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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 541 records · Page 30
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NASA NTRS2022

Intercalibration of the reflective solar bands of MODIS and MISR instruments on the Terra platform

As a part of NASA’s Earth Observing System (EOS), the Terra spacecraft was launched on December 18, 1999, with the goal of understanding the changes of the Earth, by examining the Earth’s hydrological, geophysical, and climatic processes. The MODIS and MISR instruments on the Terra platform, combined with their continuous operation, broad spectral coverage, and different spatial resolutions, have played an important role to achieve the goals of the EOS. Over two decades of successful operations, these multispectral imaging instruments have benefited a variety of scientific applications. Being on the same platform, the two sensors complement each other in terms of spatial coverage (and target viewing geometry) and facilitate synergistic applications using multispectral data. A consistent radiometric calibration between these sensors is a prerequisite for creating high quality science products from their observations. Both instruments underwent intensive prelaunch characterization and their on-orbit calibrations are monitored using their onboard calibrators. In this paper, we perform a calibration inter-comparison of the spectrally matching bands of the two instruments using vicarious techniques. These techniques include multiyear simultaneous views of the North African desert, North Atlantic Ocean, and Dome Concordia, therefore covering different reflectance regimes. Also included in this work are the near-simultaneous top-of-atmosphere (TOA) reflectance measurements from Railroad Valley, USA, as provided by the RadCalNet (converted to TOA), that are used as a calibration reference to compare the on-orbit observations between MODIS and MISR. Simultaneous overpasses from desert, ocean, Dome C, and RadCalNet over Railroad Valley reveal that the agreement between the four spectrally matching bands is within 3% for the time-period between 2014 and 2020. Also, observed are some long-term drifts in the TOA reflectance time-series from MISR for the red and NIR band that are expected to be corrected in a future calibration reprocess.

MODIS↗
NASA NTRS1999

The TRMM Precipitation Radar: Opportunities and Challenges

Although studies on the feasibility of spaceborne weather radar date back to the 1960's, it was only with the launch of the Tropical Rainfall Measuring Mission (TRMM) Satellite in November 1997 that the first weather radar was placed into low earth orbit. The long delay between the initial concept and implementation was caused not only by the demanding requirements of active sensors such as mass, power, and reliability, but because of scientific and technological challenges. For example, the demand for adequate spatial resolution arises from the need to resolve the horizontal structure of convective storm cells and to avoid surface contamination of the rain return at off-nadir angles. To achieve a horizontal resolution on the order of 4 km from low earth orbit with a modest antenna size of 2 m requires the use of a much higher frequency (Ku-band) than those typically used for ground-based weather radars (S- and C-band). Higher frequencies are subject to higher attenuation. As Hitschfeld and Bordan (1954) showed in their classic paper, attenuation correction with a single-wavelength radar is inherently unstable at high attenuations unless the drop size distribution and the radar constant are known precisely. Since these conditions are seldom met, much work over the last decade has been devoted to formulating and testing alternative methods of attenuation correction. The operational method used in the TRMM radar processing is discussed in section 3 of the paper.

Meneghini, R.↗
NASA NTRS2002

Calibration Plans for the Global Precipitation Measurement (GPM)

The Global Precipitation Measurement (GPM) is an international effort led by the National Aeronautics and Space Administration (NASA) of the U.S.A. and the National Space Development Agency of Japan (NASDA) for the purpose of improving research into the global water and energy cycle. GPM will improve climate, weather, and hydrological forecasts through more frequent and more accurate measurement of precipitation world-wide. Comprised of U.S. domestic and international partners, GPM will incorporate and assimilate data streams from many spacecraft with varied orbital characteristics and instrument capabilities. Two of the satellites will be provided directly by GPM, the core satellite and a constellation member. The core satellite, at the heart of GPM, is scheduled for launch in November 2007. The core will carry a conical scanning microwave radiometer, the GPM Microwave Imager (GMI), and a two-frequency cross-track-scanning radar, the Dual-frequency Precipitation Radar (DPR). The passive microwave channels and the two radar frequencies of the core are carefully chosen for investigating the varying character of precipitation over ocean and land, and from the tropics to the high-latitudes. The DPR will enable microphysical characterization and three-dimensional profiling of precipitation. The GPM-provided constellation spacecraft will carry a GMI radiometer identical to that on the core spacecraft. This paper presents calibration plans for the GPM, including on-board instrument calibration, external calibration methods, and the role of ground validation. Particular emphasis is on plans for inter-satellite calibration of the GPM constellation. With its Unique instrument capabilities, the core spacecraft will serve as a calibration transfer standard to the GPM constellation. In particular the Dual-frequency Precipitation Radar aboard the core will check the accuracy of retrievals from the GMI radiometer and will enable improvement of the radiometer retrievals. Observational intersections of the core with the constellation spacecraft are essential in applying this technique to the member satellites. Information from core spacecraft retrievals during intersection events will be transferred to the constellation radiometer instruments in the form of improved calibration and, with experience, improved radiometric algorithms. In preparation for the transfer standard technique, comparisons using the Tropical Rainfall Measuring Mission (TRMM) with sun-synchronous radiometers have been conducted. Ongoing research involves study of critical variables in the inter-comparison, such as correlation with spatial-temporal separation of intersection events, frequency of intersection events, variable azimuth look angles, and variable resolution cells for the various sensors.

Bidwell, S. W.↗
NASA NTRS2004

Infrared and Passive Microwave Radiometric Sea Surface Temperatures and Their Relationships to Atmospheric Forcing

The current generation of infrared (IR) and passive microwave (MW) satellite sensors provides highly complementary information for monitoring sea surface temperature (SST). On the one hand, infrared sensors provide high resolution and high accuracy but are obscured by clouds. Microwave sensors on the other hand, provide coverage through non-precipitating clouds but have coarser resolution and generally poorer accuracy. Assuming that the satellite SST measurements do not have spatially variable biases, they can be blended combining the merits of both SST products. These factors have motivated recent work in blending the MW and IR data in an attempt to produce high-accuracy SST products with improved coverage in regions with persistent clouds. The primary sources of retrieval uncertainty are, however, different for the two sensors. The main uncertainty in the MW retrievals lies in the effects of wind-induced surface roughness and foam on emissivity, whereas the IR retrievals are more sensitive to the atmospheric water vapor and aerosol content. Average nighttime differences between the products for the month periods of January 1999 and June 2000 are shown. These maps show complex spatial and temporal differences as indicated by the strong spatially coherent features in the product differences and the changes between seasons. Clearly such differences need to be understood and accounted for if the products are to be combined. The overall goals of this project are threefold: (1) To understand the sources of uncertainty in the IR and MW SST retrievals and to characterize the errors affecting the two types of retrieval as a fiction of atmospheric forcing; (2) To demonstrate how representative the temperature difference between the two satellite products is of Delta T; (3) To apply bias adjustments and to device a comprehensive treatment of the behavior of the temperature difference across the oceanic skin layer to determine the best method for blending thermal infrared and passive microwave measurements of SSTs.

Castro, Sandra L.↗
NASA NTRS2010

Normalizing Landsat and ASTER Data Using MODIS Data Products for Forest Change Detection

Monitoring forest cover and its changes are a major application for optical remote sensing. In this paper, we present an approach to integrate Landsat, ASTER and MODIS data for forest change detection. Moderate resolution (10-100m) images (e.g. Landsat and ASTER) acquired from different seasons and times are normalized to one "standard" date using MODIS data products as reference. The normalized data are then used to compute forest disturbance index for forest change detection. Comparing to the results from original data, forest disturbance index from the normalized images is more consistent spatially and temporally. This work demonstrates an effective approach for mapping forest change over a large area from multiple moderate resolution sensors on various acquisition dates.

Gao, Feng↗
NASA NTRS2015

Using Satellite Observations to Infer the Relationship Between Cold Pools and Subsequent Convection Development

Cold pools are increasingly being recognized as important players in the evolution of both shallow and deep convection; hence, the incorporation of cold pool processes into a number of recently developed convective parameterizations. Unfortunately, observations serving to inform cold pool parameterization development are limited to select field programs and limited radar domains. However, a number of recent studies have noted that cold pools are often associated with arcs-lines of shallow clouds traversing 10 100 km in visible satellite imagery. Boundary layer thermodynamic perturbations are plausible at such scales, coincident with such mesoscale features. Atmospheric signatures of features at these spatial scales are potentially observable from satellites. In this presentation, we discuss recent work that uses multi-sensor, high-resolution satellite products for observing mesoscale wind vector fluctuations and boundary layer temperature depressions attributed to cold pools produced by antecedent convection. The relationship to subsequent convection as well as convective system longevity is discussed. As improvements in satellite technology occur and efforts to reduce noise in high-resolution orbital products progress, satellite pixel level (10 km) thermodynamic and dynamic (e.g. mesoscale convergence) parameters can increasingly serve as useful benchmarks for constraining convective parameterization development, including for regimes where organized convection contributes substantially to the cloud and rainfall climatology.

thermodynamics↗
NASA NTRS2020

Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) Mission Integration and Testing

This paper describes the plans, flows, key facilities, components and equipment necessary to fully integrate, functionally test and qualify the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) Observatory. PACE is currently in the design phase of mission implementation. It is scheduled to launch in 2022, extending and improving NASA's twenty-year record of satellite observations of global ocean biology, aerosols and clouds. PACE will advance the assessment of ocean health by measuring the distribution of phytoplankton, which are small plants and algae that sustain the marine food web. It will also continue systematic records of key atmospheric variables associated with air quality and the Earth's climate. The PACE observatory is comprised of the spacecraft and three instruments, an Ocean Color Instrument (OCI) and two polarimeters, the Hyper-Angular Rainbow Polarimeter 2 (HARP2) and the Spectro-Polarimeter for Exploration (SPEXone). The spacecraft and the OCI, which is the primary instrument, are developed and integrated at the NASA Goddard Space Flight Center (GSFC). The OCI is a hyper-spectral scanning (HSS) radiometer designed to measure spectral radiances from the ultraviolet to shortwave infrared (SWIR) to enable advanced ocean color and heritage cloud and aerosol particle science. The HARP2 and SPEXone are secondary instruments on the PACE observatory, acquired outside of GSFC. The Hyper-Angular Rainbow Polarimeter instrument (HARP2) is a wide swath imaging polarimeter that is capable of characterizing atmospheric aerosols for purposes of sensor atmospheric correction as well as atmospheric science. The SPEXone provides atmospheric aerosol and cloud data at high temporal and spatial resolution. This paper will focus on the Integration and Test (I&T) activities for the PACE mission at NASA GSFC. This I&T phase consists of mechanical, electrical and thermal integration and test of all the spacecraft subsystems and the integration of the instruments with the spacecraft. The PACE observatory environmental tests include electromagnetic interference (EMI)/electromagnetic compatibility (EMC), vibration, acoustics, shock, thermal balance, thermal vacuum, mass properties and center of gravity. This paper will also discuss the observatory shipment to the launch site as well as the launch site processing.

Petro, Susanna↗
NASA NTRSDate not supplied

Assessing the Feasibility of using PlanetScope Data for Air Quality Applications

Planet is a commercial company known for having one of the largest operational smallsat satellite constellations. This constellation comprises over 120 3U CubeSats called Doves (equipped with a sensor called PlanetScope), which combined, are able to image the entire Earth’s surface daily at a high 3-meter spatial resolution. With Planet data becoming more readily available to scientists due to NASA’s Commercial Smallsat Data Acquisition Program (CSDAP), this study investigates the feasibility of utilizing Planet data to conduct scientific analyses with an emphasis on air quality research. This study offers a comparison of PlanetScope data with MODIS over a variety of land cover types, as well as in response to varying PM2.5 conditions. It also investigates the feasibility of utilizing PlanetScope data for estimating PM2.5 concentrations using deep learning

Jeanne Le Roux↗
NASA NTRSDate not supplied

The Application of Remote Sensing using NASA Earth Observations paired with Sociodemographic Indicators to Identify Communities Most Susceptible to Urban Heat Exposure in Austin, Texas

In recent years, Austin, Texas has experienced an increase in population and urban development. Additionally, the City’s climate—already characterized by periods of extreme heat and drought—continues to change. As temperatures and demand for utilities and cooling resources rise, the number of heat-related deaths and illnesses in socially vulnerable populations (e.g., older, lower-income populations) is expected to increase. The City of Austin, The University of Texas at Austin (UT Austin), and The University of Texas Health Science Center at Houston (UT Health) partnered with NASA DEVELOP to examine the distribution of urban heat throughout the City. This project used land surface temperature, greenness, plant water content, and urban surface material analysis parameters derived from NASA Earth observations from Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), and Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). The project team produced three different indices to create a spatial analysis for the study area including a social vulnerability index (SoVI), heat exposure index (HEI), and an overall heat priority index (HPI) score. This overall score was determined with a weighted analysis of heat-related environmental variables from NASA Earth observations and socioeconomic data from the 2019 American Community Survey. Based on the HPI score, the project team identified 121 census block groups out of 605 total that are designated as being most at risk of adverse impacts from extreme heat events. To test the sensitivity of the HPI, the team used a Monte Carlo analysis using different approaches for geographic scale, variable inclusion, census uncertainty, and index aggregation. Based on the sensitivity analysis, the resulting HPI score showed the metric was consistent with the baseline HPI. This provided increased confidence the score can be used as a tool to make informed infrastructure improvement plans in targeted areas (e.g., siting of cooling centers) and ensure equitable sustainable development.

Ryan Hammock↗
NASA NTRS2001

The Bermuda Bio-Optics Program (BBOP)

The Bermuda Bio-Optics Project (BBOP) is a collaborative effort between the Institute for Computational Earth System Science (ICESS) at the University of California at Santa Barbara (UCSB) and the Bermuda Biological Station for Research (BBSR). This research program is designed to characterize light availability and utilization in the Sargasso Sea, and to provide an optical link by which biogeochemical observations may be used to evaluate bio-optical models for pigment concentration, primary production, and sinking particle fluxes from satellite-based ocean color sensors. The BBOP time-series was initiated in 1992, and is carried out in conjunction with the US JGOFS Bermuda Atlantic Time-series Study (BATS) at the Bermuda Biological Station for Research. The BATS program itself has been observing biogeochemical processes (primary productivity, particle flux at and elemental cycles) in the mesotrophic waters of the Sargasso Sea since 1988. Closely affiliated with BBOP and BATS is a separate NASA-funded study of the spatial variability of biogeochemical processes in the Sargasso Sea using high-resolution Advanced Very High Resolution Radiometer (AVHRR) and Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) data collected at Bermuda. The collaboration between BATS and BBOP measurements has resulted in a unique data set that addresses not only the SIMBIOS goals but also the broader issues of important factors controlling the carbon cycle.

Siegel, David A.↗
NASA NTRS2000

BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-sensor Radiance

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the National Oceanic and Atmospheric Administration (NOAA-11) and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4b data are gridded, 10-day composites of at-sensor radiance values produced from sets of single-day images. Temporally, the 10- day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files.

Cihlar, Josef↗
NASA NTRS1990

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

Olson, William S.↗
NASA NTRS1991

Real time quantitative imaging for semiconductor crystal growth, control and characterization

A quantitative real time image processing system has been developed which can be software-reconfigured for semiconductor processing and characterization tasks. In thermal imager mode, 2D temperature distributions of semiconductor melt surfaces (900-1600 C) can be obtained with temperature and spatial resolutions better than 0.5 C and 0.5 mm, respectively, as demonstrated by analysis of melt surface thermal distributions. Temporal and spatial image processing techniques and multitasking computational capabilities convert such thermal imaging into a multimode sensor for crystal growth control. A second configuration of the image processing engine in conjunction with bright and dark field transmission optics is used to nonintrusively determine the microdistribution of free charge carriers and submicron sized crystalline defects in semiconductors. The IR absorption characteristics of wafers are determined with 10-micron spatial resolution and, after calibration, are converted into charge carrier density.

Wargo, Michael J.↗
DOE OSTI2022

Investigation of signal characteristics and charge sharing in AC-LGADs with laser and test beam measurements

AC-LGADs, also referred to as resistive silicon detectors, are a recent development of low-gain avalanche detectors (LGADs), based on a sensor design where the multiplication layer and n + contact are continuous, and only the metal layer is patterned. In AC-LGADs, the signal is capacitively coupled from the continuous, resistive n + layer over a dielectric to the metal electrodes. Therefore, the spatial resolution is not only influenced by the electrode pitch, but also the relative size of the metal electrodes. Signal propagation between the metallized areas and charge sharing between electrodes plays a larger role in these detectors than in conventional silicon sensors read out in DC mode. AC-LGADs from two manufacturers were studied in beam tests and with infrared laser scans. The impact of n + layer resistivity and metal electrode pitch on the charge sharing and achievable position resolution is shown. For strips with 100 μm pitch, a resolution of ¡ 5 μm can be reached. Additionally, the charge sharing between neighboring strips is investigated in more detail, indicating the induction of signal charge and subsequent re-sharing over the n + layer. Furthermore, an approach to identify signal sharing over large distances is presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Landscape-scale characterization of Arctic tundra vegetation composition, structure, and function with a multi-sensor unoccupied aerial system

The Arctic is experiencing some of the most rapid climate change on Earth, with strong impacts on tundra ecosystems that are characterized by high land-surface and vegetation heterogeneity. Previous studies have explored this complexity using satellite remote sensing, however these typically coarse spatial resolution data have generally missed sub-pixel heterogeneity, leaving critical gaps in our understanding of tundra vegetation dynamics from the community to landscape scales. To address these gaps, we collected very high-resolution (1-5 cm) optical, structural, and thermal data at three low-Arctic tundra sites on the Seward Peninsula, Alaska, using a multi-sensor unoccupied aerial system (UAS). We examined the application of these data to studying tundra vegetation dynamics, by quantifying (1) canopy height and thermoregulation (leaf-air temperature) of representative plant functional types (PFTs), (2) fine-scale patterns of vegetation composition across landscapes, and (3) impacts of fine-scale vegetation composition on landscape-scale variation of canopy height and thermoregulation. Our results show that deciduous tall shrubs (those that can potentially grow >2 m) had a strong cooling effect, with canopy temperatures significantly lower than local air temperatures and other PFTs. Increased cover of tall shrubs also had the potential to reduce the cover of low-stature PFTs across the landscape, potentially associated with their closed canopy (i.e., increased light competition) and strong thermoregulation. To understand the connections between fine-scale vegetation composition and large-scale ecosystem processes, we produced a random forest model which showed that fine-scale PFT composition accounted for 86.8% and 74.2% of the landscape-scale variation in canopy height and thermoregulation, respectively. These findings highlight the importance of spatially detailed characterization of tundra PFTs to improve our ecological understanding and model representation of tundra vegetation, also transcend our study to show the need for continued collection of similar datasets to better understand the impacts of surface heterogeneity on the mapping and modeling of tundra ecosystem dynamics, as well as assist with conservation management and biodiversity monitoring strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Nanoscale Three-Dimensional Imaging of Integrated Circuits Using a Scanning Electron Microscope and Transition-Edge Sensor Spectrometer

X-ray nanotomography is a powerful tool for the characterization of nanoscale materials and structures, but it is difficult to implement due to the competing requirements of X-ray flux and spot size. Due to this constraint, state-of-the-art nanotomography is predominantly performed at large synchrotron facilities. We present a laboratory-scale nanotomography instrument that achieves nanoscale spatial resolution while addressing the limitations of conventional tomography tools. The instrument combines the electron beam of a scanning electron microscope (SEM) with the precise, broadband X-ray detection of a superconducting transition-edge sensor (TES) microcalorimeter. The electron beam generates a highly focused X-ray spot on a metal target held micrometers away from the sample of interest, while the TES spectrometer isolates target photons with a high signal-to-noise ratio. This combination of a focused X-ray spot, energy-resolved X-ray detection, and unique system geometry enables nanoscale, element-specific X-ray imaging in a compact footprint. The proof of concept for this approach to X-ray nanotomography is demonstrated by imaging 160 nm features in three dimensions in six layers of a Cu-SiO 2 integrated circuit, and a path toward finer resolution and enhanced imaging capabilities is discussed.

47 OTHER INSTRUMENTATION↗
NASA NTRS1988

Infrared low-level wind shear work

Results of field experiments for the detection of clear air disturbance and low level wind shear utilizing an infrared airborne system are given in vugraph form. The hits, misses and nuisance alarms scores are given. Information is given on the infrared spatial resolution technique. The popular index of aircraft hazard (F= WX over g - VN over AS) is developed for a remote temperature sensor.

Adamson, Pat↗