We assess the recent contribution of the Greenland ice sheet (GrIS) to sea level change. We use the mass budget method, which quantifies ice sheet mass balance (MB) as the difference between surface ...mass balance (SMB) and solid ice discharge across the grounding line (D). A comparison with independent gravity change observations from GRACE shows good agreement for the overlapping period 2002–2015, giving confidence in the partitioning of recent GrIS mass changes. The estimated 1995 value of D and the 1958–1995 average value of SMB are similar at 411 and 418 Gt yr−1, respectively, suggesting that ice flow in the mid-1990s was well adjusted to the average annual mass input, reminiscent of an ice sheet in approximate balance. Starting in the early to mid-1990s, SMB decreased while D increased, leading to quasi-persistent negative MB. About 60 % of the associated mass loss since 1991 is caused by changes in SMB and the remainder by D. The decrease in SMB is fully driven by an increase in surface melt and subsequent meltwater runoff, which is slightly compensated by a small ( < 3 %) increase in snowfall. The excess runoff originates from low-lying ( < 2000 m a.s.l.) parts of the ice sheet; higher up, increased refreezing prevents runoff of meltwater from occurring, at the expense of increased firn temperatures and depleted pore space. With a 1991–2015 average annual mass loss of ∼ 0.47 ± 0.23 mm sea level equivalent (SLE) and a peak contribution of 1.2 mm SLE in 2012, the GrIS has recently become a major source of global mean sea level rise.
Osteoporosis is a metabolic bone disease with a high prevalence that affects the population worldwide, particularly the elderly. It is often due to fractures associated with bone fragility that the ...diagnosis of osteoporosis becomes clinically evident. However, early diagnosis would be necessary to initiate therapy and to prevent occurrence of further fractures, thus reducing morbidity and mortality. X-ray-based imaging plays a key role for fracture risk assessment and monitoring of osteoporosis. Whereas over decades dual-energy X-ray absorptiometry (DXA) has been the main method used and still reflects the reference standard, another modality reemerges with quantitative computed tomography (QCT) because of its three-dimensional advantages and the opportunistic exploitation of routine CT scans. Against this background, this article intends to review and evaluate recent advances in the field of X-ray-based quantitative imaging of osteoporosis at the spine. First, standard DXA with the recent addition of trabecular bone score (TBS) is presented. Secondly, standard QCT, dual-energy BMD quantification, and opportunistic BMD screening in non-dedicated CT exams are discussed. Lastly, finite element analysis and microstructural parameter analysis are reviewed.
The Greenland Ice Sheet is losing mass at accelerated rates in the 21st century, making it the largest single contributor to rising sea levels. Faster flow of outlet glaciers has substantially ...contributed to this loss, with the cause of speedup, and potential for future change, uncertain. Here we combine more than three decades of remotely sensed observational products of outlet glacier velocity, elevation, and front position changes over the full ice sheet. We compare decadal variability in discharge and calving front position and find that increased glacier discharge was due almost entirely to the retreat of glacier fronts, rather than inland ice sheet processes, with a remarkably consistent speedup of 4–5% per km of retreat across the ice sheet. We show that widespread retreat between 2000 and 2005 resulted in a step-increase in discharge and a switch to a new dynamic state of sustained mass loss that would persist even under a decline in surface melt.
Glacier retreat is the main process behind Greenland Ice Sheet dynamic mass loss over the past three decades, according to an analysis of discharge variability and calving front positions.
Accurate projections of the mass loss from the Greenland Ice Sheet (GrIS) require a complete understanding of the ice‐dynamic response to climate forcings on seasonal and interannual timescales and ...would greatly benefit from more observational evidence. Here, we analyze a 5‐year, high‐resolution data set of ice velocities of the GrIS using K‐means, an unsupervised clustering algorithm, to identify ice‐sheet wide characteristic seasonal flow patterns. We include all areas flowing >0.3 m/d and obtain an ice‐sheet wide overview of the seasonality and the interannual variability. It shows both a spatial and interannual variability in seasonal flow patterns, both along individual glaciers and between glaciers. We compare with runoff from a regional climate model and infer that the ice‐sheet wide patterns are linked to the availability of water penetrating to the base of the ice.
Plain Language Summary
The Greenland Ice Sheet (GrIS) is currently losing mass but the response from the marine outlet glaciers to atmospheric and oceanic forcings is uncertain and limiting the accuracy of the estimated future mass loss. Here, we analyze a 5‐year satellite based ice velocity data set with an unprecedented spatial and temporal resolution in order to investigate the variability on all fast flowing areas of the GrIS. We use a machine learning algorithm to sort the annual time series into characteristic seasonal patterns, and we compare the results to modeled runoff from a climate model. We find that individual glaciers are not classified to be one type, but the response depends on the availability of drained meltwater, and that the seasonal pattern of ice velocity varies spatially and temporally, both along individual glaciers and between neighboring glaciers. We conclude that the seasonal pattern of response to runoff provide insights to the evolution of the subglacial hydrological system during the runoff season. Understanding the response of ice flow to meltwater and how it is linked to the subglacial hydrological system is crucial for understanding the dynamic response of the ice sheet to future climate warming.
Key Points
We have identified typical ice‐sheet wide seasonal ice‐flow patterns using an unsupervised ML algorithm
There is a spatial and interannual variability in the seasonal flow patterns both between and along glaciers
The spatiotemporal variability of the seasonal patterns provides new insights into the evolution of the basal hydrology depending on runoff
By providing pore space for storage or refreezing of meltwater, the Greenland
ice sheet firn layer strongly modulates runoff. Correctly representing the
firn layer is therefore crucial for Greenland ...(surface) mass balance studies.
Here, we present a simulation of the Greenland firn layer with the firn model
IMAU-FDM forced by the latest output of the regional climate model RACMO2,
version 2.3p2. In the percolation zone, much improved agreement is found with firn
density and temperature observations. A full simulation of Greenland
firn at high temporal (10 days) and spatial (11 km) resolution is available
for the period 1960–2016.
We evaluate modelled Antarctic ice sheet (AIS) near-surface climate, surface
mass balance (SMB) and surface energy balance (SEB) from the updated polar
version of the regional atmospheric climate ...model, RACMO2 (1979–2016). The
updated model, referred to as RACMO2.3p2, incorporates upper-air relaxation,
a revised topography, tuned parameters in the cloud scheme to generate more
precipitation towards the AIS interior and modified snow properties reducing
drifting snow sublimation and increasing surface snowmelt. Comparisons of RACMO2 model output with several independent observational
data show that the existing biases in AIS temperature, radiative fluxes and
SMB components are further reduced with respect to the previous model
version. The model-integrated annual average SMB for the ice sheet including
ice shelves (minus the Antarctic Peninsula, AP) now amounts to
2229 Gt y−1, with an interannual variability of 109 Gt y−1. The
largest improvement is found in modelled surface snowmelt, which now compares
well with satellite and weather station observations. For the high-resolution
(∼ 5.5 km) AP simulation, results remain comparable to earlier
studies. The updated model provides a new, high-resolution data set of the contemporary
near-surface climate and SMB of the AIS; this model version will be used for
future climate scenario projections in a forthcoming study.
The spin-orbit coupling relating the electron spin and momentum allows for spin generation, detection and manipulation. It thus fulfils the three basic functions of the spin field-effect transistor. ...However, the spin Hall effect in bulk germanium is too weak to produce spin currents, whereas large Rashba effect at Ge(111) surfaces covered with heavy metals could generate spin-polarized currents. The Rashba spin splitting can actually be as large as hundreds of meV. Here we show a giant spin-to-charge conversion in metallic states at the Fe/Ge(111) interface due to the Rashba coupling. We generate very large charge currents by direct spin pumping into the interface states from 20 K to room temperature. The presence of these metallic states at the Fe/Ge(111) interface is demonstrated by first-principles electronic structure calculations. By this, we demonstrate how to take advantage of the spin-orbit coupling for the development of the spin field-effect transistor.
Understanding the interactions among anthropogenic stressors is critical for effective conservation and management of ecosystems. Freshwater scientists have invested considerable resources in ...conducting factorial experiments to disentangle stressor interactions by testing their individual and combined effects. However, the diversity of stressors and systems studied has hindered previous syntheses of this body of research. To overcome this challenge, we used a novel machine learning framework to identify relevant studies from over 235,000 publications. Our synthesis resulted in a new dataset of 2396 multiple‐stressor experiments in freshwater systems. By summarizing the methods used in these studies, quantifying trends in the popularity of the investigated stressors, and performing co‐occurrence analysis, we produce the most comprehensive overview of this diverse field of research to date. We provide both a taxonomy grouping the 909 investigated stressors into 31 classes and an open‐source and interactive version of the dataset (https://jamesaorr.shinyapps.io/freshwater‐multiple‐stressors/). Inspired by our results, we provide a framework to help clarify whether statistical interactions detected by factorial experiments align with stressor interactions of interest, and we outline general guidelines for the design of multiple‐stressor experiments relevant to any system. We conclude by highlighting the research directions required to better understand freshwater ecosystems facing multiple stressors.
We used a novel machine learning framework to compile a dataset of 2396 multiple‐stressor experiments in freshwater systems and we provide a quantitative summary of this diverse field of research. We also propose a framework to help clarify whether statistical interactions detected by factorial experiments align with stressor interactions of interest, and we outline general guidelines for the design of multiple‐stressor experiments relevant to any system.
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