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Atmospheric rivers (ARs) transport large amounts of moisture from the mid- to high-latitudes and they are a primary driver of the most extreme snowfall events on Antarctica. ARs also raise surface temperatures when they make landfall over Antarctica, leading to surface melting. In this study, we characterize the climatology and surface impacts of ARs on West Antarctica, focusing on the Amundsen Sea Embayment and Marie Byrd Land. First, we develop a climatology of ARs in this region, using an Antarctic-specific AR detection tool combined with MERRA-2 and ERA5 atmospheric reanalyses. We find that while ARs are infrequent, they cause intense precipitation in short periods of time and account for 11 % of the annual surface accumulation. They are driven by the coupling of a blocking high over the Antarctic Peninsula with a low--pressure system known as the Amundsen Sea Low. Next, we use observations from automatic weather stations on Thwaites Eastern Ice Shelf to examine a case study of 3 ARs that made landfall in rapid succession from February 2 to 8, known as an AR family event. We use snow height observations to force the firn model SNOWPACK to reconstruct accumulation and surface melting during the event, and compare these results with accumulation higher up on the glacier derived from surface height changes using interferometric reflectometry. While accumulation dominates the surface impacts of the event on Thwaites Eastern Ice Shelf (>100 kg m−2), we find small amounts of surface melt as well (

Owing to drifting snow processes, snow accumulation and surface density in polar environments are variable in space and time. We present new field data of manual measurements, repeat terrestrial laser scanning and snow micro-penetrometry from Dronning Maud Land, Antarctica, showing the density of new snow accumulations. We combine these data with published drifting snow mass flux observations, to evaluate the performance of the 1-D, detailed, physics-based snow cover model SNOWPACK in representing drifting snow and surface density. For two sites in East Antarctica with multiple years of data, we found a coefficient of determination for the simulated drifting snow of r2 = 0.42 and r2 = 0.50, respectively. The field observations show the existence of low-density snow accumulations during low wind conditions. Successive high wind speed events generally erode these low-density layers while producing spatially variable erosion/deposition patterns with typical length scales of a few metres. We found that a model setup that is able to represent low-density snow accumulating during low wind speed conditions, as well as subsequent snow erosion and redeposition at higher densities during drifting snow events was mostly able to describe the observed temporal variability of surface density in the field.

Earth system models (ESMs) allow us to explore minimally observed components of the Antarctic Ice Sheet (AIS) climate system, both historically and under future climate change scenarios. Here, we present and analyze surface climate output from the most recent version of the National Center for Atmospheric Research's ESM: the Community Earth System Model version 2 (CESM2). We compare AIS surface climate and surface mass balance (SMB) trends as simulated by CESM2 with reanalysis and regional climate models and observations. We find that CESM2 substantially better represents the mean-state AIS near-surface temperature, wind speed, and surface melt compared with its predecessor, CESM1. This improvement likely results from the inclusion of new cloud microphysical parameterizations and changes made to the snow model component. However, we also find that grounded CESM2 SMB (2269 ± 100 Gt yr−1) is significantly higher than all other products used in this study and that both temperature and precipitation are increasing across the AIS during the historical period, a trend that cannot be reconciled with observations. This study provides a comprehensive analysis of the strengths and weaknesses of the representation of AIS surface climate in CESM2, work that will be especially useful in preparation for CESM3 which plans to incorporate a coupled ice sheet model that interacts with the ocean and atmosphere.

Objectives To delineate the impact of peripheral musculoskeletal manifestations on stratification of disease phenotype and outcome in new-onset spondyloarthritis (SpA), using a prospective observational nationwide inception cohort, the BelGian Inflammatory Arthritis and spoNdylitis cohorT (Be-Giant). Methods Newly diagnosed adult SpA patients, fulfilling the Assessment of SpondyloArthritis International Society (ASAS) criteria for axial or peripheral SpA, were included in Be-Giant and prospectively followed every six months. Peripheral involvement (defined as arthritis, enthesitis and/or dactylitis) was determined in relation to clinically similar patient subsets at baseline and disease activity patterns during two-year follow-up, identified through K-means cluster analysis and latent class growth analysis. Results From November 2010 to March 2020, 367 patients were enrolled in Be-Giant, of whom 162 (44%) had peripheral manifestations. Two patient clusters [A, axial predominant (n = 248) and B, peripheral predominant (n = 119)] were identified at diagnosis. Longitudinal analysis (n = 115) revealed two trajectories of disease activity in each cluster: one with persistently high disease activity over time (‘High’), the other rapidly evolving to low disease activity (‘Low’). In cluster A patients, peripheral manifestations predisposed to the ‘High’ trajectory [odds ratio (OR) = 2.0, 95% CI: 1.3, 3.1, P = 0.001], despite more rapid initiation of biologics compared with patients without peripheral manifestations (hazard ratio (HR) = 2.1, 95% CI: 1.0, 4.4, P = 0.04 – Cox proportional-hazards model). Conclusion Peripheral musculoskeletal manifestations are major determinants of phenotypical diversity in new-onset SpA. Intriguingly, stratification of axial SpA according to concomitant peripheral involvement identified an endotype with an unfavorable outcome despite more prompt therapeutic intensification with biologics. These observations justify an endotype-tailored approach beyond current ASAS/EULAR management recommendations.

Earth System Models are essential tools for understanding the impacts of a warming world, particularly on the contribution of polar ice sheets to sea level change. However, current models lack full coupling of the ice sheets to the ocean, and are typically run at a coarse resolution (1 degree grid spacing or coarser) to save on computational expense. Coarse spatial resolution is particularly a problem over Antarctica, where sub-gridscale orography is well-known to influence precipitation fields. This resolution limitation has been partially addressed by regional climate models (RCMs), which must be forced at their lateral and ocean surface boundaries by (usually coarser) global atmospheric datasets, However, RCMs fail to capture the coupling between the regional domain and the global climate system. Conversely, running high spatial resolution models globally is computationally expensive, and can produce vast amounts of data. Alternatively, variable-resolution, nested grids are a promising way forward, as they can retain the benefits of high resolution over a specified domain without the computational costs of running at a high resolution globally. Here we evaluate a historical simulation of the Community Earth System Model, version 2, (CESM2) implementing the spectral element (SE) numerical dynamical core with an enhanced-horizontal-resolution (0.25°) grid over the Antarctic Ice Sheet and the surrounding Southern Ocean; the rest of the global domain is on the standard 1° grid. We compare it to a 1° model run of CESM2 using the standard finite-volume dynamical core with identical physics and forcing, including prescribed SSTs and sea ice concentrations from observations. Our evaluation indicates both improvements and degradations in VR-CESM2 performance relative to the 1° CESM2. Surface mass balance estimates are slightly higher, but within one standard deviation of the ensemble mean, except for over the Antarctic Peninsula, which is impacted strongly by better-articulated surface topography. Temperature and wind estimates are improved over both the near-surface and aloft, although the overall correction of a cold bias (within the 1° CESM2 runs) has resulted in temperatures which are too high over the interior of the ice sheet. The major degradations include the enhancement of surface melt as well as excessive liquid cloud water over the ocean, with resultant impacts on the radiation balance. Despite these changes, VR-CESM2 is a valuable tool for the analysis of future estimates of precipitation and surface mass balance, and thus constraining estimates of sea level rise.

The Greenland Ice Sheet's (GrIS) firn layer buffers the ice sheet's contribution to sea level rise by storing meltwater in its pore space. However, available pore space and meltwater retention capability is lost due to ablation of the firn layer and refreezing of meltwater as near-surface ice slabs in the firn. Understanding how firn properties respond to climate is important for constraining the GrIS's future contribution to sea level rise in a warming climate. Observations of firn density provide detailed information about firn properties, but they are spatially and temporally limited. Here we use two firn models, the physics-based SNOWPACK model and the semi-empirical Community Firn Model (CFM) to quantify firn properties across the GrIS from 1980 through 2020. We use an identical forcing (MERRA-2 atmospheric reanalysis) for SNOWPACK and the CFM in order to isolate model differences. To evaluate the models, we compare simulated firn properties, including firn air content (FAC), to measurements from the SUMup dataset of snow and firn density. Both models perform well, though their performance is hindered by meltwater percolation and the spatial resolution of the atmospheric forcing. In the full ice-sheet simulations, the spatially-integrated FAC (i.e., air volume in the firn) for the upper 100 m is 34,645 km3 from SNOWPACK and 28,581 km3 from the CFM. The discrepancy in the magnitude of the modeled FAC stems from differences in densification with depth and variations in the models' treatment of atmospheric input. In more recent years (2005–2020), both models simulate substantial depletion of pore space. During this period, the spatially-integrated FAC across the entire GrIS decreases by 2.8 % and 1.2 % in SNOWPACK and the CFM, respectively. The differing magnitudes of the 2005–2020 spatially-integrated FAC of -66.6 km3 yr-1 in SNOWPACK and -17.4 km3 yr-1 in the CFM demonstrate how model differences propagate throughout the FAC record. Over the full modeled record (1980–2020), SNOWPACK simulates a loss of pore space equivalent to 3 mm of sea level rise buffering, while the CFM simulates a loss of 1 mm. The greatest depletion in FAC is along the margins, and especially along the western margin where observations and models show the formation of near-surface, low-permeability ice slabs that inhibit meltwater storage.

The Arctic is the region on Earth that is warming the fastest. At the same time, Arctic sea ice is reducing while the Greenland ice sheet (GrIS) is losing mass at an accelerated pace. Here, we study the seasonal impact of reduced Arctic sea ice on GrIS surface mass balance (SMB), using the Community Earth System Model version 2.1 (CESM2), which features an advanced, interactive calculation of SMB. Addressing the impact of sea-ice reductions on the GrIS SMB from observations is difficult due to the short observational records. Also, signals detected using transient climate simulations may be aliases of other forcings. Here, we analyze dedicated simulations from the Polar Amplification Model Intercomparison Project with reduced Arctic sea ice and compare them with preindustrial sea ice simulations while keeping all other forcings constant. In response to reduced sea ice, the GrIS SMB increases in winter due to increased precipitation, driven by the more humid atmosphere and increasing cyclones. In summer, surface melt increases due to a warmer, more humid atmosphere providing increased energy transfer to the surface through the sensible and latent heat fluxes, which triggers the melt-albedo feedback. Further, warming occurs throughout the entire troposphere over Baffin Bay. This deep warming results in regional enhancement of the 500 hPa geopotential heights over the Baffin Bay and Greenland, increasing blocking and heat advection over the GrIS’ surface. This anomalous circulation pattern has been linked to recent increases in the surface melt of the GrIS. Supplementary Information The online version contains supplementary material available at 10.1007/s00382-021-05897-4.

Introduction Myositis-specific autoantibodies (MSAs) are thought to be mutually exclusive in patients with idiopathic inflammatory myopathies (IIM) based on studies with immunoprecipitation-based (IP) detection methods. Recently, detection of multiple MSAs in unique patients is increasingly reported, but the extent of this phenomenon remains unclear. Methods At our centre, we reviewed results from two line immunoassays and one dot immunoassay in 145 IIM patients and 240 controls for the presence of multiple MSAs. Pubmed and Embase were systematically searched for articles mentioning detection of multiple MSAs in IIM patients, published until February 2019. We assessed the frequency, detection method, the precise combinations and clinical phenotypes of participants with multiple MSAs. Results At our centre, detection of multiple MSAs occurred in 3.4-8.3% of patients with IIM, depending on the assay. However, no cases with full concordance across all three assays were identified. Forty-four articles reported detection of multiple MSAs, representing a total of 133 cases, including four patients with a connective tissue disease other than IIM and two healthy controls. In 101 cases all MSAs were detected using only one detection method: 40 cases with IP-based methods (most frequently used technique) and 61 cases with other assay types. In most cases the phenotype of patients with multiple MSAs matched the predicted presentation associated with one MSA and in few cases the phenotype matched with both MSAs. Conclusion Detection of multiple MSAs in unique IIM patients is less rare than commonly accepted. Specificity issues of the commercially available multiplex immunoassays may, at least partly, explain the higher frequency compared to IP-based methods. ‘True multiple MSA-positive’ patients may exist, though they are most likely rare.

An increase in Antarctic Ice Sheet (AIS) surface mass balance (SMB) has the potential to mitigate future sea level rise that is driven by enhanced solid ice discharge from the ice sheet. For climate models, AIS SMB provides a difficult challenge, as it is highly susceptible to spatial, seasonal, and interannual variability. Here we use a reconstructed data set of AIS snow accumulation as “true” observational data, to evaluate the ability of the CMIP5 and CMIP6 suites of models in capturing the mean, trends, temporal variability, and spatial variability in SMB over the historical period (1850–2000). This gives insight into which models are most reliable for predicting SMB into the future. We found that the best scoring models included the National Aeronautics and Space Administration (NASA) GISS model and the Max Planck Institute (MPI) for Meteorology's model for CMIP5, as well as one of the Community Earth System Model v2 (CESM2) models and one MPI model for CMIP6. Using a scoring system based on SMB mean value, trend, and temporal variability across the AIS, as well as spatial SMB variability, we selected a subset of the top 10th percentile of models to refine 21st century (2000–2100) AIS-integrated SMB projections to 2274 ± 282 Gt yr−1, 2358 ± 286 Gt yr−1, and 2495 ± 291 Gt yr−1 for Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5, respectively. We also reduced the spread in AIS-integrated mean SMB by 79 %, 79 %, and 74 % in RCPs 2.6, 4.5, and 8.5, respectively. Notably, we find that there is no improvement from CMIP5 to CMIP6 in overall score. In fact, CMIP6 performed slightly worse on average compared to CMIP5 at capturing the aforementioned SMB criteria. Our results also indicate that model performance scoring is affected by internal climate variability (particularly the spatial variability), which is illustrated by the fact that the range in overall score between ensemble members within the CESM1 Large Ensemble is comparable to the range in overall score between CESM1 model simulations within the CMIP5 model suite. We also find that a higher horizontal resolution does not yield to a conclusive improvement in score.

Antarctic sea ice plays a pivotal role in the global climate system. Forming a highly reflective,dynamic, and insulative blanket that varies seasonally in its areal coverage from ~3 × 106 km2to ~19–20 × 106 km2, sea ice and its snow cover strongly modifies ocean–atmosphere fluxes andinteraction processes (Bourassa et al. 2013). Moreover, brine rejection into the underlying oceanduring sea ice formation onsome continental shelf areasleads to the formationof Antarctic Bottom Waterthat contributes to the globalocean overturning circulation(Johnson 2008). Antarcticsea ice also acts as a protectivebuffer for ice shelvesagainst destructive oceanswells (Massom et al. 2018)and modulates the interactionof warm ocean waterswith ice shelf basal cavitiesto affect basal melt there(Timmermann and Hellmer2013). Finally, it also formsa key habitat for a myriad ofbiota—ranging from microorganismsto whales (Thomas2017)—that are strongly affectedby changes in the presenceand seasonal rhythms ofthe sea ice cover (e.g., Massomand Stammerjohn 2010).

Increasing precipitation on the Antarctic Ice Sheet (AIS) in a warming climate has the potential to partially mitigate Antarctica’s contribution to sea level rise. We show that a simple, physically motivated change to the shallow convective cloud phase in the Community Earth System Model (CESM)—improving a long-standing bias in shortwave cloud forcing over the Southern Ocean—leads to an enhanced response of precipitation when the model is forced with realistic stratospheric ozone depletion, with other radiative forcing remaining constant. We analyze two ozone-forced ensemble experiments with the CESM version 1.1: one using the standard version of the model and the other using the cloud-modified version. The standard version exhibits a precipitation increase on the AIS of 34 gigatons year−1; the cloud-modified version shows an increase of 109 Gt year−1. The cloud-modified version shows a more robust, year-round poleward shift in the westerly jet and storm tracks, which brings more precipitation to the AIS, compared to the standard version. Greater surface warming and larger-amplitude stationary waves further increase the Antarctic precipitation response. The enhanced warming in the cloud-modified version is explained by larger positive shortwave cloud feedbacks, while the enhanced poleward jet shift is associated with a stronger meridional temperature gradient in the upper troposphere—lower stratosphere. These results illustrate (1) the sensitivity of forced changes in Antarctic precipitation to the mean state of a climate model and (2) the strong role of atmospheric dynamics in driving that forced precipitation response.

In systemic sclerosis, baseline extent of radiological involvement is an important outcome predictor and baseline absence of radiological involvement suggests a more favourable prognosis. As current predictive models are based on cohorts with variable disease duration, we aim to assess disease dynamics in early disease.Patients were included from the prospective longitudinal Belgian Systemic Sclerosis Cohort. We included patients with a disease duration = 36 months at baseline with available baseline thoracic high-resolution computed tomography (HRCT) images and longitudinal pulmonary function test (PFT) results until 42 months of follow-up.Fifty-two patients were included; 50% were male and 44% suffered from diffuse cutaneous systemic sclerosis. A total of 46% carried anti-topoisomerase 1 antibodies. The mean disease duration at baseline visit was 11 months. At baseline visit, 40.4% (21/52) patients had HRCT abnormalities. Patients with abnormal HRCT findings more frequently suffered from diffuse cutaneous systemic sclerosis (p 0.05) and less frequently carried anti-centromere antibodies (p 0.05). Patients without CT abnormalities at baseline had a shorter disease duration (9 ± 7 months versus 14 ± 12 months). After 42 months, 8/52 patients, including 3 patients with normal HRCT findings at baseline, died due to SSc-related manifestations. Progression of lung fibrosis occurred in 16 patients at month 42, including 7 patients with normal CT at baseline. No clear predictors of progression could be identified.In early SSc patients, the disease dynamics differ from the large published cohorts. Progressive lung fibrosis and mortality can also occur in patients without radiological abnormalities at baseline. Key Points • Disease dynamics in early SSc differ from more established SSc. • In early SSc, progressive pulmonary fibrosis can occur in patients without CT abnormalities at baseline. • In early SSc, more stringent pulmonary follow-up is warranted both in lcSSc and dcSSc.

Antarctic Ice Sheet (AIS) mass loss can be mitigated by an increase in surface mass balance (SMB) which is impacted by the ice sheet's surface climate. Because of Antarctica’s remoteness, in-situ observations of its surface climate are spatially and temporally sparse, limiting our understanding of how the surface climate, and therefore SMB, are changing. To that end, Earth System Models (ESMs) fill an important gap, allowing us to explore components of the AIS climate system, both historically and under future climate change scenarios. Here, we present and analyze output of the most recent version of the National Center for Atmospheric Research’s ESM: the Community Earth System Model version 2 (CESM2). We compare AIS surface climate and SMB as simulated by CESM2 with regional climate models and observations. We find that CESM2 substantially better represents AIS near-surface temperature, wind speed, and surface melt compared with its predecessor, CESM1, which is likely a result of the inclusion of new cloud microphysical parameterizations and changes made to the snow model. However, CESM2 SMB is shown to be biased high, particularly because of excessive precipitation. ESMs such as CESM2 are used as forcing for ice sheet models, which provide estimates and projections of ice sheet contribution to sea level rise. Thus, it is important to fully understand the limitations and biases of this climate model forcing. This study provides a comprehensive analysis of the strengths and weaknesses of CESM2 representation of AIS surface climate, which will be especially useful in preparation for CESM3, which plans to incorporate a coupled Antarctic Ice Sheet that interacts with the ocean and atmosphere.

Oceans and cryosphere are immediately affected by human-induced climate change. Our Editorial Board members present viewpoints on the most pressing and fruitful avenues of research on frozen and liquid water, and the transition from one to the other.

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5. National Science Foundation (NSF)National Science Foundation (NSF); National Center for Atmospheric Research - NSF [1852977]; RUBISCO Scientific Focus Area (SFA) - Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science; Columbia University Presidential Fellowship; U.S. Department of Agriculture NIFA Award [2015-67003-23485]; NASA Interdisciplinary Science Program Award [NNX17AK19G]; U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science programUnited States Department of Energy (DOE) [DE-SC0008317, DESC0016188]; National Science FoundationNational Science Foundation (NSF) [DEB-1153401]; NASA's CARBON program; NASA's TE program; National Aeronautics and Space AdministrationNational Aeronautics & Space Administration (NASA) We would like to thank the reviewers for their insightful comments and helpful suggestions that improved the clarity and presentation of the manuscript. The CESM project is supported primarily by the National Science Foundation (NSF). This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement 1852977. Computing and data storage resources, including the Cheyenne supercomputer (doi: 10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. D. M. L. was supported in part by the RUBISCO Scientific Focus Area (SFA), which is sponsored by the Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science. D. K. and P. G. were supported by Columbia University Presidential Fellowship. G. B., D. L. L., W. R. W., and R. Q. T. were supported by the U.S. Department of Agriculture NIFA Award 2015-67003-23485. W. R. W. and G. K. A. were supported by the NASA Interdisciplinary Science Program Award NNX17AK19G. J. B. F. and M. S. carried out the research in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged. All rights reserved. J. B. F. and M. S. were supported in part by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science program under Awards DE-SC0008317 and DESC0016188; the National Science Foundation Ecosystem Science program (DEB-1153401); and NASA's CARBON and TE programs. All model data are archived and publicly available at the UCAR/NCAR Climate Data Gateway (https://doi.org/10.5065/d6154fwh).

Across the Antarctic Ice Sheet, accumulation heavily influences firn compaction and surface height changes. Therefore, accumulation varies over short distances ( 25 km) that are too coarse to resolve this variability. To address this limitation, we construct a fine-scale accumulation product from airborne snow radar observations by superimposing along-track fluctuations in accumulation onto an atmospheric reanalysis product. Our resulting airborne product reflects large-scale (>25 km) orographic precipitation patterns while providing robust and unprecedented insight into Antarctic accumulation variability on subgrid scales. On these smaller scales, we find significant, regionally dependent accumulation variability (𝜎(sub relative) > 40%). This variability in accumulation is correlated with variability in topographic surface slope in the wind direction (p < 0.01), confirming that subgrid-scale accumulation variability is driven by snow redistribution by wind.

More than one-third of Earth's landmass is drained by rivers that seasonally freeze over. Ice transforms the hydrologic1,2, ecologic3,4, climatic5 and socio-economic6-8 functions of river corridors. Although river ice extent has been shown to be declining in many regions of the world1, the seasonality, historical change and predicted future changes in river ice extent and duration have not yet been quantified globally. Previous studies of river ice, which suggested that declines in extent and duration could be attributed to warming temperatures9,10, were based on data from sparse locations. Furthermore, existing projections of future ice extent are based solely on the location of the 0-°C isotherm11. Here, using satellite observations, we show that the global extent of river ice is declining, and we project a mean decrease in seasonal ice duration of 6.10 ± 0.08 days per 1-°C increase in global mean surface air temperature. We tracked the extent of river ice using over 400,000 clear-sky Landsat images spanning 1984-2018 and observed a mean decline of 2.5 percentage points globally in the past three decades. To project future changes in river ice extent, we developed an observationally calibrated and validated model, based on temperature and season, which reduced the mean bias by 87 per cent compared with the 0-degree-Celsius isotherm approach. We applied this model to future climate projections for 2080-2100: compared with 2009-2029, the average river ice duration declines by 16.7 days under Representative Concentration Pathway (RCP) 8.5, whereas under RCP 4.5 it declines on average by 7.3 days. Our results show that, globally, river ice is measurably declining and will continue to decline linearly with projected increases in surface air temperature towards the end of this century. ispartof: JOURNAL OF CLIMATE vol:32 issue:20 pages:6899-6915 ispartof: location:England status: Published online

Antarctic blue ice zones, the most productive locations for meteorite recovery on Earth, contain old ice that is easily accessible and available in large quantities. However, the mechanisms behind these meteorite traps remain a topic of ongoing debate. Here, we propose an interdisciplinary approach to improve our understanding of a meteorite trap in Dronning Maud Land (East Antarctica) on the Nansen blue ice field meteorite trap (2600–3100 m above sea level), where more than half of the Asuka meteorites have been collected. Based on 185 surface blue ice samples, one of the largest observed spatial patterns in oxygen isotopic variation to date is found. Relying on meteorites for which the terrestrial ages are determined using 14C and 36Cl, this surface ice is interpreted to date from the Last Interglacial up to the present-day. By combining state-of-the-art satellite derived surface velocities, surface mass balance modelling and ice flow modelling, we estimate that about 75–85% of the meteorites found on the ice field were supplied by ice flow after entering the ice sheet in an accumulation area of a few hundred square kilometres located south (upstream) of the ice field. Less than 0.4 new meteorites per year are supplied to the ice field through ice flow, suggesting that the hundreds of meteorites found 25 years after the first visit to this ice field mostly represent meteorites that were previously not found, rather than newly supplied meteorites. By combining these findings, the infall rate of meteorites from space is estimated, which is in line with values from the literature, but situated at the higher end of the range. A comparison of the oxygen isotopic variation of the surface blue ice to that of the European Project for Ice Coring in Antarctica (EPICA), Dronning Maud Land (EDML) ice core (located 750 km to the west, at the same elevation), suggests that the regional changes in topography have been relatively limited since the Last Interglacial, supporting theories of an overall stable East Antarctic Ice Sheet (EAIS) over this time period., SCOPUS: ar.j, info:eu-repo/semantics/published

The Antarctic ice sheet mass balance is a major component of the sea level budget and results from the difference of two fluxes of a similar magnitude: ice flow discharging in the ocean and net snow accumulation on the ice sheet surface, i.e. the surface mass balance (SMB). Separately modelling ice dynamics and SMB is the only way to project future trends. In addition, mass balance studies frequently use regional climate models (RCMs) outputs as an alternative to observed fields because SMB observations are particularly scarce on the ice sheet. Here we evaluate new simulations of the polar RCM MAR forced by three reanalyses, ERA-Interim, JRA-55, and MERRA-2, for the period 1979–2015, and we compare MAR results to the last outputs of the RCM RACMO2 forced by ERA-Interim. We show that MAR and RACMO2 perform similarly well in simulating coast-to-plateau SMB gradients, and we find no significant differences in their simulated SMB when integrated over the ice sheet or its major basins. More importantly, we outline and quantify missing or underestimated processes in both RCMs. Along stake transects, we show that both models accumulate too much snow on crests, and not enough snow in valleys, as a result of drifting snow transport fluxes not included in MAR and probably underestimated in RACMO2 by a factor of 3. Our results tend to confirm that drifting snow transport and sublimation fluxes are much larger than previous model-based estimates and need to be better resolved and constrained in climate models. Sublimation of precipitating particles in low-level atmospheric layers is responsible for the significantly lower snowfall rates in MAR than in RACMO2 in katabatic channels at the ice sheet margins. Atmospheric sublimation in MAR represents 363 Gt yr−1 over the grounded ice sheet for the year 2015, which is 16 % of the simulated snowfall loaded at the ground. This estimate is consistent with a recent study based on precipitation radar observations and is more than twice as much as simulated in RACMO2 because of different time residence of precipitating particles in the atmosphere. The remaining spatial differences in snowfall between MAR and RACMO2 are attributed to differences in advection of precipitation with snowfall particles being likely advected too far inland in MAR.

The East Antarctic Ice Sheet contains the vast majority of Earth's glacier ice (about 52 metres sea-level equivalent), but is often viewed as less vulnerable to global warming than the West Antarctic or Greenland ice sheets. However, some regions of the East Antarctic Ice Sheet have lost mass over recent decades, prompting the need to re-evaluate its sensitivity to climate change. Here we review the response of the East Antarctic Ice Sheet to past warm periods, synthesize current observations of change and evaluate future projections. Some marine-based catchments that underwent notable mass loss during past warm periods are losing mass at present but most projections indicate increased accumulation across the East Antarctic Ice Sheet over the twenty-first century, keeping the ice sheet broadly in balance. Beyond 2100, high-emissions scenarios generate increased ice discharge and potentially several metres of sea-level rise within just a few centuries, but substantial mass loss could be averted if the Paris Agreement to limit warming below 2 degrees Celsius is satisfied.

International audience; The Antarctic ice sheet (AIS) is classified as a polar desert where, similar to other deserts around the world, the annual precipitation is dependent on a few episodic precipitation events. Recent research has highlighted that certain regions of the AIS receive 40%-60% of their total annual precipitation from the largest 10% of daily precipitation events (Turner et al., 2019). There is a high coast-inland snowfall gradient, as most

Several studies have shown that there is often a poor match between surface mass balance (SMB, mass gain at the surface of the ice sheet) simulated by regional climate models and the one locally measured from ice cores in Antarctica. Models’ representation of the physical processes that affect SMB is known to be imperfect, while ice core records may be strongly influenced by local processes such as post-depositional wind redistribution and precipitation intermittency. These two sources of uncertainty likely both have a role to play in the discrepancy identified between modeled and observed ice core SMB estimates over the past centuries.The goal here is to estimate the uncertainties associated with the difference between a point-wise measurement of SMB as provided by the ice core and the SMB averages over a grid of several square kilometers of the models. To do so, we use ground-penetrating radar (GPR) data, collected over several ice rises, located along the high accumulation Princess Ragnhild Coast (East Antarctica), to obtain a multi-year resolution record that goes back ∼30-40 years, representing SMB spatial and temporal variability at the scale of a few km2 for each ice rise. Ice cores were collected during each radar field campaign, which allows us to place age constraints on the radar stratigraphy obtained and compare the GPR SMB estimates with the ice core SMB estimate.Therefore, we are able to calculate an error of representativeness for each ice core SMB, estimated as the difference between the average GPR SMB over a few km2 and the ice core SMB. This representativeness error can be split into two components: a systematic error (on the order of ∼0.1 m w.e. yr-1) and a random error (on the order of ±1 cm w.e. yr-1). Finally, we then compare our corrected ice core SMB records to regional SMB derived from a state-of-the-art polar-oriented regional climate model to quantify the impact of ice core uncertainties on the modeled-observed SMB discrepancy.

Objectives The level of detail included when describing nailfold videocapillaroscopy (NVC) methods varies among research studies, making interpretation and comparison of results challenging. The overarching objective of the present study was to seek consensus on the reporting standards in NVC methodology for clinical research in rheumatic diseases and to propose a pragmatic reporting checklist. Methods Based on the items derived from a systematic review focused on this topic, a three-step web-based Delphi consensus on minimum reporting standards in NVC was performed among members of the European League against Rheumatism (EULAR) Study Group on Microcirculation in Rheumatic Diseases and the Scleroderma Clinical Trials Consortium. Results A total of 319 articles were selected by the systematic review, and 46 items were proposed in the Delphi process. This Delphi exercise was completed by 80 participants from 31 countries, including Australia and countries within Asia, Europe, North America and South America. Agreement was reached on items covering three main areas: patient preparation before NVC (15 items), device description (5 items) and examination details (13 items). Conclusion Based on the available evidence, the description of NVC methods was highly heterogeneous in the identified studies and differed markedly on several items. A reporting checklist of 33 items, based on practical suggestions made (using a Delphi process) by international participants, has been developed to provide guidance to improve and standardize the NVC methodology to be applied in future clinical research studies.

The Greenland Ice Sheet (GrIS) rapid mass loss is primarily driven by an increase in meltwater runoff, which highlights the importance of understanding the formation, evolution and impact of meltwater features on the ice sheet. Buried lakes are meltwater features that contain liquid water and exist under layers of snow, firn, and/or ice. These lakes are invisible in optical imagery, challenging the analysis of their evolution and implication for larger GrIS dynamics and mass change. Here, we present a method that uses a convolutional neural network, a deep learning method, to automatically detect buried lakes across the GrIS. For the years 2018 and 2019, we compare total areal extent of both buried and surface lakes across six regions, and use a regional climate model to explain the spatial and temporal differences. We find that the total buried lake extent after the 2019 melt season is 56 % larger than after the 2018 melt season across the entire ice sheet. Northern Greenland observes the largest increase in buried lake extent after the 2019 melt season, which we attribute to late-summer surface melt and high autumn temperatures. We also provide evidence that different processes are responsible for buried lake formation in different regions of the ice sheet. For example, in western Greenland, buried lakes often appear on the surface during the previous melt season, indicating that these features form when surface lakes partially freeze and become insulated as snowfall buries them. In contrast, in southeast Greenland, most buried lakes never appear on the surface, signifying that these features may form due to subsurface penetration of shortwave radiation and/or downward percolation of meltwater. This study helps to provide additional perspective on the potential role of meltwater on GrIS dynamics and mass loss.

Under anticipated future warming, the Greenland ice sheet (GrIS) will pass a threshold when meltwater runoff exceeds the accumulation of snow, resulting in a negative surface mass balance (SMB

The Thwaites Eastern Ice Shelf (TEIS) buttresses the eastern grounded portion of Thwaites Glacier through contact with a pinning point at its seaward limit. Loss of this ice shelf will promote further acceleration of Thwaites Glacier. Understanding the dynamic controls and structural integrity of the TEIS is therefore important to estimating Thwaites' future sea-level contribution. We present a ∼ 20-year record of change on the TEIS that reveals the dynamic controls governing the ice shelf's past behaviour and ongoing evolution. We derived ice velocities from MODIS and Sentinel-1 image data using feature tracking and speckle tracking, respectively, and we combined these records with ITS_LIVE and GOLIVE velocity products from Landsat-7 and Landsat-8. In addition, we estimated surface lowering and basal melt rates using the Reference Elevation Model of Antarctica (REMA) DEM in comparison to ICESat and ICESat-2 altimetry. Early in the record, TEIS flow dynamics were strongly controlled by the neighbouring Thwaites Western Ice Tongue (TWIT). Flow patterns on the TEIS changed following the disintegration of the TWIT around 2008, with a new divergence in ice flow developing around the pinning point at its seaward limit. Simultaneously, the TEIS developed new rifting that extends from the shear zone upstream of the ice rise and increased strain concentration within this shear zone. As these horizontal changes occurred, sustained thinning driven by basal melt reduced ice thickness, particularly near the grounding line and in the shear zone area upstream of the pinning point. This evidence of weakening at a rapid pace suggests that the TEIS is likely to fully destabilize in the next few decades, leading to further acceleration of Thwaites Glacier.