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NASA NTRS1994

(abstract) Galaxy Morphology in the Digital Era

A Galaxy Reconstruction Program (GREP) is to be described. Using structural primitives related to galactic structural components, it is demonstrated that realistic galaxy images can be produced. By assigning spectral energy distributions to each of these primitives, the images can be mapped into other wavelengths and thereby viewed at alternate redshifts. This is essentially a method for producing spatially resolved K-corrections for spiral galaxies.

galaxies images spiral galaxies GREP↗
NASA NTRS2008

Remote Sensing of Tropospheric Pollution from Space

We review the progress of tropospheric trace gas observations and address the need for additional measurement capabilities as recommended by the National Academy of Science (NAS, 2007). Tropospheric measurements from current and earlier instruments show pollution in the Northern Hemisphere as a result of fossil fuel burning and a strong seasonal dependence with the largest amounts of photochemically-generated ozone in summer. At low latitudes, where photon flux is stronger throughout the year, trace gas concentrations are driven by the abundance of the emissions, where the largest source, biomass burning, is readily seen in carbon monoxide measurements, but lightning and biogenic trace gases may also contribute to trace gas variability. Although substantive progress has been achieved in seasonal and global mapping of a few tropospheric trace gases, satellite trace-gas observations with considerably better temporal and spatial resolution are essential to forecasting air quality at scales required by policy-makers. The concurrent use of atmospheric composition measurements for both scientific and operational purposes is a new paradigm for the atmospheric chemistry community. The examples presented illustrate both the promise and challenge of merging satellite information with in situ observations in state-of-the-art data assimilation models.

Fishman, Jack↗
NASA NTRS2013

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Crosson, William L↗
NASA NTRS2013

Mineralogical Composition of the Different Types of Bright Deposits on Vesta

VIR-MS, Dawn's Visible and Infrared Mapping Spectrometer, obtained hyperspectral images of a wide part of Vesta's surface at a variety of spatial resolutions [1]. Vesta spectra are similar to those of the howardite-eucrite-diogenite (HED) meteorites. Moreover, they are characterized by the two iron-bearing pyroxene bands at 0.9 (band I) and 1.9 microns (band II). Vesta surface's is dominated by eucrite/howardite with some diogenitic regions situated in the southern hemisphere near the Rheasilvia basin [2]. The surface is heavily craterized and impacts can expose fresh material, thus generating the Bright Material Deposits (BMD) observed within and surrounding certain craters. BMD can be classified into six different types based on their morphological characteristics: Crater Wall/Scarp Material (CWM), Radial Material (RM), Slope Material (SM), Patchy Material (PM), Spot Material (SpM) and Diffuse Plains Material (DPM) [3]. The most widespread BMD are CWM, SM and RM. CWM, SM, RM originate from impacts. CWM is situated on the edge of the craters. Mass wasting from the crater walls and generates the SM, while RM is associated with the ejecta of the craters [4]. BMD are characterized by albedo greater than that of the vestan average, 0.38 [5]. Therefore the different types of deposits present distinct levels of reflectance respect to the Surrounding Regions (SR), in particular: the CWM and SM is approx.40% brighter, the RM is approx.30- 40% brighter; the SpM is about 20-25% brighter and the PM is about 20% brighter. Near the edge of the Rheasilvia basin it is possible to find some extremely bright areas ~80% brighter than the vestan average [6].

Zambon, F.↗
NASA NTRS2013

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Quattrochi, Dale A.↗
NASA NTRS2014

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Quattrochi, Dale A.↗
NASA NTRSDate not supplied

Joint Acceptance Attenuation Factor of Integrated Pressure with Unsteady Pressure-Sensitive Paint Measurements

The Unsteady Pressure-Sensitive Paint (uPSP) is widely used to measure the surface pressure of the scaled model in the wind tunnel tests. Compared to the conventional pressure transducers, uPSP has the advantage of high spatial resolution. With multiple high-speed cameras, the uPSP data collected with the camera pixels are mapped to the surface grid of the scaled model and converted to pressure. The shot noise, which is associated with the quantum processes both in the generation of the photons by the luminescent uPSP and in the conversion of the photons into electrons within the camera, is the dominant component of the noise in the uPSP measurement. The integrated pressure is usually computed as an area-weighted average of the uPSP measured pressures on the grid nodes of a user-defined patch. The effect of the shot noise is reduced in the integrated pressure; however, the measurement of the aerodynamic pressure is also attenuated. This paper discusses the Joint Acceptance Attenuation Factor (JAAF) of the integrated pressure with uPSP measurements. The JAAF is defined as the ratio of the auto or cross Power Spectral Density (PSD) of the integrated aerodynamic pressure on the patch to the average auto PSD of the aerodynamic pressure on the grid nodes of the patch. Under the assumption that the cross spectrum of the aerodynamic pressure can be described with the Corcos model, the closed-form formula of the JAAF is derived for the integrated pressure on rectangular patches via the summation of uPSP measurements on discrete grid nodes. The closed-form formula is verified via the integration of the pressure field of Corcos model over continuous areas. The properties of the JAAF with different parameters are presented and the applications in the comparison of the spectrum of the pressure transducers and uPSP measurements, which were collected in the NASA Space Launch System (SLS) tests with the 11-by-11-foot transonic wind tunnel at NASA Ames Research Center in December 2017 and September 2019 respectively, are also discussed. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. Funding was provided by the NASA Aerosciences Evaluation and Test Capabilities(AETC) Portfolio Office.

Unsteady Pressure-Sensitive Paint↗
NASA NTRS2023

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy Data Fusion to Map Global Surface Ozone Concentration and Associated Uncertainty

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R 2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m −3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Ozone↗
DOE OSTI2024

Understanding the Influence of Urban Form on the Spatial Pattern of Precipitation

Urban areas are known to modify the spatial pattern of precipitation climatology. Existing observational evidence suggests that precipitation can be enhanced downwind of a city. Among the proposed mechanisms, the thermodynamic and aerodynamic processes in the urban lower atmosphere interact with the meteorological conditions and can play a key role in determining the resulting precipitation patterns. In addition, these processes are influenced by urban form, such as the impervious surface extent. This study aims to unravel how different urban forms impact the spatial patterns of precipitation climatology under different meteorological conditions. We use the Multi-Radar Multi-Sensor quantitative precipitation estimation data products and analyze the hourly precipitation maps for 27 selected cities across the continental United States from the years 2015–2021 summer months. Results show that about 80% of the studied cities exhibit a statistically significant downwind enhancement of precipitation. Additionally, we find that the precipitation pattern tends to be more spatially clustered in intensity under higher wind speed; the location of radial precipitation maxima is located closer to the city center under low background winds but shifts downwind under high wind conditions. The magnitude of downwind precipitation enhancement is highly dependent on wind directions and is positively correlated with the city size for the south, southwest, and west directions. This study presents observational evidence through a cross-city analysis that the urban precipitation pattern can be influenced by the urban modification of atmospheric processes, providing insight into the mechanistic link between future urban land-use change and hydroclimates.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Aerosol Airmass Type Mapping Over the Urban Mexico City Region From Space-based Multi-angle Imaging

Using Multi-angle Imaging SpectroRadiometer (MISR) and sub-orbital measurements from the 2006 INTEX-B/MILAGRO field campaign, in this study we explore MISR's ability to map different aerosol air mass types over the Mexico City metropolitan area. The aerosol air mass distinctions are based on shape, size and single scattering albedo retrievals from the MISR Research Aerosol Retrieval algorithm. In this region, the research algorithm identifies dust-dominated aerosol mixtures based on non-spherical particle shape, whereas spherical biomass burning and urban pollution particles are distinguished by particle size. Two distinct aerosol air mass types based on retrieved particle microphysical properties, and four spatially distributed aerosol air masses, are identified in the MISR data on 6 March 2006. The aerosol air mass type identification results are supported by coincident, airborne high-spectral-resolution lidar (HSRL) measurements. Aerosol optical depth (AOD) gradients are also consistent between the MISR and sub-orbital measurements, but particles having single-scattering albedo of approx. 0.7 at 558 nm must be included in the retrieval algorithm to produce good absolute AOD comparisons over pollution-dominated aerosol air masses. The MISR standard V22 AOD product, at 17.6 km resolution, captures the observed AOD gradients qualitatively, but retrievals at this coarse spatial scale and with limited spherical absorbing particle options underestimate AOD and do not retrieve particle properties adequately over this complex urban region. However, we demonstrate how AOD and aerosol type mapping can be accomplished with MISR data over complex urban regions, provided the retrieval is performed at sufficiently high spatial resolution, and with a rich enough set of aerosol components and mixtures.

aerosol optical depth↗
NASA NTRS2013

The Atacama Cosmology Telescope: Beam Measurements and the Microwave Brightness Temperatures of Uranus and Saturn

We describe the measurement of the beam profiles and window functions for the Atacama Cosmology Telescope (ACT), which operated from 2007 to 2010 with kilopixel bolometer arrays centered at 148, 218, and 277 GHz. Maps of Saturn are used to measure the beam shape in each array and for each season of observations. Radial profiles are transformed to Fourier space in a way that preserves the spatial correlations in the beam uncertainty to derive window functions relevant for angular power spectrum analysis. Several corrections are applied to the resulting beam transforms, including an empirical correction measured from the final cosmic microwave background (CMB) survey maps to account for the effects of mild pointing variation and alignment errors. Observations of Uranus made regularly throughout each observing season are used to measure the effects of atmospheric opacity and to monitor deviations in telescope focus over the season. Using the WMAP-based calibration of the ACT maps to the CMB blackbody, we obtain precise measurements of the brightness temperatures of the Uranus and Saturn disks at effective frequencies of 149 and 219 GHz. For Uranus we obtain thermodynamic brightness temperatures T(149/U) = 106.7 +/- 2.2 K and T(219/U) = 100.1 +/- 3.1 K. For Saturn, we model the effects of the ring opacity and emission using a simple model and obtain resulting (unobscured) disk temperatures of T(149/S) = 137.3 +/- 3.2 K and T(219/S) = 137.3 +/- 4.7 K.

Atacama Cosmology Telescope (ACT)↗
NASA NTRS2004

The Antarctic Ozone Hole: Initial Results from Aura / OMI Compared with TOMS

A series of TOMS instruments (on November 7 , Meteor 3, and Earth Probe) has been monitoring the annual development of the Antarctic ozone hole since the 1980s. The ozone mapping instrument on Aura, OMI, is expected to take over this record of observation from the aging Earth Probe TOMS instrument. The area of the ozone hole can be taken as a sensitive indicator of the magnitude of ozone destruction each year. The timing of initial formation of the ozone hole and its duration are sensitive to the atmospheric dynamics of the southern polar regions. The entire TOMS data record (1978 - 2004) has recently been reprocessed with the new version 8 algorithm, which includes a revised calibration. The effect has been to slightly increase ozone hole area over earlier estimates, but only by 23%. OMI (ozone monitoring instrument) on Aura is a hyperspectral imaging instrument that operates in a pushbroom mode to measure solar backscattered radiation in the ultraviolet and visible. OMI has higher spatial resolution than TOMS - 14 x 24 km versus 38 km x 38 km from TOMS. OMI has now begin mapping total column ozone on a global basis in a measurement similar to TOMS. The ozone hole measurements for 2003 are compared with those from Earth Probe TOMS.

McPeters, R.↗
DOE OSTI2025

Map-level baryonification: unified treatment of weak lensing two-point and higher-order statistics

Precision cosmology benefits from extracting maximal information from cosmic structures, motivating the use of higher-order statistics (HOS) at small spatial scales. However, predicting how baryonic processes modify matter statistics at these scales has been challenging. The baryonic correction model (BCM) addresses this by modifying dark-matter-only simulations to mimic baryonic effects, providing a flexible, simulation-based framework for predicting both two-point and HOS. We show that a 3-parameter version of the BCM can jointly fit weak lensing maps' two-point statistics, wavelet phase harmonics coefficients, scattering coefficients, and the third and fourth moments to within 2% accuracy across all scales ℓ < 2000 and tomographic bins for a DES-Y3-like redshift distribution ( z ≲ 2), using the FLAMINGO simulations. These results demonstrate the viability of BCM-assisted, simulation-based weak lensing inference of two-point and HOS, paving the way for robust cosmological constraints that fully exploit non-Gaussian information on small spatial scales.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Evaluation of ERTS-1 image sensor spatial resolution in photographic form

The author has identified the following significant results. A coherent optical system was used to display the spatial frequency content of the amplitude image of one area of the ground as obtained in the four wavelength bands of the multispectral scanner. This enabled a rapid comparison to be made between the four bands, from which it was clear that bands 5 and 7 were preferred to the others in terms of image definition, and thus mapping and acreage estimation, for the particular agricultural area imaged. With suitable scaling it was also possible to compare the modulation, as a function of spatial frequency, of MSS bands 4 and 5 with the green (BB) and red (DD) bands of the same area from the Apollo 9, SO65 experiment. A significant result is that the modulation in the MSS amplitude imagery is 65%-90% of that in the Apollo 9 amplitude imagery. In addition, the ratio of spatial frequencies for the ERTS-1 and Apollo imagery, at which the same modulation occurs, lies between 0.55 and 0.75 for the red band. This ratio is closely related to the ratio of resolutions for the two sensors. These values corroborate statements that the resolution of the MSS imagery is better than anticipated by pre-flight predictions.

Slater, P. N.↗
NASA NTRS2003

A New Objective Technique for Verifying Mesoscale Numerical Weather Prediction Models

This report presents a new objective technique to verify predictions of the sea-breeze phenomenon over east-central Florida by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical weather prediction (NWP) model. The Contour Error Map (CEM) technique identifies sea-breeze transition times in objectively-analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean post-sea breeze wind direction and speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique is superior to traditional objective verification techniques and previously-used subjective verification methodologies because: It is automated, requiring little manual intervention, It accounts for both spatial and temporal scales and variations, It accurately identifies and verifies the sea-breeze transition times, and It provides verification contour maps and simple statistical parameters for easy interpretation. The CEM uses a parallel lowpass boxcar filter and a high-order bandpass filter to identify the sea-breeze transition times in the observed and model grid points. Once the transition times are identified, CEM fits a Gaussian histogram function to the actual histogram of transition time differences between the model and observations. The fitted parameters of the Gaussian function subsequently explain the timing bias and variance of the timing differences across the valid comparison domain. Once the transition times are all identified at each grid point, the CEM computes the mean wind direction and speed during the remainder of the day for all times and grid points after the sea-breeze transition time. The CEM technique performed quite well when compared to independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation. The algorithm correctly identified a forecast or observed sea-breeze occurrence or absence 93% of the time during the two- month evaluation period from July and August 2000. Nearly all failures in CEM were the result of complex precipitation features (observed or forecast) that contaminated the wind field, resulting in a false identification of a sea-breeze transition. A qualitative comparison between the CEM timing errors and the subjectively determined observed and forecast transition times indicate that the algorithm performed very well overall. Most discrepancies between the CEM results and the subjective analysis were again caused by observed or forecast areas of precipitation that led to complex wind patterns. The CEM also failed on a day when the observed sea- breeze transition affected only a very small portion of the verification domain. Based on the results of CEM, the RAMS tended to predict the onset and movement of the sea-breeze transition too early and/or quickly. The domain-wide timing biases provided by CEM indicated an early bias on 30 out of 37 days when both an observed and forecast sea breeze occurred over the same portions of the analysis domain. These results are consistent with previous subjective verifications of the RAMS sea breeze predictions. A comparison of the mean post-sea breeze winds indicate that RAMS has a positive wind-speed bias for .all days, which is also consistent with the early bias in the sea-breeze transition time since the higher wind speeds resulted in a faster inland penetration of the sea breeze compared to reality.

Case, Jonathan L.↗
DOE OSTI2024

Phase-resolving spin-wave microscopy using infrared strobe light

The need for sensitively and reliably probing magnetization dynamics has been increasing in various contexts such as studying novel hybrid magnonic systems, in which the spin dynamics strongly and coherently couple to other excitations, including microwave photons, light photons, or phonons. Recent advances in quantum magnonics also highlight the need for employing the magnon phase as quantum state variable, which is to be detected and mapped out with high precision in on-chip micro- and nanoscale magnonic devices. Here, in this study, we demonstrate a facile optical technique that can directly perform concurrent spectroscopic and imaging functionalities with spatial and phase resolutions, using infrared strobe light operating at 1550-nm wavelength. To showcase the methodology, we spectroscopically studied the phaseresolved spin dynamics in a bilayer of Permalloy and yttrium iron garnet Y 3 Fe 5 O 12 (YIG), and spatially imaged the backward-volume spin-wave modes of YIG in the dipolar spin-wave regime. Using the strobe light probe, the detected precessional phase contrast can be directly used to construct the map of the spin wave's wave front, in the continuous-wave regime of spin-wave propagation and in the stationary state, without needing any optical reference path. By selecting the applied field, frequency, and detection phase, the spin-wave images can be made sensitive to the precession amplitude and phase. Our results demonstrate that infrared optical strobe light can serve as a versatile platform for magneto-optical probing of magnetization dynamics, with potential implications in investigating hybrid magnonic systems.

Xiong, Yuzan [University of North Carolina, Chapel↗
DOE OSTI2021

Field validation of an actuated convergent-beam acoustic Doppler profiler for high resolution flow mapping

Abstract Energetic river and tidal flow environments feature complex hydrodynamic conditions. Conventional acoustic Doppler profiling instrumentation typically requires assumptions of flow homogeneity over the spatial scales of the divergent beam separation. This removes the ability to measure spatio-temporal variability within the flow. However, velocity variability within these spatial scales is often important in the design of structures and devices exposed to such flow, informing dynamic and peak hydrodynamic load predictions. The research presented outlines the development and testing of a flow measurement instrument consisting of multiple spatially-separated single beam acoustic Doppler profilers converging on a remote focal point, the location of which can be programmatically adjusted through actuation. This increases the spatial resolution at which remote field measurements can be made in energetic flow environments. Field testing of the instrument was conducted in a tidal channel at Sequim Bay Inlet, WA, USA. Results are compared with independent reference measurements made by a co-located, motion-corrected acoustic Doppler velocimeter. This comparison, across tidal velocities of 0.4–0.7 m s −1 , showed a mean velocity error of 0.5%–13.2% across nine sample locations within a 3.00 m × 2.25 m plane. To the authors’ knowledge, this is the first publication of flow velocity results from non-intrusive acoustic measurements at an off-axis, focal point location that features 3D positional control.

13 HYDRO ENERGY↗
NASA NTRS1990

Information analysis of a spatial database for ecological land classification

An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

Davis, Frank W.↗