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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]

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 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]

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]

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]

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]

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]

Sea-level rise rates have become important drivers for policy makers dealing with the long-term protection of coastal populations. Scenario studies suggest that an acceleration in sea-level rise is imminent. The anticipated acceleration is hard to detect because of spatial and temporal variability, which consequently, have become important research topics. A known decadal-scale variation is the 18.6-year nodal cycle. Here, we show how failing to account for the nodal cycle resulted in an overestimation of Dutch sea-level rise. The nodal cycle is present across the globe with a varying phase and a median amplitude of 2.2 cm. Accounting for the nodal cycle increases the probability of detecting acceleration in the rate of sea-level rise. In an analysis of the Dutch coast, however, still no significant acceleration was found. The nodal cycle causes sea level to drop or to rise at an increased rate; therefore, accounting for it is crucial to accurately estimate regional sea-level rise. [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 mass balance of the Antarctic ice sheet from satellite gravimetry, and to a lesser extent altimetry, observations remains uncertain due to the poorly known correction for the glacial isostatic adjustment of the solid Earth (GIA). Although much progress has been made in consistently modelling ice-sheet evolu-tion, related bedrock deformation and sea-level change, predictions of GIA remain ambiguous due to the lack of observational constraints in Antarctica. Here, we present an improved GIA estimate based on the joint inversion of GRACE, Envisat/ICESat and GPS measurements, making use of the different sen-sitivities of the satellite observations to surface-mass and solid Earth processes. We base our joint inver-sion on viscoelastic response functions to a disc load forcing, allowing us to account for lateral variations in the lithosphere thickness and mantle viscosity in Antarctica. Our estimate is able to reproduce extreme GPS-measured uplift rates (up to 3 cm yr-1) in the Amundsen Sea Embayment, indicating that large parts of the uplift are caused by GIA induced by recent load changes in the presence of a low-viscosity upper mantle. We compare our GIA inversion estimate with the prediction obtained with a coupled model of the ice sheet and solid Earth, as well as with published estimates. We evaluate its impact on the determination of ice-mass balance in Antarctica from gravimetry and altimetry. The results present-ed here are the final results of the Support To Science Element Project REGINA and its Supplementary Study of the European Space Agency, www.regina-science.eu. [ABSTRACT FROM AUTHOR]

The bedrock displacement recorded with GNET-GPS stations in Greenland reveal viscoelastic uplift rates that strongly contradict published predictions of glacial-isostatic adjustment (GIA). In particular, GPS provides evidence that GIA-induced uplift rates are considerably higher in the northwest and southeast of the ice sheet. Both regions are characterized by a lack of relative sea level (RSL) data to constrain the past ice sheet evolution and related viscoelastic displacement, thus causing large uncer-tainties in GIA predictions. Here, we develop a new GIA prediction by adjusting the geomorphological ice-sheet reconstruction of Fleming & Lambeck (2004) simultaneously to the RSL indicators and the newly available GPS data. Special focus lies on south Greenland, where an increasing number of high-quality RSL indicators from isolation basins suggest a fast relaxation of the solid Earth. This finding is consistent with global seismic models indicating a gradient in the lithosphere thickness and astheno-sphere viscosity from high values in the northwest to low values in the southeast. We demonstrate that the GIA prediction fits the GPS and RSL data significantly better for a lateral varying distribution of Earth model parameters. Finally, we evaluate the impact of our new GIA model on determining ice-mass bal-ances from GRACE. We show that commonly used GIA predictions have underestimated the solid Earth response by 17 Gt/yr, which is about 7 % of Greenland current ice-mass loss. [ABSTRACT FROM AUTHOR]