Ice Sheet Surface Mass Balance Research Articles

Comparison of Multiple Methods for Supraglacial Melt-Lake Volume Estimation in Western Greenland During the 2021 Summer Melt Season

Supraglacial melt-lakes form and evolve along the western edge of the Greenland Ice Sheet and have proven to play a significant role in ice sheet surface hydrology and mass balance. Prior methods to quantify melt-lake volume have relied upon Landsat-8 optical imagery, available at 30 m spatial resolution but with temporal resolution limited by satellite overpass times and cloud cover. We propose two novel methods to quantify the volume of meltwater stored in these lakes, including a high-resolution surface DEM (ArcticDEM) and an ablation model using daily averaged automated weather station data. We compare our methods to the depth-reflectance method for five supraglacial melt-lakes during the 2021 summer melt season. We find agreement between the depth-reflectance and DEM lake infilling methods, within +/−15% for most cases, but our ablation model underproduces by 0.5–2 orders of magnitude the volumetric melt needed to match our other methods, and with a significant lag in meltwater onset for routing into the lake basin. Further information regarding energy balance parameters, including insolation and liquid precipitation amounts, is needed for adequate ablation modelling. Despite the differences in melt-lake volume estimates, our approach in combining remote sensing and meteorological methods provides a framework for analysis of seasonal melt-lake evolution at significantly higher spatial and temporal scales, to understand the drivers of meltwater production and its influence on the spatial distribution and extent of meltwater volume stored on the ice sheet surface.

How does a change in climate variability impact the Greenland ice sheet surface mass balance?

Abstract. Given the long response time of ice sheets, simulations of the Greenland ice sheet typically exceed the availability of input climate data to reliably simulate the fast processes underlying surface mass balance. Strong feedback processes are known to make the mass balance sensitive to inter- and intra-annual variability. Even simulations with climate models do not always cover the full period of interest, motivating bridging these gaps using relatively coarsely resolved climate reconstructions or temporal interpolation methods. However, both of these approaches usually only provide information about the climatological average but not variability. We investigate how this simplification impacts the surface mass balance using the BErgen Snow SImulator. The model was run for up to 500 years using the same atmospheric climatology but different synthetic variabilities. While changing inter-annual variations has an impact of less than 5 % on the surface mass balance of the Greenland ice sheet, neglecting intra-annual variability by using a daily climatology causes a 40 % change in mass balance. Decomposing the total effect into contributions from different input variables, the biggest contributor is precipitation followed by temperature. Using a daily climatology, a small amount of snowfall every day overestimates the albedo and thus surface mass balance (SMB). We propose a correction that re-captures the effect of intermittent precipitation, reducing the SMB overestimation to 15 %–25 %. We conclude that simulations of the Greenland surface mass and energy balance should be forced with a transient climate, in particular for models that are calibrated with transient data.

The Effect of Physically Based Ice Radiative Processes on Greenland Ice Sheet Albedo and Surface Mass Balance in E3SM

AbstractA significant portion of surface melt on the Greenland Ice Sheet (GrIS) is due to dark ice regions in the ablation zone, where solar absorption is influenced by the physical properties of the ice, light absorbing constituents (LACs), and the overlying crustal surface or melt ponds. Earth system models (ESMs) typically prescribe the albedo of ice surfaces as a constant value in the visible and near‐infrared spectral regions. This work advances ESM ice radiative transfer modeling by (a) incorporating a physically based radiative transfer model (SNow, ICe and Aerosol Radiation model Adding‐Doubling Version 4; SNICAR‐ADv4) into the Energy Exascale Earth System Model (E3SM), (b) determining spatially and temporally varying bare ice physical properties over the GrIS ablation zone from satellite observations to inform SNICAR‐ADv4, and (c) assessing the impacts on simulated GrIS albedo and surface mass balance associated with modeling of more realistic bare ice albedo. GrIS‐wide bare ice albedo in E3SMv2 is overestimated by ∼4% in the visible and ∼7% in the near‐infrared wavelengths compared to the Moderate Resolution Imaging Spectroradiometer. Our bare ice physical property retrieval method found that LACs, ice crustal surfaces, and melt ponds reduce visible albedo by 30% in the bare ice region of the GrIS ablation zone. The realistic bare ice albedo reduces surface mass balance by ∼145 Gt, or 0.4 mm of sea‐level equivalent between 2000 and 2021 compared to the default E3SM. This work highlights the importance of simulating bare ice albedo accurately and realistically to improve our ability to quantify changes in the GrIS surface mass and radiative energy budgets.

A stochastic parameterization of ice sheet surface mass balance for the Stochastic Ice-Sheet and Sea-Level System Model (StISSM v1.0)

Abstract. Many scientific and societal questions that draw on ice sheet modeling necessitate sampling a wide range of potential climatic changes and realizations of internal climate variability. For example, coastal planning literature demonstrates a demand for probabilistic sea level projections with quantified uncertainty. Further, robust attribution of past and future ice sheet change to specific processes or forcings requires a full understanding of the space of possible ice sheet behaviors. The wide sampling required to address such questions is computationally infeasible with sophisticated numerical climate models at the resolution required to accurately force ice sheet models. Stochastic generation of climate forcing of ice sheets offers a complementary alternative. Here, we describe a method to construct a stochastic generator for ice sheet surface mass balance varying in time and space. We demonstrate the method with an application to Greenland Ice Sheet surface mass balance for 1980–2012. We account for spatial correlations among glacier catchments using sparse covariance techniques, and we apply an elevation-dependent downscaling to recover gridded surface mass balance fields suitable for forcing an ice sheet model while including feedback from changing ice sheet surface elevation. The efficiency gained in the stochastic method supports large-ensemble simulations of ice sheet change in a new stochastic ice sheet model. We provide open source Python workflows to support use of our stochastic approach for a broad range of applications.

Surface mass balance and climate of the Last Glacial Maximum Northern Hemisphere ice sheets: simulations with CESM2.1

Abstract. The Last Glacial Maximum (LGM, from ∼26 to 20 ka BP) was the most recent period with large ice sheets in Eurasia and North America. At that time, global temperatures were 5–7 ∘C lower than today, and sea level ∼125 m lower. LGM simulations are useful to understand earth system dynamics, including climate–ice sheet interactions, and to evaluate and improve the models representing those dynamics. Here, we present two simulations of the Northern Hemisphere ice sheet climate and surface mass balance (SMB) with the Community Earth System Model v2.1 (CESM2.1) using the Community Atmosphere Model v5 (CAM5) with prescribed ice sheets for two time periods that bracket the LGM period: 26 and 21 ka BP. CESM2.1 includes an explicit simulation of snow/firn compaction, albedo, refreezing, and direct coupling of the ice sheet surface energy fluxes with the atmosphere. The simulated mean snow accumulation is lowest for the Greenland and Barents–Kara Sea ice sheets (GrIS, BKIS) and highest for British and Irish (BIIS) and Icelandic (IcIS) ice sheets. Melt rates are negligible for the dry BKIS and GrIS, and relatively large for the BIIS, North American ice sheet complex (NAISC; i.e. Laurentide, Cordilleran, and Innuitian), Scandinavian ice sheet (SIS), and IcIS, and are reduced by almost a third in the colder (lower temperature) 26 ka BP climate compared with 21 ka BP. The SMB is positive for the GrIS, BKIS, SIS, and IcIS during the LGM (26 and 21 ka BP) and negative for the NAISC and BIIS. Relatively wide ablation areas are simulated along the southern (terrestrial), Pacific and Atlantic margins of the NAISC, across the majority of the BIIS, and along the terrestrial southern margin of the SIS. The integrated SMB substantially increases for the NAISC and BIIS in the 26 ka BP climate, but it does not reverse the negative sign. Summer incoming surface solar radiation is largest over the high interior of the NAISC and GrIS, and minimum over the BIIS and southern margin of NAISC. Summer net radiation is maximum over the ablation areas and minimum where the albedo is highest, namely in the interior of the GrIS, northern NAISC, and all of the BKIS. Summer sensible and latent heat fluxes are highest over the ablation areas, positively contributing to melt energy. Refreezing is largest along the equilibrium line altitude for all ice sheets and prevents 40 %–50 % of meltwater entering the ocean. The large simulated melt for the NAISC suggests potential biases in the climate simulation, ice sheet reconstruction, and/or highly non-equilibrated climate and ice sheet at the LGM time.

Atmospheric Response to Antarctic Sea-Ice Reductions Drives Ice Sheet Surface Mass Balance Increases

Abstract The mass balance of the Antarctic ice sheet is intricately linked to the state of the surrounding atmosphere and ocean. As a direct result, improving projections of future sea level change requires understanding change in the Antarctic atmosphere and Southern Ocean, and the processes that couple these systems. Here, we examine the influence of sea ice cover on the overlying atmosphere and subsequently the surface mass balance (SMB) of the adjacent Antarctic ice sheet. We investigate these processes both over the observational era using the ERA5 atmospheric reanalysis and in ensemble simulations of the Community Earth System Model 2.1 (CESM2) where only sea ice coverage is altered. Comparing extreme high and low sea ice over the satellite era in ERA5 reveals atmospheric and ice sheet SMB anomalies that largely mirror anomalies simulated by CESM2 in response to sea ice loss. Results highlight significant near-surface atmospheric warming in response to sea ice reductions that are particularly pronounced in nonsummer seasons and driven by significant ocean-to-atmosphere turbulent heat fluxes. In areas of sea ice loss, significant ocean surface evaporation increases occur. On the eastern flank of climatological low pressure systems, moisture is readily advected toward the ice sheet, driving positive anomalies in the ice sheet SMB. These results indicate that underestimation of Antarctic sea ice, which is common in many current-generation coupled climate models, may lead to overestimation of the ice sheet SMB and therefore underestimation of Antarctica’s contributions to global sea level. Significance Statement The Antarctic ice sheet is the largest potential source of global sea level rise. Its sea level contributions depend in part on how much snow accumulates across its surface. Through observation-incorporating reanalysis data and climate model sensitivity studies, we find that Southern Ocean sea ice coverage exerts an important influence on the near-surface climate and mass balance of the Antarctic ice sheet. Our results show that reductions in Antarctic sea ice promote enhanced ocean surface evaporation and subsequent increases in snowfall across the Antarctic ice sheet. Because current climate models tend to simulate too little Antarctic sea ice, we conclude they may therefore overestimate Antarctic ice sheet snowfall, leading to underprediction of future sea level rise.

A wind-driven snow redistribution module for Alpine3D v3.3.0: adaptations designed for downscaling ice sheet surface mass balance

Abstract. Ice sheet surface mass balance describes the net snow accumulation at the ice sheet surface. On the Antarctic ice sheet, winds redistribute snow, resulting in a surface mass balance that is variable in both space and time. Representing wind-driven snow redistribution processes in models is critical for local assessments of surface mass balance, repeat altimetry studies, and interpretation of ice core accumulation records. To this end, we have adapted Alpine3D, an existing distributed snow modeling framework, to downscale Antarctic surface mass balance to horizontal resolutions up to 1 km. In particular, we have introduced a new two-dimensional advection-based wind-driven snow redistribution module that is driven by an offline coupling between WindNinja, a wind downscaling model, and Alpine3D. We then show that large accumulation variability can be at least partially explained by terrain-induced wind speed variations which subsequently redistribute snow around rolling topography. By comparing Alpine3D to airborne-derived snow accumulation measurements within a testing domain over Pine Island Glacier in West Antarctica, we demonstrate that our Alpine3D downscaling approach improves surface mass balance estimates when compared to the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), a global atmospheric reanalysis which we use as atmospheric forcing. In particular, when compared to MERRA-2, Alpine3D reduces simulated surface mass balance root mean squared error by 23.4 mmw.e.yr-1 (13 %) and increases variance explained by 24 %. Despite these improvements, our results demonstrate that considerable uncertainty stems from the employed saltation model, confounding simulations of surface mass balance variability.

Discussing an extreme mock/what-if scenario over the antarctic peninsula: the effect of intense melt on surface mass balance

This discussion paper interprets the findings of a recent study comparing melt estimates from the regional atmospheric model MAR, those derived from Automatic Weather Stations (AWS), and microwave remote sensing images over the Antarctic Peninsula from 2019 to 2021. Our interpretation reveals a paradox: MAR overestimates melt when compared to AWS-based melt estimates, yet underestimates melt when compared to satellite imagery. This discrepancy underscores a fundamental gap in our understanding of surface processes. To illustrate the potential implications of this gap, we present a fictional (“what-if”) scenario that explores an extreme case of melting, based on parametrizations from Kittel et al., 2022, and the outliers of Dethinne et al., 2023. We examine the potential impact on the ice sheet's surface mass balance (SMB), drawing parallels with the situation in Greenland during the 1990s, where increased melt production had cascading effects on SMB. Moreover, we highlight that the presence of liquid water at the surface of the snowpack can be a precursor to significant destabilization processes over ice shelves, although this aspect is not the focus of our current paper. By opening a debate on the accuracy and interpretation of melt modeling, we aim to draw attention to the potential consequences of extreme melting events on the Antarctic Ice Sheet's SMB and stability.

Light absorption and albedo reduction by pigmented microalgae on snow and ice

AbstractPigmented microalgae inhabiting snow and ice environments lower the albedo of glacier and ice-sheet surfaces, significantly enhancing surface melt. Our ability to accurately predict their role in glacier and ice-sheet surface mass balance is limited by the current lack of empirical data to constrain their representation in predictive models. Here we present new empirical optical properties for snow and ice algae and incorporate them in a radiative transfer model to investigate their impact on snow and ice surface albedo. We found ice algal cells to be more efficient absorbers than snow algal cells, but their blooms had comparable impact on surface albedo due to the different photic conditions of their habitats. We then used the model to reconstruct the effect of ice algae on bare ice albedo spectra collected at our field site in southern Greenland, where blooms dropped the albedo locally by between 3 and 43%, equivalent to 1–10 L m$^{-2}$ d$^{-1}$ of melted ice. Using the newly parametrized model, future studies could investigate biological albedo reduction and algal quantification from remote hyperspectral and multispectral imagery.

Multi-decadal retreat of marine-terminating outlet glaciers in northwest and central-west Greenland

Abstract. The retreat and acceleration of marine-terminating outlet glaciers in Greenland over the past 2 decades have been widely attributed to climate change. Here we present a comprehensive annual record of glacier terminus positions in northwest and central-west Greenland and compare it against local and regional climatology to assess the regional sensitivity of glacier termini to different climatic factors. This record is derived from optical and radar satellite imagery and spans 87 marine-terminating outlet glaciers from 1972 through 2021. We find that in this region, most glaciers have retreated over the observation period and widespread regional retreat accelerated from around 1996. The acceleration of glacier retreat coincides with the timing of sharp shifts in ocean surface temperatures, the duration of the sea-ice season, ice-sheet surface mass balance, and meltwater and runoff production. Regression analysis indicates that terminus retreat is most sensitive to increases in runoff and ocean temperatures, while the effect of offshore sea ice is weak. Because runoff and ocean temperatures can influence terminus positions through several mechanisms, our findings suggest that a variety of processes – such as ocean-interface melting, mélange presence and rigidity, and hydrofracture-induced calving – may contribute to, but do not conclusively dominate, the observed regional retreat.

Brief communication: Impact of common ice mask in surface mass balance estimates over the Antarctic ice sheet

Abstract. Regional climate models compute ice sheet surface mass balance (SMB) over a mask that defines the area covered by glacier ice, but ice masks have not been harmonised between models. Intercomparison studies of modelled SMB therefore use a common ice mask. The SMB in areas outside the common ice mask, which are typically coastal and high-precipitation regions, is discarded. Ice mask differences change integrated SMB by between 40.5 and 140.6 Gt yr−1 (1.8 % to 6.0 % of ensemble mean SMB), equivalent to the entire Antarctic mass imbalance. We conclude there is a pressing need for a common ice mask protocol.

Coupling the U.K. Earth System Model to Dynamic Models of the Greenland and Antarctic Ice Sheets

AbstractThe physical interactions between ice sheets and the atmosphere and ocean around them are major factors in determining the state of the climate system, yet many current Earth System models omit them entirely or treat them very simply. In this work we describe how models of the Greenland and Antarctic ice sheets have been incorporated into the global U.K. Earth System model (UKESM1) via substantial technical developments with a two‐way coupling that passes fluxes of energy and water, and the topography of the ice sheet surface and ice shelf base, between the component models. File‐based coupling outside the running model executables is used throughout to pass information between the components, which we show is both physically appropriate and convenient within the UKESM1 structure. Ice sheet surface mass balance is computed in the land surface model using multi‐layer snowpacks in subgrid‐scale elevation ranges and compares well to the results of regional climate models. Ice shelf front discharge forms icebergs, which drift and melt in the ocean. Ice shelf basal mass balance is simulated using the full three‐dimensional ocean model representation of the circulation in ice‐shelf cavities. We show a range of example results, including from simulations with changes in ice sheet height and thickness of hundreds of meters, and changes in ice sheet grounding line and land‐terminating margin of many tens of kilometres, demonstrating that the coupled model is computationally stable when subject to significant changes in ice sheet geometry.

Local and Remote Atmospheric Circulation Drivers of Arctic Change: A Review

Arctic Amplification is a fundamental feature of past, present, and modelled future climate. However, the causes of this “amplification” within Earth’s climate system are not fully understood. To date, warming in the Arctic has been most pronounced in autumn and winter seasons, with this trend predicted to continue based on model projections of future climate. Nevertheless, the mechanisms by which this will take place are numerous, interconnected. and complex. Will future Arctic Amplification be primarily driven by local, within-Arctic processes, or will external forces play a greater role in contributing to changing climate in this region? Motivated by this uncertainty in future Arctic climate, this review seeks to evaluate several of the key atmospheric circulation processes important to the ongoing discussion of Arctic amplification, focusing primarily on processes in the troposphere. Both local and remote drivers of Arctic amplification are considered, with specific focus given to high-latitude atmospheric blocking, poleward moisture transport, and tropical-high latitude subseasonal teleconnections. Impacts of circulation variability and moisture transport on sea ice, ice sheet surface mass balance, snow cover, and other surface cryospheric variables are reviewed and discussed. The future evolution of Arctic amplification is discussed in terms of projected future trends in atmospheric blocking and moisture transport and their coupling with the cryosphere. As high-latitude atmospheric circulation is strongly influenced by lower-latitude processes, the future state of tropical-to-Arctic teleconnections is also considered.

The AntSMB dataset: a comprehensive compilation of surface mass balance field observations over the Antarctic Ice Sheet

Abstract. A comprehensive compilation of observed records is needed for accurate quantification of surface mass balance (SMB) over Antarctica, which is a key challenge for calculation of Antarctic contribution to global sea level change. Here, we present the AntSMB dataset: a new quality-controlled dataset of a variety of published field measurements of the Antarctic Ice Sheet SMB by means of stakes, snow pits, ice cores, ultrasonic sounders, and ground-penetrating radar (GPR). The dataset collects 3579 individual multi-year-averaged observations, 687 annually resolved time series from 675 sites extending back over the past 1000 years, and daily resolved records covering 245 years from 32 sites across the whole ice sheet. These records are derived from ice cores, snow pits, stakes/stake farms, and ultrasonic sounders. Furthermore, GPR multi-year-averaged measurements are included in the dataset, covering an area of 22 025 km2. This is the first ice-sheet-scale compilation of SMB records at different temporal (daily, annual, and multi-year) resolutions from multiple types of measurement and is available at https://doi.org/10.11888/Glacio.tpdc.271148 (Wang et al., 2021). The database has potentially wide applications such as the investigation of temporal and spatial variability in SMB, model validation, assessment of remote sensing retrievals, and data assimilation. As a case of model estimation, records of the AntSMB dataset are used to assess the performance of ERA5 for temporal and spatial variability in SMB over Antarctica.

Surface melting over the Greenland ice sheet derived from enhanced resolution passive microwave brightness temperatures (1979–2019)

Abstract. Surface melting is a major component of the Greenland ice sheet surface mass balance, and it affects sea level rise through direct runoff and the modulation of ice dynamics and hydrological processes, supraglacially, englacially and subglacially. Passive microwave (PMW) brightness temperature observations are of paramount importance in studying the spatial and temporal evolution of surface melting due to their long temporal coverage (1979–present) and high temporal resolution (daily). However, a major limitation of PMW datasets has been the relatively coarse spatial resolution, which has historically been of the order of tens of kilometers. Here, we use a newly released PMW dataset (37 GHz, horizontal polarization) made available through a NASA “Making Earth System Data Records for Use in Research Environments” (MeASUREs) program to study the spatiotemporal evolution of surface melting over the Greenland ice sheet at an enhanced spatial resolution of 3.125 km. We assess the outputs of different detection algorithms using data collected by automatic weather stations (AWSs) and the outputs of the Modèle Atmosphérique Régional (MAR) regional climate model. We found that sporadic melting is well captured using a dynamic algorithm based on the outputs of the Microwave Emission Model of Layered Snowpack (MEMLS), whereas a fixed threshold of 245 K is capable of detecting persistent melt. Our results indicate that, during the reference period from 1979 to 2019 (from 1988 to 2019), surface melting over the ice sheet increased in terms of both duration, up to 4.5 (2.9) d per decade, and extension, up to 6.9 % (3.6 %) of the entire ice sheet surface extent per decade, according to the MEMLS algorithm. Furthermore, the melting season started up to 4.0 (2.5) d earlier and ended 7.0 (3.9) d later per decade. We also explored the information content of the enhanced-resolution dataset with respect to the one at 25 km and MAR outputs using a semi-variogram approach. We found that the enhanced product is more sensitive to local-scale processes, thereby confirming the potential of this new enhanced product for monitoring surface melting over Greenland at a higher spatial resolution than the historical products and for monitoring its impact on sea level rise. This offers the opportunity to improve our understanding of the processes driving melting, to validate modeled melt extent at high resolution and, potentially, to assimilate these data in climate models.

Long-Term Snow Height Variations in Antarctica from GNSS Interferometric Reflectometry

Acquiring reliable estimates of the Antarctic Ice Sheet surface mass balance is essential for trustworthy predictions of its evolution and future contribution to sea level rise. Snow height variations, i.e., the net change of the surface elevation resulting from a combination of surface processes such as snowfall, ablation, and wind redistribution, can provide a unique tool to constrain the uncertainty on mass budget estimations. In this study, GNSS Interferometric Reflectometry (GNSS-IR) is exploited to assess the long-term variations of snow accumulation and ablation processes. Eight antennas belonging to the Polar Earth Observing Network (POLENET) network are considered, together with the ROB1 antenna, deployed in the east part of Antarctica by the Royal Observatory of Belgium. For ROB1, which is located on an ice rise, we highlight an annual variation of snow accumulation in April–May (~30–50 cm) and ablation during spring/summer period. A snow surface elevation velocity of +0.08 ± 0.01 ma−1 is observed in the 2013–2016 period, statistically rejecting the “no trend” null hypothesis. As the POLENET stations are all located on moving glaciers, their associated downhill motion must be corrected for using an elevation model. This induces an increased uncertainty on the snow surface elevation change determined from GNSS-IR. Among the eight stations analyzed, only three of them show a long-term snow height variation larger than the uncertainties. One is located on the Flask Galcier in the Antarctic Peninsula, with a decrease of more than 4 m between 2012 and 2014, with an uncertainty of 2.5 m. The second one is located on the Lower Thwaites Glacier where we observe, between 2010 and 2020, a snow surface drop of 10 m, with a conservative uncertainty of 1 m. The third station, located on the West Antarctic Ice Sheet (WAIS) divide, shows on the opposite an upward motion from 2005 to 2019, of 1.2 m with an uncertainty of 0.4 m. The snow surface change of the other POLENET stations analyzed is smaller than the uncertainty associated with the glacier slope.

Review article: Earth's ice imbalance

Abstract. We combine satellite observations and numerical models to show that Earth lost 28 trillion tonnes of ice between 1994 and 2017. Arctic sea ice (7.6 trillion tonnes), Antarctic ice shelves (6.5 trillion tonnes), mountain glaciers (6.1 trillion tonnes), the Greenland ice sheet (3.8 trillion tonnes), the Antarctic ice sheet (2.5 trillion tonnes), and Southern Ocean sea ice (0.9 trillion tonnes) have all decreased in mass. Just over half (58 %) of the ice loss was from the Northern Hemisphere, and the remainder (42 %) was from the Southern Hemisphere. The rate of ice loss has risen by 57 % since the 1990s – from 0.8 to 1.2 trillion tonnes per year – owing to increased losses from mountain glaciers, Antarctica, Greenland and from Antarctic ice shelves. During the same period, the loss of grounded ice from the Antarctic and Greenland ice sheets and mountain glaciers raised the global sea level by 34.6 ± 3.1 mm. The majority of all ice losses were driven by atmospheric melting (68 % from Arctic sea ice, mountain glaciers ice shelf calving and ice sheet surface mass balance), with the remaining losses (32 % from ice sheet discharge and ice shelf thinning) being driven by oceanic melting. Altogether, these elements of the cryosphere have taken up 3.2 % of the global energy imbalance.

Review of the current polar ice sheet surface mass balance and its modelling: the 2020 summer edition

Review of the current polar ice sheet surface mass balance and its modelling: the 2020 summer edition

Scoring Antarctic surface mass balance in climate models to refine future projections

Abstract. 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.

Large and irreversible future decline of the Greenland ice sheet

Abstract. We have studied the evolution of the Greenland ice sheet under a range of constant climates typical of those projected for the end of the present century using a dynamical ice sheet model (Glimmer) coupled to an atmosphere general circulation model (FAMOUS–ice AGCM). The ice sheet surface mass balance (SMB) is simulated within the AGCM by a multilayer snow scheme from snowfall and surface energy fluxes, including refreezing and dependence on altitude within AGCM grid boxes. Over millennia under any warmer climate, the ice sheet reaches a new steady state, whose mass is correlated with the magnitude of global climate change imposed. If a climate that gives the recently observed SMB were maintained, global-mean sea level rise (GMSLR) would reach 0.5–2.5 m. For any global warming exceeding 3 K, the contribution to GMSLR exceeds 5 m. For the largest global warming considered (about +5 K), the rate of GMSLR is initially 2.7 mm yr−1, and eventually only a small ice cap endures, resulting in over 7 m of GMSLR. Our analysis gives a qualitatively different impression from previous work in that we do not find a sharp threshold warming that divides scenarios in which the ice sheet suffers little reduction from those in which it is mostly lost. The final steady state is achieved by withdrawal from the coast in some places and a tendency for increasing SMB due to enhancement of cloudiness and snowfall over the remaining ice sheet by the effects of topographic change on atmospheric circulation, outweighing the tendency for decreasing SMB from the reduction in surface altitude. If late 20th-century climate is restored after the ice sheet mass has fallen below a threshold of about 4 m of sea level equivalent, it will not regrow to its present extent because the snowfall in the northern part of the island is reduced once the ice sheet retreats from there. In that case, about 2 m of GMSLR would become irreversible. In order to avoid this outcome, anthropogenic climate change must be reversed before the ice sheet has declined to the threshold mass, which would be reached in about 600 years at the highest rate of mass loss within the likely range of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.