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The intrusion of Circumpolar Deep Water in the Amundsen and Bellingshausen Sea embayments of Antarctica causes ice shelves in the region to melt from below, potentially putting their stability at risk. Earlier studies have shown how digital elevation models can be used to obtain ice shelf basal melt rates at a high spatial resolution. However, there has been limited availability of high-resolution elevation data, a gap the Reference Elevation Model of Antarctica (REMA) has filled. In this study we use a novel combination of REMA and CryoSat-2 elevation data to obtain high-resolution basal melt rates of the Dotson Ice Shelf in a Lagrangian framework, at a 50 m spatial posting on a 3-yearly temporal resolution. We present a novel method: Basal melt rates Using REMA and Google Earth Engine (BURGEE). The high resolution of BURGEE is supported through a sensitivity study of the Lagrangian displacement. The high-resolution basal melt rates show a good agreement with an earlier basal melt product based on CryoSat-2. Both products show a wide melt channel extending from the grounding line to the ice front, but our high-resolution product indicates that the pathway and spatial variability of this channel is influenced by a pinning point on the ice shelf. This result emphasizes the importance of high-resolution basal melt rates to expand our understanding of channel formation and melt patterns. BURGEE can be expanded to a pan-Antarctic study of high-resolution basal melt rates. This will provide a better picture of the (in)stability of Antarctic ice shelves. [ABSTRACT FROM AUTHOR]

We introduce an algorithm (Watta) which automatically calculates supraglacial lake bathymetry and detects potential ice layers along tracks of the ICESat-2 (Ice, Cloud, and Land Elevation Satellite) laser altimeter. Watta uses photon heights estimated by the ICESat-2 ATL03 product and extracts supraglacial lake surface, bottom, and depth corrected for refraction and (sub-)surface ice cover in addition to producing surface heights at the native resolution of the ATL03 photon cloud. These measurements are used to constrain empirical estimates of lake depth from satellite imagery, which were thus far dependent on sparse sets of in situ measurements for calibration. Imagery sources include Landsat 8 Operational Land Imager (OLI), Sentinel-2, and high-resolution Planet Labs PlanetScope and SkySat data, used here for the first time to calculate supraglacial lake depths. The Watta algorithm was developed and tested using a set of 46 lakes near Sermeq Kujalleq (Jakobshavn) glacier in western Greenland, and we use multiple imagery sources (available for 45 of these lakes) to assess the use of the red vs. green band to extrapolate depths along a profile to full lake volumes. We use Watta-derived estimates in conjunction with high-resolution imagery from both satellite-based sources (tasked over the season) and nearly simultaneous Operation IceBridge CAMBOT (Continuous Airborne Mapping By Optical Translator) imagery (on a single airborne flight) for a focused study of the drainage of a single lake over the 2019 melt season. Our results suggest that the use of multiple imagery sources (both publicly available and commercial), in combination with altimetry-based depths, can move towards capturing the evolution of supraglacial hydrology at improved spatial and temporal scales. [ABSTRACT FROM AUTHOR]

Abstract Biodegradable polymeric materials may eventually replace biostable materials for medical applications, including therapeutic devices, scaffolds for tissue engineering, and drug-delivery vehicles. To further develop such materials, a more fundamental understanding is necessary to correlate parameters including chemical-composition distribution within a macromolecular structure with the final properties of the material, including particle-size. A wide variety of analytical techniques have been applied for the characterization of polymer materials, including hyphenated techniques such as comprehensive two-dimensional liquid chromatography (LC × LC). In this context, we have investigated enzymatic degradation of polyester-based nanoparticles, both in-solution and by the use of an immobilized-enzyme reactor (IMER). We have demonstrated for the first time the implementation of such an IMER in a size-exclusion chromatography system for on-line degradation and subsequent analysis of the polymer degradation products. The effect of residence times ranging from 12 s to 4 min on polymer degradation was assessed. IMER-assisted degradation is much faster compared to in-solution degradation, which requires several hours to days, and opens the possibility to use such reactors in LC × LC modulation interfaces. Graphical abstract Image 1 Highlights • A microfluidic immobilized-enzyme reactor for polymer degradation was developed. • Lipase was immobilized in a microfluidic reactor through vinylazlactone chemistry. • The reactor was used for on-line degradation of polymeric nanoparticles. • Degradation products were analysed on-line by size-exclusion chromatography. • A residence time of a few minutes proved sufficient for full degradation. [ABSTRACT FROM AUTHOR]

A critical step in the bottom-up characterization of proteomes is the conversion of proteins to peptides, by means of endoprotease digestion. Nowadays this method typically uses overnight digestion and as such represents a considerable bottleneck for high-throughput analysis. This report describes protein digestion using an immobilized-enzyme reactor (IMER), which enables accelerated digestion times that are completed within seconds to minutes. For rapid digestion to occur, a cyclic-olefin-copolymer microfluidic reactor was constructed containing trypsin immobilized on a polymer monolithic material through a 2-vinyl-4,4-dimethylazlactone linker. The IMER was applied for the rapid offline digestion of both singular protein standards and a complex protein mixture prior to liquid chromatography–electrospray ionisation-tandem mass spectrometry (LC–ESI-MS/MS) analysis. The effects of protein concentration and residence time in the IMER were assessed for protein standards of varying molecular weight between 11 and 240 kDa. Compared to traditional in-solution digestion, IMER-facilitated protein digestion at room temperature for 5 min yielded similar results in terms of sequence coverage and number of identified peptides. Good repeatability was demonstrated with a relative standard deviation of 6% for protein-sequence coverage. The potential of the IMER was also demonstrated for a complex protein mixture in the analysis of dried blood spots. Compared to a traditional workflow a similar number of proteins could be identified, while reducing the total analysis time from 22.5 h to 4 h and importantly omitting the sample-pre-treatment steps (denaturation, reduction, and alkylation). The identified proteins from two workflows showed similar distributions in terms of molecular weight and hydrophobic character. [ABSTRACT FROM AUTHOR]

In order to successfully tackle the truly complex separation problems arising from areas such as proteomics research, the development of ultra-efficient and fast separation technology is required. In spatial three-dimensional chromatography, components are separated in the space domain with each peak being characterized by its coordinates in a three-dimensional separation body. Spatial three-dimensional (3D-)LC has the potential to offer unprecedented resolving power when orthogonal retention mechanisms are applied, since the total peak capacity is the product of the three individual peak capacities. Due to parallel developments during the second- and third-dimension separations, the analysis time is greatly reduced compared to a coupled-column multi-dimensional LC approach. This communication discusses the different design aspects to create a microfluidic chip for spatial 3D-LC. The use of physical barriers to confine the flow between the individual developments, and flow control by the use of 2D and 3D flow distributors is discussed. Furthermore, the in situ synthesis of monolithic stationary phases is demonstrated. Finally, the potential performance of a spatial 3D-LC systems is compared with the performance obtained with state-of-the-art 1D-LC and (coupled-column) 2D-LC approaches via a Pareto-optimization approach. The proposed microfluidic device for 3D-LC featuring 16 2D channels and 256 3D channels can potentially yield a peak capacity of 8000 in a total analysis time of 10 minutes. [ABSTRACT FROM AUTHOR]

This study discusses the design aspects for the construction of a microfluidic device for comprehensive spatial two-dimensional liquid chromatography. In spatial two-dimensional liquid chromatography each peak is characterized by its coordinates in the plane. After completing the first-dimension separation all fractions are analyzed in parallel second-dimension separations. Hence, spatial two-dimensional liquid chromatography potentially provides much higher peak-production rates than a coupled column multi-dimensional liquid chromatography approach in which the second-dimension analyses are performed sequentially. A chip for spatial two-dimensional liquid chromatography has been manufactured from cyclic olefin copolymer and features a first-dimension separation channel and 21 parallel second-dimension separation channels oriented perpendicularly to the former. Compartmentalization of first- and second-dimension developments by physical barriers allowed for a preferential flow path with a minimal dispersion into the second-dimension separation channels. To generate a homogenous flow across all the parallel second-dimension channels, a radially interconnected flow distributor containing two zones of diamond-shaped pillars was integrated on-chip. A methacrylate ester based monolithic stationary phase with optimized macroporous structure was created in situ in the confines of the microfluidic chip. In addition, the use of a photomask was explored to localize monolith formation in the parallel second-dimension channels. Finally, to connect the spatial chip to the liquid chromatography instrument, connector ports were integrated allowing the use of Viper fittings. As an alternative, a chip holder with adjustable clasp locks was designed that allows the clamping force to be adjusted. [ABSTRACT FROM AUTHOR]

The gradient-performance limits of capillary ion chromatography have been assessed at maximum system pressure (34.5 MPa) using capillary columns packed with 4.1 μm macroporous anion-exchange particles coated with 65 nm positively-charged nanobeads. In analogy to the van-Deemter curve, the gradient performance was assessed applying different flow rates, while decreasing the gradient time inversely proportional to the increase in flow rate in order to maintain the same retention properties. The gradient kinetic-performance limits were determined at maximum system pressure, applying t G / t 0 = 5, 10, and 20. In addition, the effect of retention on peak width was assessed in gradient mode for mono-, di-, and trivalent inorganic anions. The peak width of late-eluting ions can be significantly reduced by using concave gradient, resulting in better detection sensitivity. A signal enhancement factor of 8 was measured for a late-eluting ion when applying a concave instead of a linear gradient. For the analysis of a complex anion mixture, a coupled column with a total length of 1.05 m was operated at the kinetic-performance limit applying a linear 250 min gradient ( t G / t 0 = 10). The peak capacity varied between 200 and 380 depending on analyte retention, and hence on charge and size of the ion. [ABSTRACT FROM AUTHOR]

A microfluidic membrane suppressor has been constructed to suppress ions of alkaline mobile-phases via an acid-base reaction across a sulfonated poly(tetrafluoroethylene)-based membrane and was evaluated for anion-exchange separations using conductivity detection. The membrane was clamped between two chip substrates, accommodating rectangular microchannels for the eluent and regenerant flow, respectively. Additionally, a clamp-on chip holder has been constructed which allows the alignment and stacking of different chip modules. The response and efficacy of the microfluidic chip suppressor was assessed for a wide range of eluent (KOH) concentrations, using 127 and 183µm thick membranes, while optimizing the flow rate and concentration of the regenerant solution (H2SO4). The optimal operating eluent flow rate was determined at 5µL/min, corresponding to the optimal van-Deemter flow velocity of commercially-available column technology, i.e. a 0.4mm i.d.×250mm long column packed with 7.5µm anion-exchange particles. When equilibrated at 10mM KOH, a 99% decrease in conductivity signal could be obtained within 5min when applying 10mM H2SO4 regenerant at 75µL/min. A background signal as low as 1.2µS/cm was obtained, which equals the performance of a commercially-available electrolytic hollow-fiber suppressor. When increasing the temperature of the membrane suppressor from 15 to 20°C, ion suppression was significantly improved allowing the application of 75mM KOH. The applicability of the chip suppressor has been demonstrated with an isocratic baseline separation of a mixture of seven inorganic ions, yielding plate numbers between 5300 and 10,600 and with a gradient separation of a complex ion mixture. [ABSTRACT FROM AUTHOR]

Thermal analysis and SEM were employed to gain insights in the different stages of morphology development and the thermal properties of polymer-monolithic stationary phases. The studied system was a thermally initiated free-radical copolymerization reaction at 70°C of styrene and divinylbenzene in the presence of tetrahydrofuran and 1-decanol. The key events in the early stages of morphology development are initiation, chain growth, branching, and cyclization, leading to microgel particles. Interparticle reactions through pendant vinyl groups lead to the formation of microgel clusters. The rapid increase in molecular weight and cross-link density of the microgel clusters causes a reaction-induced phase separation, and the formation of a macroscopic network of interconnected globules was observed (macrogelation) at around 45 min. After 3 h or 65% conversion, a space-filling macroporous monolithic network was observed. Afterwards, mainly growth of existing globules takes place, reducing the macropore size. The porogen ratio affects the timing of the reaction-induced phase separation, strongly influencing the morphology of the polymer material. The use of a mixture of divinylbenzene isomers yielded a monolithic material that is less cross-linked at the surface compared to the central part of the polymer backbone due to copolymerization-composition drift. The less cross-linked outer layer starts devitrifying at 100°C. [ABSTRACT FROM AUTHOR]

Abstract: The present study concerns the application of visualization methods, i.e. coomassie-brilliant-blue-R staining (CBB-R), silver-nitrate staining, and fluorescamine labeling, and subsequent MALDI-MS analysis of intact proteins and peptides on the surface of flat-bed monoliths, intended for spatial two-dimensional chromatographic separations. The use of 100-μm thick macroporous poly(butyl methacrylate-co-ethylene dimethacrylate) flat-bed monoliths renders a fixation step obsolete, so that CBB-R and silver-nitrate staining and destaining could be achieved in 10–15min as opposed to up to 24h, as is typical on 2D-PAGE gels. The detection limits remained comparable. The compatibility of the monolithic layer with subsequent MALDI-MS analysis of individual proteins and peptide spots was investigated with regards to mass accuracy, mass precision, resolution, and signal intensity. When comparing results from MALDI-MS analysis of proteins and peptides on a flat-bed monolith to results obtained directly on stainless-steel target plates, significant losses in mass precision, signal intensity, and an increased variation in resolution were observed. In addition, a loss in signal intensity up to two orders of magnitude was observed when using monolithic layers. After CCB-R and silver-nitrate staining and destaining to disrupt the protein–dye complexes no MALDI spectra with significant S/N ratios could be achieved. After fluorescamine labeling heterogeneous signals were observed, which resulted from a distribution in the number of fluorescence-labeled lysine groups and from the presence of labeled derivatives that had undergone condensation reactions. [Copyright &y& Elsevier]

The Atlantic meridional overturning circulation (AMOC) in a 600 years pre-industrial run of the newly developed EC-EARTH model features marked interdecadal variability with a dominant time-scale of 50-60 years. An oscillation of approximately 2 Sverdrup (1 Sv = 10 m s) is identified, which manifests itself as a monopole causing the overturning to simultaneously strengthen (/weaken) and deepen (/shallow) as a whole. Eight years before the AMOC peaks, density in the Labrador-Irminger Sea region reaches a maximum, triggering deep water formation. This density change is caused by a counterclockwise advection of temperature and salinity anomalies at lower latitudes, which we relate to the north-south excursions of the subpolar-subtropical gyre boundary and variations in strength and position of the subpolar gyre and the North Atlantic Current. The AMOC fluctuations are not directly forced by the atmosphere, but occur in a delayed response of the ocean to forcing by the North Atlantic Oscillation, which initiates 'intergyre'-gyre fluctuations. Associated with the AMOC is a 60-year sea surface temperature variability in the Atlantic, with a pattern and timescale showing similarities with the real-world Atlantic Multidecadal Variability. This good agreement with observations lends a certain degree of credibility that the mechanism that is described in this article could be seen as representative of the real climate system. [ABSTRACT FROM AUTHOR]

The application of high pressure and temperature in ion chromatography (IC) can significantly improve the efficiency and reduce the analysis time. In this work, the kinetic-performance limits of capillary IC columns with inner diameters of 400 μm packed with 4 and 7 μm macroporous anion-exchange particles were investigated employing a capillary ion-exchange instrument allowing column pressures up to 34 MPa and column temperatures up to 80 °C. Plate heights below 10 μm could be realized using capillary columns packed with 4 μm particles. Compared to conventional IC using 7 μm particles and pressures up to 21 MPa, a 40% improvement in plate number could be achieved when working at the kinetic performance limits at 34 MPa and using columns packed with 4 μm particles. Using coupled columns with a total length of 400 mm, a mixture of seven anions was separated within 7.5 min while yielding 20 000 plates. Increasing the temperature improved the performance limits when operating in the C-term region (for fast IC separation using columns <75 cm). Temperature also affected the retention properties and hence the selectivity. At higher temperature, retention for monovalent ions was mainly governed by ion diameter. An increase in retention with temperature was observed for small ions, and there was a decrease for ions having a larger diameter. The retention factor for divalent and trivalent anions increased with temperature. [ABSTRACT FROM AUTHOR]

LC-MS-based top-down proteomics involves the chromatographic separation and mass spectrometric characterization of intact proteins without prior enzymatic cleavage into peptides. This article describes the preparation of monolithic reversed-phase (RP) columns with optimized porous structure and their performance separating intact proteins. Peak capacities of around 600 could be achieved within a 2 h gradient. The combination of high-resolution monolith chromatography with high-accuracy time-of-flight mass spectrometrY (TOF-MS) allowed intact proteins and protein isoforms that differ only in their oxidation state to be distinguished. The article also describes various MS fragmentation techniques for the identification and the more detailed characterization of intact proteins. [ABSTRACT FROM AUTHOR]

Abstract: The separation of intact proteins, including protein isoforms arising from various amino-acid modifications, employing a poly(styrene-co-divinylbenzene) monolithic capillary column in high-performance liquid chromatography coupled on-line to a time-of-flight mass spectrometer (MS) is described. Using a 250mm×0.2mm monolithic capillary column high-sensitivity separations yielding peak capacities of >600 were achieved with a 2h linear gradient and formic acid added in the mobile phase as ion-pairing agent. The combination of high-resolution chromatography with high-accuracy MS allowed to distinguish protein isoforms that differ only in their oxidation and biotinylation state allowing the separation between structural isoforms. Finally, the potential to separate proteins isoforms due to glycosylation is discussed. [Copyright &y& Elsevier]

Because Antarctic surface melt is mostly driven by local processes, its simulation necessitates high‐resolution regional climate models (RCMs). However, the current horizontal resolution of RCMs (≈25–30 km) is inadequate for capturing small‐scale melt processes. To address this limitation, we present SUPREME (SUPer‐REsolution‐based Melt Estimation over Antarctica), a deep learning method to downscale surface melt to 5.5 km resolution using a physically‐informed super‐resolution model. The physical information integrated into the model originates from observations tied to surface melt, specifically remote sensing‐derived albedo and elevation. These remote sensing data, in addition to a Regional Atmospheric Climate Model (RACMO) run at 27 km resolution, account for the diverse drivers of surface melt across Antarctica, facilitating effective generalization beyond the training region of the Antarctic Peninsula. A comparison of SUPREME with a dynamically downscaled RACMO run at 5.5 km over the Antarctic Peninsula shows high accuracy, with average yearly RMSE and bias of 5.5 mm w.e. yr−1 and 4.5 mm w.e. yr−1, respectively. Validation at five automatic weather stations reveals SUPREME's marked improvement with substantially lower average RMSE (81 mm w.e.) compared to RACMO 27 km (129 mm w.e.). Beyond the training region, SUPREME aligns more closely with remote sensing products associated with surface melt than super‐resolution models lacking physical constraints. While further validation of SUPREME is needed, our study highlights the potential of super‐resolution techniques with physical constraints for high‐resolution surface melt monitoring in Antarctica, providing insights into the impacts of localized melting on processes affecting ice shelf integrity such as hydrofracturing. Plain Language Summary: To improve surface melt monitoring in Antarctica, high‐resolution climate models are essential. Existing models, like the Regional Atmospheric Climate Model (RACMO), do not have a fine enough spatial resolution to capture small‐scale melt processes. To overcome this, we introduce SUPREME (SUPer‐REsolution‐based Melt Estimation over Antarctica), a method that refines surface melt data to a higher resolution of 5.5 km using an advanced super‐resolution model. We enhance this model with physical information derived from observations directly related to surface melt, specifically using albedo and elevation data from remote sensing. By incorporating these observations, along with RACMO data at 27 km resolution, we account for the various triggers of surface melt across Antarctica. SUPREME accurately predicts high‐resolution surface melt beyond the training region of the Antarctic Peninsula, showing promising results compared to existing melt observations. Further validation is needed, but this approach, combining super‐resolution techniques and remote sensing data, holds potential for accurate surface melt monitoring in Antarctica. This may advance our understanding of the impacts of localized features on processes affecting ice shelf integrity such as meltwater‐induced hydrofracturing. Key Points: Our method downscales Antarctic surface melt from a regional climate model, employing a physically‐informed super‐resolution architectureThe super‐resolution model relies on physical information derived from remote sensing data, specifically surface albedo and elevationIncorporating physical information boosts model generalization, enabling accurate high‐resolution surface melt beyond the training region [ABSTRACT FROM AUTHOR]

In recent years a vast amount of glacier surface velocity data from satellite imagery has emerged based on correlation between repeat images. Thereby, much emphasis has been put on the fast processing of large data volumes and products with complete spatial coverage. The metadata of such measurements are often highly simplified when the measurement precision is lumped into a single number for the whole dataset, although the error budget of image matching is in reality neither isotropic nor constant over the whole velocity field. The spread of the correlation peak of individual image offset measurements is dependent on the image structure and the non-uniform flow of the ice and is used here to extract a proxy for measurement uncertainty. A quantification of estimation error or dispersion for each individual velocity measurement can be important for the inversion of, for instance, rheology, ice thickness and/or bedrock friction. Errors in the velocity data can propagate into derived results in a complex and exaggerating way, making the outcomes very sensitive to velocity noise and outliers. Here, we present a computationally fast method to estimate the matching precision of individual displacement measurements from repeat imaging data, focusing on satellite data. The approach is based upon Gaussian fitting directly on the correlation peak and is formulated as a linear least-squares estimation, making its implementation into current pipelines straightforward. The methodology is demonstrated for Sermeq Kujalleq (Jakobshavn Isbræ), Greenland, a glacier with regions of strong shear flow and with clearly oriented crevasses, and Malaspina Glacier, Alaska. Directionality within an image seems to be the dominant factor influencing the correlation dispersion. In our cases these are crevasses and moraine bands, while a relation to differential flow, such as shear, is less pronounced on the correlation spread. [ABSTRACT FROM AUTHOR]

The human metabolome provides a direct physiological read-out of an individual's actual health state and includes biomarkers that may predict disease or response to a treatment. The discovery and validation of these metabolomic biomarkers requires large-scale cohort studies, typically involving thousands of samples. This analytical challenge drives novel technological developments to enable faster, cheaper, and more comprehensive metabolomic analysis: more for less. This review summarises recent (2012–2018) developments towards this goal in all aspects of the analytical workflow, in relation to NMR but primarily to mass spectrometry (MS). Recent trends include miniaturisation and automation of extraction techniques, online coupling to fast analysis methods including direct infusion ion mobility MS, integrated microfluidic devices, and sharing and standardizing metabolomics software and data. The technological advances in metabolomics support its widespread application, integration with other -omics fields, and ultimately disease prediction and precision medicine. • Overviews trends towards faster, cheaper and more comprehensive metabolomics. • Features automation and miniaturisation to increase throughput and reduce costs. • Reports progress in fast separations and sample introduction for mass spectrometry. • Describes emergence of open-source and independent, automated, data analysis tools. • Substantiates the increasing power of metabolomics as a tool in precision medicine. [ABSTRACT FROM AUTHOR]

Geoscientific models are facing increasing challenges to exploit growing datasets coming from remote sensing. Universal differential equations (UDEs), aided by differentiable programming, provide a new scientific modelling paradigm enabling both complex functional inversions to potentially discover new physical laws and data assimilation from heterogeneous and sparse observations. We demonstrate an application of UDEs as a proof of concept to learn the creep component of ice flow, i.e. a nonlinear diffusivity differential equation, of a glacier evolution model. By combining a mechanistic model based on a two-dimensional shallow-ice approximation partial differential equation with an embedded neural network, i.e. a UDE, we can learn parts of an equation as nonlinear functions that then can be translated into mathematical expressions. We implemented this modelling framework as ODINN.jl, a package in the Julia programming language, providing high performance, source-to-source automatic differentiation (AD) and seamless integration with tools and global datasets from the Open Global Glacier Model in Python. We demonstrate this concept for 17 different glaciers around the world, for which we successfully recover a prescribed artificial law describing ice creep variability by solving ∼ 500 000 ordinary differential equations in parallel. Furthermore, we investigate which are the best tools in the scientific machine learning ecosystem in Julia to differentiate and optimize large nonlinear diffusivity UDEs. This study represents a proof of concept for a new modelling framework aiming at discovering empirical laws for large-scale glacier processes, such as the variability in ice creep and basal sliding for ice flow, and new hybrid surface mass balance models. [ABSTRACT FROM AUTHOR]

Geoscientific models are facing increasing challenges to exploit growing datasets coming from remote sensing. Universal Differential Equations (UDEs), aided by differentiable programming, provide a new scientific modelling paradigm enabling both complex functional inversions to potentially discover new physical laws and data assimilation from heterogeneous and sparse observations. We demonstrate an application of UDEs as a proof of concept to learn the creep component of ice flow, i.e. a nonlinear diffusivity differential equation, of a glacier evolution model. By combining a mechanistic model based on a 2D Shallow Ice Approximation Partial Differential Equation with an embedded neural network, i.e. a UDE, we can learn parts of an equation as nonlinear functions that then can be translated into mathematical expressions. We implemented this modelling framework as ODINN.jl, a package in the Julia programming language, providing high performance, source-to- source automatic differentiation (AD) and seamless integration with tools and global datasets from the Open Global Glacier Model in Python. We demonstrate this concept for 17 different glaciers around the world, for which we successfully recover a prescribed artificial law describing ice creep variability by solving ~500,000 Ordinary Differential Equations in parallel. Furthermore, we investigate which are the best tools in the scientific machine learning ecosystem in Julia to differentiate and optimize large nonlinear diffusivity UDEs. This study represents a proof of concept for a new modelling framework aiming at discovering empirical laws for large-scale glacier processes, such as the variability of ice creep and basal sliding for ice flow, and new hybrid surface mass balance models. [ABSTRACT FROM AUTHOR]

Canada's Queen Elizabeth Islands (QEI) contain ~14% of the world's glacier and ice-cap area. Sparse in-situ measurements indicate that interannual variability in glacier surface mass balance in this region is driven primarily by variations in summer melt, and that the annual surface mass balance of four index glaciers has become increasingly negative since 2007. Here, we use a 16-a record of satellite-derived mean summer (June–August) land surface temperatures (LST) from NASA's Moderate Resolution Imaging Spectroradiometer to investigate large-scale spatial and temporal variability in the duration and intensity of summer melt across glaciated surfaces in the QEI from 2000 to 2015. During this period, QEI mean summer glacier surface temperatures increased at an average rate of 0.06 ± 0.04°C a−1, for a total of nearly 1°C. Most of this increase occurred between 2005 and 2012, when mean summer near-surface (2 m) and upper-air (700 hPa) temperatures were 1.0–1.2°C higher than the 1948–2015 mean. There is a strong correlation between the glacier LST and 700 hPa air temperature records (r> 0.8). The period 2005–12, when mean summer LSTs were anomalously high, was likely the warmest period in the region since at least 1948. [ABSTRACT FROM AUTHOR]

Sample preparation is a challenge for high-throughput analysis, especially for volume-limited samples with low-abundant analytes. Ideally, sample preparation enriches the analytes of interest while removing the interferents to reduce the matrix effect and improve both sensitivity and quantification. In this study, a three-phase electroextraction (EE) method hyphenated to fast online liquid chromatography–mass spectrometry (LC-MS) was developed. Four model acidic drugs of relevance for drug monitoring in plasma, i.e. naproxen, fenoprofen, flurbiprofen, and ibuprofen, were utilized for the optimization and evaluation of the method. A Design of Experiment approach (Box-Behnken design) was used to optimize the critical parameters of the method, i.e., the type of organic solvent, pH of the sample and acceptor phase, and the extraction voltage and time. Good fitness (P < 0.02, R2 > 0.95) was observed for the developed quadratic model. Extraction could be achieved in less than 2 min (115 s) with enrichment factors (EF) up to 190 and extraction recoveries (ER) up to 38% for academic samples. Additionally, the optimized three-phase EE method was successfully applied to spiked plasma samples with low-abundant (50 ng mL−1) analytes and a low sample volume of 15 μL plasma in 10-fold diluted samples. Finally, two crucial contributors to the matrix effect of three-phase EE application on plasma samples were determined. Specifically, the ion-suppression effect in the MS source was reduced by the fast LC separation, and the matrix effect during extraction was negligible for the diluted protein-precipitated plasma samples. The developed three-phase EE method is easy to operate and provides fast and online extraction of trace-level acidic analytes from volume-limited biological samples. Therefore, this method can provide a potential solution for sample-preparation bottlenecks in high-throughput bioanalysis workflows. [Display omitted] • Fast extraction of acidic analytes, less than 2 min. • High enrichment factors, up to 190-fold. • Low sample consumption, down to 15 μL. • Hyphenation to fast LC-MS. • Limit of detection as low as 1.05 ng mL−1. [ABSTRACT FROM AUTHOR]

In Antarctica, Global Positioning System (GPS) vertical time series exhibit non‐linear signals over a wide range of temporal scales. To explain these non‐linearities, a number of hypotheses have been proposed, among them the short‐term rapid solid Earth response to contemporaneous ice mass change. Here we use GPS vertical time series to reveal the solid Earth response to variations in surface mass balance (SMB) in the Southern Antarctic Peninsula (SAP). At four locations in the SAP we show that interannual variations of SMB anomalies cause measurable elastic deformation. We use regional climate model SMB products to calculate the induced displacement assuming a perfectly elastic Earth. Our results show a reduction of the misfit when fitting a linear trend to GPS time series corrected for the elastic response to SMB variations. Our results imply that, for a better understanding of the glacial isostatic adjustment signal in Antarctica, SMB variability must be considered. Plain Language Summary: The Global Positioning System (GPS) allows us to measure the changing shape of the Earth's surface with high accuracy. These changes reflect multiple processes operating both within the Earth and at the surface. Using continuously recording GPS instruments in the Antarctic Peninsula, we study the response of the solid Earth to seasonal and annual variations in snow and ice accumulation over the past decade. We show that such loading triggers a measurable response that varies between years, complicating efforts to calculate the long‐term Earth response to past ice sheet change. We discuss the importance of our findings for understanding feedbacks between the solid Earth and the Antarctic ice sheet. Key Points: Global Positioning System time series of vertical deformation in the Southern Antarctic Peninsula show transient signalsModeled elastic deformation due to surface mass balance (SMB) variation can largely explain these signalsConsidering SMB elastic deformation improves estimates of linear vertical velocities [ABSTRACT FROM AUTHOR]

Icelandic glaciers have been losing mass since the Little Ice Age in the mid‐to‐late 1800s, with higher mass loss rates in the early 21st century, followed by a slowdown since 2011. As of yet, it remains unclear whether this mass loss slowdown will persist in the future. By reconstructing the contemporary (1958–2019) surface mass balance of Icelandic glaciers, we show that the post‐2011 mass loss slowdown coincides with the development of the Blue Blob, an area of regional cooling in the North Atlantic Ocean to the south of Greenland. This regional cooling signal mitigates atmospheric warming in Iceland since 2011, in turn decreasing glacier mass loss through reduced meltwater runoff. In a future high‐end warming scenario, North Atlantic cooling is projected to mitigate mass loss of Icelandic glaciers until the mid‐2050s. High mass loss rates resume thereafter as the regional cooling signal weakens. Plain Language Summary: Icelandic glaciers are currently losing mass, but with a recent slowdown in the last decade. We show that this slowdown coincides with the development of an area of regional cooling in the North Atlantic Ocean to the south of Greenland, called Blue Blob. Cooling in the Blue Blob has been mitigating atmospheric warming in Iceland since 2011, reducing glacier melt. In a future warmer climate, North Atlantic cooling is projected to persist until the mid‐2050s, further slowing down mass loss of Icelandic glaciers. High mass loss resumes thereafter as the regional cooling in the Blue Blob weakens. Key Points: We project daily surface mass balance of Icelandic glaciers at 500 m spatial resolution under a high‐end warming scenario until 2100We correlate the post‐2011 glacier mass loss slowdown with a local cooling in the North Atlantic OceanWe predict that local North Atlantic cooling will continue mitigating Icelandic glaciers mass loss until the mid‐2050s [ABSTRACT FROM AUTHOR]

Decadal climate predictions may have skill due to predictable components in boundary conditions (mainly greenhouse gas concentrations but also tropospheric and stratospheric aerosol distributions) and initial conditions (mainly the ocean state). We investigate the skill of temperature and precipitation hindcasts from a multi-model ensemble of four climate forecast systems based on coupled ocean-atmosphere models. Regional variations in skill with and without trend are compared with similarly analysed uninitialised experiments to separate the trend due to monotonically increasing forcings from fluctuations around the trend due to the ocean initial state and aerosol forcings. In temperature most of the skill in both multi-model ensembles comes from the externally forced trends. The rise of the global mean temperature is represented well in the initialised hindcasts, but variations around the trend show little skill beyond the first year due to the absence of volcanic aerosols in the hindcasts and the unpredictability of ENSO. The models have non-trivial skill in hindcasts of North Atlantic sea surface temperature beyond the trend. This skill is highest in the northern North Atlantic in initialised experiments and in the subtropical North Atlantic in uninitialised simulations. A similar result is found in the Pacific Ocean, although the signal is less clear. The uninitialised simulations have good skill beyond the trend in the western North Pacific. The initialised experiments show some skill in the decadal ENSO region in the eastern Pacific, in agreement with previous studies. However, the results in this study are not statistically significant ( p ≈ 0.1) by themselves. The initialised models also show some skill in forecasting 4-year mean Sahel rainfall at lead times of 1 and 5 years, in agreement with the observed teleconnection from the Atlantic Ocean. Again, the skill is not statistically significant ( p ≈ 0.2). Furthermore, uninitialised simulations that include volcanic aerosols have similar skill. It is therefore still an open question whether initialisation improves predictions of Sahel rainfall. We conclude that the main source of skill in forecasting temperature is the trend forced by rising greenhouse gas concentrations. The ocean initial state contributes to skill in some regions, but variations in boundary forcings such as aerosols are as important in decadal forecasting. [ABSTRACT FROM AUTHOR]

Mountain glaciers and ice caps are contributing significantly to present rates of sea level rise and will continue to do so over the next century and beyond. The Canadian Arctic Archipelago, located off the northwestern shore of Greenland, contains one-third of the global volume of land ice outside the ice sheets, but its contribution to sea-level change remains largely unknown. Here we show that the Canadian Arctic Archipelago has recently lost 61 ± 7 gigatonnes per year (Gt yr−1) of ice, contributing 0.17 ± 0.02 mm yr−1 to sea-level rise. Our estimates are of regional mass changes for the ice caps and glaciers of the Canadian Arctic Archipelago referring to the years 2004 to 2009 and are based on three independent approaches: surface mass-budget modelling plus an estimate of ice discharge (SMB+D), repeat satellite laser altimetry (ICESat) and repeat satellite gravimetry (GRACE). All three approaches show consistent and large mass-loss estimates. Between the periods 2004-2006 and 2007-2009, the rate of mass loss sharply increased from 31 ± 8 Gt yr−1 to 92 ± 12 Gt yr−1 in direct response to warmer summer temperatures, to which rates of ice loss are highly sensitive (64 ± 14 Gt yr−1 per 1 K increase). The duration of the study is too short to establish a long-term trend, but for 2007-2009, the increase in the rate of mass loss makes the Canadian Arctic Archipelago the single largest contributor to eustatic sea-level rise outside Greenland and Antarctica. [ABSTRACT FROM AUTHOR]

Meltwater from Himalayan glaciers sustains the flow of rivers such as the Ganges and Brahmaputra on which over half a billion people depend for day-to-day needs. Upstream areas are likely to be affected substantially by climate change, and changes in the magnitude and timing of meltwater supply are expected to occur in coming decades. About 10 % of the Himalayan glacier population terminates into proglacial lakes, and such lake-terminating glaciers are known to exhibit higher-than-average total mass losses. However, relatively little is known about the mechanisms driving exacerbated ice loss from lake-terminating glaciers in the Himalaya. Here we examine a composite (2017–2019) glacier surface velocity dataset, derived from Sentinel 2 imagery, covering central and eastern Himalayan glaciers larger than 3 km 2. We find that centre flow line velocities of lake-terminating glaciers (N = 70; umedian : 18.83 m yr -1 ; IQR – interquartile range – uncertainty estimate: 18.55–19.06 m yr -1) are on average more than double those of land-terminating glaciers (N = 249; umedian : 8.24 m yr -1 ; IQR uncertainty estimate: 8.17–8.35 m yr -1) and show substantially more heterogeneity than land-terminating glaciers around glacier termini. We attribute this large heterogeneity to the varying influence of lakes on glacier dynamics, resulting in differential rates of dynamic thinning, which causes about half of the lake-terminating glacier population to accelerate towards the glacier termini. Numerical ice-flow model experiments show that changes in the force balance at the glacier termini are likely to play a key role in accelerating the glacier flow at the front, with variations in basal friction only being of modest importance. The expansion of current glacial lakes and the formation of new meltwater bodies will influence the dynamics of an increasing number of Himalayan glaciers in the future, and these factors should be carefully considered in regional projections. [ABSTRACT FROM AUTHOR]

The aerodynamic roughness of heat, moisture, and momentum of a natural surface are important parameters in atmospheric models, as they co-determine the intensity of turbulent transfer between the atmosphere and the surface. Unfortunately this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available. In this study we adapt a bulk drag partitioning model to estimate the aerodynamic roughness length (z0m) such that it can be applied to 1D (i.e. unidirectional) elevation profiles, typically measured by laser altimeters. We apply the model to a rough ice surface on the K-transect (west Greenland Ice Sheet) using UAV photogrammetry, and we evaluate the modelled roughness against in situ eddy-covariance observations. We then present a method to estimate the topography at 1 m horizontal resolution using the ICESat-2 satellite laser altimeter, and we demonstrate the high precision of the satellite elevation profiles against UAV photogrammetry. The currently available satellite profiles are used to map the aerodynamic roughness during different time periods along the K-transect, that is compared to an extensive dataset of in situ observations. We find a considerable spatio-temporal variability in z0m , ranging between 10-4 m for a smooth snow surface and 10-1 m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets. [ABSTRACT FROM AUTHOR]

Surface melting occurs during summer on the Antarctic and Greenland ice sheets, but the volume of stored surface meltwater has been difficult to quantify due to a lack of accurate depth estimates. NASA's ICESat‐2 laser altimeter brings a new capability: photons penetrate water and are reflected from both the water and the underlying ice; the difference provides a depth estimate. ICESat‐2 sampled Amery Ice Shelf on January 2, 2019 and showed double returns from surface depressions, indicating meltwater. For four melt features, we compared depth estimates from eight algorithms: six based on ICESat‐2 and two from coincident Landsat‐8 and Sentinel‐2 imagery. All algorithms successfully identified surface water at the same locations. Algorithms based on ICESat‐2 produced the most accurate depths; the image‐based algorithms underestimated depths (by 30%–70%). This implies that ICESat‐2 depths can be used to tune image‐based algorithms, moving us closer to quantifying stored meltwater volumes across Antarctica and Greenland. Plain Language Summary: Summer surface melting on Antarctica's ice shelves is a small component of overall ice sheet mass loss but can be important for individual ice shelves and may increase as the climate warms. However, the volume of meltwater has been difficult to monitor because depth estimates are challenging. NASA's ICESat‐2 laser altimetry mission brings a new capability to this problem. ICESat‐2 532 nm photons (green light) are able to pass through water and reflect from both the water surface and the underlying ice surface; the difference in elevation provides meltwater depth estimates. In this pilot study, we compared depths from eight algorithms (six ICESat‐2 and two image based) over four Amery Ice Shelf meltwater lakes for an ICESat‐2 pass in early January 2019. The ICESat‐2 algorithms all produced more reliable depth estimates, and the image‐based algorithms underestimated the depths. This implies that ICESat‐2 water depths can be used to tune image‐based depth retrieval algorithms, enabling improved performance and allowing us to estimate more accurately how much surface melt is stored in melt ponds on the ice sheets each summer. Key Points: ICESat‐2 photons penetrate surface melt lakes and reflect from both the water surface and the underlying ice, providing depth estimatesWe compared depths from eight algorithms (six ICESat‐2 and two image‐based) for four lakes present on Amery Ice Shelf in January 2019Depths from ICESat‐2 were more accurate than from imagery (30%–70% too low); merging these data will improve estimates ice‐sheet wide [ABSTRACT FROM AUTHOR]

While the influence of surface melt on Antarctic ice shelf stability can be large, the duration and affected area of melt events are often small. Therefore, melt events are difficult to capture with remote sensing, as satellite sensors always face the trade-off between spatial and temporal resolution. To overcome this limitation, we developed UMelt: a surface melt record for all Antarctic ice shelves with a high spatial (500 m) and high temporal (12 h) resolution for the period 2016–2021. Our approach is based on a deep learning model, specifically a U-Net, which was developed in Google Earth Engine. The U-Net combines microwave remote sensing observations from three sources: Sentinel-1, Special Sensor Microwave Imager/Sounder (SSMIS), and Advanced Scatterometer (ASCAT). The U-Net was trained on the Shackleton Ice Shelf for melt seasons 2017–2021, using the fine-scale melt patterns of Sentinel-1 as reference data and SSMIS, ASCAT, a digital elevation model, and multi-year Sentinel-1 melt fraction as predictors. The trained U-Net performed well on the Shackelton Ice Shelf for test melt season 2016–2017 (accuracy: 91.3%; F1-score: 86.9%), and the Larsen C Ice Shelf, which was not considered during training (accuracy: 91.0%; F1-score: 89.3%). Using the trained U-Net model, we have successfully developed the UMelt record. UMelt allows Antarctic-wide surface melt to be detected at a small scale while preserving a high temporal resolution, which could lead to new insights into the response of ice shelves to a changing atmospheric forcing. • Satellite resolution trade-offs hamper accurate surface melt detection in Antarctica. • We present UMelt: An Antarctic-wide, high-resolution surface melt record. • UMelt was developed by merging multi-source remote sensing data using deep learning. • UMelt detects intricate surface melt events that were difficult to capture before. [ABSTRACT FROM AUTHOR]

Sample preparation is often reported as the main bottleneck of analytical processes. To meet the requirements of both high-throughput and high sensitivity, improved sample-preparation methods capable of fast analyte preconcentration are urgently needed. To this end, a new three-phase electroextraction (EE) method is presented that allows for ultrafast electroextraction hyphenated to flow-injection analysis mass spectrometry (FIA-MS). Four model compounds, i.e., propranolol, amitriptyline, bupivacaine, and oxeladin, were used to optimize and evaluate the method. Within only 30 s extraction time, enrichment factors (EF) of 105–569 and extraction recoveries (ER) of 10.2%–55.7% were achieved for these analytes, with limits of detection (LODs) ranging from 0.36 to 3.21 ng mL−1, good linear response function (R2 > 0.99), low relative standard deviation (0.6%–17.8%) and acceptable accuracy (73–112%). Finally, the optimized three-phase EE method was successfully applied to human urine and plasma samples. Our three-phase electroextraction method is simple to construct and offers ultrafast, online extraction of trace amounts of analytes from biological samples, and therefore has great potential for high-throughput analysis. Image 1 • Ultrafast analyte extraction, down to 30 s. • High enrichment factors of up to 569-fold. • Direct hyphenation to MS. • Simple extraction setup. • Limit of detection as low as 360 pg/mL. [ABSTRACT FROM AUTHOR]

Pine Island Glacier and Thwaites Glacier in the Amundsen Sea Embayment are among the fastest changing outlet glaciers in West Antarctica with large consequences for global sea level. Yet, assessing how much and how fast both glaciers will weaken if these changes continue remains a major uncertainty as many of the processes that control their ice shelf weakening and grounding line retreat are not well understood. Here, we combine multisource satellite imagery with modeling to uncover the rapid development of damage areas in the shear zones of Pine Island and Thwaites ice shelves. These damage areas consist of highly crevassed areas and open fractures and are first signs that the shear zones of both ice shelves have structurally weakened over the past decade. Idealized model results reveal moreover that the damage initiates a feedback process where initial ice shelf weakening triggers the development of damage in their shear zones, which results in further speedup, shearing, and weakening, hence promoting additional damage development. This damage feedback potentially preconditions these ice shelves for disintegration and enhances grounding line retreat. The results of this study suggest that damage feedback processes are key to future ice shelf stability, grounding line retreat, and sea level contributions from Antarctica. Moreover, they underline the need for incorporating these feedback processes, which are currently not accounted for in most ice sheet models, to improve sea level rise projections. [ABSTRACT FROM AUTHOR]

We present a reconstruction of historical (1950–2014) surface mass balance (SMB) of the Greenland ice sheet (GrIS) using a high-resolution regional climate model (RACMO2; ∼11 km) to dynamically downscale the climate of the Community Earth System Model version 2 (CESM2; ∼111 km). After further statistical downscaling to 1 km spatial resolution, evaluation using in situ SMB measurements and remotely sensed GrIS mass change shows good agreement. Comparison with an ensemble of previously conducted RACMO2 simulations forced by climate reanalysis demonstrates that the current product realistically represents the long-term average and variability of individual SMB components and captures the recent increase in meltwater runoff that accelerated GrIS mass loss. This means that, for the first time, climate forcing from an Earth system model (CESM2), which assimilates no observations, can be used without additional corrections to reconstruct the historical GrIS SMB and its recent decline that initiated mass loss in the 1990s. This paves the way for attribution studies of future GrIS mass loss projections and contribution to sea level rise. [ABSTRACT FROM AUTHOR]

• Absence of stationary-phase material in 1D channel deteriorates analyte transfer. • Porous materials in both 1D and 2D lead to reduced band broadening. • Thin or no spacers in the 2D are preferred in terms of band broadening. • Fabrication imperfections of 3D-printed devices increase A-term dispersion. • Pressure resistance is affected by the thickness of the encasing of devices. Conventional one-dimensional column-based liquid chromatographic (LC) systems do not offer sufficient separation power for the analysis of complex mixtures. Column-based comprehensive two-dimensional liquid chromatography offers a higher separation power, yet suffers from instrumental complexity and long analysis times. Spatial two-dimensional liquid chromatography can be considered as an alternative to column-based approaches. The peak capacity of the system is ideally the product of the peak capacities of the two dimensions, yet the analysis time remains relatively short due to parallel second-dimension separations. Aspects affecting the separation efficiency of this type of systems include flow distribution to homogeneously distribute the mobile phase for the second-dimension (2D) separation, flow confinement during the first-dimension (1D) separation, and band-broadening effects during analyte transfer from the 1D separation channel to the 2D separation area. In this study, the synergy between computational fluid dynamics (CFD) simulations and rapid prototyping was exploited to address band broadening during the 2D development and analyte transfer from 1D to 2D. Microfluidic devices for spatial two-dimensional liquid chromatography were designed, simulated, 3D-printed and tested. The effects of presence and thickness of spacers in the 2D separation area were addressed and leaving these out proved to be the most efficient solution regarding band broadening reduction. The presence of a stationary-phase material in the 1D channel had a great effect on the analyte transfer from the 1D to the 2D and the resulting band broadening. Finally, pressure limit of the fabricated devices and printability are discussed. [ABSTRACT FROM AUTHOR]

Surface mass balance (SMB) provides mass input to the surface of the Antarctic and Greenland Ice Sheets and therefore comprises an important control on ice sheet mass balance and resulting contribution to global sea level change. As ice sheet SMB varies highly across multiple scales of space (meters to hundreds of kilometers) and time (hourly to decadal), it is notoriously challenging to observe and represent in models. In addition, SMB consists of multiple components, all of which depend on complex interactions between the atmosphere and the snow/ice surface, large‐scale atmospheric circulation and ocean conditions, and ice sheet topography. In this review, we present the state‐of‐the‐art knowledge and recent advances in ice sheet SMB observations and models, highlight current shortcomings, and propose future directions. Novel observational methods allow mapping SMB across larger areas, longer time periods, and/or at very high (subdaily) temporal frequency. As a recent observational breakthrough, cosmic ray counters provide direct estimates of SMB, circumventing the need for accurate snow density observations upon which many other techniques rely. Regional atmospheric climate models have drastically improved their simulation of ice sheet SMB in the last decade, thanks to the inclusion or improved representation of essential processes (e.g., clouds, blowing snow, and snow albedo), and by enhancing horizontal resolution (5–30 km). Future modeling efforts are required in improving Earth system models to match regional atmospheric climate model performance in simulating ice sheet SMB, and in reinforcing the efforts in developing statistical and dynamic downscaling to represent smaller‐scale SMB processes. Plain Language Summary: Ice sheets, the largest class of glaciers, contain the majority of ice on Earth. The amount of ice contained in ice sheets changes constantly with the addition of new snow and ice, and melting taking place at the surface, base, and terminus of ice sheets. The balance between these inputs and outputs is known as the "mass balance." Processes affecting the addition and removal of snow on top of the ice sheet are termed the "surface mass balance" and include rainfall, moisture evaporation, snow‐transporting winds, and melting due to temperature changes. Scientists can now monitor these processes with tools on‐site, such as automated weather stations, Global Positioning Systems, and sensors that record high‐energy radiation (cosmic rays) originating outside the Earth's atmosphere. Several methods are also available where Earth‐orbiting satellites measure how ice is changing. Data collected in these ways have revealed how the surface mass balance varies over time and space. A better understanding of these processes is critical to predicting future behavior of ice sheets and their effect on sea level. Improvements to regional‐scale models in the past decade have allowed good simulations of surface mass balance, and the next step is to build models that work at a global scale. Key Points: Emerging (remote) observational techniques provide enhanced insights in spatial and temporal variability of ice sheet surface mass balance (SMB)Regional climate models can be used to assess ice sheet SMB, although deficiencies remain in representing subgrid processesIn the near future, Earth System Models can be used to assess internal variability, forced change, and positive feedbacks on ice sheet SMB [ABSTRACT FROM AUTHOR]

Rapid changes in thickness and velocity have been observed at many marine-terminating glaciers in Greenland, impacting the volume of ice they export, or discharge, from the ice sheet. While annual estimates of ice-sheet-wide discharge have been previously derived, higher-resolution records are required to fully constrain the temporal response of these glaciers to various climatic and mechanical drivers that vary in sub-annual scales. Here we sample outlet glaciers wider than 1 km (N=230) to derive the first continuous, ice-sheet-wide record of total ice sheet discharge for the 2000–2016 period, resolving a seasonal variability of 6 %. The amplitude of seasonality varies spatially across the ice sheet from 5 % in the southeastern region to 9 % in the northwest region. We analyze seasonal to annual variability in the discharge time series with respect to both modeled meltwater runoff, obtained from RACMO2.3p2, and glacier front position changes over the same period. We find that year-to-year changes in total ice sheet discharge are related to annual front changes (r2=0.59 , p=10-4) and that the annual magnitude of discharge is closely related to cumulative front position changes (r2=0.79), which show a net retreat of >400 km, or an average retreat of >2 km, at each surveyed glacier. Neither maximum seasonal runoff or annual runoff totals are correlated to annual discharge, which suggests that larger annual quantities of runoff do not relate to increased annual discharge. Discharge and runoff, however, follow similar patterns of seasonal variability with near-coincident periods of acceleration and seasonal maxima. These results suggest that changes in glacier front position drive secular trends in discharge, whereas the impact of runoff is likely limited to the summer months when observed seasonal variations are substantially controlled by the timing of meltwater input. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet (GrIS) is currently losing ice mass. In order to accurately predict future sea level rise, the mechanisms driving the observed mass loss must be better understood. Here, we combine data from the satellite gravimetry mission Gravity Recovery and Climate Experiment (GRACE), surface mass balance (SMB) output of the Regional Atmospheric Climate Model v. 2 (RACMO2), and ice discharge estimates to analyze the mass budget of Greenland at various temporal and spatial scales. We find that the mean rate of mass variations in Greenland observed by GRACE was between -277 and -269 Gt yr-1 in 2003-2012. This estimate is consistent with the sum (i.e., -304±126 Gt yr-1) of individual contributions - surface mass balance (SMB, 216±122 Gt yr-1) and ice discharge (520±31 Gt yr-1) - and with previous studies. We further identify a seasonal mass anomaly throughout the GRACE record that peaks in July at 80-120 Gt and which we interpret to be due to a combination of englacial and subglacial water storage generated by summer surface melting. The robustness of this estimate is demonstrated by using both different GRACE-based solutions and different meltwater runoff estimates (namely, RACMO2.3, SNOWPACK, and MAR3.9). Meltwater storage in the ice sheet occurs primarily due to storage in the high-accumulation regions of the southeast and northwest parts of Greenland. Analysis of seasonal variations in outlet glacier discharge shows that the contribution of ice discharge to the observed signal is minor (at the level of only a few gigatonnes) and does not explain the seasonal differences between the total mass and SMB signals. With the improved quantification of meltwater storage at the seasonal scale, we highlight its importance for understanding glaciohydrological processes and their contributions to the ice sheet mass variability. [ABSTRACT FROM AUTHOR]

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 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. [ABSTRACT FROM AUTHOR]

A major uncertainty in determining the mass balance of the Antarctic ice sheet from measurements of satellite gravimetry, and to a lesser extent satellite altimetry, is the poorly known correction for the ongoing deformation of the solid Earth caused by glacial isostatic adjustment (GIA). Although much progress has been made in consistently modeling the ice-sheet evolution throughout the last glacial cycle, as well as the induced bedrock deformation caused by these load changes, forward models of GIA remain ambiguous due to the lack of observational constraints on the ice sheet's past extent and thickness and mantle rheology beneath the continent. As an alternative to forward-modeling GIA, we estimate GIA from multiple spacegeodetic observations: Gravity Recovery and Climate Experiment (GRACE), Envisat/ICESat and Global Positioning System (GPS). Making use of the different sensitivities of the respective satellite observations to current and past surface-mass (ice mass) change and solid Earth processes, we estimate GIA based on viscoelastic response functions to disc load forcing. We calculate and distribute the viscoelastic response functions according to estimates of the variability of lithosphere thickness and mantle viscosity in Antarctica. We compare our GIA estimate with published GIA corrections and evaluate its impact in determining the ice-mass balance in Antarctica from GRACE and satellite altimetry. Particular focus is applied to the Amundsen Sea Sector in West Antarctica, where uplift rates of several centimetres per year have been measured by GPS. We show that most of this uplift is caused by the rapid viscoelastic response to recent ice-load changes, enabled by the presence of a low-viscosity upper mantle in West Antarctica. This paper presents the second and final contributions summarizing the work carried out within a European Space Agency funded study, REGINA(www.regina-science.eu). [ABSTRACT FROM AUTHOR]

The present paper discusses practical aspects of prototyping of microfluidic chips using cyclic olefin copolymer as substrate and the application in high-performance liquid chromatography. The developed chips feature a 60 mm long straight separation channel with circular cross section (500 μm i.d.) that was created using a micromilling robot. To irreversibly seal the top and bottom chip substrates, a solvent-vapor-assisted bonding approach was optimized, allowing to approximate the ideal circular channel geometry. Four different approaches to establish the micro-to-macro interface were pursued. The average burst pressure of the microfluidic chips in combination with an encasing holder was established at 38 MPa and the maximum burst pressure was 47 MPa, which is believed to be the highest ever report for these polymer-based microfluidic chips. Porous polymer monolithic frits were synthesized in-situ via UV-initiated polymerization and their locations were spatially controlled by the application of a photomask. Next, high-pressure slurry packing was performed to introduce 3 μm silica reversed-phase particles as the stationary phase in the separation channel. Finally, the application of the chip technology is demonstrated for the separation of alkyl phenones in gradient mode yielding baseline peak widths of 6 s by applying a steep gradient of 1.8 min at a flow rate of 10 μL/min. [ABSTRACT FROM AUTHOR]

Polymeric nanoparticles have become indispensable in modern society with a wide array of applications ranging from waterborne coatings to drug-carrier-delivery systems. While a large range of techniques exist to determine a multitude of properties of these particles, relating physicochemical properties of the particle to the chemical structure of the intrinsic polymers is still challenging. A novel, highly orthogonal separation system based on comprehensive two-dimensional liquid chromatography (LC x LC) has been developed. The system combines hydrodynamic chromatography (HDC) in the first-dimension to separate the particles based on their size, with ultrahigh-performance size-exclusion chromatography (SEC) in the second dimension to separate the constituting polymer molecules according to their hydrodynamic radius for each of 80 to 100 separated fractions. A chip-based mixer is incorporated to transform the sample by dissolving the separated nanoparticles from the first-dimension online in tetrahydrofuran. The polymer bands are then focused using stationary-phase-assisted modulation to enhance sensitivity, and the water from the first-dimension eluent is largely eliminated to allow interaction-free SEC. Using the developed system, the combined two-dimensional distribution of the particle-size and the molecular-size of a mixture of various polystyrene (PS) and polyacrylate (PACR) nanoparticles has been obtained within 60 min. [ABSTRACT FROM AUTHOR]

Sample preparation is a labor-intensive and time-consuming procedure, especially for the bioanalysis of small-volume samples with low-abundant analytes. To minimize losses and dilution, sample preparation should ideally be hyphenated to downstream on-line analysis such as liquid chromatography-mass spectrometry (LC-MS). In this study, an automated three-phase electro-extraction (EE) method coupled to machine vision was developed, integrated with a robotic autosampler hyphenated to LC-MS. Eight model compounds, i.e. amitriptyline, clemastine, clomipramine, haloperidol, loperamide, propranolol, oxeladin, and verapamil were utilized for the optimization and evaluation of the automated EE setup. The stability of automated EE was evaluated by monitoring the acceptor droplet size by machine vision and recording the current during EE. A Design of Experiment approach (Box-Behnken design) was utilized to optimize the critical parameters of the EE method, i.e., the ratio of formic acid in the sample to acceptor phase, extraction voltage, and extraction time. The developed quadratic models showed good fitness (p < 0.001, R2 > 0.95). Automated EE could be achieved in less than 2 min with enrichment factors (EF) up to 387 and extraction recoveries (ER) up to 97% for academic samples. Finally, the optimized EE method was successfully applied to both spiked human urine and plasma samples with low-concentration (50 ng mL−1) analytes and a low starting sample volume of 20 μL of plasma and urine in 10-fold diluted samples. The developed automated EE setup is easy to operate, provides a fast extraction method for analytes from volume-limited biological samples, and is hyphenated with on-line LC-MS analysis. Therefore, this method can provide fast and automated sample preparation to solve bottlenecks in high-throughput bioanalysis workflows. [Display omitted] • An automated EE setup was integrated with a robotic autosampler coupled to LC-MS. • The stability of EE process was assessed by machine vision and current monitoring. • High enrichment factors up to 387 of the automated three-phase EE were achieved. • Limits of detection were as low as 3.2 pg mL-1 in plasma samples. [ABSTRACT FROM AUTHOR]

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 lowlying (<2000ma.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 1.2mm SLE in 2012, the GrIS has recently become a major source of global mean sea level rise. [ABSTRACT FROM AUTHOR]

Observations over the past 2 decades show substantial ice loss associated with the speed-up of marine-terminating glaciers in Greenland. Here we use a regional three-dimensional outlet glacier model to simulate the behaviour of Jakobshavn Isbræ (JI) located in western Greenland. Our approach is to model and understand the recent behaviour of JI with a physical process-based model. Using atmospheric forcing and an ocean parametrization we tune our model to reproduce observed frontal changes of JI during 1990-2014. In our simulations, most of the JI retreat during 1990-2014 is driven by the ocean parametrization used and the glacier's subsequent response, which is largely governed by bed geometry. In general, the study shows significant progress in modelling the temporal variability of the flow at JI. Our results suggest that the overall variability in modelled horizontal velocities is a response to variations in terminus position. The model simulates two major accelerations that are consistent with observations of changes in glacier terminus. The first event occurred in 1998 and was triggered by a retreat of the front and moderate thinning of JI prior to 1998. The second event, which started in 2003 and peaked in the summer 2004, was triggered by the final break-up of the floating tongue. This break-up reduced the buttressing at the JI terminus that resulted in further thinning. As the terminus retreated over a reverse bed slope into deeper water, sustained high velocities over the last decade have been observed at JI. Our model provides evidence that the 1998 and 2003 flow accelerations are most likely initiated by the ocean parametrization used but JI's subsequent dynamic response was governed by its own bed geometry. We are unable to reproduce the observed 2010-2012 terminus retreat in our simulations. We attribute this limitation to either inaccuracies in basal topography or to misrepresentations of the climatic forcings that were applied. Nevertheless, the model is able to simulate the previously observed increase in mass loss through 2014. [ABSTRACT FROM AUTHOR]

Satellite gravimetry is a unique measurement technique for observing mass transport processes in the Earth system on a global scale, providing essential indicators of both subtle and dramatic global change. Although past and current satellite gravity missions have achieved spectacular science results, due to their limited spatial and temporal resolution as well as limited length of the available time series numerous important questions are still unresolved. Therefore, it is important to move from current demonstration capabilities to sustained observation of the Earth's gravity field. In an international initiative performed under the umbrella of the International Union of Geodesy and Geophysics, consensus on the science and user needs for a future satellite gravity observing system has been derived by an international panel of scientists representing the main fields of application, i.e., continental hydrology, cryosphere, ocean, atmosphere and solid Earth. In this paper the main results and findings of this initiative are summarized. The required target performance in terms of equivalent water height has been identified as 5 cm for monthly fields and 0.5 cm/year for long-term trends at a spatial resolution of 150 km. The benefits to meet the main scientific and societal objectives are investigated, and the added value is demonstrated for selected case studies covering the main fields of application. The resulting consolidated view on the required performance of a future sustained satellite gravity observing system represents a solid basis for the definition of technological and mission requirements, and is a prerequisite for mission design studies of future mission concepts and constellations. [ABSTRACT FROM AUTHOR]

The impact of initial conditions relative to external forcings in decadal integrations from an ensemble of state-of-the-art prediction models has been assessed using specifically designed sensitivity experiments (SWAP experiments). They consist of two sets of 10-yr-long ensemble hindcasts for two initial dates in 1965 and 1995 using either the external forcings from the "correct" decades or swapping the forcings between the two decades. By comparing the two sets of integrations, the impact of external forcing versus initial conditions on the predictability over multiannual time scales was estimated as the function of lead time of the hindcast. It was found that over time scales longer than about 1 yr, the predictability of sea surface temperatures (SSTs) on a global scale arises mainly from the external forcing. However, the correct initialization has a longer impact on SST predictability over specific regions such as the North Atlantic, the northwestern Pacific, and the Southern Ocean. The impact of initialization is even longer and extends to wider regions when below-surface ocean variables are considered. For the western and eastern tropical Atlantic, the impact of initialization for the 700-m heat content (HTC700) extends to as much as 9 years for some of the models considered. In all models the impact of initial conditions on the predictability of the Atlantic meridional overturning circulation (AMOC) is dominant for the first 5 years. [ABSTRACT FROM AUTHOR]

A multi-model analysis of Atlantic multidecadal variability is performed with the following aims: to investigate the similarities to observations; to assess the strength and relative importance of the different elements of the mechanism proposed by Delworth et al. (J Clim 6:1993-2011, 1993) (hereafter D93) among coupled general circulation models (CGCMs); and to relate model differences to mean systematic error. The analysis is performed with long control simulations from ten CGCMs, with lengths ranging between 500 and 3600 years. In most models the variations of sea surface temperature (SST) averaged over North Atlantic show considerable power on multidecadal time scales, but with different periodicity. The SST variations are largest in the mid-latitude region, consistent with the short instrumental record. Despite large differences in model configurations, we find quite some consistency among the models in terms of processes. In eight of the ten models the mid-latitude SST variations are significantly correlated with fluctuations in the Atlantic meridional overturning circulation (AMOC), suggesting a link to northward heat transport changes. Consistent with this link, the three models with the weakest AMOC have the largest cold SST bias in the North Atlantic. There is no linear relationship on decadal timescales between AMOC and North Atlantic Oscillation in the models. Analysis of the key elements of the D93 mechanisms revealed the following: Most models present strong evidence that high-latitude winter mixing precede AMOC changes. However, the regions of wintertime convection differ among models. In most models salinity-induced density anomalies in the convective region tend to lead AMOC, while temperature-induced density anomalies lead AMOC only in one model. However, analysis shows that salinity may play an overly important role in most models, because of cold temperature biases in their relevant convective regions. In most models subpolar gyre variations tend to lead AMOC changes, and this relation is strong in more than half of the models. [ABSTRACT FROM AUTHOR]

The modeling of the surface mass balance (SMB) of the Greenland Ice Sheet (GIS) requires high-resolution models in order to capture the observed large gradients in the steep marginal areas. Until now, global climate models have not been considered suitable to model ice sheet SMB owing to model biases and insufficient resolution. This study analyzes the GIS SMB simulated for the period 1850-2005 by the Community Earth System Model (CESM), which includes a new ice sheet component with multiple elevation classes for SMB calculations. The model is evaluated against observational data and output from the regional model Regional Atmospheric Climate Model version 2 (RACMO2). Because of a lack of major climate biases, a sophisticated calculation of snow processes (including surface albedo evolution) and an adequate downscaling technique, CESM is able to realistically simulate GIS surface climate and SMB. CESM SMB agrees reasonably well with in situ data from 475 locations ( r = 0.80) and output from RACMO2 ( r = 0.79). The simulated mean SMB for 1960-2005 is 359 ± 120 Gt yr−1 in the range of estimates from regional climate models. The simulated seasonal mass variability is comparable with mass observations from the Gravity Recovery and Climate Experiment (GRACE), with synchronous annual maximum (May) and minimum (August-September) and similar amplitudes of the seasonal cycle. CESM is able to simulate the bands of precipitation maxima along the southeast and northwest margins, but absolute precipitation rates are underestimated along the southeastern margin and overestimated in the high interior. The model correctly simulates the major ablation areas. Total refreezing represents 35% of the available liquid water (the sum of rain and melt). [ABSTRACT FROM AUTHOR]

Glaciers distinct from the Greenland and Antarctic Ice Sheets are losing large amounts of water to the world's oceans. However, estimates of their contribution to sea level rise disagree. We provide a consensus estimate by standardizing existing, and creating new, mass-budget estimates from satellite gravimetry and altimetry and from local glaciological records. In many regions, local measurements are more negative than satellite-based estimates. All regions lost mass during 2003-2009, with the largest losses from Arctic Canada, Alaska, coastal Greenland, the southern Andes, and high-mountain Asia, but there was little loss from glaciers in Antarctica. Over this period, the global mass budget was -259 ± 28 gigatons per year, equivalent to the combined loss from both ice sheets and accounting for 29 ± 13% of the observed sea level rise. [ABSTRACT FROM AUTHOR]

Abstract: Within the last decade, the Greenland ice sheet (GrIS) and its surroundings have experienced record high surface temperatures (), ice sheet melt extent () and record-low summer sea-ice extent (). Using three independent data sets, we derive, for the first time, consistent ice-mass trends and temporal variations within seven major drainage basins from gravity fields from the Gravity Recovery and Climate Experiment (GRACE; ), surface-ice velocities from Inteferometric Synthetic Aperture Radar (InSAR; ) together with output of the regional atmospheric climate modelling (RACMO2/GR; ), and surface-elevation changes from the Ice, cloud and land elevation satellite (ICESat; ). We show that changing ice discharge (D), surface melting and subsequent run-off (M/R) and precipitation (P) all contribute, in a complex and regionally variable interplay, to the increasingly negative mass balance of the GrIS observed within the last decade. Interannual variability in P along the northwest and west coasts of the GrIS largely explains the apparent regional mass loss increase during 2002–2010, and obscures increasing M/R and D since the 1990s. In winter 2002/2003 and 2008/2009, accumulation anomalies in the east and southeast temporarily outweighed the losses by M/R and D that prevailed during 2003–2008, and after summer 2010. Overall, for all basins of the GrIS, the decadal variability of anomalies in P, M/R and D between 1958 and 2010 (w.r.t. 1961–1990) was significantly exceeded by the regional trends observed during the GRACE period (2002–2011). [Copyright &y& Elsevier]