Browse
Submit Data
Databases
API
Help

Dataset Information

29 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Thermodynamics of a fast-moving Greenlandic outlet glacier revealed by fiber-optic distributed temperature sensing.

ABSTRACT: Measurements of ice temperature provide crucial constraints on ice viscosity and the thermodynamic processes occurring within a glacier. However, such measurements are presently limited by a small number of relatively coarse-spatial-resolution borehole records, especially for ice sheets. Here, we advance our understanding of glacier thermodynamics with an exceptionally high-vertical-resolution (~0.65 m), distributed-fiber-optic temperature-sensing profile from a 1043-m borehole drilled to the base of Sermeq Kujalleq (Store Glacier), Greenland. We report substantial but isolated strain heating within interglacial-phase ice at 208 to 242 m depth together with strongly heterogeneous ice deformation in glacial-phase ice below 889 m. We also observe a high-strain interface between glacial- and interglacial-phase ice and a 73-m-thick temperate basal layer, interpreted as locally formed and important for the glacier's fast motion. These findings demonstrate notable spatial heterogeneity, both vertically and at the catchment scale, in the conditions facilitating the fast motion of marine-terminating glaciers in Greenland.

SUBMITTER: Law R

PROVIDER: S-EPMC8121432 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Supraglacial lake drainage at a fast-flowing Greenlandic outlet glacier.

Project description:Supraglacial lake drainage events influence Greenland Ice Sheet dynamics on hourly to interannual timescales. However, direct observations are rare, and, to date, no in situ studies exist from fast-flowing sectors of the ice sheet. Here, we present observations of a rapid lake drainage event at Store Glacier, west Greenland, in 2018. The drainage event transported 4.8 × 106 m3 of meltwater to the glacier bed in ∼5 h, reducing the lake to a third of its original volume. During drainage, the local ice surface rose by 0.55 m, and surface velocity increased from 2.0 m⋅d-1 to 5.3 m⋅d-1 Dynamic responses were greatest ∼4 km downstream from the lake, which we interpret as an area of transient water storage constrained by basal topography. Drainage initiated, without any precursory trigger, when the lake expanded and reactivated a preexisting fracture that had been responsible for a drainage event 1 y earlier. Since formation, this fracture had advected ∼500 m from the lake's deepest point, meaning the lake did not fully drain. Partial drainage events have previously been assumed to occur slowly via lake overtopping, with a comparatively small dynamic influence. In contrast, our findings show that partial drainage events can be caused by hydrofracture, producing new hydrological connections that continue to concentrate the supply of surface meltwater to the bed of the ice sheet throughout the melt season. Our findings therefore indicate that the quantity and resultant dynamic influence of rapid lake drainages are likely being underestimated.

| S-EPMC6926039 | biostudies-literature

Fiber Optic Distributed Sensing Network for Shape Sensing-Assisted Epidural Needle Guidance.

Project description:Epidural anesthesia is a pain management process that requires the insertion of a miniature needle through the epidural space located within lumbar vertebrae. The use of a guidance system for manual insertion can reduce failure rates and provide increased efficiency in the process. In this work, we present and experimentally assess a guidance system based on a network of fiber optic distributed sensors. The fibers are mounted externally to the needle, without blocking its inner channel, and through a strain-to-shape detection method reconstruct the silhouette of the epidural device in real time (1 s). We experimentally assessed the shape sensing methods over 25 experiments performed in a phantom, and we observed that the sensing system correctly identified bending patterns typical in epidural insertions, characterized by the different stiffness of the tissues. By studying metrics related to the curvatures and their temporal changes, we provide identifiers that can potentially serve for the (in)correct identification of the epidural space, and support the operator through the insertion process by recognizing the bending patterns.

| S-EPMC8615863 | biostudies-literature

Calibrating single-ended fiber-optic Raman spectra distributed temperature sensing data.

Project description:Hydrologic research is a very demanding application of fiber-optic distributed temperature sensing (DTS) in terms of precision, accuracy and calibration. The physics behind the most frequently used DTS instruments are considered as they apply to four calibration methods for single-ended DTS installations. The new methods presented are more accurate than the instrument-calibrated data, achieving accuracies on the order of tenths of a degree root mean square error (RMSE) and mean bias. Effects of localized non-uniformities that violate the assumptions of single-ended calibration data are explored and quantified. Experimental design considerations such as selection of integration times or selection of the length of the reference sections are discussed, and the impacts of these considerations on calibrated temperatures are explored in two case studies.

| S-EPMC3274318 | biostudies-literature

Well-scale demonstration of distributed pressure sensing using fiber-optic DAS and DTS.

Project description:In this study, we used data from optical fiber-based Distributed Acoustic Sensor (DAS) and Distributed Temperature Sensor (DTS) to estimate pressure along the fiber. A machine learning workflow was developed and demonstrated using experimental datasets from gas-water flow tests conducted in a 5163-ft deep well instrumented with DAS, DTS, and four downhole pressure gauges. The workflow is successfully demonstrated on two experimental datasets, corresponding to different gas injection volumes, backpressure, injection methods, and water circulation rates. The workflow utilizes the random forest algorithm and involves a two-step process for distributed pressure prediction. In the first step, single-depth predictive modeling is performed to explore the underlying relationship between the DAS (in seven different frequency bands), DTS, and the gauge pressures at the four downhole locations. The single-depth analysis showed that the low-frequency components (< 2 Hz) of the DAS data, when combined with DTS, consistently demonstrate a superior capability in predicting pressure as compared to the higher frequency bands for both the datasets achieving an average coefficient of determination (or R2) of 0.96. This can be explained by the unique characteristic of low-frequency DAS which is sensitive to both the strain and temperature perturbations. In the second step, the DTS and the low-frequency DAS data from two gauge locations were used to predict pressures at different depths. The distributed pressure modeling achieved an average R2 of 0.95 and an average root mean squared error (RMSE) of 24 psi for the two datasets across the depths analyzed, demonstrating the distributed pressure measurement capability using the proposed workflow. A majority of the current DAS applications rely on the higher frequency components. This study presents a novel application of the low-frequency DAS combined with DTS for distributed pressure measurement.

| S-EPMC8203739 | biostudies-literature

Estimation of Temperature and Associated Uncertainty from Fiber-Optic Raman-Spectrum Distributed Temperature Sensing.

Project description:Distributed temperature sensing (DTS) systems can be used to estimate the temperature along optic fibers of several kilometers at a sub-meter interval. DTS systems function by shooting laser pulses through a fiber and measuring its backscatter intensity at two distinct wavelengths in the Raman spectrum. The scattering-loss coefficients for these wavelengths are temperature-dependent, so that the temperature along the fiber can be estimated using calibration to fiber sections with a known temperature. A new calibration approach is developed that allows for an estimate of the uncertainty of the estimated temperature, which varies along the fiber and with time. The uncertainty is a result of the noise from the detectors and the uncertainty in the calibrated parameters that relate the backscatter intensity to temperature. Estimation of the confidence interval of the temperature requires an estimate of the distribution of the noise from the detectors and an estimate of the multi-variate distribution of the parameters. Both distributions are propagated with Monte Carlo sampling to approximate the probability density function of the estimated temperature, which is different at each point along the fiber and varies over time. Various summarizing statistics are computed from the approximate probability density function, such as the confidence intervals and the standard uncertainty (the estimated standard deviation) of the estimated temperature. An example is presented to demonstrate the approach and to assess the reasonableness of the estimated confidence intervals. The approach is implemented in the open-source Python package "dtscalibration".

| S-EPMC7218869 | biostudies-literature

Utilizing distributed acoustic sensing and ocean bottom fiber optic cables for submarine structural characterization.

Project description:The sparsity of permanent seismic instrumentation in marine environments often limits the availability of subsea information on geohazards, including active fault systems, in both time and space. One sensing resource that provides observational access to the seafloor environment are existing networks of ocean bottom fiber optic cables; these cables, coupled to modern distributed acoustic sensing (DAS) systems, can provide dense arrays of broadband seismic observations capable of recording both seismic events and the ambient noise wavefield. Here, we report a marine DAS application which demonstrates the strength and limitation of this new technique on submarine structural characterization. Based on ambient noise DAS records on a 20 km section of a fiber optic cable offshore of Moss Landing, CA, in Monterey Bay, we extract Scholte waves from DAS ambient noise records using interferometry techniques and invert the resulting multimodal dispersion curves to recover a high resolution 2D shear-wave velocity image of the near seafloor sediments. We show for the first time that the migration of coherently scattered Scholte waves observed on DAS records can provide an approach for resolving sharp lateral contrasts in subsurface properties, particularly shallow faults and depositional features near the seafloor. Our results provide improved constraints on shallow submarine features in Monterey Bay, including fault zones and paleo-channel deposits, thus highlighting one of many possible geophysical uses of the marine cable network.

| S-EPMC7946901 | biostudies-literature

Non-destructive real-time monitoring of underground root development with distributed fiber optic sensing.

Project description:Crop genetic engineering for better root systems can offer practical solutions for food security and carbon sequestration; however, soil layers prevent the direct visualization of plant roots, thus posing a challenge to effective phenotyping. Here, we demonstrate an original device with a distributed fiber-optic sensor for fully automated, real-time monitoring of underground root development. We show that spatially encoding an optical fiber with a flexible and durable polymer film in a spiral pattern can significantly enhance sensor detection. After signal processing, the resulting device can detect the penetration of a submillimeter-diameter object in the soil, indicating more than a magnitude higher spatiotemporal resolution than previously reported with underground monitoring techniques. Additionally, we also developed computational models to visualize the roots of tuber crops and monocotyledons and then applied them to radish and rice to compare the results with those of X-ray computed tomography. The device's groundbreaking sensitivity and spatiotemporal resolution enable seamless and laborless phenotyping of root systems that are otherwise invisible underground.

| S-EPMC10905790 | biostudies-literature

On-chip silicon electro-optical modulator with ultra-high extinction ratio for fiber-optic distributed acoustic sensing.

Project description:Ultra-high extinction ratio (ER) optical modulation is crucial for achieving high-performance fiber-optic distributed acoustic sensing (DAS) for various applications. Bulky acousto-optical modulators (AOM) as one of the key devices in DAS have been used for many years, but their relatively large volume and high power consumption are becoming the bottlenecks to hinder the development of ultra-compact and energy-efficient DAS systems that are highly demanded in practice. Here, an on-chip silicon electro-optical modulator (EOM) based on multiple coupled microrings is demonstrated with ultra-high ER of up to 68 dB while the device size and power consumption are only 260 × 185 μm2 and 3.6 mW, respectively, which are at least two orders of magnitude lower than those of a typical AOM. Such an on-chip EOM is successfully applied to DAS with an ultra-high sensitivity of -71.2 dB rad2/Hz (4 pε/√Hz) and a low spatial crosstalk noise of -68.1 dB rad2/Hz, which are very similar to those using an AOM. This work may pave the way for realization of next-generation ultra-compact DAS systems by integration of on-chip opto-electronic devices and modules with the capability of mass-production.

| S-EPMC10654388 | biostudies-literature

Fiber-Optic Theranostics (FOT): Interstitial Fiber-Optic Needles for Cancer Sensing and Therapy.

Project description:Photonics has spurred a myriad of diagnostic and therapeutic applications for defeating cancer owing to its superiority in spatiotemporal maneuverability and minimal harm. The limits of light penetration depth and elusiveness of photosensitizer utilization, however, impede the implementation of the photodiagnostic and -therapy for determining and annihilating the deep-situated tumor. Herein, a promising strategy that harnesses functional optical fibers is developed and demonstrated to realize an in vivo endoscopic cancer sensing and therapy ensemble. Tumor detection is investigated using hypoxia-sensitive fluorescent fibers to realize fast and accurate tumor recognition and diagnosis. The tumor treatment is further performed by exploiting the endogenous photothermal effect of rare-earth-doped optical fibers. The eradication of orthotopic and subcutaneous xenografts significantly validates the availability of tumoricidal fibers. The strategy opens horizons to inspire the design of optical fiber-mediated "plug and play" precise tumor theranostics with high safety, which may intrigue broader fields, such as fiber optics, materials, chemistry, medicine, and clinics.

| S-EPMC9130922 | biostudies-literature

Fibre optic distributed acoustic sensing of volcanic events.

Project description:Understanding physical processes prior to and during volcanic eruptions has improved significantly in recent years. However, uncertainties about subsurface structures distorting observed signals and undetected processes within the volcano prevent volcanologists to infer subtle triggering mechanisms of volcanic phenomena. Here, we demonstrate that distributed acoustic sensing (DAS) with optical fibres allows us to identify volcanic events remotely and image hidden near-surface volcanic structural features. We detect and characterize strain signals associated with explosions and locate their origin using a 2D-template matching between picked and theoretical wave arrival times. We find evidence for non-linear grain interactions in a scoria layer of spatially variable thickness. We demonstrate that wavefield separation allows us to incrementally investigate the ground response to various excitation mechanisms. We identify very small volcanic events, which we relate to fluid migration and degassing. Those results provide the basis for improved volcano monitoring and hazard assessment using DAS.

| S-EPMC8971480 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data