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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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14 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Can We Rely on Satellite Visible/Infrared Microphysical Retrievals of Boundary Layer Clouds in Partially Cloudy Scenes? Implications for Climate Research

This study addresses the longstanding question of the reliability of gridded visible/infrared satellite cloud properties in partially cloudy scenes. By using in-situ cloud probes and airborne Research Scanning Polarimeter (RSP) observations, we analyze bias changes in satellite retrievals from the Spinning Enhanced Visible Infra-Red Imager (SEVIRI) geostationary sensor during the ORACLES campaign. Biases in cloud optical depth (τ) and droplet effective radius (r e ) modestly change for cloud area fraction greater than 35%. The agreement between SEVIRI and RSP r e substantially improves when the retrievals are averaged after removing pixels with τ < 3.0, yielding biases indistinguishable from overcast scenes. In addition, satellite and RSP show an excellent agreement for closed- and open-cell stratocumulus clouds, showing that the satellite retrievals capture spatial changes of r e , and confirming that satellites can faithfully reproduce real physical features for optically thick and partially cloudy scenes. We demonstrate that a simple methodology can minimize uncertainties in satellite-based climate studies.

Painemal, David [NASA Langley Research Center, Ham↗
DOE OSTI2012

Thermo-mechanical analysis of ITER first mirrors and its use for the ITER equatorial visible/infrared wide angle viewing system optical design

ITER first mirrors (FMs), as the first components of most ITER optical diagnostics, will be exposed to high plasma radiation flux and neutron load. To reduce the FMs heating and optical surface deformation induced during ITER operation, the use of relevant materials and cooling system are foreseen. The calculations led on different materials and FMs designs and geometries (100 mm and 200 mm) show that the use of CuCrZr and TZM, and a complex integrated cooling system can limit efficiently the FMs heating and reduce their optical surface deformation under plasma radiation flux and neutron load. These investigations were used to evaluate, for the ITER equatorial port visible/infrared wide angle viewing system, the impact of the FMs properties change during operation on the instrument main optical performances. The results obtained are presented and discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Concept development for the ITER equatorial port visible/infrared wide angle viewing system

The ITER equatorial port visible/infrared wide angle viewing system concept is developed from the measurement requirements. The proposed solution situates 4 viewing systems in the equatorial ports 3, 9, 12, and 17 with 4 views each (looking at the upper target, the inner divertor, and tangentially left and right). This gives sufficient coverage. The spatial resolution of the divertor system is 2 times higher than the other views. For compensation of vacuum-vessel movements, an optical hinge concept is proposed. Compactness and low neutron streaming is achieved by orienting port plug doglegs horizontally. Calibration methods, risks, and R and D topics are outlined.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties

A major goal of remote sensing is the development of generalizable algorithms to repeatedly and accurately map ecosystem properties across space and time. Imaging spectroscopy has great potential to map vegetation traits that cannot be retrieved from broadband spectral data, but rarely have such methods been tested across broad regions. Here we illustrate a general approach for estimating key foliar chemical and morphological traits through space and time using NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-Classic). We apply partial least squares regression (PLSR) to data from 237 field plots within 51 images acquired between 2008 and 2011. Using a series of 500 randomized 50/50 subsets of the original data, we generated spatially explicit maps of seven traits (leaf mass per area (M area ), percentage nitrogen, carbon, fiber, lignin, and cellulose, and isotopic nitrogen concentration, δ 15 N) as well as pixel-wise uncertainties in their estimates based on error propagation in the analytical methods. Both Marea and %N PLSR models had a R 2 > 0.85. Root mean square errors (RMSEs) for both variables were less than 9% of the range of data. Fiber and lignin were predicted with R 2 > 0.65 and carbon and cellulose with R 2 > 0.45. Although R 2 of %C and cellulose were lower than Marea and %N, the measured variability of these constituents (especially %C) was also lower, and their RMSE values were beneath 12% of the range in overall variability. Model performance for δ 15 N was the lowest (R 2 = 0.48, RMSE = 0.95‰), but within 15% of the observed range. The resulting maps of chemical and morphological traits, together with their overall uncertainties, represent a first-of-its-kind approach for examining the spatiotemporal patterns of forest functioning and nutrient cycling across a broad range of temperate and sub-boreal ecosystems. These results offer an alternative to categorical maps of functional or physiognomic types by providing non-discrete maps (i.e., on a continuum) of traits that define those functional types. A key contribution of this work is the ability to assign retrieval uncertainties by pixel, a requirement to enable assimilation of these data products into ecosystem modeling frameworks to constrain carbon and nutrient cycling projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites: TL-LUE Parameterization and Validation

We present the first extended validation of satellitemicrowave (MW) liquidwater path (LWP) for low nonprecipitating clouds, from four operational sensors, against ship-borne observations from a three-channel MW radiometer collected along ship transects over the northeast Pacific during May–August 2013. Satellite MW retrievals have an overall correlation of 0.84 with ship observations and a bias of 9.3 g/m2. The bias for broken cloud scenes increases linearly with water vapor path and remains below 17.7 g/m2. In contrast, satelliteMWLWP is unbiased in overcast scenes with correlations up to 0.91, demonstrating that the retrievals are accurate and reliable under these conditions. Satellite MW retrievals produce a diurnal cycle amplitude consistent with ship-based observations (33 g/m2). Observations taken aboard extended ship cruises to evaluate not only satellite MW LWP but also LWP derived from visible/infrared sensors offer a new way to validate this important property over vast oceanic regions.

Zhou, Yanlian↗
DOE OSTI2015

Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy

To date, the utility of ecosystem and Earth system models (EESMs) has been limited by poor spatial and temporal representation of critical input parameters. For example, EESMs often rely on leaf-scale or literature-derived estimates for a key determinant of canopy photosynthesis, the maximum velocity of RuBP carboxylation (Vcmax, μmol m –2 s –1 ). Our recent work (Ainsworth et al., 2014; Serbin et al., 2012) showed that reflectance spectroscopy could be used to estimate Vcmax at the leaf level. Here, we present evidence that imaging spectroscopy data can be used to simultaneously predict Vcmax and its sensitivity to temperature (E V ) at the canopy scale. In 2013 and 2014, high-altitude Airborne Visible/Infrared Imaging Spectroscopy (AVIRIS) imagery and contemporaneous ground-based assessments of canopy structure and leaf photosynthesis were acquired across an array of monospecific agroecosystems in central and southern California, USA. A partial least-squares regression (PLSR) modeling approach was employed to characterize the pixel-level variation in canopy V cmax (at a standardized canopy temperature of 30 °C) and E V , based on visible and shortwave infrared AVIRIS spectra (414–2447 nm). Our approach yielded parsimonious models with strong predictive capability for Vcmax (at 30 °C) and E V (R 2 of withheld data = 0.94 and 0.92, respectively), both of which varied substantially in the field (≥ 1.7 fold) across the sampled crop types. The models were applied to additional AVIRIS imagery to generate maps of V cmax and E V , as well as their uncertainties, for agricultural landscapes in California. The spatial patterns exhibited in the maps were consistent with our in-situ observations. As a result, these findings highlight the considerable promise of airborne and, by implication, space-borne imaging spectroscopy, such as the proposed HyspIRI mission, to map spatial and temporal variation in key drivers of photosynthetic metabolism in terrestrial vegetation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Integrating very-high-resolution UAS data and airborne imaging spectroscopy to map the fractional composition of Arctic plant functional types in Western Alaska

Widespread changes in vegetation cover and composition are driving strong impacts on Arctic ecosystem functioning and global climate feedbacks. An accurate characterization of tundra vegetation composition is required to understand how the Arctic will respond to future climate change. However, quantifying tundra vegetation composition over large areas is challenging as commonly-used satellite observations are too coarse, spatially and spectrally, to differentiate low-lying tundra vegetation types. Recent airborne and spaceborne imaging spectroscopy platforms provide better data to characterize vegetation composition. Yet, our ability to characterize vegetation composition with imaging spectroscopy remains largely unexplored in the Arctic, particularly due to a lack of ground observations needed to train and test classification models. To address this problem, we collected very-high-resolution (VHR, ~5 cm) unoccupied aerial system (UAS) imagery at three low-Arctic tundra sites located on the Seward Peninsula, western Alaska. In this paper, we examine the feasibility of integrating imagery from the UAS and the hyperspectral Airborne Visible/Infrared Imaging Spectrometer, Next Generation (AVIRIS-NG) airborne instrument to map the fractional composition of 12 key Arctic plant functional types (PFTs). To this end, we first mapped the 12 PFTs from our VHR UAS imagery using random forest classification. We then used these UAS-derived PFT maps as ground truth to develop partial least squares regression (PLSR) models to predict the fractional cover (FCover) of each PFT from AVIRIS-NG imagery. Further, we evaluated the performance of our PLSR models using reserved UAS samples, as well as by mapping PFT FCover and dominant PFT for large tundra landscapes. Our results show that 1) Arctic PFTs can be effectively mapped using VHR UAS imagery, with overall accuracy between 86% and 92%, 2) when the UAS mapped PFTs were used to inform PLSR scaling models, the FCover of the 12 PFTs could be effectively estimated from AVIRIS-NG imagery with a mean absolute error (MAE) <0.13, and 3) our PLSR models outperformed traditional, fully constrained least-squares (FCLS) linear mixture analysis and produced high-quality, spatially contiguous PFT FCover and PFT maps that captured vegetation spatial patterns with similar accuracy to those developed from UAS imagery. The developed PLSR models have the potential to be broadly applied for quantifying vegetation composition with AVIRIS-NG images to help monitor tundra vegetation dynamics and improve process-based modeling of tundra ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

MODIS Aerosol and Low‐Cloud Retrievals: Orographic Effects in the Wake of Macquarie Island

Abstract Visible/infrared imagery from passive satellites is commonly relied upon to study low cloud microphysics over oceanic regions, including for the Southern Ocean (SO), but relatively little validation has been undertaken for the SO. In this article, we compare low‐cloud effective radius ( r e ), cloud droplet number concentration ( N d ) and cloud liquid water path (LWP) retrievals from the NASA Moderate Imaging Spectroradiometer (MODIS) with surface measurements collected during the Macquarie Island Cloud and Radiation Experiment (MICRE). MODIS 3.7‐μm band retrievals show little bias and moderately good correlation relative to MICRE retrievals for liquid‐phase low clouds when restricted to Solar Zenith Angles <65° on spatial scales of 50–100 km. However, the low overall bias in 3.7‐μm band effective radius ( r e 3.7 ) retrievals partly results from cancellation of errors: r e 3.7 is overestimated for non‐to‐lightly precipitating clouds, and underestimated for heavier drizzling clouds by ∼1–1.5 μm. 1.6‐μm and 2.1‐μm band r e retrievals are biased high. N d may likewise be slightly under‐ or overestimated depending on the concentration, but there is insufficient data to provide confidence in this result. Interestingly, a composite of MODIS retrievals from 2002 to 2020 show a distinct region of enhanced cloud cover and N d (and lower r e ) in the wake of Macquarie Island associated with orographic cloud formation. MODIS retrievals of aerosol optical depth (AOD) and Angstrom Exponent (AE) upwind and downwind of the island do not differ significantly. Comparison with MICRE measurements suggests that MODIS Collection 6 AOD retrievals are reasonable, while AE is problematically large.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Airborne imaging spectroscopy surveys of Arctic and boreal Alaska and northwestern Canada 2017–2023

Since 2015, NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) has investigated how climate change impacts the vulnerability and/or resilience of the permafrost-affected ecosystems of Alaska and northwestern Canada. ABoVE conducted extensive surveys with the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) during 2017, 2018, 2019, and 2022 and with AVIRIS-3 in 2023 to characterize tundra, taiga, peatlands, and wetlands in unprecedented detail. The ABoVE AVIRIS dataset comprises ~1700 individual flight lines covering ~120,000 km 2 with nominal 5 m × 5 m spatial resolution. Data include individual transects to capture important gradients like the tundra-taiga ecotone and maps of up to 10,000 km 2 for key study areas like the Mackenzie Delta. The ABoVE AVIRIS surveys enable diverse ecosystem science, provide crucial benchmark data for validating retrievals from the PACE, PRISMA, and EnMAP satellite sensors and help prepare for the SBG and CHIME missions. This paper guides interested researchers to fully explore the ABoVE AVIRIS spectral imagery and complements our guide to the ABoVE airborne synthetic aperture radar surveys.

Miller, Charles E. [California Institute of Techno↗
DOE OSTI2018

Design and Analysis Progress of ITER Diagnostic Equatorial Port #09

ITER is the world's largest fusion device currently under construction in the South of France with >50 diagnostic systems to be installed inside the port plugs (PPs), the interspace (IS), or the port cell region of various diagnostic ports. The plasma facing diagnostic first wall (DFW) and its supporting diagnostic shield modules (DSM) are designed to protect front-end diagnostics from plasma neutron and plasma radiation, while providing apertures for diagnostic access to the plasma. The design of ITER port plug structures including the DFW and the DSM is largely driven by the electromagnetic loads included on the PP structural components during plasma major disruptions and the vertical displacement events (VDEs). Unlike DFW and DSM, the design of diagnostic system, however, is likely driven by the steady-state thermal loads from plasma volumetric and surface heating and the dynamic response of the in-port components attached to the port-specific DSM or closure plate under transient loads induced on the vacuum vessel and the port extension during asymmetric VDEs. Three tenant diagnostic systems are integrated into the equatorial port 09. The toroidal interferometer/polarimeter, or TIP system, is installed in the left drawer (DSM3, left looking from plasma) for measuring the plasma density so to control the fuel input. The electron cyclotron emission (ECE) system is installed in the middle drawer (DSM2) to provide the high spatial and temporal resolution measurements of electron temperature evolution and the electron thermal transport inferences. The visible/infrared wide angle viewing system is installed in the right drawer (DSM1) to provide visible and infrared viewing and temperature data of the first wall for its protection in support of machine operation. The port plug integration design and multiphysics analyses are performed following port integration requirements including the weight limit (45 tones total), shut down dose rate limits, the cooling/heating and structural integrity validation. Mass distribution for TIP and ECE DSMs has been optimized to minimize the total weight by a new design of the boron carbide shielding pocket. Furthermore, the lightened DSM maintains its front-end load distribution and the structural stiffness with minimum impact to the DFW so to better protect on-board diagnostics; while still provides sufficient front-end stiffness for its structural integrity as well as the diagnostics function requirements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Determination of Large-Scale Cloud Ice Water Concentration by Combining Surface Radar and Satellite Data in Support of ARM SCM Activities

Single-column modeling (SCM) is one of the key elements of Atmospheric Radiation Measurement (ARM) research initiatives for the development and testing of various physical parameterizations to be used in general circulation models (GCMs). The data required for use with an SCM include observed vertical profiles of temperature, water vapor, and condensed water, as well as the large-scale vertical motion and tendencies of temperature, water vapor, and condensed water due to horizontal advection. Surface-based measurements operated at ARM sites and upper-air sounding networks supply most of the required variables for model inputs, but do not provide the horizontal advection term of condensed water. Since surface cloud radar and microwave radiometer observations at ARM sites are single-point measurements, they can provide the amount of condensed water at the location of observation sites, but not a horizontal distribution of condensed water contents. Consequently, observational data for the large-scale advection tendencies of condensed water have not been available to the ARM cloud modeling community based on surface observations alone. This lack of advection data of water condensate could cause large uncertainties in SCM simulations. Additionally, to evaluate GCMs cloud physical parameterization, we need to compare GCM results with observed cloud water amounts over a scale that is large enough to be comparable to what a GCM grid represents. To this end, the point-measurements at ARM surface sites are again not adequate. Therefore, cloud water observations over a large area are needed. The main goal of this project is to retrieve ice water contents over an area of 10 x 10 deg. surrounding the ARM sites by combining surface and satellite observations. Built on the progress made during previous ARM research, we have conducted the retrievals of 3-dimensional ice water content by combining surface radar/radiometer and satellite measurements, and have produced 3-D cloud ice water contents in support of cloud modeling activities. The approach of the study is to expand a (surface) point measurement to an (satellite) area measurement. That is, the study takes the advantage of the high quality cloud measurements (particularly cloud radar and microwave radiometer measurements) at the point of the ARM sites. We use the cloud ice water characteristics derived from the point measurement to guide/constrain a satellite retrieval algorithm, then use the satellite algorithm to derive the 3-D cloud ice water distributions within an 10° (latitude) x 10° (longitude) area. During the research period, we have developed, validated and improved our cloud ice water retrievals, and have produced and archived at ARM website as a PI-product of the 3-D cloud ice water contents using combined satellite high-frequency microwave and surface radar observations for SGP March 2000 IOP and TWP-ICE 2006 IOP over 10 deg. x 10 deg. area centered at ARM SGP central facility and Darwin sites. We have also worked on validation of the 3-D ice water product by CloudSat data, synergy with visible/infrared cloud ice water retrievals for better results at low ice water conditions, and created a long-term (several years) of ice water climatology in 10 x 10 deg. area of ARM SGP and TWP sites and then compared it with GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Neptune's Latitudinal Variations as Viewed with ALMA

We present spatially resolved millimeter maps of Neptune between 95 and 242 GHz taken with the Atacama Large Millimeter/submillimeter Array (ALMA) in 2016–2017. The millimeter weighting functions peak between 1 and 10 bar on Neptune, lying in between the altitudes probed at visible/infrared and centimeter wavelengths. Thus, these observations provide important constraints on the atmospheric structure and dynamics of Neptune. We identify seven well-resolved latitudinal bands of discrete brightness temperature variations, on the order of 0.5–3 K in all three observed ALMA spectral bands. We model Neptune’s brightness temperature using the radiative-transfer code Radio-BEAR and compare how various H{sub 2}S, CH{sub 4}, and ortho-/para-H{sub 2} abundance profiles can fit the observed temperature variations across the disk. We find that observed variations in brightness temperature with latitude can be explained by variations in the H{sub 2}S profile that range from sub- to supersaturations at altitudes above the 10 bar pressure level, while variations in CH{sub 4} improve the quality of fit near the equator. At the south polar cap, our best-fit model has a depleted deep atmospheric abundance of H{sub 2}S from 30 to only 1.5 times the protosolar value, while simultaneously depleting the CH{sub 4} abundance. This pattern of enhancement and depletion of condensible species is consistent with a global circulation structure where enriched air rises at the midlatitudes (32°–12°S) and north of the equator (2°–20°N), and dry air descends at the poles (90°–66°S) and just south of the equator (12°S–2°N). Our analysis finds more complex structure near the equator than accounted for in previous circulation models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types.

54 ENVIRONMENTAL SCIENCES↗