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At least 145 records · Page 8

A global gridded dataset for cloud vertical structure from combined CloudSat and CALIPSO observations

Abstract. The vertical structure of clouds has a profound effect on the global energy budget, the global circulation, and the atmospheric hydrological cycle. The CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) missions have taken complementary, colocated observations of cloud vertical structure for over a decade. However, no globally gridded dataset is available to the public for the full length of this unique combined data record. Here we present the 3S-GEOPROF-COMB product (Bertrand et al. 2023, https://doi.org/10.5281/zenodo.8057791), a globally gridded (level 3S) community data product summarizing geometrical profiles (GEOPROF) of hydrometeor occurrence from combined (COMB) CloudSat and CALIPSO data. Our product is calculated from the latest release (R05) of per-orbit (level-2) combined cloud mask profiles. We process a set of cloud cover, vertical cloud fraction, and sampling variables at 2.5, 5, and 10° spatial resolutions and monthly and seasonal temporal resolutions. We address the 2011 reduction in CloudSat data collection with Daylight-Only Operations (DO-Op) mode by subsampling pre-2011 data to mimic DO-Op collection patterns, thereby allowing users to evaluate the impact of the reduced sampling on their analyses. We evaluate our data product against CloudSat-only and CALIPSO-only global-gridded data products as well as four comparable surface-based sites, underscoring the added value of the combined product. Interest in the product is anticipated for the study of cloud processes, cloud–climate interactions, and as a candidate baseline climate data record for comparison to follow-up satellite missions, among other uses.

Bertrand, Leah (ORCID:0009000001607558)↗

In operando cryo-STEM of pulse-induced charge density wave switching in TaS 2

The charge density wave material 1T-TaS 2 exhibits a pulse-induced insulator-to-metal transition, which shows promise for next-generation electronics such as memristive memory and neuromorphic hardware. However, the rational design of TaS 2 devices is hindered by a poor understanding of the switching mechanism, the pulse-induced phase, and the influence of material defects. Here, we operate a 2-terminal TaS 2 device within a scanning transmission electron microscope at cryogenic temperature, and directly visualize the changing charge density wave structure with nanoscale spatial resolution and down to 300 μs temporal resolution. We show that the pulse-induced transition is driven by Joule heating, and that the pulse-induced state corresponds to the nearly commensurate and incommensurate charge density wave phases, depending on the applied voltage amplitude. With our in operando cryogenic electron microscopy experiments, we directly correlate the charge density wave structure with the device resistance, and show that dislocations significantly impact device performance. This work resolves fundamental questions of resistive switching in TaS 2 devices, critical for engineering reliable and scalable TaS 2 electronics.

36 MATERIALS SCIENCE↗

Advances in detection for neutron reflectometry with time-resolved imaging detectors

Thermal neutron detection in neutron scattering science is a challenging endeavour due to a limited number of technologies which are sensitive to these weakly interacting particles. While many improvements to conventional detectors are underway at various facilities, there is a great opportunity to make a leap in performance by combining the spatial resolution benefits of imaging and the temporal resolution and background discrimination of event-driven radiation detectors. This idea has been realized by using a neutron sensitive scintillator read out by a single-photon sensitive camera based on a Timepix3 ASIC. We demonstrate how such data-driven imaging sensors can enable unprecedented performance in neutron reflectometry using the ASTERIX instrument at the Los Alamos Neutron Scattering Center. Several samples were measured with both the new and a conventional 3 He detector systems. The results from this work demonstrate that these imaging based systems can satisfy performance parameters for the future QIKR reflectometer to be built at the Second Target Station at Oak Ridge National Laboratory. Further improvements to the detector are already underway which will allow streamlined and expedited experiments. We demonstrate at least a two order of magnitude increase in detection rate at an acceptable dead time and introduce a new way of tuning the detector efficiency using light collecting optics to accommodate highly intense direct beams which cannot be measured with any current detectors without severe attenuation. This will allow measurements of complete reflectometry profiles and using a single sample measurement combined with fewer direct beam calibration measurements on QIKR and potentially other reflectometers.

36 MATERIALS SCIENCE↗

Installation of a solid state neutral particle analyzer array on mega ampere spherical tokamak upgrade

A compact solid state neutral particle analyzer (SSNPA) diagnostic, previously installed at NSTX-U, has been moved to MAST-U and successfully operated in the first physics campaign (MU01). The SSNPA operates by detecting the flux of fast neutral particles produced by charge exchange (CX) reactions to diagnose the fast ion distribution. The diagnostic consists of three 16-channel sensors, which provide a radial view of the plasma and have a sightline intersection with the South–South neutral beam line. From this radial geometry, active CX signals from mostly trapped particles are observed. Each channel has a spatial resolution of 3–4 cm, a temporal resolution of 200 kHz, and an average pitch angle resolution of a few degrees. The three-sensor configuration allows for coarse energy resolution of the CX signals; each sensor sees similar sightlines but different filter thicknesses alter the energy cutoffs by known amounts. Experimental data show that all channels are collecting data as intended. The signal to noise ratio is typically around 15. Preliminary data analysis shows a correlation between the SSNPA signal and magnetohydrodynamic activity in the plasma as expected.

Instruments & Instrumentation↗

Distributed Fiber Optic Sensing to Identify Locations of Resistive Transitions in REBCO Conductors and Magnets

High-temperature superconductors such as REBa 2 Cu 3 O 7-x (REBCO, RE = rare earth) can generate strong magnetic fields that are promising for applications in particle accelerators and compact fusion reactors. Traditionally, voltage taps are installed in superconducting magnets to measure the voltage signals due to resistive transitions. The voltage-tap-based diagnostics is important for the development of magnet technology as it can help pinpoint the locations in the magnet windings that limit the magnet performance. The architecture of the multi-tape REBCO cable such as CORC wires, however, makes it difficult to apply the voltage-tap-based diagnostics to identify the locations of resistive transitions. Distributed fiber optic sensing (DFOS) has the potential to address this issue. In this paper, we report the measurements of thermal strain along a CORC wire based on optical frequency domain reflectometry with a maximum spatial resolution of 0.65 mm and a temporal resolution of 10 Hz. The optical fiber is co-wound with the CORC wire that is epoxy impregnated. During the test, current was increased until a resistive transition occurred in the conductor. The spectrum shift of the reflected light along the fiber was recorded. The results suggested that with proper thermal isolation from the cryogen, DFOS can be used to identify the locations of resistive transitions in CORC wires and magnets. In conclusion, the results will allow a better understanding of the causes of resistive transitions in REBCO conductors and magnets, which will help improve the REBCO magnet technology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dataset Repository for Investigating Suicide Risk Using Social and Environmental Determinants of Health

Suicide is frequently modeled as a function of genetics and environment, where the latter refers to factors other than direct biological consequences, such as air quality, financial level, social connectivity, transportation and food access, and homelessness status. According to the World Health Organization, clean air, a stable climate, adequate water, sanitation and hygiene, safe chemical use, radiation protection, healthy and safe workplaces, sound agricultural practices, health-supportive cities and built environments, and a preserved natural environment are all prerequisites for good health. Understanding the relationships between these determinants and mental health outcomes requires standardized data that can be included in healthcare programs and health outcome models. There is a wealth of publicly available data on social and environmental factors provided by various US organizations that can benefit the design of health care systems and public health interventions, as well as improve our comprehension of factors that impact health. Such information would not only help improve the understanding of individual and community risk but also identify new risk factors that have not previously been therapeutically targeted, especially in terms of their impact on mental health. However, curating and standardizing such datasets is challenging because they are often recorded at numerous geographical and temporal resolutions and with varying spatial and temporal granularities. To address this challenge, we launched an endeavor in conjunction with the Veterans Health Administration to collect publicly available socioeconomic and environmental determinants of health statistics in the US. In this manuscript, we describe a social and environmental determinants of health (SEDH) datasets repository, data curation documentation, and a pipeline framework for data generation; This effort started in 2020, when we began constructing a scalable pipeline to automate the download, extraction, preparation, analysis, and production of datasets. These datasets have been made available to the VHA and may be shared upon agreement with collaborating organizations.

60 APPLIED LIFE SCIENCES↗

Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model

Abstract. Lakes in the Arctic are important reservoirs of heat with much lower albedo in summer and greater absorption of solar radiation than surrounding tundra vegetation. In the winter, lakes that do not freeze to their bed have a mean annual bed temperature >0 ∘C in an otherwise frozen landscape. Under climate warming scenarios, we expect Arctic lakes to accelerate thawing of underlying permafrost due to warming water temperatures in the summer and winter. Previous studies of Arctic lakes have focused on ice cover and thickness, the ice decay process, catchment hydrology, lake water balance, and eddy covariance measurements, but little work has been done in the Arctic to model lake heat balance. We applied the LAKE 2.0 model to simulate water temperatures in three Arctic lakes in northern Alaska over several years and tested the sensitivity of the model to several perturbations of input meteorological variables (precipitation, shortwave radiation, and air temperature) and several model parameters (water vertical resolution, sediment vertical resolution, depth of soil column, and temporal resolution). The LAKE 2.0 model is a one-dimensional model that explicitly solves vertical profiles of water state variables on a grid. We used a combination of meteorological data from local and remote weather stations, as well as data derived from remote sensing, to drive the model. We validated modeled water temperatures with data of observed lake water temperatures at several depths over several years for each lake. Our validation of the LAKE 2.0 model is a necessary step toward modeling changes in Arctic lake ice regimes, lake heat balance, and thermal interactions with permafrost. The sensitivity analysis shows us that lake water temperature is not highly sensitive to small changes in air temperature or precipitation, while changes in shortwave radiation and large changes in precipitation produced larger effects. Snow depth and lake ice strongly affect water temperatures during the frozen season, which dominates the annual thermal regime of Arctic lakes. These findings suggest that reductions in lake ice thickness and duration could lead to more heat storage by lakes and enhanced permafrost degradation.

Clark, Jason A. (ORCID:0000000248105261)↗

Time series methods for the analysis of soundscapes and other cyclical ecological data

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near-continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

54 ENVIRONMENTAL SCIENCES↗

Swap motion–directed twinning of nanocrystals

Twinning frequently occurs in nanocrystals during various thermal, chemical, or mechanical processes. However, the nucleation and propagation mechanisms of twinning in nanocrystals remain poorly understood. Through in situ atomic resolution transmission electron microscopy observation at millisecond temporal resolution, we show the twinning in Pb individual nanocrystals via a double-layer swap motion where two adjacent atomic layers shift relative to one another. The swap motion results in twin nucleation, and it also serves as a basic unit of movement for twin propagation. Our calculations reveal that the swap motion is a phonon eigenmode of the face-centered cubic crystal structure of Pb, and it is enhanced by the quantum size effect of nanocrystals.

36 MATERIALS SCIENCE↗

GeoCarb Calibration Campaign Field Campaign Report

The GeoCarb Calibration Campaign, referred to as the Total Carbon Column Observing Network (TCCON) calibration campaign within this report for clarity, involved a series of single- and multiple-day Bruker EM27/SUN Fourier transform infrared (FTIR) spectrometer deployments at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory in Oklahoma. The EM27/SUN instruments directly measure infrared solar radiation in a wavelength range from 4000 to 11000 cm -1 at a spectral resolution of 0.5 cm -1 and varied temporal resolution of approximately 15 seconds. The solar radiation observed by these spectrometers contains information about the concentrations of atmospheric constituents present between the instruments and the top of the atmosphere, as every gas and particle in the atmosphere absorbs solar radiation at different wavelengths depending on their physical and chemical makeup. Through retrieval algorithm processing, the solar radiation data collected by EM27/SUN instruments can be used to infer total column dry-air mole fractions, or total column concentrations, of different trace gases present in the atmosphere. These total column concentrations, denoted as Xgas , represent the concentration, in ppb or ppm, of a trace gas in the column of atmosphere between an instrument and the top of the atmosphere. EM27/SUN instruments are primarily used to infer total column concentrations of carbon dioxide (CO 2 ), carbon monoxide (CO), methane (CH 4 ), and water vapor.

54 ENVIRONMENTAL SCIENCES↗

Fast data-driven spectrometer with direct measurement of time and frequency for multiple single photons

We present a single-photon-sensitive spectrometer based on a linear array of 512 single-photon avalanche diode detectors with 0.04 nm spectral and 40 ps temporal resolutions. We employ a fast data-driven operation that allows direct measurement of time and frequency for simultaneous single photons, time- and frequency-stamping each single-photon detection. Our results combine excellent temporal and spectral resolution. This work opens numerous applications in quantum photonics, especially when both spectral and temporal properties of single photons can be exploited.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantifying transport and electrocatalytic reaction processes in a gastight rotating cylinder electrode reactor via integration of Computational Fluid Dynamics modeling and experiments

Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.

42 ENGINEERING↗

Toward monochromated sub-nanometer UEM and femtosecond UED

A preliminary design of a mega-electron-volt (MeV) monochromator with 10 –5 energy spread for ultrafast electron diffraction (UED) and ultrafast electron microscopy (UEM) is presented. Such a narrow energy spread is advantageous in both the single shot mode, where the momentum resolution in diffraction is improved, and the accumulation mode, where shot-to-shot energy jitter is reduced. In the single-shot mode, we numerically optimized the monochromator efficiency up to 13% achieving 1.3 million electrons per pulse. In the accumulation mode, to mitigate the efficiency degradation caused by the shot-to-shot energy jitter, an optimized gun phase yields only a mild reduction of the single-shot efficiency, therefore the number of accumulated electrons nearly proportional to the repetition rate. Inspired by the recent work of Qi et al. (Phys Rev Lett 124:134803, 2020), a novel concept of applying reverse bending magnets to adjust the energy-dependent path length difference has been successfully realized in designing a MeV monochromator to achieve the minimum energy-dependent path length difference between cathode and sample. Thanks to the achromat design, the pulse length of the electron bunches and the energy-dependent timing jitter can be greatly reduced to the 10 fs level. The introduction of such a monochromator provides a major step forward, towards constructing a UEM with sub-nm resolution and a UED with ten-femtosecond temporal resolution. The one-to-one mapping between the electron beam parameter and the diffraction peak broadening enables a real-time nondestructive diagnosis of the beam energy spread and divergence. The tunable electric–magnetic monochromator allows the scanning of the electron beam energy with a 10 –5 precision, enabling online energy matching for the UEM, on-momentum flux maximizing for the UED and real-time energy measuring for energy-loss spectroscopy. A combination of the monochromator and a downstream chicane enables “two-color” double pulses with femtosecond duration and the tunable delay in the range of 10 to 160 fs, which can potentially provide an unprecedented femtosecond time resolution for time resolved UED.

36 MATERIALS SCIENCE↗

XFEL imaging techniques for high energy density and inertial fusion energy research at HED-HiBEF

The imaging platform developed at the High Energy Density-Helmholtz International Beamline for Extreme Fields (HED-HiBEF) instrument at the European X-ray Free Electron Laser (XFEL) and its applications to HED and fusion related research are presented. The platform combines the XFEL beam with the high-intensity short-pulse laser ReLaX and the high-energy nanosecond-pulse laser DiPOLE-100X. The spatial resolution is better than 500 nm and the temporal resolution of the order of 50 fs. The influence of the XFEL source in the x-ray imaging method is discussed. Free-propagation x-ray phase contrast imaging and Talbot-Lau imaging setups are shown. We show examples of blast waves and converging cylindrical shocks in aluminum, resonant absorption measurements of specific charged states in copper with ReLaX and planar shocks in polystyrene material generated by DiPOLE-100X. For the first time, we show the application of Talbot-Lau interferometry to convergent cylindrical shocks as well as resonant absorption processes. We also discuss the possibilities introduced by combining this imaging platform with a kJ-class laser.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Temperature Mapping of Stacked Silicon Dies from X-Ray-Diffraction Intensities

Increasing power densities in integrated circuits have led to an increased prevalence of thermal hotspots in integrated circuits. Tracking these thermal hotspots is imperative to prevent circuit failures. In three- dimensional (3D) integrated circuits, conventional surface techniques like infrared thermometry are unable to measure the 3D temperature distribution, and optical and magnetic resonance techniques are difficult to apply due to the presence of metals and large current densities. X-rays offer a high penetration depth and can be used to probe 3D structures. We report a method utilizing the temperature dependence of x-ray-diffraction intensity via the Debye-Waller factor to simultaneously map the temperature of individual silicon dies in a stack. Here, utilizing beamline 1-ID-E at the Advanced Photon Source (Argonne), we demonstrate, for each individual silicon die, a temperature resolution of 3 K, a spatial resolution of 100 × 400 μm 2 , and a temporal resolution of 20 s. Utilizing a sufficiently high-intensity laboratory source, e.g., from a liquid-anode source, this method can be scaled down to laboratories for noninvasive temperature mapping of 3D integrated circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Temperature Inversions below 1 km from a V-Band Scanning Radiometer at the North Slope of Alaska

A single-channel (56.7 GHz) scanning radiometer was deployed in August 2022 at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska site near Utqiaġvik. The radiometer is designed to provide temperature profiles between 0 and 1 km every 5 min. Averaging kernels show that this single-channel radiometer, taking observations at 10 discrete elevation angles, yields approximately the same information as a seven-channel V-band radiometer scanning three elevation angles. The instrument is able to reproduce the occurrence of temperature inversions between the surface and 1 km and their strength showing a correlation of 0.85, bias of −0.6 K, and slope of 1.04 with respect to radiosondes. Uncertainty in the inversion base height varies from 50 m near the surface to ∼300 m above 0.4 km when compared with radiosondes. Conversely, the inversion top height is overestimated and has higher uncertainty due to the degrading effects of the averaging kernels on the vertical resolution of the retrievals. Thanks to the high temporal resolution of the retrievals, the diurnal cycle of boundary layer temperature was evaluated showing that the radiometer can capture some aspects of the boundary layer thermal structure. The present analysis provides an overview of the capabilities of this simple observing configuration for selected applications.

Atmospheric profilers↗

A validated thermal and biological model for predicting algal productivity in large scale outdoor cultivation systems

Proper assessment of the sustainability of algal products requires an understanding of algal growth rate with regional and temporal resolution. This study developed a bulk growth model that utilizes geospatial data, reactor geometry inputs, and a maximum of six strain-specific parameters to predict algal productivity with temporal and regional resolution. The model requires local weather data to calculate the time-resolved culture temperature which is combined with a biological model based on maximum theoretical carbon fixation to predict the time-resolved algal concentration. Validation of the model against experimental data illustrates an average ac- curacy of 0.27% ± 5.32% when comparing algal concentration at harvest over 45 days of cultivation data for Galdieria sulphuraria 5587.1, and Galdieria sulphuraria Soos grown in photobioreactors (PBRs) in Mesa, AZ (33.4152° N, 111.8315° W). For open raceway ponds (ORPs), an accuracy of 0.9% ± 2.35% was achieved when comparing algal concentration at harvest over 50 days of cultivation data for Chlorella vulgaris, Desmodesmus intermedius, Nannochloropsis oceanica grown in Atlanta, GA (33.7490° N, 84.3880° W) and Mesa, AZ (33.4152° N, 111.8315° W). The validation trials spanned three seasons (winter, spring, and summer) to ensure model ac- curacy throughout the year, and concentration between harvests was modeled with hourly resolution. The validated model is used to assess the productivity at several case-study locations in the United States with Chlorella vulgaris, grown in open raceway ponds and Galdieria sulphuraria grown in vertical flat panel photo- bioreactors. In conclusion, the model has been published as an open-source tool, in an effort to increase the fidelity of future studies that rely on outdoor algae cultivation for feedstock production and allow for time resolved results for future techno-economic and life cycle assessments.

59 BASIC BIOLOGICAL SCIENCES↗

Gridded Sub-daily Climate Forcings for North America Based on Daymet and GSWP3 (Daymet-GSWP3)

To support high spatial and temporal resolution land surface modeling, this dataset provides 3-hourly time step historic weather forcing at 1-km spatial resolution for the entire North America. The latest Daymet V4 data provides gridded historic daily weather observations at 1-km spatial resolution from 1980 to 2014. Using sub-daily temporal information from the Global Soil Wetness Project Phase 3 (GSWP3), Daymet was further temporally downscaled to 3-hourly time steps and provided in the format required for land surface model simulations. The process of temporal downscaling preserves the relative magnitude in each sub-daily time step from GSWP3 while maintaining the total and average values from Daymet for each day. This results in a blended 1980-2014 Daymet-GSWP3 dataset. Available variables include surface air temperature, precipitation, specific humidity, shortwave and longwave radiation, wind speed, and pressure. These data can be used as a high-resolution meteorological forcing dataset to support high-resolution land surface modeling where accurate meteorological forcing datasets built from historic observations and/or reanalysis datasets are desirable.

54 ENVIRONMENTAL SCIENCES↗