposition and/or insect and disease infestations. Several types of passive and active remote sensing measurements were made in conjunction with biophysical measurements on vegetative samples collected from four study sites representing a strong elevational gradient. Relatively cloud-free SPOT data were also acquired over the study area. Moderate canopy damage was recorded at the mid-elevation site (3400 ft/1037 m). The lowest levels of damage were recorded at the lowest elevation site (2300 ft/701 m.) At all sites, east versus west flagging of the canopy was noted (i.e., full canopy on the west-facing side of the canopy, significantly less foliage on the east-facing side).

Williams, D. L.↗