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Abstract. During the concluding phase of the NASA OperationIceBridge (OIB), we successfully completed two airborne measurementcampaigns (in 2018 and 2021, respectively) using a compact S and C band radarinstalled on a Single Otter aircraft and collected data over Alaskanmountains, ice fields, and glaciers. This paper reports seasonal snow depthsderived from radar data. We found large variations in seasonalradar-inferred depths with multi-modal distributions assuming a constantrelative permittivity for snow equal to 1.89. About 34 % of the snowdepths observed in 2018 were between 3.2 and 4.2 m, and close to 30 % of thesnow depths observed in 2021 were between 2.5 and 3.5 m. We observed snowstrata in ice facies, combined percolation and wet-snow facies, and dry-snow facies fromradar data and identified the transition areas from wet-snow facies to icefacies for multiple glaciers based on the snow strata and radarbackscattering characteristics. Our analysis focuses on the measured strataof multiple years at the caldera of Mount Wrangell (K'elt'aeni) to estimate the localsnow accumulation rate. We developed a method for using our radar readingsof multi-year strata to constrain the uncertain parameters of interpretationmodels with the assumption that most of the snow layers detected by theradar at the caldera are annual accumulation layers. At a 2004 ice core and2005 temperature sensor tower site, the locally estimated average snowaccumulation rate is ∼2.89 m w.e. a−1 between the years2003 and 2021. Our estimate of the snow accumulation rate between 2005 and2006 is 2.82 m w.e. a−1, which matches closely to the 2.75 m w.e. a−1 inferred from independent ground-truth measurements made the sameyear. The snow accumulation rate between the years 2003 and 2021 also showeda linear increasing trend of 0.011 m w.e. a−2. This trend iscorroborated by comparisons with the surface mass balance (SMB) derived forthe same period from the regional atmospheric climate model MAR (ModèleAtmosphérique Régional). According to MAR data, which show anincrease of 0.86 ∘C in this area for the period of 2003–2021, thelinear upward trend is associated with the increase in snowfall and rainfallevents, which may be attributed to elevated global temperatures. Thefindings of this study confirmed the viability of our methodology, as wellas its underlying assumptions and interpretation models.

 

Modèle Atmosphérique Régional (MAR) is a regional climate model that is fully coupled to a one-dimensional surface-atmosphere energy and mass transfer scheme, SISVAT (Soil Ice Snow Vegetation Atmosphere Transfer) (Fettweis et al., 2005, 2020; Lefebre et al., 2005). SISVAT employs a multilayered snowpack model, CROCUS, that simulates meltwater production, percolation, and refreeze (Brun et al., 1989), while also accounting for changes in albedo due to snow metamorphism (Brun et al., 1992). MAR has been extensively verified over the Greenland Ice Sheet and is therefore particularly well suited for analyses of Greenland ice sheet surface mass balance (Fettweis et al., 2011; Fettweis et al., 2020; Lefebre et al. 2005; Mattingly et al. 2020). Brun, E., Martin, E., Simon, V., Gendre, C., and Coléou, C. (1989). An energy and mass model of snow cover suitable for operational avalanche forecasting. Journal of Glaciology, 35, 333. https://doi.org/10.1017/S0022143000009254 Brun, E., David, P., Sudul, M., and Brunot, G. (1992). A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting. Journal of Glaciology, 38(128), 13–22. https://doi.org/10.3189/S0022143000009552 Fettweis, X., Gallée, H., Lefebre, F., and van Ypersele, J.-P. (2005). Greenland surface mass balance simulated by a regional climate model and comparison with satellite-derived data in 1990–1991. Climate Dynamics, 24(6), 623–640. https://doi.org/10.1007/s00382-005-0010-y Fettweis, X., Tedesco, M., van den Broeke, M., and Ettema, J. (2011). Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models. The Cryosphere, 5(2), 359–375. https://doi.org/10.5194/tc-5-359-2011 Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., et al. (2020). GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet. The Cryosphere, 14(11), 3935–3958. https://doi.org/10.5194/tc-14-3935-2020 Lefebre, F., Fettweis, X., Gallée, H., Van Ypersele, J.-P., Marbaix, P., Greuell, W., and Calanca, P. (2005). Evaluation of a high-resolution regional climate simulation over Greenland. Climate Dynamics, 25(1), 99–116. https://doi.org/10.1007/s00382-005-0005-8 Mattingly, K. S., Mote, T. L., Fettweis, X., van As, D., Van Tricht, K., Lhermitte, S., et al. (2020). Strong summer atmospheric rivers trigger Greenland ice sheet melt through spatially varying surface energy balance and cloud regimes. Journal of Climate, 33(16), 6809–6832. https://doi.org/10.1175/JCLI-D-19-0835.1 

Abstract. Surface mass loss from the Greenland ice sheet (GrIS) hasaccelerated over the past decades, mainly due to enhanced surface meltingand liquid water runoff in response to atmospheric warming. A large portionof runoff from the GrIS originates from exposure of the darker bare ice inthe ablation zone when the overlying snow melts, where surface albedo playsa critical role in modulating the energy available for melting. In thisregard, it is imperative to understand the processes governing albedovariability to accurately project future mass loss from the GrIS. Bare-icealbedo is spatially and temporally variable and contingent on non-linearfeedbacks and the presence of light-absorbing constituents. An assessment ofmodels aiming at simulating albedo variability and associated impacts onmeltwater production is crucial for improving our understanding of theprocesses governing these feedbacks and, in turn, surface mass loss fromGreenland. Here, we report the results of a comparison of the bare-iceextent and albedo simulated by the regional climate model ModèleAtmosphérique Régional (MAR) with satellite imagery from theModerate Resolution Imaging Spectroradiometer (MODIS) for the GrIS below70∘ N. Our findings suggest that MAR overestimates bare-ice albedoby 22.8 % on average in this area during the 2000–2021 period with respectto the estimates obtained from MODIS. Using an energy balance model toparameterize meltwater production, we find this bare-ice albedo bias canlead to an underestimation of total meltwater production from the bare-icezone below 70∘ N of 42.8 % during the summers of 2000–2021. 

Abstract. Understanding the role of atmospheric circulation anomalies on the surfacemass balance of the Greenland ice sheet (GrIS) is fundamental for improvingestimates of its current and future contributions to sea level rise. Here,we show, using a combination of remote sensing observations, regionalclimate model outputs, reanalysis data, and artificial neural networks, thatunprecedented atmospheric conditions (1948–2019) occurring in the summerof 2019 over Greenland promoted new record or close-to-record values ofsurfacemass balance (SMB), runoff, and snowfall. Specifically, runoff in 2019 ranked second withinthe 1948–2019 period (after 2012) and first in terms of surface massbalance negative anomaly for the hydrological year 1 September 2018–31 August 2019. The summer of 2019 was characterized by an exceptionalpersistence of anticyclonic conditions that, in conjunction with low albedoassociated with reduced snowfall in summer, enhanced the melt–albedofeedback by promoting the absorption of solar radiation and favoredadvection of warm, moist air along the western portion of the ice sheettowards the north, where the surface melt has been the highest since 1948.The analysis of the frequency of daily 500 hPa geopotential heights obtainedfrom artificial neural networks shows that the total number of days with thefive most frequent atmospheric patterns that characterized the summer of2019 was 5 standard deviations above the 1981–2010 mean, confirming theexceptional nature of the 2019 season over Greenland. 

Abstract. Changes in ocean temperature and salinity are expected to be an important determinant of the Greenland ice sheet's future sea level contribution. Yet, simulating the impact of these changes in continental-scale ice sheet models remains challenging due to the small scale of key physics, such as fjord circulation and plume dynamics, and poor understanding of critical processes, such as calving and submarine melting. Here we present the ocean forcing strategy for Greenland ice sheet models taking part in the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), the primary community effort to provide 21st century sea level projections for the Intergovernmental Panel on Climate Change Sixth Assessment Report. Beginning from global atmosphere–ocean general circulation models, we describe two complementary approaches to provide ocean boundary conditions for Greenland ice sheet models, termed the “retreat” and “submarine melt” implementations. The retreat implementation parameterises glacier retreat as a function of projected subglacial discharge and ocean thermal forcing, is designed to be implementable by all ice sheet models and results in retreat of around 1 and 15 km by 2100 in RCP2.6 and 8.5 scenarios, respectively. The submarine melt implementation provides estimated submarine melting only, leaving the ice sheet model to solve for the resulting calving and glacier retreat and suggests submarine melt rates will change little under RCP2.6 but will approximately triple by 2100 under RCP8.5. Both implementations have necessarily made use of simplifying assumptions and poorly constrained parameterisations and, as such, further research on submarine melting, calving and fjord–shelf exchange should remain a priority. Nevertheless, the presented framework will allow an ensemble of Greenland ice sheet models to be systematically and consistently forced by the ocean for the first time and should result in a significant improvement in projections of the Greenland ice sheet's contribution to future sea level change. 

Abstract. The effect of the North Atlantic Ocean on the Greenland Ice Sheet through submarine melting of Greenland's tidewater glacier calving fronts is thought to be a key driver of widespread glacier retreat, dynamic mass loss and sea level contribution from the ice sheet. Despite its critical importance, problems of process complexity and scale hinder efforts to represent the influence of submarine melting in ice-sheet-scale models. Here we propose parameterizing tidewater glacier terminus position as a simple linear function of submarine melting, with submarine melting in turn estimated as a function of subglacial discharge and ocean temperature. The relationship is tested, calibrated and validated using datasets of terminus position, subglacial discharge and ocean temperature covering the full ice sheet and surrounding ocean from the period 1960–2018. We demonstrate a statistically significant link between multi-decadal tidewater glacier terminus position change and submarine melting and show that the proposed parameterization has predictive power when considering a population of glaciers. An illustrative 21st century projection is considered, suggesting that tidewater glaciers in Greenland will undergo little further retreat in a low-emission RCP2.6 scenario. In contrast, a high-emission RCP8.5 scenario results in a median retreat of 4.2 km, with a quarter of tidewater glaciers experiencing retreat exceeding 10 km. Our study provides a long-term and ice-sheet-wide assessment of the sensitivity of tidewater glaciers to submarine melting and proposes a practical and empirically validated means of incorporating ocean forcing into models of the Greenland ice sheet. 

From early 2003 to mid-2013, the total mass of ice in Greenland declined at a progressively increasing rate. In mid-2013, an abrupt reversal occurred, and very little net ice loss occurred in the next 12–18 months. Gravity Recovery and Climate Experiment (GRACE) and global positioning system (GPS) observations reveal that the spatial patterns of the sustained acceleration and the abrupt deceleration in mass loss are similar. The strongest accelerations tracked the phase of the North Atlantic Oscillation (NAO). The negative phase of the NAO enhances summertime warming and insolation while reducing snowfall, especially in west Greenland, driving surface mass balance (SMB) more negative, as illustrated using the regional climate model MAR. The spatial pattern of accelerating mass changes reflects the geography of NAO-driven shifts in atmospheric forcing and the ice sheet’s sensitivity to that forcing. We infer that southwest Greenland will become a major future contributor to sea level rise.

 

Abstract. Projection of the contribution of ice sheets to sea level change as part ofthe Coupled Model Intercomparison Project Phase 6 (CMIP6) takes the formof simulations from coupled ice sheet–climate models and stand-alone icesheet models, overseen by the Ice Sheet Model Intercomparison Project forCMIP6 (ISMIP6). This paper describes the experimental setup forprocess-based sea level change projections to be performed with stand-aloneGreenland and Antarctic ice sheet models in the context of ISMIP6. TheISMIP6 protocol relies on a suite of polar atmospheric and oceanicCMIP-based forcing for ice sheet models, in order to explore the uncertaintyin projected sea level change due to future emissions scenarios, CMIPmodels, ice sheet models, and parameterizations for ice–ocean interactions.We describe here the approach taken for defining the suite of ISMIP6stand-alone ice sheet simulations, document the experimental framework andimplementation, and present an overview of the ISMIP6 forcing to beused by participating ice sheet modeling groups.