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At least 199 records · Page 11

High-Resolution Electron Energy-Loss Spectroscopy (HREELS) Using a Monochromated TEM/STEM

A 200 keV FEI TF20 XT monochromated (scanning) transmission electron microscope funded by NASA's SRLIDAP program is undergoing installation at Lawrence Livermore National Laboratory. Instrument specifications in STEM mode are Cs =1.0 mm, Cc =1.2 mm, image resolution =0.18 nm, and in TEM mode Cs =1.3 mm, Cc =1.3 mm, information limit =0.14 nm. Key features of the instrument are a voltage-stabilized high tension (HT) supply, a monochromator, a high-resolution electron energy-loss spectrometer/energy filter, a high-resolution annular darkfield detector, and a solid-state x-ray energy-dispersive spectrometer. The high-tension tank contains additional sections for 60Hz and high frequency filtering, resulting in an operating voltage of 200 kV plus or minus 0.005V, a greater than 10-fold improvement over earlier systems. The monochromator is a single Wien filter design. The energy filter is a Gatan model 866 Tridiem-ERS high resolution GIF spec d for less than or equal to 0.15 eV energy resolution with 29 pA of current in a 2 nm diameter probe. 0.13 eV has already been achieved during early installation. The x-ray detector (EDAX/Genesis 4000) has a take-off angle of 20 degrees, an active area of 30 square millimeters, and a solid angle of 0.3 steradians. The higher solid angle is possible because the objective pole-piece allows the detector to be positioned as close as 9.47 mm from the specimen. The voltage-stabilized HT supply, monochromator and GIF enable high-resolution electron energy-loss spectroscopy (HREELS) with energy resolution comparable to synchrotron XANES, but with approximately 100X better spatial resolution. The region between 0 and 100 eV is called the low-loss or valence electron energy-loss spectroscopy (VEELS) region where features due to collective plasma oscillations and single electron transitions of valence electrons are observed. Most of the low-loss VEELS features we are detecting are being observed for the first time in IDPs. A major focus of our research is to understand the origin and significance of these features and how they might be exploited to gain insight about IDPs and other meteoritic materials.

Sai, Z. R.↗

Combining hyperspectral imaging and micro-X-ray fluorescence imaging methods for ultra-high-resolution biogeochemical analysis

Current non-destructive methods for high-resolution geochemical imaging open new avenues for high-resolution paleoenvironmental research. We discuss how two of these methods, hyperspectral imaging and micro-X-ray fluorescence imaging, can be combined for organic and inorganic geochemical analyses at a micrometer scale.

Zander, Paul [Lawrence Livermore National Laborato↗

Detecting Atmospheric Molecules of Nontransiting Temperate Terrestrial Exoplanets Using High-resolution Spectroscopy in the Mid-infrared Domain

Motivated by the development of high-dispersion spectrographs in the mid-infrared (MIR) range, we study their application to the atmospheric characterization of nearby nontransiting temperate terrestrial planets around M-type stars. We examine the detectability of CO{sub 2}, H{sub 2}O, N{sub 2}O, and O{sub 3 }features in high-resolution planetary thermal emission spectra at 12–18 μm assuming an Earth-like profile and a simplified thermal structure. The molecular line width of such planets can be comparable to or broader than the Doppler shift due to the planetary orbital motion. Given the likely difficulty in knowing the high-resolution MIR spectrum of the host star with sufficient accuracy, we propose observing the target system at two quadrature phases and extracting the differential spectra as the planetary signal. In this case, the signals can be substantially suppressed compared with the case where the host star spectrum is perfectly known, as some parts of the spectral features do not remain in the differential spectra. Despite this self-subtraction, the CO{sub 2} and H{sub 2}O features of nearby (≲5 pc) systems with mid-/late-M host stars would be feasible with a 6.5 m class cryogenic space telescope, and orbital inclination could also be constrained for some of them. For CO{sub 2} and N{sub 2}O in a 1 bar Earth-like atmosphere, this method would be sensitive when the mixing ratio is 1–10{sup 3} ppm. The detectability of molecules except O{sub 3} is not significantly improved when the spectral resolution is higher than R≳10,000, although the constraint on the orbital inclination is improved. This study provides some benchmark cases useful for assessing the value of MIR high-resolution spectroscopy in terms of characterization of potentially habitable planets.

47 OTHER INSTRUMENTATION↗

Microfabrication of a Chamber for High-Resolution, In Situ Imaging of the Whole Root for Plant–Microbe Interactions

Fabricated ecosystems (EcoFABs) offer an innovative approach to in situ examination of microbial establishment patterns around plant roots using nondestructive, high-resolution microscopy. Previously high-resolution imaging was challenging because the roots were not constrained to a fixed distance from the objective. Here, we describe a new ‘Imaging EcoFAB’ and the use of this device to image the entire root system of growing Brachypodium distachyon at high resolutions (20×, 40×) over a 3-week period. The device is capable of investigating root–microbe interactions of multimember communities. We examined nine strains of Pseudomonas simiae with different fluorescent constructs to B. distachyon and individual cells on root hairs were visible. Succession in the rhizosphere using two different strains of P. simiae was examined, where the second addition was shown to be able to establish in the root tissue. The device was suitable for imaging with different solid media at high magnification, allowing for the imaging of fungal establishment in the rhizosphere. Overall, the Imaging EcoFAB could improve our ability to investigate the spatiotemporal dynamics of the rhizosphere, including studies of fluorescently-tagged, multimember, synthetic communities.

59 BASIC BIOLOGICAL SCIENCES↗

An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics

Flow depth and velocity are the most important hydrodynamic variables that govern various river functions, including water resources, navigation, sediment transport, and biogeochemical cycling. Existing high-resolution flow depth simulations rely on either computationally expensive river hydrodynamic models (RHMs) or data-driven models with formidable training costs, whereas data-driven modeling of flow velocity has rarely been explored. Here, using the hybrid Low-fidelity, Spatial analysis, and Gaussian process learning (LSG) model, we developed a downscaling approach to construct high-resolution flow depth and velocity from a two-dimensional (2-D) RHM simulation at coarse resolution. The LSG models were trained and tested in an urban watershed in Houston using two different hurricane-driven flood events. The high-resolution (as fine as 30 m resolution) and low-resolution (mostly 1000 m resolution) meshes include 664 724 and 14 536 grid cells, respectively. The results showed that through downscaling, the simulation errors were reduced to less than one-fourth and one-third of the errors of the low-resolution 2-D RHM for flow depth and velocity, respectively. Our analysis further revealed that the dominant uncertainty sources of the downscaled hydrodynamics are different, with flow velocity dominated by the dimensionality reduction error, which we reduced by using a regionalized training procedure. The downscaling approach achieves an 84-fold acceleration in computational time compared to the high-resolution 2-D RHM, making high-fidelity ensemble flood modeling feasible. More importantly, the developed method provides an opportunity to couple large-scale hydrodynamical processes with local physical, chemical, and biological processes in river models.

Tan, Zeli [Pacific Northwest National Laboratory (↗

Spatially Local Surrogate Modeling of Subgrid-Scale Effects in Idealized Atmospheric Flows: A Deep Learned Approach Using High-Resolution Simulation Data

Abstract We introduce a machine learned surrogate model from high-resolution simulation data to capture the subgrid-scale effects in dry, stratified atmospheric flows. We use deep neural networks (NNs) to model the spatially local state differences between a coarse-resolution simulation and a high-resolution simulation. The setup enables the capture of both dissipative and antidissipative effects in the state differences. The NN model is able to accurately capture the state differences in offline tests outside the training regime. In online tests intended for production use, the NN-coupled coarse simulation has higher accuracy over a significant period of time compared to the coarse-resolution simulation without any correction. We provide evidence of the capability of the NN model to accurately capture high-gradient regions in the flow field. With the accumulation of the errors, the NN-coupled simulation becomes computationally unstable after approximately 90 coarse simulation time steps. Insights gained from these surrogate models further pave the way for formulating stable, complex, physics-based spatially local NN models which are driven by traditional subgrid-scale turbulence closure models. Significance Statement Flows in the atmosphere are highly chaotic and turbulent, comprising flow structures of broad scales. For effective computational modeling of atmospheric flows, the effects of the small- and large-scale structures need to be captured by the simulations. Capturing the small-scale structures requires fine-resolution simulations. Even with the current state-of-the-art supercomputers, it can be prohibitively expensive to simulate these flows when computed for the entire earth over climate time scales. Thus, it is necessary to focus on the larger-scale structures using a coarse-resolution simulation while capturing the effects of the smaller-scale structures using some parameterization (approximation) scheme and incorporating it into the coarse-resolution simulation. We use machine learning to model the effects of the small-scale structures (subgrid-scale effects) in atmospheric flows. Data from a fine-resolution simulation is used to compute the missing subgrid-scale effects in coarse-resolution simulations. We then use machine learning models to approximate these differences between the coarse- and fine-resolution simulations. We see improved accuracy for the coarse-resolution simulations when corrected using these machine learned models.

54 ENVIRONMENTAL SCIENCES↗

High Resolution X-ray Imaging

Improved image quality is of central importance to the future of X ray astronomy. We show that the optical tolerances necessary to push the quality of grazing incidence telescopes well beyond their current one arcsecond limit, are achievable. We also discuss a new approach to X ray optics that has been under development and is already showing resolution as high a 0.1 arcseconds. We argue that diffraction limited resolution should be considered as a viable goal for a new start among the next generation observatories, and follow the line of reasoning into X ray interferometry as a long term goal.

Cash, Webster↗

Image Collection Simulation Using High-Resolution Atmospheric Modeling

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

54 ENVIRONMENTAL SCIENCES↗

A Disaggregation Algorithm for the High Resolution Soil Moisture Product from the Upcoming NISAR Mission

The NASA-ISRO Synthetic Aperture Radar (NISAR) is in the developmental stage and is planned to launch in Jan 2024 with two different microwave frequency bands L-band (~1.25 GHz) and S-band (~3.20 GHz), respectively, to provide fine-scale observations at resolutions of 5 to 10 meters. NISAR mission will provide a very high-resolution (200m) soil moisture product globally with a temporal resolution of 6 days, using L-band SAR observations. A data-driven approach is developed for disaggregating the coarse resolution (9 km) soil moisture data to a very high-resolution (200 m) soil moisture product using fine-scale (~ 10 m) NISAR L-band observations. In this study, we used ALOS PALSAR-2 L-band SAR observations in place of expected NISAR L-band observations. The developed disaggregation approach was tested on two different locations of India and USA and showed that the proposed approach has a great potential to estimate soil moisture at a very high resolution of 200m with very low uncertainties (0.02 m3/m3 – 0.04 m3/m3).

Vanama, Venkat↗

The SMAP and Copernicus Sentinel 1A/B Microwave Active-Passive High Resolution Surface Soil Moisture Product and Its Applications

SMAP project released a new enhanced high-resolution (3km and 1 km) soil moisture active-passive product. This product is obtained by combining the SMAP radiometer data and the Sentinel-1A and -1B Synthetic Aperture Radar (SAR) data. The approach used for this product draws heavily from the heritage SMAP active-passive algorithm. Modifications in the SMAP active-passive algorithm are done to accommodate the Copernicus Program's Sentinel-1A and -1B multi-angular C-band SAR data. Assessment of the SMAP and Sentinel active-passive algorithm has been conducted and results show feasibility of estimating surface soil moisture at high-resolution in regions with low vegetation density (~< 3 kg/sq.m). A new version of this product is released to public in May 2018. This high resolution (3 km and 1 km) soil moisture product with reasonable accuracy of 0.05 m3/m3 is useful for agriculture, flood mapping, watershed/rangeland management, and ecological/hydrological applications.

microwave remote sensing↗

High-Resolution Laser Spectroscopy on the Hyperfine Structure of 255Fm (𝑍=100)

We report on high-resolution laser spectroscopy of 255Fm (𝑇1/2=20 h), one of the heaviest nuclides available from reactor breeding. The hyperfine structures in two different atomic ground-state transitions at 398.4 nm and 398.2 nm were probed by in-source laser spectroscopy at the RISIKO mass separator in Mainz, using the perpendicularly illuminated laser ion source and trap (PI-LIST) high-resolution ion source. Experimental results were combined with hyperfine fields from various atomic ab initio calculations, in particular using multiconfiguration Dirac-Hartree-Fock theory, as implemented in grasp18. In this manner, the nuclear magnetic dipole and electric quadrupole moments were derived to be 𝜇=−0.75⁢(5) 𝜇N and 𝑄s=+5.84⁢(13) eb, respectively. The magnetic moment indicates occupation of the 𝜈⁢7/2⁢[613] Nilsson orbital, while the large quadrupole moment confirms strong, stable prolate deformation consistent with systematics in the heavy actinides. Comparisons with available expectation values from nuclear theory show good agreement, providing a stringent benchmark for the used theoretical models. These results revise earlier data and establish 255Fm as a reference isotope for future high-resolution studies.

Ezold, Julie [ORNL] (ORCID:0000000250550022)↗

Determination of atmospheric moisture structure and infrared cooling rates from high resolution MAMS radiance data

This program has applied Multispectral Atmospheric Mapping Sensor (MAMS) high resolution data to the problem of monitoring atmospheric quantities of moisture and radiative flux at small spatial scales. MAMS, with 100-m horizontal resolution in its four infrared channels, was developed to study small scale atmospheric moisture and surface thermal variability, especially as related to the development of clouds, precipitation, and severe storms. High-resolution Interferometer Sounder (HIS) data has been used to develop a high spectral resolution retrieval algorithm for producing vertical profiles of atmospheric temperature and moisture. The results of this program are summarized and a list of publications resulting from this contract is presented. Selected publications are attached as an appendix.

Menzel, W. Paul↗

High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.

In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.

Putnam, WilliamM.↗

First results from the Goddard High-Resolution Spectrograph - A demonstration of spectral resolution and experiments with deconvolution

High-quality spectra of the sharp-lined star Chi Lupi were obtained with the Goddard High Resolution Spectrograph (GHRS). Spectra for the various resolving powers achievable with the echelle and G160M gratings are displayed. The effect of spherical aberration upon the spectral resolution is found to be negligible when using the small science aperture. The resolution of the large science aperture spectra is degraded by less than a factor of two. Efforts with spectral deconvolution using several techniques show that it is possible to regain much of the spectral resolution lost in the large science aperture if high signal-to-noise spectra are obtained.

Wahlgren, Glenn M.↗

Improved Simulation of East Asian Summer Monsoon in the High-resolution CESM1 and Its Causes

Based on the high- and low-resolution Community Earth System Model, version 1 (CESM1), and corresponding simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6), we compare the interannual variability of the East Asian summer monsoon (EASM). The EASM interannual variability is characterized by the anomalous western North Pacific anticyclone (WNPAC) circulation and the dipole rainfall pattern with a negative southern lobe over the western North Pacific and a positive northern lobe along the Meiyu–Baiu region, which is better reproduced by the high-resolution models. Here, the reason for the improvement in the high-resolution models has been attributed to the better simulation of the warm temperature advection from the wind anomalies on the climatological temperature gradient. Positive sea surface temperature (SST) anomalies over the tropical Indian Ocean are the key to the improved wind anomalies featuring a WNPAC in the high-resolution models. The warm SST anomalies over the tropical Indian Ocean strengthen the WNPAC by triggering a Kelvin-wave response to the enhanced heat release induced by the increased precipitation. Based on the mixed-layer heat budget analysis, the warm SST anomalies over the western Indian Ocean in the high-resolution CESM1 are tied to the anomalous easterly wind along the equator, which reduces surface evaporation and upwelling. Therefore, the better simulations of air-sea feedback and the oceanic mesoscale eddy over the western Indian Ocean are the key for the improved simulation of the EASM interannual variations in the high-resolution CESM1.

54 ENVIRONMENTAL SCIENCES↗

Estimating snow cover from high-resolution satellite imagery by thresholding blue wavelengths

We report the extent and duration of snow cover, a critical component of the hydrologic cycle and the global climate system, is expected to shift dramatically under climate change. Therefore, developing high-resolution assessments of snow cover change is crucial for estimating the impact of changing snow cover on watershed and ecosystems processes in cold regions. Remote sensing tools provide a powerful method for mapping snow-covered area (SCA) across a landscape. The most common method for estimating SCA utilizes the normalized difference snow index (NDSI), which relies on spectral measurements in the shortwave-infrared wavelengths (SWIR). NDSI can effectively estimate catchment- to regional-scale SCA, but it cannot be used to assess fine-scale SCA because of current limitations on the spatial resolution of satellite-derived SWIR measurements. Here, we map SCA using a threshold of blue wavelengths and high-resolution satellite imagery. The thresholding method, which we call the Blue Snow Threshold algorithm (BST), has previously been used with digital camera imagery. We refine and automate the algorithm for use with cloud-free high-resolution satellite imagery and find that the BST can be used to assess fine-scale SCA. For validation, we compared BST-derived estimates of SCA to a) airborne lidar surveys, b) Landsat fractional SCA, and c) snow disappearance dates from Snow Telemetry (SNOTEL) stations. When compared to airborne lidar surveys of SCA, the BST predicted SCA had a range of F-scores between 0.81 and 0.94 in four study areas in California and Colorado. We also found general agreement between SCA and snow disappearance at multiple SNOTEL sites across the western United States. Given the relatively recent availability of high-resolution satellite imagery with spectral measurements in the visible wavelengths but lacking in SWIR, the BST offers a reliable and easy-to-apply tool for examining fine-scale snow-related processes.

54 ENVIRONMENTAL SCIENCES↗

Investigation of solar active regions at high resolution by balloon flights of the solar optical universal polarimeter, extended definition phase

Technical studies of the feasibility of balloon flights of the former Spacelab instrument, the Solar Optical Universal Polarimeter, with a modern charge-coupled device (CCD) camera, to study the structure and evolution of solar active regions at high resolution, are reviewed. In particular, different CCD cameras were used at ground-based solar observatories with the SOUP filter, to evaluate their performance and collect high resolution images. High resolution movies of the photosphere and chromosphere were successfully obtained using four different CCD cameras. Some of this data was collected in coordinated observations with the Yohkoh satellite during May-July, 1992, and they are being analyzed scientifically along with simultaneous X-ray observations.

Tarbell, Theodore D.↗

High-resolution passive microwave imaging of the surface of the Earth

The physics of passive microwave observations of the Earth and the system requirements for high-resolution imaging within this spectral band are summarized. High resolution is achieved in a straightforward manner by increasing the size of the primary antenna. However, with a single receiver, it is shown that the combination of high resolution and crosstrack scanning cannot produce images which have valuable geophysical content. The concept of a multiple receiver array located in the focal plane is presented as the only practical solution to the dilemma. Exploring this concept, system requirements are generated which, for the first order, appear to offer solutions to the problem.

Swift, C. T.↗