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The Arctic is warming rapidly, significantly reducing the Greenland ice sheet (GrIS) surface mass balance (SMB) and raising its contribution to global sea‐level rise. Since these trends are expected to continue, it is essential to explore the GrIS SMB response to projected climate warming. We compare projections from three polar regional climate models, RACMO, MAR, and HIRHAM, forced by the Community Earth System Model CESM2 under a high‐end warming scenario (SSP5‐8.5, 1970–2099). We reveal different modeled SMB by 2100, including a twofold larger annual surface mass loss in MAR (−1735 Gt/yr) and HIRHAM (−1698 Gt/yr) relative to RACMO (−964 Gt/yr). Discrepancies primarily stem from differences in projected runoff, triggering melt‐albedo positive feedback and subsequent modeled ablation zone expansion. In addition, we find different responses of modeled meltwater production to similar atmospheric warming. Our analysis suggests clear avenues for model developments to further improve SMB projections and contribution to sea‐level rise. Plain Language Summary: We explore how three different polar climate models predict the future surface mass balance (SMB) of the Greenland ice sheet (GrIS), a major contributor to global sea‐level rise. Our results show that SMB projections among these models differ significantly by the end of the century. Differences primarily stem from how models convert meltwater into surface runoff toward the ocean, a crucial SMB component that directly contributes to sea‐level rise. Another key factor is the response of these models to climate warming, substantially affecting future melting rates. Our research highlights the need for further improvements of these climate models. By identifying and understanding the drivers behind model differences, we can improve SMB predictions and better estimate future global sea‐level rise. Key Points: With identical forcing, Greenland Ice Sheet surface mass balance from 3 regional climate models shows a two‐fold difference by 2100Different runoff projections stem from substantial discrepancies in projected ablation zone expansion, and reciprocallyThe response of meltwater production to similar atmospheric warming differs significantly among regional climate models [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet is a key contributor to sea level rise. By melting, the ice sheet thins, inducing higher surface melt due to lower surface elevations, accelerating the melt coming from global warming. This process is called the melt–elevation feedback and can be considered by using two types of models: either (1) atmospheric models, which can represent the surface mass balance (SMB), or SMB estimates resulting from simpler models such as positive degree day models or (2) ice sheet models representing the surface elevation evolution. The latter ones do not represent the surface mass balance explicitly as well as polar-oriented climate models. A new coupling between the MAR (Modèle Atmosphérique Régional) regional climate model and the PISM (Parallel Ice Sheet Model) ice sheet model is presented here following the CESM2 (Community Earth System Model; SSP5-8.5, Shared Socioeconomic Pathway) scenario until 2100 at the MAR lateral boundaries. The coupling is extended to 2200 with a stabilised climate (+7 ∘ C compared to 1961–1990) by randomly sampling the last 10 years of CESM2 to force MAR and reaches a sea level rise contribution of 64 cm. The fully coupled simulation is compared to a one-way experiment where surface topography remains fixed in MAR. However, the surface mass balance is corrected for the melt–elevation feedback when interpolated on the PISM grid by using surface mass balance vertical gradients as a function of local elevation variations (offline correction). This method is often used to represent the melt–elevation feedback and prevents a coupling which is too expensive in computation time. In the fully coupled MAR simulation, the ice sheet morphology evolution (changing slope and reducing the orographic barrier) induces changes in local atmospheric patterns. More specifically, wind regimes are modified, as well as temperature lapse rates, influencing the melt rate through modification of sensible heat fluxes at the ice sheet margins. We highlight mitigation of the melt lapse rate on the margins by modifying the surface morphology. The lapse rates considered by the offline correction are no longer valid at the ice sheet margins. If used (one-way simulation), this correction implies an overestimation of the sea level rise contribution of 2.5 %. The mitigation of the melt lapse rate on the margins can only be corrected by using a full coupling between an ice sheet model and an atmospheric model. [ABSTRACT FROM AUTHOR]

Global warming has already substantially altered the Arctic cryosphere. Due to the Arctic warming amplification, the temperature is increasing more strongly, leading to pervasive changes in this area. Recent years were notably marked by melt records over the Greenland Ice Sheet, while other regions such as Svalbard seem to remain less influenced. This raises the question of the current state of the Greenland Ice Sheet and the various ice caps in the Arctic for which few studies are available. Here, we run the regional climate model (RCM) Modèle Atmosphérique Régional (MAR) at a resolution of 6 km over four different domains covering all Arctic land ice to produce a unified surface mass balance product from 1950 to the present day. We also compare our results to large-scale indices to better understand the heterogeneity of the evolutions across the Arctic and their links to recent climate change. We find a sharp decrease of surface mass balance (SMB) over the western Arctic (Canada and Greenland) in relationship with the atmospheric blocking situations that have become more frequent in summer, resulting in a 41 % increase of the melt rate since 1950. This increase is not seen over the Russian Arctic permanent ice areas, where melt rates have increased by only 3 % on average, illustrating a heterogeneity in the Arctic SMB response to global warming. [ABSTRACT FROM AUTHOR]

The Greenland Ice Sheet (GrIS) will be losing mass at an accelerating pace throughout the 21st century, with a direct link between anthropogenic greenhouse gas emissions and the magnitude of Greenland mass loss. Currently, approximately 60 % of the mass loss contribution comes from surface melt and subsequent meltwater runoff, while 40 % are due to ice calving. In the ablation zone covered by bare ice in summer, most of the surface melt energy is provided by absorbed shortwave fluxes, which could be reduced by solar geoengineering measures. However, so far very little is known about the potential impacts of an artificial reduction in the incoming solar radiation on the GrIS surface energy budget and the subsequent change in meltwater production. By forcing the regional climate model MAR with the latest CMIP6 shared socioeconomic pathways (SSP) future emission scenarios (SSP245, SSP585) and associated G6solar experiment from the CNRM-ESM2-1 Earth system model, we estimate the local impact of a reduced solar constant on the projected GrIS surface mass balance (SMB) decrease. Overall, our results show that even in the case of a low-mitigation greenhouse gas emissions scenario (SSP585), the Greenland surface mass loss can be brought in line with the medium-mitigation emissions scenario (SSP245) by reducing the solar downward flux at the top of the atmosphere by ∼ 40 W/m 2 or ∼ 1.5 % (using the G6solar experiment). In addition to reducing global warming in line with SSP245, G6solar also decreases the efficiency of surface meltwater production over the Greenland ice sheet by damping the well-known positive melt–albedo feedback. With respect to a MAR simulation where the solar constant remains unchanged, decreasing the solar constant according to G6solar in the MAR radiative scheme mitigates the projected Greenland ice sheet surface melt increase by 6 %. However, only more constraining geoengineering experiments than G6solar would allow us to maintain a positive SMB until the end of this century without any reduction in our greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

The Greenland blocking index (GBI), an indicator of the synoptic‐scale circulation over Greenland, has been anomalously positive during most summers since the late 1990s. Such changes in atmospheric circulation, favouring anticyclonic conditions, have led to an increase in Greenland summer temperatures, a decrease in cloud cover and larger surface melt. The GBI is therefore a key indicator of melting and surface mass balance variability over the Greenland ice sheet. However, the models of fifth phase of the Coupled Model Intercomparison Project (CMIP5) do not represent the increase in GBI that is suggested by recent observations, and do not project any significant increase in GBI until 2100. In this study, the new generation of CMIP6 Earth‐system models is evaluated in order to analyse the evolution of the future GBI. All CMIP5 and CMIP6 projections reveal the same trend towards a decrease of the GBI until 2100 and no model reproduces the strong increase in the persistence of summer blocking events observed over the last few decades. Significant melting events related to a highly positive GBI, as observed in summer 2019, are still not considered by CMIP6 models and therefore the projected surface melt increase of the ice sheet could be underestimated if such summer circulation changes persist in the next decades. [ABSTRACT FROM AUTHOR]

Future climate projections show a marked increase in Greenland Ice Sheet (GrIS) runoff during the 21st century, a direct consequence of the Polar Amplification signal. Regional climate models (RCMs) are a widely used tool to downscale ensembles of projections from global climate models (GCMs) to assess the impact of global warming on GrIS melt and sea level rise contribution. Initial results of the CMIP6 GCM model intercomparison project have revealed a greater 21st century temperature rise than in CMIP5 models. However, so far very little is known about the subsequent impacts on the future GrIS surface melt and therefore sea level rise contribution. Here, we show that the total GrIS sea level rise contribution from surface mass loss in our high-resolution (15 km) regional climate projections is 17.8 ± 7.8 cm in SSP585, 7.9 cm more than in our RCP8.5 simulations using CMIP5 input. We identify a +1.3 °C greater Arctic Amplification and associated cloud and sea ice feedbacks in the CMIP6 SSP585 scenario as the main drivers. Additionally, an assessment of the GrIS sea level contribution across all emission scenarios highlights, that the GrIS mass loss in CMIP6 is equivalent to a CMIP5 scenario with twice the global radiative forcing. The potential contribution of Greenland Ice Sheet to sea level rise in the future is known to be substantial. Here, the authors undertake new modelling showing that the Greenland Ice Sheet sea level rise contribution is 7.9 cm more using the CMIP6 SSP585 scenario compared to CMIP5 using multiple RCP8.5 simulations. [ABSTRACT FROM AUTHOR]

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

The ERA5 reanalysis, recently made available by the European Centre for Medium-Range Weather Forecasts (ECMWF), is a new reanalysis product at a high resolution replacing ERA-Interim and is considered to provide the best climate reanalysis over Greenland to date. However, so far little is known about the performance of ERA5 over the Greenland Ice Sheet (GrIS). In this study, we compare the near-surface climate from the new ERA5 reanalysis to ERA-Interim, the Arctic System Reanalysis (ASR) as well as to a state-of-the-art polar regional climate model (MAR). The results show (1) that ERA5 does not outperform ERA-Interim significantly when compared with near-surface climate observations over GrIS, but ASR better models the near-surface temperature than both ERA reanalyses. (2) Polar regional climate models (e.g., MAR) are still a useful tool to downscale the GrIS climate compared to ERA5, as in particular the near-surface temperature in summer has a key role for representing snow and ice processes such as the surface melt. However, assimilating satellite data and using a more recent radiative scheme enable both ERA and ASR reanalyses to represent more satisfactorily than MAR the downward solar and infrared fluxes. (3) MAR near-surface climate is not affected when forced at its lateral boundaries by either ERA5 or ERA-Interim. Therefore, forcing polar regional climate models with ERA5 starting from 1950 will enable long and homogeneous surface mass balance reconstructions. [ABSTRACT FROM AUTHOR]

The new reanalysis produced by the ECMWF, ERA5, is currently available over the period 2000-2017. Ultimately, it will cover the period 1950 to the present-time and will replace the ERA-Interim, which is by many considered as one of the best reanalyses over the Greenland ice sheet (GrIS). We first compare the ERA5 reanalysis to ERA-Interim and ASR (Arctic System reanalysis), which is a regional reanalysis specifically developed for the Arctic area at a finer resolution. We evaluate them against a set of near-surface climate observations from the AWS of the PROMICE network covering the GrIS. This observation data set is not assimilated in these reanalyses. We furthermore assess the ability of the state-of-the-art regional climate model (RCM) MAR, forced by the ECMWF reanalyses, ERA-Interim and ERA5, to represent the AWS observations. Finally, we demonstrate the advantages of using MAR compared to the forcing reanalyses alone. ERA5 improves ERA-Interim almost for radiative fluxes, but not significantly. ASR, which is more specific for Arctic region and has a finer spatial resolution, outclasses other reanalyses for wind speed and near-surface temperature. The comparison of results from MAR simulations forced by ERA-Interim and ERA5 reanalysis shows that the near-surface climate variables are closed to each other and then not significantly different according to the forcing used. ERA5 which should replace ERA-Interim after 2018, can be used to force a RCM such as MAR in the same way than ERA-Interim now. Although the reanalyses seem to be sufficient to study the surface climate of Greenland, the RCM MAR has the best representation of the near-surface temperature even without any data assimilation. This is mainly due to a better representation of the snowpack and interactions between surface and atmosphere by MAR, resulting in a better representation of the surface melt and the GrIS surface mass balance (SMB). Near-surface temperature and SMB are both very useful for constraining glacial dynamics models in order to represent the current and future evolution of the ice dynamics of the GrIS. [ABSTRACT FROM AUTHOR]