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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Observations of Aerosol, Cloud, Turbulence, and Radiation Properties at the Top of the Marine Boundary Layer over the Eastern North Atlantic Ocean: The ACORES Campaign

We report on the Azores Stratocumulus Measurements of Radiation, Turbulence and Aerosols (ACORES) campaign, which took place around Graciosa and Pico Islands/Azores in July 2017. The main objective was to investigate the vertical distribution of aerosol particles, stratocumulus microphysical and radiative properties, and turbulence parameters in the eastern North Atlantic. The vertical exchange of mass, momentum, and energy between the free troposphere (FT) and the cloudy marine boundary layer (MBL) was explored over a range of scales from submeters to kilometers. To cover these spatial scales with appropriate measurements, helicopter-borne observations with unprecedented high resolution were realized using the Airborne Cloud Turbulence Observation System (ACTOS) and Spectral Modular Airborne Radiation Measurement System–Helicopter-Borne Observations (SMART-HELIOS) instrumental payloads. Here, the helicopter-borne observations were combined with ground-based aerosol measurements collected at two continuously running field stations on Pico Mountain (2,225 m above sea level, in the FT), and at the Atmospheric Radiation Measurement (ARM) station on Graciosa (at sea level). First findings from the ACORES observations we are discussing in the paper are as follows: (i) we have observed a high variability of the turbulent cloud-top structure on horizontal scales below 100 m with local temperature gradients of up to 4 K over less than 1 m vertical distance, (ii) we have collected strictly collocated radiation measurements supporting the relevance of small-scale processes by revealing significant inhomogeneities in cloud-top brightness temperature to scales well below 100 m, and (iii) we have concluded that aerosol properties are completely different in the MBL and FT with often-complex stratification and frequently observed burst-like new particle formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Aerosol–Ice Formation Closure: A Southern Great Plains Field Campaign

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. Furthermore, the closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

58 GEOSCIENCES↗
DOE OSTI2022

The Response of the Polar Vortex to Tropospheric Temperature Eddies in an Idealized General Circulation Model

Abstract A dry-core idealized general circulation model with a stratospheric polar vortex in the Northern Hemisphere is run with a combination of simplified topography and imposed tropospheric temperature perturbations, each located in the Northern Hemisphere with a zonal wavenumber of 1. The phase difference between the imposed temperature wave and the topography is varied to understand what effect this has on the occurrence of polar vortex displacements. Geometric moments are used to identify the centroid of the polar vortex for the purposes of classifying whether or not the polar vortex is displaced. Displacements of the polar vortex are a response to increased tropospheric wave activity. Compared to a model run with only topography, the likelihood of the polar vortex being displaced increases when the warm region is located west of the topography peak, and decreases when the cold region is west of the topography peak. This response from the polar vortex is due to the modulation of vertically propagating wave activity by the temperature forcing. When the southerly winds on the western side of the topographically forced anticyclone are collocated with warm- or cold-temperature forcing, the vertical wave activity flux in the troposphere becomes more positive or negative, respectively. This is in line with recent reanalysis studies that showed that anomalous warming west of the surface pressure high, in the climatological standing wave, precedes polar vortex disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Droplet Growth or Evaporation Does Not Buffer the Variability in Supersaturation in Clean Clouds

Abstract Water vapor supersaturation in clouds is a random variable that drives activation and growth of cloud droplets. The Pi Convection–Cloud Chamber generates a turbulent cloud with a microphysical steady state that can be varied from clean to polluted by adjusting the aerosol injection rate. The supersaturation distribution and its moments, e.g., mean and variance, are investigated for varying cloud microphysical conditions. High-speed and collocated Eulerian measurements of temperature and water vapor concentration are combined to obtain the temporally resolved supersaturation distribution. This allows quantification of the contributions of variances and covariances between water vapor and temperature. Results are consistent with expectations for a convection chamber, with strong correlation between water vapor and temperature; departures from ideal behavior can be explained as resulting from dry regions on the warm boundary, analogous to entrainment. The saturation ratio distribution is measured under conditions that show monotonic increase of liquid water content and decrease of mean droplet diameter with increasing aerosol injection rate. The change in liquid water content is proportional to the change in water vapor concentration between no-cloud and cloudy conditions. Variability in the supersaturation remains even after cloud droplets are formed, and no significant buffering is observed. Results are interpreted in terms of a cloud microphysical Damköhler number (Da), under conditions corresponding to , i.e., the slow-microphysics regime. This implies that clouds with very clean regions, such that is satisfied, will experience supersaturation fluctuations without them being buffered by cloud droplet growth. Significance Statement The saturation ratio (humidity) in clouds controls the growth rate and formation of cloud droplets. When air in a turbulent cloud mixes, the humidity varies in space and time throughout the cloud. This is important because it means cloud droplets experience different growth histories, thereby resulting in broader size distributions. It is often assumed that growth and evaporation of cloud droplets buffers out some of the humidity variations. Measuring these variations has been difficult, especially in the field. The purpose of this study is to measure the saturation ratio distribution in clouds with a range of conditions. We measure the in-cloud saturation ratio using a convection cloud chamber with clean to polluted cloud properties. We found in clouds with low concentrations of droplets that the variations in the saturation ratio are not suppressed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Modulation of Gulf Stream Influence on the Troposphere by the Eddy-Driven Jet

This study suggests that the Gulf Stream influence on the wintertime North Atlantic troposphere is most pronounced when the eddy-driven jet (EDJ) is farthest south and better collocated with the Gulf Stream. Using the reanalysis dataset NCEP-CFSR for December–February 1979–2009, the daily EDJ latitude is separated into three regimes (northern, central, and southern). It is found that the average trajectory of atmospheric fronts covaries with EDJ latitude. In the southern EDJ regime (~19% of the time), the frequency of near-surface atmospheric fronts that pass across the Gulf Stream is maximized. Analysis suggests that this leads to significant strengthening in near-surface atmospheric frontal convergence resulting from strong air–sea sensible heat flux gradients (due to strong temperature gradients in the atmosphere and ocean). In recent studies, it was shown that the pronounced band of time-mean near-surface wind convergence across the Gulf Stream is set by atmospheric fronts. Here, it is shown that an even smaller subset of atmospheric fronts—those associated with a southern EDJ—primarily sets the time mean, due to enhanced Gulf Stream air–sea interaction. Furthermore, statistically significant anomalies in vertical velocity extending well above the boundary layer are identified in association with changes in EDJ latitude. These anomalies are particularly strong for a southern EDJ and are spatially consistent with increases in near-surface atmospheric frontal convergence over the Gulf Stream. These results imply that much of the Gulf Stream influence on the time-mean atmosphere is modulated on synoptic time scales, and enhanced when the EDJ is farthest south.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Columnar Vertical Profile (CVP) Methodology for Validating Polarimetric Radar Retrievals in Ice Using In Situ Aircraft Measurements

Abstract A novel way to process polarimetric radar data collected via plan position indicator (PPI) scans and display those data in a time–height format is introduced. The columnar vertical profile (CVP) methodology uses radar data collected via multiple elevation scans, limited to data within a set region in range and azimuth relative to the radar, to create vertical profiles of polarimetric radar data representative of that limited region in space. This technique is compared to others existing in the literature, and various applications are discussed. Polarimetric ice microphysical retrievals are performed on CVPs created within the stratiform rain region of two mesoscale convective systems sampled during two field campaigns, where CVPs follow the track of research aircraft. Aircraft in situ data are collocated to microphysical retrieval data, and the accuracy of these retrievals is tested against other retrieval techniques in the literature.

Engineering↗
DOE OSTI2025

Estimating Ice Water Content for Winter Storms from Millimeter-Wavelength Radar Measurements Using a Synthesis of Polarimetric and Dual-Frequency Radar Observations

The potential of millimeter-wavelength radar-based ice water content (IWC) estimation is demonstrated using a Ka-band Scanning Polarimetric Radar (KASPR) for the U.S. northeast coast winter storms. Two IWC relations for Ka-band polarimetric radar measurements are proposed: one that uses a combination of the radar reflectivity Z and the estimated total number concentration of snow particles N t and the other based on the joint use of Z, specific differential phase K DP , and the degree of riming f rim . A key element of the algorithms is to obtain the “Rayleigh-equivalent” value of Z measured at the Ka band, i.e., the corresponding Z at a longer radar wavelength for which Rayleigh scattering takes place. This is achieved via polarimetric retrieval of the mean volume diameter D m and incorporating the relationship between the dual-wavelength ratio DWR S/Ka and D m . Those techniques allow for retrievals from single millimeter-wavelength radar measurements and do not necessarily require the dual-wavelength ratio (DWR) measurements, if the DWR–D m relation and Rayleigh assumption for Ka-band K DP are valid. Comparison between the quasivertical profile product obtained from KASPR and the columnar vertical profile product generated from the nearby WSR-88D S-band radar measurements demonstrates that the DWR S/Ka can be estimated from the two close radars without the need for collocated radar beams and synchronized antenna scanning and can be used for determining the Rayleigh-equivalent value of Z. As a result, the performance of the suggested techniques is evaluated for seven winter storms using surface disdrometer and snow accumulation measurements.

Cloud retrieval↗
DOE OSTI2021

A Bimodal Diagnostic Cloud Fraction Parameterization. Part I: Motivating Analysis and Scheme Description

Cloud fraction parameterizations are beneficial to regional, convection-permitting numerical weather prediction. For its operational regional midlatitude forecasts, the Met Office uses a diagnostic cloud fraction scheme that relies on a unimodal, symmetric subgrid saturation-departure distribution. This scheme has been shown before to underestimate cloud cover and hence an empirically based bias correction is used operationally to improve performance. This first of a series of two papers proposes a new diagnostic cloud scheme as a more physically based alternative to the operational bias correction. The new cloud scheme identifies entrainment zones associated with strong temperature inversions. Additionally, for model grid boxes located in this entrainment zone, collocated moist and dry Gaussian modes are used to represent the subgrid conditions. The mean and width of the Gaussian modes, inferred from the turbulent characteristics, are then used to diagnose cloud water content and cloud fraction. It is shown that the new scheme diagnoses enhanced cloud cover for a given gridbox mean humidity, similar to the current operational approach. It does so, however, in a physically meaningful way. Using observed aircraft data and ground-based retrievals over the southern Great Plains in the United States, it is shown that the new scheme improves the relation between cloud fraction, relative humidity, and liquid water content. An emergent property of the scheme is its ability to infer skewed and bimodal distributions from the large-scale state that qualitatively compare well against observations. A detailed evaluation and resolution sensitivity study will follow in Part II.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Deep Convection Initiation, Growth, and Environments in the Complex Terrain of Central Argentina during CACTI

This study characterizes the wide range of deep convective cloud life cycles and their relationships with ambient environments observed during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign near the Sierras de Córdoba (SDC) range in central Argentina. We develop a novel convective cell tracking database for the entire field campaign using C-band polarimetric radar observations. The cell tracking database includes timing, location, area, depth, merge/split information, microphysical properties, collocated satellite-retrieved cloud properties, and sounding-derived environmental conditions. Results show that the SDC exerts a strong control on convection initiation (CI) and growth. CI preferentially occurs east of the SDC ridge during the afternoon, and cells often undergo upscale growth through the evening as they travel eastward toward the plains. Larger and more intense cells tend to occur in more unstable and humid low-level environments, and surface-based cells are stronger than elevated cells. Midtropospheric relative humidity and vertical wind shear also jointly affect the size and depth of the cells. Rapid cell area growth rates exhibit dependence on both large environmental wind shear and low-level moisture. Evolution of convective cell macro- and microphysical properties are strongly influenced by convective available potential energy and low-level humidity, as well as the presence of other cells in their vicinity. This cell tracking database demonstrates a framework that ties measurements from various platforms centering around convective life cycles to facilitate process understanding of factors that control convective evolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Temporal and spatial characterization of a thermogenic, fault-controlled gas hydrate system, Woolsey Mound, Gulf of Mexico

Woolsey Mound, located at Mississippi Canyon Lease Block 118 (MC118), is the site of the Gulf of Mexico hydrate research consortium’s seafloor observatory, where gas hydrates outcrop at the seafloor. The presence of gas hydrates in the mound is confirmed directly by coring and indirectly by 3D seismic reflection data. Craters, pockmarks, chemosynthetic communities, and authigenic carbonates populate the seafloor at Woolsey Mound. Each crater is characterized by a network of shallow crestal faults that connect the hydrate mound to the underlying allochthonous salt body. We characterize the temporal and spatial evolution of gas hydrates at Woolsey Mound under natural perturbations using four collocated 3D seismic reflection data sets that span over 14 years. Data acquisition differences embedded in the data sets arising from variation in geometry, sample rate, and phase are minimized using the “cross-equalization” method. Our results indicate that hydrate formation and dissociation vary temporally and spatially in close connection to the shallow crestal faults. Evidence of gas hydrate dissociation is observed over a period of three years (2000–2003), where major dissociation occurred along the southern portion of the crestal fault in the southeast crater. The dissociation is less prominent in the southwest crater. Evidence of methane venting is observed between 2000 and 2010, which is mostly concentrated in the southeast crater. The residual amplitude anomalies observed between 2000 and 2014 in the mound are mostly positive, implying that the methane venting had increased significantly. The positive anomalies are correlated with the methane seepage recorded in 2011. Our results indicate the evolution of a fault-controlled gas hydrate system in the northern Gulf of Mexico, which would aid in assessing its impact on the seafloor.

Geochemistry & Geophysics↗
DOE OSTI2022

Profile Images and Annotations for Vehicle Re-identification Algorithms (PRIMAVERA)

This dataset contains 636,246 profile images of vehicles representing 13,963 unique vehicles. The data was collected by a set of roadside sensors over the course of three years. Each time a vehicle passed by one of the sensors, a series of images was collected. The images were processed to detect and localize each vehicle, and a license plate reader collocated with the sensor was used to provide a unique ID for the vehicle. Actual license plate numbers have been obfuscated by replacing with an arbitrary numerical ID for each vehicle. After localizing the vehicle in each image, the original RGB image was rotated, scaled, and shifted to produce a new RGB image of size 234x234 pixels such that the outermost two wheels are located at predetermined pixel locations in the image. In this way, all vehicle images are aligned to one another. This registration process occasionally results in a portion of certain vehicles being cutoff at the edges of the image. The dataset has been partitioned into two sets called training and validation. The two partitions no common vehicles, i.e., a vehicle present in one partition is guaranteed not to be present in the other. In this way, an algorithm can be validated against a set of new vehicles that were not seen during the training process. The training set contains 543,926 images from 64,440 vehicle passes representing 11,918 unique vehicles, while the validation set contains 92,320 images from 10,991 vehicle passes representing 2,045 unique vehicles. Vehicle images are organized by directories corresponding to unique vehicles. The file naming scheme is as follows: veh_{vehID}_tr_{passID}_{frameID}_{elevation}_{timeofday}.jpg where {vehID} is the vehicle ID (unique across the entire dataset), {passID} is an identifier for each tracked vehicle pass (unique across the entire dataset), {frameID} is the index of the frame within the given vehicle pass starting at 0, {elevation} is a two-letter string indicating whether the sensor was elevated (el) or at ground-level (gl), and {timeofday} is a two-letter string indicating whether the image was captured during daytime (dt) or nighttime (nt).

image↗
DOE OSTI2020

Utah FORGE: Phase 3 Microgravity Data

A 4D microgravity survey began in early 2019 in order to benchmark surface and subsurface elevations prior to Phase 3 drilling and stimulation campaigns. Microgravity stations are collocated with GPS deformation benchmarks and use the same location survey data. Surveys are undertaken on a quarterly basis. The focus of current activities is comparative analysis of GPS survey results and InSAR analysis (see GDR Submission 1251) to check seasonal variance and to evaluate possible changes in the groundwater elevation. The attached zip file contains a text file and an Excel spreadsheet containing Utah FORGE Phase 3 processed "final" microgravity data through time. The data are identical in both files. The spreadsheet is only supplied for convenience. There is also a ReadMe.txt file that describes the field headings.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado and New Mexico

Temporally continuous snow depth estimates are vital for understanding changing snow patterns in the Arctic and impacts on permafrost. We trained random forest machine learning models to predict snow depth from temperature data recorded at or just below the ground surface. Training data was collected at the Teller 27 Watershed and Kougarok 64 Hillslope during the 2021 - 2022 water year on the Seward Peninsula, Alaska using distributed temperature profiling (DTP) systems. We then applied this model to other sites where ground surface or shallow soil temperature data was available for at least one water year (see Related Datasets). Many of these temperature measurements were collocated with snow depth observations. Ground surface temperature (i.e. snow-ground interface temperature) is easy to measure using small, cheap and easy-to-deploy temperature sensors such as iButtons and TinyTags, and such measurements have previously been used to calculate a variety of snow metrics (e.g. snow onset date). However, this is the first study to estimate snow depth directly from ground surface temperature data. The present dataset contains one *.csv file which includes machine learning snow depth predictions at sites in Alaska, Norway, Siberia, Colorado, and New Mexico and one *.kml file including the locations of sites with snow depth predictions. No training data predictions are included in the *.csv file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Monitoring of ground water table depth and soil moisture at the Point Reyes field site

Ground water table (GWT) depth and soil moisture (SM) have been monitored at several locations at the Point Reyes field site (Californian coastal grassland) from 2021 to 2024. Monitoring is still on-going and data may be added to this archive at later time. The SM data have been acquired using Teros 12 Meter soil moisture sensors placed at 10, 30, 60 and 90 cm depth at 5 locations along a small hillslope. These sensors also collect soil temperature and bulk conductance. In addition, some collocated sensors provide pore pressure and Photochemical Reflectance Index (PRI). The GWT depth has been inferred from various type of Onset pressure transducers. The pressure measurements have been corrected for atmospheric pressure variations and sensor position relative to the ground surface to infer GWT depth, as well as with RTK GPS data to infer GWT elevation. The GWT data have been acquired at 5 distinct locations from 2020 to 2024 with the sensors placed at about 4 m depth. In addition, GWT data has been acquired for the 2023-2024 period with sensors located in 1 m deep shallow wells installed near each deeper well. This data is intended to evaluate possibly different dynamic in shallow (perched) and deep aquifer. The datasets are all provided in csv format. Please note that the interpretation of the GWT data needs to be done with consideration of environmental and well characteristics at the site and uncertainty in various variables. For more information on GWT and SM data, please contact the author.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

AmeriFlux FLUXNET-1F US-xTL NEON Toolik (TOOL)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xTL NEON Toolik (TOOL). This is the FLUXNET version of the carbon flux data for the site US-xTL NEON Toolik (TOOL) produced by applying the standard ONEFlux (1F) software. Site Description - The Toolik field site is located in a remote wilderness area at the Toolik Field Station which is on land managed by the Bureau of Land Management. The area is underlain by continuous permafrost, which exerts a major influence on hydrology and the distribution, structure, and function of terrestrial and aquatic ecosystems. Because of its location between the Brooks Range and the coastal plain, the vegetation and soils at TOOL are representative of much of the Alaskan foothills tundra. This terrestrial field site is collocated with NEON’s Toolik Lake aquatic site. The closest city, Fairbanks, Alaska is 400 miles away. The Dalton Highway (also known as the Haul Road or Pipeline Road), which traverses the middle of the state from Fairbanks to Prudhoe Bay, provides access to the area.

Network), NEON (National Ecological Observatory↗
DOE OSTI2023

A New Decade in Seismoacoustics (2010–2022)

Several sources of interest often generate both low‐frequency acoustic and seismic signals due to energy propagation through the atmosphere and the solid Earth. Seismic and acoustic observations are associated with a wide range of sources, including earthquakes, volcanoes, bolides, chemical and nuclear explosions, ocean noise, and others. The fusion of seismic and acoustic observations contributes to a better understanding of the source, both in terms of constraining source location and physics, as well as the seismic to acoustic coupling of energy. Here in this review, we summarize progress in seismoacoustic data processing, including recent developments in open‐source data availability, low‐cost seismic and acoustic sensors, and large‐scale deployments of collocated sensors from 2010 to 2022. Similarly, we outline the recent advancements in modeling efforts for both source characteristics and propagation dynamics. Finally, we highlight the advantages of fusing multiphenomenological signals, focusing on current and future techniques to improve source detection, localization, and characterization efforts. This review aims to serve as a reference for seismologists, acousticians, and others within the growing field of seismoacoustics and multiphenomenology research.

58 GEOSCIENCES↗
DOE OSTI2025

Effect of Time Window and Spectral Measurement Options on Empirical Green’s Function Analysis Using DAS Array and Seismic Stations

The recorded seismic waveform is a convolution of event source term, path term, and station term. Removing high-frequency attenuation due to path effect is a challenging problem. Empirical Green’s function (EGF) method uses nearly collocated small earthquakes to correct the path and station terms for larger events recorded at the same station. However, this method is subject to variability due to many factors. Here, we focus on three events that were well recorded by the seismic network and a rapid response distributed acoustic sensing (DAS) array. Using a suite of high-quality EGF events, we assess the influence of time window, spectral measurement options, and types of data on the spectral ratio and relative source time function (RSTF) results. Increased number of tapers (from 2 to 16) tends to increase the measured corner frequency and reduce the source complexity. Extended long time window (e.g., 30 s) tends to produce larger variability of corner frequency. The multitaper algorithm that simultaneously optimizes both target and EGF spectra produces the most stable corner-frequency measurements. The stacked spectral ratio and RSTF from the DAS array are more stable than two nearby seismic stations, and are comparable to stacked results from the seismic network, suggesting that DAS array has strong potential in source characterization.

58 GEOSCIENCES↗
DOE OSTI2025

Detection of a Space Capsule Entering Earth’s Atmosphere with Distributed Acoustic Sensing (DAS)

On 24 September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer sample return capsule (SRC) entered Earth’s atmosphere after successfully collecting samples from an asteroid. The known trajectory and timing of this return provided a rare opportunity to strategically instrument sites to record geophysical signals produced by the capsule because it travelled at hypersonic speeds through the atmosphere. For this work, we deployed two distributed acoustic sensing (DAS) interrogators to sample over 12 km of surface-draped fiber-optic cables, as well as six collocated seismometer-infrasound sensor pairs, spread across two sites near Eureka, Nevada. This campaign-style rapid deployment is the first reported recording of an SRC re-entry with any distributed fiber-optic sensing technology. The DAS interrogators recorded an impulsive arrival with an extended coda which had features that were similar to recordings from both the seismometers and infrasound sensors. While the signal-to-noise ratio of the DAS data was lower than the seismic-infrasound data, the extremely dense spacing of fiber-optic sensors allowed for more phases to be clearly distinguished and the visualization of the continuous transformation of the wavefront as it impacted the ground. Unexpectedly, the DAS recordings contain less low-frequency content than is present in both the seismic and infrasound data. The deployment conditions strongly affected the recorded DAS data; in particular, we observed that fiber selection and placement exert strong controls on data quality.

58 GEOSCIENCES↗