The simulation of ice sheet-climate interactions, such as surface mass balance fluxes, is sensitive to model grid resolution. Here we simulate the multi-century evolution of the Greenland Ice Sheet (GrIS) and its interaction with the climate using the Community Earth System Model version 2.2 (CESM2.2) including an interactive GrIS component (the Community Ice Sheet Model v2.1 [CISM2.1]) under an idealized warming scenario (atmospheric (Formula presented.) increases by 1% (Formula presented.) until quadrupling the pre-industrial level and then is held fixed). A variable-resolution (VR) grid with 1/ (Formula presented.) regional refinement over the broader Arctic and (Formula presented.) resolution elsewhere is applied to the atmosphere and land components, and the results are compared with conventional (Formula presented.) lat-lon grid simulations to investigate the impact of grid refinement. Compared with the (Formula presented.) runs, the VR run features a slower rate of surface melt, especially over the western and northern GrIS, where the ice surface slopes gently toward the periphery. This difference pattern originates primarily from higher snow albedo and, thus, weaker albedo feedback in the VR run. The VR grid better captures the CISM ice sheet topography by reducing elevation discrepancies between CAM and CISM and is, therefore, less reliant on the downscaling algorithm, which is known to underestimate albedo gradients. The sea level rise contribution from the GrIS in the VR run is 53 mm by year 150 and 831 mm by year 350, approximately 40% and 20% less than that of the (Formula presented.) runs, respectively.

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The future contributions of the Antarctic Ice Sheet to sea level rise will depend on the evolution of its surface mass balance (SMB), which could amplify/dampen mass losses increasingly observed at the ice sheet's edge. In situ constraints of SMB over annual-to-decadal timescales consist mostly of firn/ice cores that have a surface footprint cm. SMB constraints also come from climate models, which have a higher temporal resolution but a larger surface footprint of several km. We use ice-penetrating radar data to obtain an intermediate spatial and temporal resolution SMB record over three ice rises along the Princess Ragnhild Coast. The co-located ice cores allow us to obtain absolute radar-derived SMB rates at a multi-annual-to-decadal temporal resolution. By comparing the ice core SMB measurements and the radar-derived SMB records, we determine that pointwise measurements of SMB are representative of a small surface area, m radius extending from the ice core drill site for the ice rises studied here, and that the pointwise measurements are systematically 7–15 cm w.e. a lower than the mean SMB value calculated for the whole ice rises. However, ice core records are representative of an entire ice rise's temporal variability at the temporal resolution examined.@en

Earth system/ice-sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea-level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2). This study describes the coupling and novel capabilities of the model, including: (1) an advanced energy-balance-based surface mass balance calculation in the land component with downscaling via elevation classes; (2) a closed freshwater budget from ice sheet to the ocean from surface runoff, basal melting, and ice discharge; (3) dynamic land surface types; and (4) dynamic atmospheric topography. The Earth system/ice-sheet coupling is demonstrated in a simulation with an evolving Greenland Ice Sheet (GrIS) under an idealized high CO₂ scenario. The model simulates a large expansion of ablation areas (where surface ablation exceeds snow accumulation) and a large increase in surface runoff. This results in an elevated freshwater flux to the ocean, as well as thinning of the ice sheet and area retreat. These GrIS changes result in reduced Greenland surface albedo, changes in the sign and magnitude of sensible and latent heat fluxes, and modified surface roughness and overall ice sheet topography. Representation of these couplings between climate and ice sheets is key for the simulation of ice and climate interactions.

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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.

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Continuous measurements of blowing snow are scarce, both in time and space. Satellites now provide the opportunity to derive blowing snow occurrences, transport and sublimation rates over Antarctica. These products are extremely valuable and offer a continental-wide assessment of blowing snow, which is an important but unknown component of the surface mass balance of the Antarctic ice sheet. However, little ground truth is available to validate these retrievals. The recent application of ceilometers for detection of blowing snow frequencies provides an opportunity to validate the satellite retrievals of blowing snow. A routine to detect blowing snow occurrence from ground-based remote sensing ceilometers has been developed at two coastal locations in East Antarctica for the 2011–2016 time period. Thanks to their ground-based location, ceilometers are able to detect blowing snow events in the presence of clouds and precipitation, which can be missed by the satellite, since optically thick clouds impede the penetration of the signal. In coastal areas, more than 90% of blowing snow occurs under cloudy conditions and represent 30 to 56% of all cloudy conditions at Princess Elisabeth and Neumayer III (Neumayer hereafter) stations, respectively. For cloud-free conditions, 8% of the measurements at Princess Elisabeth (and none at Neumayer) are identified as blowing snow by the satellite but not by the ceilometer, likely due to differences in sensors, limitation of the surface identification by the satellite, or the spatial inhomogeneity of the blowing snow event. While the satellite blowing snow retrieval is a useful product, further investigation is needed to reduce the uncertainties on blowing snow frequencies associated with clouds.

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The Greenland Ice Sheet (GrIS) mass balance is examined with an Earth system/ice sheet model that interactively couples the GrIS to the broader Earth system. The simulation runs from 1850 to 2100, with historical and SSP5-8.5 forcing. By the mid-21st century, the cumulative GrIS contribution to global mean sea level rise (SLR) is 23 mm. During the second half of the 21st century, the surface mass balance becomes negative in all drainage basins, with an additional SLR contribution of 86 mm. The annual mean GrIS mass loss in the last two decades is 2.7-mm sea level equivalent (SLE) year⁻¹. The increased SLR contribution from the surface mass balance (3.1 mm SLE year⁻¹) is partly offset by reduced ice discharge from thinning and retreat of outlet glaciers. The southern GrIS drainage basins contribute 73% of the mass loss in mid-century but 55% by 2100, as surface runoff increases in the northern basins.

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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.
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To better understand and quantify the impact of clouds on the Greenland Ice Sheet surface mass balance (SMB), we study the spatiotemporal variability of the cloud radiative effect (CRE). The total CRE is separated in short-term and long-term impacts by performing multiple simulations with the SNOWPACK model for 2001-+2010. The annual total CRE is 16.8 ± 4.5 W m⁻², reducing the SMB with −157 ± 3.8 Gt yr⁻¹. Summer cloud radiative cooling is −6.4 ± 5.7 W m⁻² in the ablation area, increasing the SMB with 121 ± 2.2 Gt yr⁻¹. The annual integrated impact is cloud-reduced SMB of −36 Gt yr⁻¹. The short-term effect dominates the opposing long-term effects through the albedo-melt feedback. A long-term warming effect decreases the albedo and so preconditions the surface for enhanced (summer) melt. The impact of the CRE, determined by spatial, temporal and initial conditions, explains existing conflicted views on the role of cloud radiation and emphasizes the need for accurate cloud and albedo representations in future studies.

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A new set of stratospheric aerosol geoengineering (SAG) model experiments has been performed with Community Earth System Model version 2 (CESM2) with the Whole Atmosphere Community Climate Model (WACCM6) that are based on the Coupled Model Intercomparison Project phase 6 (CMIP6) overshoot scenario (SSP5-34-OS) as a baseline scenario to limit global warming to 1.5 or 2.0&thinsp;<span classCombining double low line"inline-formula">ĝ</span>C above 1850-1900 conditions. The overshoot scenario allows us to applying a peak-shaving scenario that reduces the needed duration and amount of SAG application compared to a high forcing scenario. In addition, a feedback algorithm identifies the needed amount of sulfur dioxide injections in the stratosphere at four pre-defined latitudes, 30<span classCombining double low line"inline-formula">ĝ</span>&thinsp;N, 15<span classCombining double low line"inline-formula">ĝ</span>&thinsp;N, 15<span classCombining double low line"inline-formula">ĝ</span>&thinsp;S, and 30<span classCombining double low line"inline-formula">ĝ</span>&thinsp;S, to reach three surface temperature targets: global mean temperature, and interhemispheric and pole-To-Equator temperature gradients. These targets further help to reduce side effects, including overcooling in the tropics, warming of high latitudes, and large shifts in precipitation patterns. These experiments are therefore relevant for investigating the impacts on society and ecosystems. Comparisons to SAG simulations based on a high emission pathway baseline scenario (SSP5-85) are also performed to investigate the dependency of impacts using different injection amounts to offset surface warming by SAG. We find that changes from present-day conditions around 2020 in some variables depend strongly on the defined temperature target (1.5&thinsp;<span classCombining double low line"inline-formula">ĝ</span>C vs. 2.0&thinsp;<span classCombining double low line"inline-formula">ĝ</span>C). These include surface air temperature and related impacts, the Atlantic Meridional Overturning Circulation, which impacts ocean net primary productivity, and changes in ice sheet surface mass balance, which impacts sea level rise. Others, including global precipitation changes and the recovery of the Antarctic ozone hole, depend strongly on the amount of SAG application. Furthermore, land net primary productivity as well as ocean acidification depend mostly on the global atmospheric <span classCombining double low line"inline-formula">CO2</span> concentration and therefore the baseline scenario. Multi-model comparisons of experiments that include strong mitigation and carbon dioxide removal with some SAG application are proposed to assess the robustness of impacts on societies and ecosystems.

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About 20 % of all snow accumulation in Antarctica occurs on the ice shelves. There, ice rises control the spatial surface mass balance (SMB) distribution by inducing snowfall variability and wind erosion due to their topography. Moreover these ice rises buttress the ice flow and represent ideal drilling locations for ice cores. In this study we assess the connection between snowfall variability and wind erosion to provide a better understanding of how ice rises impact SMB variability, how well this is captured in the regional atmospheric climate model RACMO2 and the implications of this SMB variability for ice rises as an ice core drilling site. By combining ground-penetrating radar (GPR) profiles from two ice rises in Dronning Maud Land with ice core dating, we reconstruct spatial and temporal SMB variations from 1983 to 2018 and compare the observed SMB with output from RACMO2 and SnowModel. Our results show snowfall-driven differences of up to 1.5 times higher SMB on the windward side of both ice rises than on the leeward side as well as a local erosion-driven minimum at the ice divide of the ice rises. RACMO2 captures the snowfall-driven differences but overestimates their magnitude, whereas the erosion on the peak can be reproduced by SnowModel with RACMO2 forcing. Observed temporal variability of the average SMBs, retrieved from the GPR data for four time intervals in the 1983-2018 range, are low at the peak of the easternmost ice rise (∼ 0.06 m w.e. yr⁻¹), while they are higher (∼ 0.09 m w.e. yr⁻¹) on the windward side of the ice rise. This implies that at the peak of the ice rise, higher snowfall, driven by orographic uplift, is balanced out by local erosion. As a consequence of this, the SMB recovered from the ice core matches the SMB from the GPR at the peak of the ice rise but not at the windward side of the ice rise, suggesting that the SMB signal is damped in the ice core.

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Surface meltwater ponding has been implicated as a major driver for recent ice shelf collapse as well as the speedup of tributary glaciers in the northeast Antarctic Peninsula. Surface melt on the NAP is impacted by the strength and frequency of westerly winds, which result in sporadic foehn flow. We estimate changes in the frequency of foehn flow and the associated impact on snow melt, density, and the percolation depth of meltwater over the period 1982–2017 using a regional climate model and passive microwave data. The first of two methods extracts spatial patterns of melt occurrence using empirical orthogonal function analysis. The second method applies the Foehn Index, introduced here to capture foehn occurrence over the full study domain. Both methods show substantial foehn-induced melt late in the melt season since 2015, resulting in compounded densification of the near-surface snow, with potential implications for future ice shelf stability.@en

The modeling of ice sheets in Earth system models (ESMs) is an active area of research with applications to future sea level rise projections and paleoclimate studies. A major challenge for surface mass balance (SMB) modeling with ESMs arises from their coarse resolution. This paper evaluates the elevation class (EC) method as an SMB downscaling alternative to the dynamical downscaling of regional climate models. To this end, we compare EC-simulated elevation-dependent surface energy and mass balance gradients from the Community Earth System Model 1.0 (CESM1.0) with those from the regional climate model RACMO2.3. The EC implementation in CESM1.0 combines prognostic snow albedo, a multilayer snow model, and elevation corrections for two atmospheric forcing variables: temperature and humidity. Despite making no corrections for incoming radiation and precipitation, we find that the EC method in CESM1.0 yields similar SMB gradients to RACMO2.3, in part due to compensating biases in snowfall, surface melt, and refreezing gradients. We discuss the sensitivity of the results to the lapse rate used for the temperature correction. We also evaluate the impact of the EC method on the climate simulated by the ESM and find minor cooling over the Greenland ice sheet and Barents and Greenland seas, which compensates for a warm bias in the ESM due to topographic smoothing. Based on our diagnostic procedure to evaluate the EC method, we make several recommendations for future implementations.@en

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 2229ĝ€Gtĝ€yĝ'1, with an interannual variability of 109ĝ€Gtĝ€yĝ'1. The largest improvement is found in modelled surface snowmelt, which now compares well with satellite and weather station observations. For the high-resolution ( ĝ1/4 ĝ€5.5ĝ€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.

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We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 (1958-2016). The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of cloud condensate into precipitation have been tuned to correct inland snowfall underestimation: snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves the spatial patterns and temporal variability of SMB compared with the previous model version, notably in the north-east, south-east and along the K-transect in south-western Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS present-day climate and SMB, and will be used for projections of the GrIS climate and SMB in response to a future climate scenario in a forthcoming study.

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Ice sheets are a major component of the Earth System, however they are not yet interactively coupled to most global climate models. Here we present past achievements in this front with the CESM1.0 version as well as first results and challenges with the upcoming CESM2.0, where the Community Ice Sheet Model 2.1 is bi-directionally coupled to the atmospheric and ocean components, as opposed to only one-way coupling in CESM1.0. In both CESM versions, the surface mass balance (SMB) is calculated in the land component (CLM) with explicit albedo and refreezing calculations, and downscaled to the ice sheet model resolution via elevation classes and bi-linear (horizontal) and linear (vertical) interpolations. A major highlight of CESM is that the most important coupling process between ice sheet and atmosphere, the albedo feedback, is explicitly modeled, as opposed to state-of-the-art parameterizations of albedo and/or surface melt. Regarding future Greenland ice sheet projections with CESM1, we summarize our results on: 1) doubled end-of-the-century melt rates under RCP8.5 from increased incoming thermal radiation and turbulent fluxes despite decreased incoming solar radiation over Greenland from more clouds, 2) increase in SMB variability due to reduced accumulation to ablation area ration, 3) bimodal emergence of an anthropogenic signal on the SMB due to both increasing melt and snow accumulation, 4) reduction in ice discharge from marginal thinning. We also outline work in progress in preparation for our contribution to the Ice Sheet Model Intercomparison Project 6 (ISMIP6) and paleo-research on the last deglaciation, e.g., on model initialization, improved SMB calculation, evaluation of CESM2.0 climate over Greenland, and parameter optimization of the higher-order CISM2.1. @en

Melting of the Greenland ice sheet (GrIS) and its peripheral glaciers and ice caps (GICs) contributes about 43% to contemporary sea level rise. While patterns of GrIS mass loss are well studied, the spatial and temporal evolution of GICs mass loss and the acting processes have remained unclear. Here we use a novel, 1 km surface mass balance product, evaluated against in situ and remote sensing data, to identify 1997 (±5 years) as a tipping point for GICs mass balance. That year marks the onset of a rapid deterioration in the capacity of the GICs firn to refreeze meltwater. Consequently, GICs runoff increases 65% faster than meltwater production, tripling the post-1997 mass loss to 36±16 Gt -'1, or -1/414% of the Greenland total. In sharp contrast, the extensive inland firn of the GrIS retains most of its refreezing capacity for now, buffering 22% of the increased meltwater production. This underlines the very different response of the GICs and GrIS to atmospheric warming.

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Blowing snow impacts Antarctic ice sheet surface mass balance by snow redistribution and sublimation. However, numerical models poorly represent blowing snow processes, while direct observations are limited in space and time. Satellite retrieval of blowing snow is hindered by clouds and only the strongest events are considered. Here, we develop a blowing snow detection (BSD) algorithm for ground-based remote-sensing ceilometers in polar regions and apply it to ceilometers at Neumayer III and Princess Elisabeth (PE) stations, East Antarctica. The algorithm is able to detect (heavy) blowing snow layers reaching 30ĝ€m height. Results show that 78ĝ€% of the detected events are in agreement with visual observations at Neumayer III station. The BSD algorithm detects heavy blowing snow 36ĝ€% of the time at Neumayer (2011-2015) and 13ĝ€% at PE station (2010-2016). Blowing snow occurrence peaks during the austral winter and shows around 5ĝ€% interannual variability. The BSD algorithm is capable of detecting blowing snow both lifted from the ground and occurring during precipitation, which is an added value since results indicate that 92ĝ€% of the blowing snow is during synoptic events, often combined with precipitation. Analysis of atmospheric meteorological variables shows that blowing snow occurrence strongly depends on fresh snow availability in addition to wind speed. This finding challenges the commonly used parametrizations, where the threshold for snow particles to be lifted is a function of wind speed only. Blowing snow occurs predominantly during storms and overcast conditions, shortly after precipitation events, and can reach up to 1300ĝ€mĝ€†a. g. l. in the case of heavy mixed events (precipitation and blowing snow together). These results suggest that synoptic conditions play an important role in generating blowing snow events and that fresh snow availability should be considered in determining the blowing snow onset.

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Surface mass balance (SMB) strongly controls spatial and temporal variations in the Antarctic Ice Sheet (AIS) mass balance and its contribution to sea level rise. Currently, the scarcity of observational data and the challenges of climate modeling over the ice sheet limit our understanding of the processes controlling AIS SMB. Particularly, the impact of blowing snow on local SMB is not yet constrained and is subject to large uncertainties.
Tho assess the impact of blowing snow on local SMB, we investigate the 15-sec attenuated backscatter profiles from 910 nm ceilometers at two East Antarctic locations in Dronning Maud Land. Ceilometers are robust ground-based remote sensing instruments that can withstand harsh conditions unmanned and produce data continuously. In addition to yielding information on cloud base height and vertical structure, these instruments also provide information on the particles present in the boundary layer. We developed a new algorithm to detect
blowing snow (snow particles lifted by the wind from the surface to substantial height) from the ceilometer attenuated backscatter. The algorithm routinely detects the presence of blowing snow if 1) a certain threshold is be exceeded at the range bin closest to the ground (signaling a large concentration of scatterers), and 2) if the intensity of the signal decreases with height (signature of the presence of a blowing snow layer). The algorithm successfully allows to detect strong blowing snow signal from layers thicker than 15 m at the Princess Elisabeth (PE, 72S, 23E) and Neumayer (70S, 8 W) stations in Dronning Maud Land, East Antarctica. Moreover, we combined the ceilometer with automatic weather stations to understand key conditions for blowing snow at the study locations.
Results show a very good match between the blowing snow events detected by the new algorithm and visual observations at Neumayer station. Applying the algorithm to PE station, we retrieve the frequency and annual cycle of blowing snow. Finally, the analysis of the automatic weather station data enables to distinguish key meteorological parameters for blowing snow conditions: wind speed, wind direction, relative humidity and temperature inversion (boundary layer stability). These parameters can then be used as input in snow models
resolving blowing snow and for validation of the blowing snow schemes in climate models.@en

Surface melt and subsequent firn air depletion is considered an important precursor for disintegration of Antarctic ice shelves, causing grounded glaciers to accelerate and sea level to rise. Recent studies have highlighted the
impact of surface winds on Antarctic ice shelf melt, both on the Antarctic Peninsula and in East Antarctica. In the Antarctic Peninsula, foehn winds enhance melting near the grounding line, which in the recent past has
led to the disintegration of the most northerly ice shelves. On the East Antarctic ice shelves, on the other hand, meltwater-induced firn air depletion is found in the grounding zone as result of persistent katabatic winds,
regionally warming the atmosphere and inducing a melt-albedo feedback.
Here, we use a combination multi-source satellite imagery, snow modelling, climate model output and insitu observations to highlight the importance of this wind-induced melt and to show its widespread occurrence across Antarctica. The satellite imagery gives insight in the meltwater drainage systems, showing spatio-temporal changes in both supraglacial and englacial water throughout the melt season and during the subsequent winter. Although the wind-induced melt is a regional phenomenon with strong inter-annual variability, it is strongly correlated to larger scale climate parameters, such as summer surface temperature. Based on these correlations and snow model output driven by future climate scenarios, we can constrain the future changes to this local melt
near the grounding line.@en

We present climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS) as simulated by the global, coupled ocean–atmosphere–land Community Earth System Model (CESM) with a horizontal resolution of ∼ 1 ^∘ in the past, present and future (1850–2100). CESM correctly simulates present-day Antarctic sea ice extent, large-scale atmospheric circulation and near-surface climate, but fails to simulate the recent expansion of Antarctic sea ice. The present-day Antarctic ice sheet SMB equals 2280 ± 131 Gtyear-1, which concurs with existing independent estimates of AIS SMB. When forced by two CMIP5 climate change scenarios (high mitigation scenario RCP2.6 and high-emission scenario RCP8.5), CESM projects an increase of Antarctic ice sheet SMB of about 70 Gtyear-1 per degree warming. This increase is driven by enhanced snowfall, which is partially counteracted by more surface melt and runoff along the ice sheet’s edges. This intensifying hydrological cycle is predominantly driven by atmospheric warming, which increases (1) the moisture-carrying capacity of the atmosphere, (2) oceanic source region evaporation, and (3) summer AIS cloud liquid water content.

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