How velocity extraction from Sentinel-2A/B affects the accuracy and availability of surface strain rate and stress: a case study of Helheim Glacier

Abstract. Calving is an important mass-loss process for many glaciers worldwide, and has been assumed to respond to a variety of environmental influences. We present a grounded, flowline tidewater glacier model using a physically-based calving mechanism, applied to Helheim Glacier, eastern Greenland. By qualitatively examining both modelled size and frequency of calving events, and the subsequent dynamic response, the model is found to realistically reproduce key aspects of observed calving behaviour. Experiments explore four environmental variables which have been suggested to affect calving rates: water depth in crevasses, basal water pressure, undercutting of the calving face by submarine melt and backstress from ice mélange. Of the four variables, only crevasse water depth and basal water pressure were found to have a significant effect on terminus behaviour when applied at a realistic magnitude. These results are in contrast to previous modelling studies, which have suggested that ocean temperatures could strongly influence the calving front. The results raise the possibility that Greenland outlet glaciers could respond to the recent trend of increased surface melt observed in Greenland more strongly than previously thought, as surface ablation can strongly affect water depth in crevasses and water pressure at the glacier bed.

Dynamical changes at the termini of tidewater glaciers may trigger sustained acceleration, thinning, and retreat, increasing a glacier's contribution to sea level rise. However, processes at the ice‐ocean interface occur across a range of spatial (cm to km) and temporal (minutes to years) scales, making these processes difficult to capture with many existing observational strategies. To fill this observational gap, we installed two autonomous terrestrial laser scanners overlooking the terminus at Helheim Glacier, East Greenland, the first in 2015 and the second in 2018. Each laser scanner system scans every six hours during non‐winter months and once a day during winter; together, these systems generate an extraordinary amount of data, including georeferenced point clouds, digital elevation models, velocity, and strain rates of Helheim Glacier. Our results show that large surface depressions form at a near‐consistent location on the lee side of a subglacial ridge and have increased in occurrence over time. We also present the first inferences of Helheim Glacier's grounding zone location and observed over 3 km of grounding zone retreat between 2018–2019. Furthermore, we identify and catalog calving events that we compare with our velocity products. We find that Helheim Glacier does not undergo sustained acceleration after individual calving episodes, and variations in calving style do not impact velocity responses. Our work reveals the insensitivity of Helheim Glacier to iceberg calving during our observational record and the importance of high temporal resolution data in inferring grounding zone dynamics.

The continuous and precise mapping of glacier calving fronts is essential for monitoring and understanding rapid glacier changes in Antarctica and Greenland, which have the potential for significant sea level rise within the current century. This effort has been mostly restricted to the slow and painstaking manual digitalization of the calving front positions in thousands of satellite imagery products. Here, we have developed a machine learning toolkit to automatically detect glacier calving front margins in satellite imagery. The toolkit is based on semantic image segmentation using Convolutional Neural Networks (CNN) with a modified U-Net architecture to isolate the calving fronts from satellite images after having been trained with a dataset of images and their corresponding manually-determined calving fronts. As a case study we train our neural network on a varied set of Landsat images with lowered resolutions from Jakobshavn, Sverdrup, and Kangerlussuaq glaciers, Greenland and test the results on images from Helheim glacier, Greenland to evaluate the performance of the approach. The neural network is able to identify the calving front in new images with a mean deviation of 96.3 m from the true fronts, equivalent to 1.97 pixels on average, while the corresponding error for manually-determined fronts on the same resolution images is 92.5 m (1.89 pixels). We find that the trained neural network significantly outperforms common edge detection techniques, and can be used to continuously map out calving-ice fronts with a variety of data products.

Accuracy evaluation of digital elevation models derived from Terrestrial Radar Interferometer over Helheim Glacier, Greenland

ABSTRACTRapid changes in Helheim Glacier and other Greenland outlet glaciers since 2000 are well-known, but knowledge on earlier decades is fragmentary. Here we exploit the satellite image archives to produce and analyze a monthly-to-seasonal record of Helheim Glacier front position, 1980–2011. Statistical analysis identifies decadal periods with abrupt changes in variability and mean. The record also reveals evidence of volatile advance/retreat behavior in the 1980s. In one of several cases of large-amplitude subannual changes, the glacier front ‘surged’ forward in 1984/85, advancing ~6 km within a few months – surpassing its Little Ice Age maximum position – and afterward retreated ~5 km within a few weeks. These findings challenge the prevailing view of front position stability in the decades before the multi-year retreat in the early 2000s. Cold conditions including rigid ice mélange appear to be a factor in the high-amplitude seasonal advances in the 1980s. However the magnitude and abruptness of the changes in the record cannot be explained solely as a climatic response, such that glacio-dynamics must be invoked. Further, the volatile advance/retreat behavior in the cold 1980s resulted in increased dynamic ice loss, complicating the interpretation of increased calving activity as a response to warming.

Recent observations of ocean temperature in several Greenland fjords suggest that ocean warming can cause large changes in the outlet glaciers in these fjords. We have observed the Helheim outlet-glacier front in the Sermilik Fjord over the last three decades using satellite images, and the vertical fjord temperature and salinity during three summer expeditions, 2008-2010. We show that the subsurface water below 250 m depth is the warm saline Atlantic Water from the Irminger Sea penetrating into the fjord and exposing the lower part of the Helheim glacier to warm water up to 4C. Lagged correlation analysis spanning the 30-year time series, using the subsurface Atlantic Water temperature off the coast as a proxy for the variability of the subsurface warm Atlantic Water in the fjord, indicates that 24% of the Helheim ice-front movement can be accounted for by ocean temperature. A strong correlation (-0.75) between the ice-front position and the surface air temperature from a nearby meteorological station suggests that the higher air temperature causes melting and subsequent downward percolation of meltwater through crevasses leading to basal lubrication; the correlation accounts for 56% of the ice-front movement. The precise contribution of air temperature versus ocean temperature however, remains an open question, as more oceanographic and meteorological measurements are needed close to the glacier terminus.

Ultrasound elastography is a convenient and affordable method for imaging mechanical properties of tissue, which are often correlated with pathologies. An emerging novel elastography technique applies an external acoustic radiation force to generate a shear wave in the tissue and uses ultrasound imaging to track the shear wave. Accurate tracking of the small tissue motion is a critical step in shear-wave elastography (SWE), but it is challenging due to various sources of noise in the ultrasound data. We formulate tissue displacement estimation as an optimization problem and propose two computationally efficient approaches to estimate the displacement field. The first algorithm is referred to as dynamic programming analytic minimization (DPAM), which utilizes first-order Taylor series expansion of the highly nonlinear cost function to allow for its efficient optimization, and was previously proposed for quasistatic elastography. The second algorithm is a novel technique that utilizes second-order derivatives of the nonlinear cost function. We call the new algorithm second-order analytic minimization elastography (SESAME). We compare DPAM and SESAME to the standard normalized cross correlation (NCC) approach in the context of displacement and speed estimation of wave propagation in SWE. The results of micrometer-order displacement estimation in a uniform simulation phantom illustrate that SESAME outperforms DPAM, which in turn outperforms NCC in terms of signal-to-noise ratio (SNR) and jitter. In addition, the relative difference between true and reconstructed shear modulus (averaged over excitations at different focal depths and several scatterer realizations at each depth) is approximately 3.41%, 1.12%, and 1.01%, respectively, for NCC, DPAM, and SESAME. The performance of the proposed methods is also assessed with real data acquired using a tissue-mimicking phantom, wherein, in comparison to NCC, DPAM and SESAME improve the SNR of displacement estimates by 7.6 and 9.5 dB, respectively. Experimental results on a tissue-mimicking phantom also show that shear modulus reconstruction substantially improved with the proposed DPAM technique over NCC and with some further improvement achieved by utilizing the second-order Taylor series approximation in SESAME instead of the first-order DPAM.

The early 2000s accelerated ice-mass loss from large outlet glaciers in W and SE Greenland has been linked to warming of the subpolar North Atlantic. To investigate the uniqueness of this event, we extend the record of glacier and ocean changes back 1700 years by analyzing a sediment core from Sermilik Fjord near Helheim Glacier in SE Greenland. We show that multidecadal to centennial increases in alkenone-inferred Atlantic Water SSTs on the shelf occurred at times of reduced solar activity during the Little Ice Age, when the subpolar gyre weakened and shifted westward promoted by atmospheric blocking events. Helheim Glacier responded to many of these episodes with increased calving, but despite earlier multidecadal warming episodes matching the 20th century high SSTs in magnitude, the glacier behaved differently during the 20th century. We suggest the presence of a floating ice tongue since at least 300 AD lasting until 1900 AD followed by elevated 20th century glacier calving due to the loss of the tongue. We attribute this regime shift to 20th century unprecedented low sea-ice occurrence in the East Greenland Current and conclude that properties of this current are important for the stability of the present ice tongues in NE Greenland.

With the rapidly expanding use of automobiles globally, the application of lighter structural materials in the form of magnesium alloys has become an urgent necessity to improve fuel efficiency and reduce the environmental impact. Within automobiles, magnesium alloys are used for components such as steering wheel frames and wheel rims, which are subjected to not only quasi-static but also dynamic strains. Indeed, catastrophic failure of a component by dynamic strain effects is a critical consideration, such as that of a wheel rim by braking at a high speed of 320 km/h. A recent consideration of magnesium for crash rail applications was rapidly brought to an end by the poor performance of initial crash test results. Dynamic strain rate testing is also important because of the emergence of magnesium alloys for armor with good ballistic properties. Just as with quasi-static strain, the mechanical behavior at dynamic strain rates depends on the microstructure. Deformation at dynamic strain rates produces more uniform distribution of dislocations and hinders the formation of discrete dislocation cells. Suppression of thermally activated dislocation processes occurs in this regime, which can lead to stresses high enough to activate deformation twins even in face-centered cubic (fcc) alloys with the high-stacking-fault energy. Among the fcc, body-centered cubic (bcc), and hexagonal closepacked (hcp) metals and alloys, high-purity fcc metals exhibit yielding that is nearly independent of the strain rate, while the strain hardening after yielding is strongly dependent on strain rate, which is due to the suppression of dynamic recovery process. In the case of bcc metals and alloys, yielding is strongly dependent on strain rate, while strain hardening is independent of the strain rate. For hcp metals, both the yielding and the strain hardening are dependent on strain rate. In hcp metals and alloys, twins play a very important role in deformation, especially for magnesium alloys in which nonbasal slips are not easily activated. The texture and c/a ratio greatly influence the deformation behavior of hcp metals. The effects of the polarity of twinning are similar to that at quasi-static tests. During in-plane testing of rolled plates with strong basal texture, in which the basal planes are parallel to the loading direction, it is observed that the twinning propensity increases with increasing strain rate. Through-thickness dynamic testing, in which the loading direction is perpendicular to the basal planes, reveals that the main deformation twinning mode, 1012 extension twinning, may not be activated. As a result, the work-hardening response in in-plane loading is more sensitive to strain rate than through-thickness loading. In this issue, we have four contributions on the dynamic behavior of magnesium alloys. The first is titled, ‘‘Dynamic Behavior of a Rare-Earth-Containing Mg Alloy WE43B-T5 Plate with Comparison to Conventional Alloy AM30-F’’ by S.R. Agnew, W. Wittington, A. Oppedal, H. El Kadiri, M. Shaeffer, K.T. Ramesh, J.J. Bhattacharyya, R. DeLorme, and B. Davis, which compares the dynamic behavior of two wrought alloys, a rolled WE43B alloy in peakaged condition, and an extruded AM30 alloy. The WE43B plate exhibited a relative isotropy of yield strength at quasi-static and dynamic strain rates, although it did show tension–compression strength asymmetry and anisotropy in strain hardening, which is consistent with the texture. The extruded AM30 alloy showed stronger anisotropy in strainhardening behavior related to the stronger texture in this material. At larger strain levels, the rate sensitivities along different directions converge in both the alloys. The authors also report that the yield strength is insensitive to strain rates along loading directions in which the rate-controlling process is 1012 type twinning, which is known to be relatively rate insensitive. The second contribution titled, ‘‘Dynamic Behavior of Some Magnesium Alloys’’ by E.S. Prasad, B. Li, N. Dixit, M. Shaefer, S.N. Mathaudhu, and K.T. Ramesh investigates the two important alloys, AZ31B and ZK60, at fine grain and ultrafine grain JOM, Vol. 66, No. 2, 2014

Seismic hazard assessment in active fault zones can benefit of strain rate measurements derived from geodetic data. Producing a continuous strain rate map from discrete data is an inverse problem traditionally tackled with standard interpolation schemes. Most algorithms require user‐defined regression parameters that determine the smoothness of the recovered velocity field and the amplitude of its spatial derivatives. This may lead to biases in the strain rates estimation which could eventually impact studies on earthquake hazard. Here we propose a transdimensional Bayesian method to estimate surface strain rates from Global Navigation Satellite System (GNSS) velocities. We parameterize the velocity field with a variable number of Delaunay triangles and use a reversible‐jump Monte‐Carlo Markov Chain algorithm to sample the probability distribution of surface velocities and spatial derivatives. The solution is a complete probability distribution function for each component of the strain rate field. We conduct synthetic tests and compare our approach to a standard b‐spline interpolation scheme. Our method is more resilient to data errors and uneven data distribution, while providing uncertainties associated with recovered velocities and strain rates. We apply our method to the Southwestern United States, an extensively studied and monitored area and infer probabilistic strain rates along the main fault systems, including the San Andreas one, from the inversion of interseismic GNSS velocities. Our approach provides a full description of the strain rate tensor for zones where strain rates are highly contrasted, with no need to manually tune user‐defined parameters. We recover sharp velocity gradients, without systematic artifacts.

SUMMARYGeodetic velocity data provide first-order constraints on crustal surface strain rates, which in turn are linked to seismic hazard. Estimating the 2-D surface strain tensor everywhere requires knowledge of the surface velocity field everywhere, while geodetic data such as Global Navigation Satellite System (GNSS) only have spatially scattered measurements on the surface of the Earth. To use these data to estimate strain rates, some type of interpolation is required. In this study, we review methodologies for strain rate estimation and compare a suite of methods, including a new implementation based on the geostatistical method of kriging, to compare variation between methods with uncertainty based on one method. We estimate the velocity field and calculate strain rates in southern California using a GNSS velocity field and five different interpolation methods to understand the sources of variability in inferred strain rates. Uncertainty related to data noise and station spacing (aleatoric uncertainty) is minimal where station spacing is dense and maximum far from observations. Differences between methods, related to epistemic uncertainty, are usually highest in areas of high strain rate due to differences in how gradients in the velocity field are handled by different interpolation methods. Parameter choices, unsurprisingly, have a strong influence on strain rate field, and we propose the traditional L-curve approach as one method for quantifying the inherent trade-off between fit to the data and models that are reflective of tectonic strain rates. Doing so, we find total variability between five representative strain rate models to be roughly 40 per cent, a much lower value than roughly 100 per cent that was found in previous studies (Hearn et al.). Using multiple methods to tune parameters and calculate strain rates provides a better understanding of the range of acceptable models for a given velocity field. Finally, we present an open-source Python package (Materna et al.) for calculating strain rates, Strain_2D, which allows for the same data and model grid to be used in multiple strain rate methods, can be extended with other methods from the community, and provides an interface for comparing strain rate models, calculating statistics and estimating strain rate uncertainty for a given GNSS data set.

Contemporary crustal strain rates derived from GPS measurements in southwestern China

Processing map-microstructure evolution correlation of hot compressed near alpha titanium alloy (TiHy 600)

In this paper we present a global model (GSRM-1) of both horizontal velocities on the Earth's surface and horizontal strain rates for almost all deforming plate boundary zones. A model strain rate field is obtained jointly with a global velocity field in the process of solving for a global velocity gradient tensor field. In our model we perform a least-squares fit between model velocities and observed geodetic velocities, as well as between model strain rates and observed geological strain rates. Model velocities and strain rates are interpolated over a spherical Earth using bi-cubic Bessel splines. We include 3000 geodetic velocities from 50 different, mostly published, studies. Geological strain rates are obtained for central Asia only and they are inferred from Quaternary fault slip rates. For all areas where no geological information is included a priori constraints are placed on the style and direction (but not magnitude) of the model strain rate field. These constraints are taken from a seismic strain rate field inferred from (normalized) focal mechanisms of shallow earthquakes. We present a global solution of the second invariant of the model strain rate field as well as strain rate solutions for a few selected plate boundary zones. Generally, the strain rate tensor field is consistent with geological and seismological data. With the assumption of plate rigidity for all areas other than the plate boundary zones we also present relative angular velocities for most plate pairs. We find that in general there is a good agreement between the present-day plate motions we obtain and long-term plate motions, but a few significant differences exist. The rotation rates for the Indian, Arabian and Nubian plates relative to Eurasia are 30, 13 and 50 per cent slower than the NUVEL-1A estimate, respectively, and the rotation rate for the Nazca Plate relative to South America is 17 per cent slower. On the other hand, Caribbean–North America motion is 76 per cent faster than the NUVEL-1A estimate. While crustal blocks in the India–Eurasia collision zone move significantly and self-consistently with respect to bounding plates, only a very small motion is predicted between the Nubian and Somalian plates. By integrating plate boundary zone deformation with the traditional modelling of angular velocities of rigid plates we have obtained a model that has already been proven valuable in, for instance, redefining a no-net-rotation model of surface motions and by confirming a global correlation between seismicity rates and tectonic moment rates along subduction zones and within zones of continental deformation.

The reduced availability of 3He is a motivation for developing alternative neutron detectors. 6Li-enriched CLYC (Cs2LiYCl6), a scintillator, is a promising candidate to replace 3He. The neutron and gamma ray signals from CLYC have different shapes due to the slower decay of neutron pulses. Some of the well-known pulse shape discrimination techniques fail to produce the desired results in a mixed radiation environment, particularly at high event rates. In the work presented here, we have applied a normalized cross correlation (NCC) approach to real neutron and gamma ray pulses produced by exposing CLYC scintillators to a mixed radiation environment generated by 137Cs and 252Cf/AmBe at different event rates. The cross correlation analysis produces distinctive results for measured neutron pulses and gamma ray pulses when they are cross correlated with reference neutron and/or gamma templates even at high event rates where the pileup is significant. With the NCC analysis shown to be a valid approach, efforts are continuing to develop a suitable algorithm to automatically process the NCC results to not only count the pulses but also to provide rudimentary neutron and gamma energy spectra. Ultimately, the technique will be implemented in an FPGA.