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

Hansen, Nicolaj; Simonsen, Sebastian B.; Boberg, Fredrik; Kittel, Christoph; Orr, Andrew; Souverijns, Niels; Wessem, Jan Melchior van; Mottram, Ruth

doi:10.5194/tc-16-711-2022

Cited by 13 publications

(12 citation statements)

References 22 publications

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“…5d at the edges of the Ronne-Filchner and Ross ice shelves. It is shown in Mottram et al (2021) and Hansen et al (2022) that these edge effects, due to inconsistent ice masks, can have a significant impact on the total estimated SMB over the ice sheet. In this paper, although ice-sheet-wide totals are computed (Table 2), the focus is primarily on evaluating variability in the time series at each 12 km grid cell after regridding products to a common high-resolution grid.…”

Section: Contribution To Variability From the Choice Of Domain Ice Ma...mentioning

confidence: 99%

Variability in Antarctic surface climatology across regional climate models and reanalysis datasets

et al. 2022

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Abstract. Regional climate models (RCMs) and reanalysis datasets provide valuable information for assessing the vulnerability of ice shelves to collapse over Antarctica, which is important for future global sea level rise estimates. Within this context, this paper examines variability in snowfall, near-surface air temperature and melt across products from the Met Office Unified Model (MetUM), Regional Atmospheric Climate Model (RACMO) and Modèle Atmosphérique Régional (MAR) RCMs, as well as the ERA-Interim and ERA5 reanalysis datasets. Seasonal and trend decomposition using LOESS (STL) is applied to split the monthly time series at each model grid cell into trend, seasonal and residual components. Significant systematic differences between outputs are shown for all variables in the mean and in the seasonal and residual standard deviations, occurring at both large and fine spatial scales across Antarctica. Results imply that differences in the atmospheric dynamics, parametrisation, tuning and surface schemes between models together contribute more significantly to large-scale variability than differences in the driving data, resolution, domain specification, ice sheet mask, digital elevation model and boundary conditions. Despite significant systematic differences, high temporal correlations are found for snowfall and near-surface air temperature across all products at fine spatial scales. For melt, only moderate correlation exists at fine spatial scales between different RCMs and low correlation between RCM and reanalysis outputs. Root mean square deviations (RMSDs) between all outputs in the monthly time series for each variable are shown to be significant at fine spatial scales relative to the magnitude of annual deviations. Correcting for systematic differences results in significant reductions in RMSDs, suggesting the importance of observations and further development of bias-correction techniques.

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Section: Contribution To Variability From the Choice Of Domain Ice Ma...mentioning

confidence: 99%

Variability in Antarctic surface climatology across regional climate models and reanalysis datasets

et al. 2022

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“…Gardner and others, 2013; Hugonnet and others, 2021). Hansen and others (2022) investigated how different ice masks defining the ice-covered area in Antarctica in regional climate models (Mottram and others, 2021) affect the modeled surface mass balance. Despite small differences in the total area (<3%), modeled surface mass balances differed substantially solely due to different ice mask definitions (up to 6% of the ensemble mean balance, which corresponds to the total Antarctic mass imbalance).…”

Section: How To Distinguish Glaciers From the Ice Sheets?mentioning

confidence: 99%

What is the global glacier ice volume outside the ice sheets?

et al. 2023

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A recent study (Millan and others, 2022a, Nature Geoscience 15(2), 124–129) claims that ice volume contained in all glaciers outside the ice sheets and its potential contribution to sea level is 20% less than previously estimated. However, the apparent decrease is largely due to differences in choice of domain, as the study excludes 80% of the glacier area in the Antarctic periphery that was included in previous global glacier volume estimates. The issue highlights the difficulty in separating glaciers from the ice-sheet proper, especially in Antarctica, and the need for both the glacier and ice-sheet communities to develop standards and protocols to avoid double-counting in global ice volume and mass-change assessments and projections. Process-based inversion models have replaced earlier scaling methods, but large uncertainties in global glacier volume estimation remain due to the ill-posed nature of the inversion problem and poorly constrained parameters emphasizing the need for more direct ice thickness observations.

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“…To ensure a consistent comparison, we apply a common ice surface mask for the RACMO and PISM melt fields in all analyses presented here (cf. Hansen et al, 2022).…”

Section: Model Parameter Calibrationmentioning

confidence: 99%

The evolution of future Antarctic surface melt using PISM-dEBM-simple

Garbe

Zeitz²,

Krebs‐Kanzow³

et al. 2023

Preprint

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Abstract. It is virtually certain that Antarctica's contribution to sea-level rise will increase with future warming, although competing mass balance processes hamper accurate quantification of the exact magnitudes. Today, ocean-induced melting underneath the floating ice shelves dominates mass losses, but melting at the surface will gain importance as global warming continues. Meltwater at the ice surface has crucial implications for the ice sheet's stability, as it increases the risk of hydrofracturing and ice-shelf collapse that could cause enhanced glacier outflow into the ocean. Simultaneously, positive feedbacks between the atmosphere and the ice elevation and albedo can accelerate mass losses and increase the ice sheet's sensitivity to warming. However, due to long response times it may take hundreds to thousands of years until the ice sheet fully adjusts to the environmental changes. Therefore, ice sheet model simulations must be computationally fast and capture the relevant feedbacks, including the ones at the ice–atmosphere interface. Here we use the novel surface melt module dEBM-simple, coupled to the Parallel Ice Sheet Model (PISM), to estimate the impact of 21st-century atmospheric warming on Antarctic surface melt and long-term ice dynamics. As an enhancement compared to the widely adopted positive degree-day (PDD) scheme, dEBM-simple includes an implicit diurnal cycle and computes melt not only from the temperature, but also from the influence of solar radiation and changes in ice albedo, thus accounting for the melt–albedo feedback. We calibrate PISM-dEBM-simple to reproduce historical and present-day Antarctic surface melt rates given by the regional climate model RACMO2.3p2 and use the calibrated model to assess the range of possible future surface melt trajectories under SSP5-8.5 warming projections, extended beyond 2100 under fixed climatological conditions. Our findings reveal a substantial speed-up in ice flow associated with large-scale elevation reductions in sensitive ice-sheet regions, underscoring the critical role of self-reinforcing ice-sheet–atmosphere feedbacks on future mass losses and sea-level contribution from the Antarctic Ice Sheet on centennial to millennial timescales.

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

Cited by 13 publications

References 22 publications

Variability in Antarctic surface climatology across regional climate models and reanalysis datasets

Variability in Antarctic surface climatology across regional climate models and reanalysis datasets

What is the global glacier ice volume outside the ice sheets?

The evolution of future Antarctic surface melt using PISM-dEBM-simple

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