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Inversion methods play an important role in glacier models, both to calibrate and estimate parameters of interest (e.g. Glen's coefficients or basal sliding). However, inversions are usually made for each glacier individually, without using any global information, i.e. without deriving general laws governing the spatiotemporal variability of those parameters. The reason behind this limitation is twofold: the statistical challenge of making constrained inferences with multiple glaciers, and the computational limitation of processing massive glacier datasets. Machine learning powered with differential programming is a tool that can address both limitations. We introduce a statistical framework for functional inversion of physical processes governing global-scale glacier changes. We apply this framework to invert a prescribed function describing the spatial variability of Glen’s coefficient (A). Instead of estimating a single parameter per glacier, we learn the parameters of a regressor (i.e. a neural network) that encodes information related to each glacier (i.e. long-term air temperature) to the parameter of interest. The inversion is done by embedding a neural network inside the Shallow Ice Approximation PDE - resulting in a Universal Differential Equation - with the goal of minimizing the error on the simulated ice surface velocities. This framework is built inside ODINN.jl, an open-source package in the Julia programming language for global glacier evolution modelling using Universal Differential Equations. ODINN exploits the latest generation of ice surface velocities and geodetic mass balance remote sensing products, as well as many preprocessing tools from the Open Global Glacier Model (OGGM)., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

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 ca 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.

It has been argued that the −5 °C annual mean 2 m air temperature isotherm defines a limit of ice shelf viability on the Antarctic Peninsula as melt ponding increases at higher temperatures. It is, however, presently unknown whether this threshold can also be applied to other Antarctic ice shelves. Here we use two present-day and three future high-resolution Antarctic climate simulations to predict warming thresholds for Antarctic ice shelf melt pond formation on the basis of the melt-over-accumulation ratio. The associated warming thresholds match well with observed melt pond volumes and are found to be spatially highly variable and controlled by snow accumulation. For relatively wet ice shelves, the −5 °C temperature threshold was confirmed; but cold and dry ice shelves such as Amery, Ross and Filchner-Ronne are more vulnerable than previously thought, with threshold temperatures well below −15 °C. Coupled Model Intercomparison Project Phase 6 models predict that towards the end of this century these thresholds can be reached on many ice shelves, even on cold ice shelves and under moderate warming scenarios.

Retreating and thinning glaciers are icons of climate change and impact the local hazard situation, regional runoff as well as global sea level. For past reports of the Intergovernmental Panel on Climate Change (IPCC), regional glacier change assessments were challenged by the small number and heterogeneous spatio-temporal distribution of in situ measurement series and uncertain representativeness for the respective mountain range as well as by spatial and temporal limitations and technical challenges of geodetic methods. Towards IPCC SROCC and AR6, there have been considerable improvements with respect to available geodetic datasets. Geodetic volume change assessments for entire mountain ranges have become possible thanks to recently available and comparably accurate digital elevation models (e.g., from ASTER or TanDEM-X). At the same time, new spaceborne altimetry (CryoSat-2, IceSat-2) and gravimetry (GRACE-FO) missions are in orbit and about to release data products to the science community. This opens new opportunities but also comes with new challenges for glacier mass-change assessments.In this presentation, we introduce the Glacier Mass Balance Intercomparison Exercise (GlaMBIE; https://glambie.org) of the European Space Agency, which is building on existing activities and the network of the International Association of Cryospheric Sciences (IACS) working group on Regional Assessments of Glacier Mass Change (RAGMAC) to tackle these challenges in a community effort. We will present our approach to develop a common framework for regional-scale glacier mass-change estimates towards a new data-driven consensus estimate of regional and global mass changes from glaciological, DEM-differencing, altimetric, and gravimetric methods., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The mass balance of the Antarctic Ice Sheet (AIS) can be obtained from time-variable gravity fields from GRACE and GRACE-FO. This is useful to investigate the ice sheet's adaption to a changing climate and its contribution to the global mean sea level. However, the correction for the present-day glacial isostatic adjustment (GIA) in Antarctica is still the largest uncertainty contributor in gravimetric mass balances. Lacks of knowledge of the ice loading history and the solid Earth's rheology lead to a large spread of GIA predictions from forward modelling approaches. We developed a method (Willen et al. 2022, https://doi.org/10.1007/s00190-022-01651-8) that allows to spatially resolve GIA, ice mass changes, and firn thickness changes in Antarctica within a globally consistent framework using geodetic satellite data and results of climate modelling. From simulation experiments, we found that the signal separation is possible despite data limitations as long as accounting for spatial error covariances of the input data sets. Here, we present and discuss results from a global inversion of satellite gravimetry data (from GRACE/GRACE-FO), satellite altimetry data (CryoSat-2), regional climate modelling (from RACMO2), and modelled firn thickness changes (from IMAU-FDM) over the time period Nov 2010 to Dec 2020. Furthermore, we will discuss the advantage of implementing this methodology in a global sea level inversion framework., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Ice loss from the Greenland ice sheet is one of the largest sources of contemporary sea-level rise (SLR). While process-based models place timescales on Greenland’s deglaciation, their confidence is obscured by model shortcomings including imprecise atmospheric and oceanic couplings. Here, we present a complementary approach resolving ice sheet disequilibrium with climate constrained by satellite-derived bare-ice extent, tidewater sector ice flow discharge and surface mass balance data. We find that Greenland ice imbalance with the recent (2000–2019) climate commits at least 274 ± 68 mm SLR from 59 ± 15 × 103 km2 ice retreat, equivalent to 3.3 ± 0.9% volume loss, regardless of twenty-first-century climate pathways. This is a result of increasing mass turnover from precipitation, ice flow discharge and meltwater run-off. The high-melt year of 2012 applied in perpetuity yields an ice loss commitment of 782 ± 135 mm SLR, serving as an ominous prognosis for Greenland’s trajectory through a twenty-first century of warming.

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.

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.

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.

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.

Glaciers in the Arctic respond sensitively to climate change, recording the polar amplification of global warming with increasing mass loss. Here, we use glacier mass balances in Svalbard and northern Arctic Canada to categorize tropospheric variability and the associated summer circulation over the Arctic. We establish a link between annual glacier mass balances and their respective atmospheric forcings since 1950 using GRACE/GRACE-FO satellite data (2002–2021), as well as regional climate models and reanalysis data (1950–2019). We find that asynchronous behaviour of mass balance between the regions has become very likely since the early 2000s, exceeding the range of previous decadal variability. Related tropospheric circulation exhibits more meridional patterns, a greater influence of meridional heat advection and a wavier summer circulation. The traceable impact on glacier mass balances emphasizes the importance of dynamic next to thermodynamic climate changes for the future of glacier mass loss, Arctic ecology and societal impacts.

Immobilized-enzyme reactors (IMERs) are flow-through devices containing enzymes that are physically confined or localized with retention of their catalytic activities. IMERs can be used repeatedly and continuously and have been applied for (bio)polymer degradation, proteomics, biomarker discovery, inhibitor screening, and detection. Online integration of IMERs with analytical instrumentation, such as high-performance liquid chromatography (HPLC) systems, reduces the time needed for multi-step workflows, reduces the need for sample handling, and enables automation. However, online integration can also be challenging, as reaching its full potential requires complex instrumental setups and experienced users. This review aims to provide an assessment of recent advances and challenges in online IMER-based (analytical) LC platforms, covering publications from 2014-2021. A critical discussion of challenges often encountered in IMER fabrication, sample preparation, integration into the analytical workflow, long-term usage, and of potential ways to overcome these is provided. Finally, the obstacles preventing the proliferation of IMERs as efficient tools for high-throughput pharmacological, industrial, and biological studies are discussed.

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 spatiooral 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.

The original version of this Article contained an error in the spelling of the author Seongsu Jeong, which was incorrectly given as Seonsgu Jeong. This has now been corrected in both the PDF and HTML versions of the Article.

The original version of this Article contained an error in the spelling of the author Seongsu Jeong, which was incorrectly given as Seonsgu Jeong. This has now been corrected in both the PDF and HTML versions of the Article.

Observations and models agree that the Greenland Ice Sheet (GrIS) surface mass balance (SMB) has decreased since the end of the 1990s due to an increase in meltwater runoff and that this trend will accelerate in the future. However, large uncertainties remain, partly due to different approaches for modelling the GrIS SMB, which have to weigh physical complexity or low computing time, different spatial and temporal resolutions, different forcing fields, and different ice sheet topographies and extents, which collectively make an inter-comparison difficult. Our GrIS SMB model intercomparison project (GrSMBMIP) aims to refine these uncertainties by intercomparing 13 models of four types which were forced with the same ERA-Interim reanalysis forcing fields, except for two global models. We interpolate all modelled SMB fields onto a common ice sheet mask at 1 km horizontal resolution for the period 1980-2012 and score the outputs against (1) SMB estimates from a combination of gravimetric remote sensing data from GRACE and measured ice discharge; (2) ice cores, snow pits and in situ SMB observations; and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting model deficiencies in an accurate representation of the GrIS ablation zone extent and processes related to surface melt and runoff. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of the same order as RCMs compared with observations and therefore remain useful tools for long-term simulations or coupling with ice sheet models. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present-day SMB relative to observations, suggesting that biases are not systematic among models and that this ensemble estimate can be used as a reference for current climate when carrying out future model developments. However, a higher density of in situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 m w.e. yr-1 due to large discrepancies in modelled snowfall accumulation.

ArticlePublished: 10 December 2019This is an unedited manuscript that has been accepted for publication. Nature Research are providing this early version of the manuscript as a service to our customers. The manuscript will undergo copyediting, typesetting and a proof review before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.Mass balance of the Greenland Ice Sheet from 1992 to 2018The IMBIE TeamNature (2019)Cite this article6914 Accesses1410 AltmetricMetricsdetailsAbstractIn recent decades, the Greenland Ice Sheet has been a major contributor to global sea-level rise1,2, and it is expected to be so in the future3. Although increases in glacier flow4–6 and surface melting7–9 have been driven by oceanic10–12 and atmospheric13,14 warming, the degree and trajectory of today’s imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. Although the ice sheet was close to a state of balance in the 1990s, annual losses have risen since then, peaking at 335 ± 62 billion tonnes per year in 2011. In all, Greenland lost 3,800 ± 339 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.6 ± 0.9 millimetres. Using three regional climate models, we show that reduced surface mass balance has driven 1,971 ± 555 billion tonnes (52%) of the ice loss owing to increased meltwater runoff. The remaining 1,827 ± 538 billion tonnes (48%) of ice loss was due to increased glacier discharge, which rose from 41 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. Between 2013 and 2017, the total rate of ice loss slowed to 217 ± 32 billion tonnes per year, on average, as atmospheric circulation favoured cooler conditions15 and as ocean temperatures fell at the terminus of Jakobshavn Isbræ16. Cumulative ice losses from Greenland as a whole have been close to the IPCC’s predicted rates for their high-end climate warming scenario17, which forecast an additional 50 to 120 millimetres of global sea-level rise by 2100 when compared to their central estimate.

Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows changes (e.g., acceleration) to be detected in one or more components. Study of the sea-level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Programme Grand Challenge entitledRegional Sea Level and Coastal Impacts, an international effort involving the sea-level community worldwide has been recently initiated with the objective of assessing the various datasets used to estimate components of the sea-level budget during the altimetry era (1993 to present). These datasets are based on the combination of a broad range of space-based and in situ observations, model estimates, and algorithms. Evaluating their quality, quantifying uncertainties and identifying sources of discrepancies between component estimates is extremely useful for various applications in climate research. This effort involves several tens of scientists from about 50 research teams/institutions worldwide (www.wcrp-climate.org/grand-challenges/gc-sea-level, last access: 22 August 2018). The results presented in this paper are a synthesis of the first assessment performed during 2017–2018. We present estimates of the altimetry-based global mean sea level (average rate of 3.1 ± 0.3 mm yr−1and acceleration of 0.1 mm yr−2over 1993–present), as well as of the different components of the sea-level budget (http://doi.org/10.17882/54854, last access: 22 August 2018). We further examine closure of the sea-level budget, comparing the observed global mean sea level with the sum of components. Ocean thermal expansion, glaciers, Greenland and Antarctica contribute 42 %, 21 %, 15 % and 8 % to the global mean sea level over the 1993–present period. We also study the sea-level budget over 2005–present, using GRACE-based ocean mass estimates instead of the sum of individual mass components. Our results demonstrate that the global mean sea level can be closed to within 0.3 mm yr−1(1σ). Substantial uncertainty remains for the land water storage component, as shown when examining individual mass contributions to sea level.

Satellite gravimetry data acquired by the Gravity Recovery and Climate Experiment (GRACE) allows to derive the temporal evolution in ice mass for both the Antarctic Ice Sheet (AIS) and the Greenland Ice Sheet (GIS). Various algorithms have been used in a wide range of studies to generate Gravimetric Mass Balance (GMB) products. Results from different studies may be affected by substantial differences in the processing, including the applied algorithm, the utilised background models and the time period under consideration. This study gives a detailed description of an assessment of the performance of GMB algorithms using actual GRACE monthly solutions for a prescribed period as well as synthetic data sets. The inter-comparison exercise was conducted in the scope of the European Space Agency’s Climate Change Initiative (CCI) project for the AIS and GIS, and was, for the first time, open to everyone. GMB products generated by different groups could be evaluated and directly compared against each other. For the period from 2003-02 to 2013-12, estimated linear trends in ice mass vary between −99 Gt/yr and −108 Gt/yr for the AIS and between −252 Gt/yr and −274 Gt/yr for the GIS, respectively. The spread between the solutions is larger if smaller drainage basins or gridded GMB products are considered. Finally, findings from the exercise formed the basis to select the algorithms used for the GMB product generation within the AIS and GIS CCI project.

Glaciers outside of the ice sheets are known to be important contributors to sea level rise. In this work, we provide an overview of changes in the mass of the world's glaciers, excluding those in Greenland and Antarctica, between 2002 and 2016, based on satellite gravimetry observations of the Gravity Recovery and Climate Experiment (GRACE). Glaciers lost mass at a rate of 199 ± 32 Gt yr −1 during this 14-yr period, equivalent to a cumulative sea level contribution of 8 mm. We present annual mass balances for 17 glacier regions, that show a qualitatively good agreement with published estimates from in situ observations. We find that annual mass balance varies considerably from year to year, which can in part be attributed to changes in the large-scale circulation of the atmosphere. These variations, combined with the relatively short observational record, hamper the detection of acceleration of glacier mass loss. Our study highlights the need for continued observations of the Earth's glacierized regions.

Presentation atPOLAR 2018, Davos, Switzerland, 15-26 June 2018

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 Antarctic Ice Sheet is an important indicator of climate change and driver of sea-level rise. Here we combine satellite observations of its changing volume, flow and gravitational attraction with modelling of its surface mass balance to show that it lost 2,720 ± 1,390 billion tonnes of ice between 1992 and 2017, which corresponds to an increase in mean sea level of 7.6 ± 3.9 millimetres (errors are one standard deviation). Over this period, ocean-driven melting has caused rates of ice loss from West Antarctica to increase from 53 ± 29 billion to 159 ± 26 billion tonnes per year; ice-shelf collapse has increased the rate of ice loss from the Antarctic Peninsula from 7 ± 13 billion to 33 ± 16 billion tonnes per year. We find large variations in and among model estimates of surface mass balance and glacial isostatic adjustment for East Antarctica, with its average rate of mass gain over the period 1992–2017 (5 ± 46 billion tonnes per year) being the least certain.

Presentation toWAIS 2017 workshop, Seattle, USA, 10 October 2017

Presentation atWorkshop on Glacial Isostatic Adjustment and Elastic Deformation, Reykjavik, Iceland, 5-7 September 2017

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.

Accurate quantification of the millennial-scale mass balance of the Greenland ice sheet (GrIS) and its contribution to global sea-level rise remain challenging because of sparse in situ observations in key regions. Glacial isostatic adjustment (GIA) is the ongoing response of the solid Earth to ice and ocean load changes occurring since the Last Glacial Maximum (LGM; ~21 thousand years ago) and may be used to constrain the GrIS deglaciation history. We use data from the Greenland Global Positioning System network to directly measure GIA and estimate basin wide mass changes since the LGM. Unpredicted, large GIA uplift rates of +12 mm/year are found in southeast Greenland. These rates are due to low upper mantle viscosity in the region, from when Greenland passed over the Iceland hot spot about 40 million years ago. This region of concentrated soft rheology has a profound influence on reconstructing the deglaciation history of Greenland. We reevaluate the evolution of the GrIS since LGM and obtain a loss of 1.5-m sea-level equivalent from the northwest and southeast. These same sectors are dominating modern mass loss. We suggest that the present destabilization of these marine-based sectors may increase sea level for centuries to come. Our new deglaciation history and GIA uplift estimates suggest that studies that use the Gravity Recovery and Climate Experiment satellite mission to infer present-day changes in the GrIS may have erroneously corrected for GIA and underestimated the mass loss by about 20 gigatons/year.

Analytical techniques hyphenated with mass-spectrometry, such as high-performance liquid chromatography – mass spectrometry (HPLC–MS), have become indispensable tools for the analysis of complex protein samples. However, to reduce spectral complexity, and to minimize ion suppression of low abundant species, a high-performance LC separation is required prior to MS analysis. A major bottleneck is the limited separation power of the LC strategies currently used. For fast separations with a total analysis time of 10 min, the peak capacity that can be reached with column-based one- and two-dimensional LC systems approaches 200 and 600, respectively, while higher peak capacities come at the expense of long analysis times. Alternatively, for so-called spatial three-dimensional (3D)-LC components are separated in the space domain with each peak being characterized by its coordinates in a three-dimensional separation body. Spatial 3D-LC has the potential to offer unprecedented resolving power, 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. Our research addresses the different design aspects to create a microfluidic chip for spatial 3D-LC. The proposed microfluidic device featuring 16 parallel second-dimension channels and 256 parallel third-dimension channels can potentially yield a peak capacity of 8000 in a total analysis time of 10 minutes.

Present destabilization of marine-based sectors in Greenland may increase sea level for centuries to come., Accurate quantification of the millennial-scale mass balance of the Greenland ice sheet (GrIS) and its contribution to global sea-level rise remain challenging because of sparse in situ observations in key regions. Glacial isostatic adjustment (GIA) is the ongoing response of the solid Earth to ice and ocean load changes occurring since the Last Glacial Maximum (LGM; ~21 thousand years ago) and may be used to constrain the GrIS deglaciation history. We use data from the Greenland Global Positioning System network to directly measure GIA and estimate basin-wide mass changes since the LGM. Unpredicted, large GIA uplift rates of +12 mm/year are found in southeast Greenland. These rates are due to low upper mantle viscosity in the region, from when Greenland passed over the Iceland hot spot about 40 million years ago. This region of concentrated soft rheology has a profound influence on reconstructing the deglaciation history of Greenland. We reevaluate the evolution of the GrIS since LGM and obtain a loss of 1.5-m sea-level equivalent from the northwest and southeast. These same sectors are dominating modern mass loss. We suggest that the present destabilization of these marine-based sectors may increase sea level for centuries to come. Our new deglaciation history and GIA uplift estimates suggest that studies that use the Gravity Recovery and Climate Experiment satellite mission to infer present-day changes in the GrIS may have erroneously corrected for GIA and underestimated the mass loss by about 20 gigatons/year.

Accurate quantification of the millennial-scale mass balance of the Greenland ice sheet (GrIS) and its contribution to global sea-level rise remain challenging because of sparse in situ observations in key regions. Glacial isostatic adjustment (GIA) is the ongoing response of the solid Earth to ice and ocean load changes occurring since the Last Glacial Maximum (LGM; ~21 thousand years ago) and may be used to constrain the GrIS deglaciation history. We use data from the Greenland Global Positioning System network to directly measure GIA and estimate basin-wide mass changes since the LGM. Unpredicted, large GIA uplift rates of +12 mm/year are found in southeast Greenland. These rates are due to low upper mantle viscosity in the region, from when Greenland passed over the Iceland hot spot about 40 million years ago. This region of concentrated soft rheology has a profound influence on reconstructing the deglaciation history of Greenland. We reevaluate the evolution of the GrIS since LGM and obtain a loss of 1.5-m sea-level equivalent from the northwest and southeast. These same sectors are dominating modern mass loss. We suggest that the present destabilization of these marine-based sectors may increase sea level for centuries to come. Our new deglaciation history and GIA uplift estimates suggest that studies that use the Gravity Recovery and Climate Experiment satellite mission to infer present-day changes in the GrIS may have erroneously corrected for GIA and underestimated the mass loss by about 20 gigatons/year.

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Conductivity detection is the most popular detection method used in ion chromatography, and its hyphenation with suppressor technology provides two main benefits: i) mobile-phase background signal reduction and ii) analyte signal amplification. By integrating all chromatographic system components in a microfluidic platform, external band broadening can be reduced, improving separation efficiency. For this purpose, a microfluidic membrane suppressor has been constructed and evaluated for anion-exchange separations. Additionally, a holder has been constructed allowing to align and stack different modules (e.g. separation and suppressor module) while ensuring zero-dead-volume chip-chip connections. Ion suppression of the alkaline eluent was achieved via an acid-base reaction across a sulfonated poly(tetrafluoroethylene)-based membrane. This membrane was clamped between the two substrate plates of the suppressor module, accommodating micro-channels for the eluent and regenerant flow, respectively. The response and efficacy of the microfluidic suppressor was assessed for a wide range of eluent (OH-) concentrations, using 127 and 183 µm thick membranes, while optimizing the flow rate and concentration of the regenerant solution (H2SO4). The optimal eluent flow rate was determined at 5 µL/min, corresponding to the optimal flow velocity of commercially-available column technology, i.e., a 250 mm long column packed with 7.5 µm particles. When equilibrated at 15 mM KOH, a 99% decrease in conductivity signal could be obtained within 5 min with the application of 10 mM H2SO4 at a flow rate of 75 µL/min as regenerant solution. A background signal as low as 1.2 µS/cm was obtained after prolonged equilibration, 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, the ion suppression at high hydroxide concentrations was significantly improved allowing the application of ion strength up to 75 mM. The applicabilityof the microfluidic suppressor has been demonstrated with an isocratic baseline separation of a mixture of seven inorganic ions yielding a maximum plate number of 10,600 and a gradient separation of a complex ion mixture.

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.

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The application of high pressures 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 super macroporous anion-exchange particles were investigated employing a capillary ion-exchange instrument allowing column pressures up to 34MPa. Plate heights below 10 µm could be realized in isocratic mode using capillary columns packed with 4 µm particles. Compared to conventional IC using 7 µm particle-packed columns and pressures up to 20 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. The performance limits were also characterized in gradient mode. Using a linear gradient significant broadening was observed with increasing retention factor. Therefore the use of concave gradients were explored to establish the performance limits at maximum operating pressure. The potential of high-efficiency capillary IC is demonstrated with high-pressure gradient IC separations using coupled columns. In a next step to system miniaturization we are focusing on the development of a portable ion analyzer, composed of different substrate layers, each with their own channel layout and functionality. In a first step, a prototype on-chip microfluidic membrane suppressor has been developed and characterized as a stand-alone module and its capabilities and limitations will be discussed.

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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 70C 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 themacropore size. The porogen ratio affects the timing of the reactioninduced 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 100C.

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The Canadian Arctic Archipelago (CAA) contains the largest volume of glacier ice on Earth outside of Antarctica and Greenland. In the absence of significant calving, CAA glacier mass balance is governed by the difference between surface snow accumulation and meltwater runoff—surface mass balance. Here we use a coupled atmosphere/snow model to simulate present-day and 21st century CAA glacier surface mass balance. Through comparison with Gravity Recovery and Climate Experiment mass anomalies and in situ observations, we show that the model is capable of representing present-day CAA glacier mass loss, as well as the dynamics of the seasonal snow cover on the CAA tundra. Next, we force this model until 2100 with a moderate climate warming scenario (AR5 RCP4.5). We show that enhanced meltwater runoff from CAA glaciers is not sufficiently compensated by increased snowfall. Extrapolation of these results toward an AR5 multimodel ensemble results in sustained 21st century CAA glacier mass loss in the vast majority (>99%) of the ~7000 temperature realizations.

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A polymer-based microfluidic device has been designed and constructed for comprehensive spatial two-dimensional chromatography, with each peak being characterized by its coordinates in the plane. The device manufactured from cyclic olefin copolymer (COC) features a first-dimension (1D) separation channel and 21 parallel second-dimension (2D) separation channels orientated perpendicular to the 1D channel. Compartmentalization of 1D and 2D flow by a physical barrier allowed for a preferential mobile phase flow path mainly restricted to the 1D separation channel, with a minimal dispersion into the 2D separation channels. After a 1D separation was halted, a radially-interconnected flow distributor of diamond-shaped pillars with diverging side-walls introduced the mobile phase for the 2D separation, allowing eluent inside the 1D channel to be fractionated and simultaneously injected into the 2D channels. A hydrophobic methacrylate-based monolithic stationary phase was polymerized in-situ in desired locations via aUV-initiated polymerization reaction employing a photo mask.

Parameters affecting the separation of intact proteins in gradient-elution reversed-phase chromatography using poly(styrene-co-divinylbenzene) monolithic capillary columns

Mass budget calculations, validated with satellite gravity observations [from the Gravity Recovery and Climate Experiment (GRACE) satellites], enable us to quantify the individual components of recent Greenland mass loss. The total 2000–2008 mass loss of ~1500 gigatons, equivalent to 0.46 millimeters per year of global sea level rise, is equally split between surface processes (runoff and precipitation) and ice dynamics. Without the moderating effects of increased snowfall and refreezing, post-1996 Greenland ice sheet mass losses would have been 100% higher. Since 2006, high summer melt rates have increased Greenland ice sheet mass loss to 273 gigatons per year (0.75 millimeters per year of equivalent sea level rise). The seasonal cycle in surface mass balance fully accounts for detrended GRACE mass variations, confirming insignificant subannual variation in ice sheet discharge

Mass budget calculations, validated with satellite gravity observations [from the Gravity Recovery and Climate Experiment (GRACE) satellites], enable us to quantify the individual components of recent Greenland mass loss. The total 2000–2008 mass loss of ~1500 gigatons, equivalent to 0.46 millimeters per year of global sea level rise, is equally split between surface processes (runoff and precipitation) and ice dynamics. Without the moderating effects of increased snowfall and refreezing, post-1996 Greenland ice sheet mass losses would have been 100% higher. Since 2006, high summer melt rates have increased Greenland ice sheet mass loss to 273 gigatons per year (0.75 millimeters per year of equivalent sea level rise). The seasonal cycle in surface mass balance fully accounts for detrended GRACE mass variations, confirming insignificant subannual variation in ice sheet discharge

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