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This paper provides the first description of the open-source Glacier Energy and Mass Balance model. GEMB models the ice sheet and glacier surface–atmospheric energy and mass exchange, as well as the firn state. It is a column model (no horizontal communication) of intermediate complexity that includes those processes deemed most relevant to glacier studies. GEMB prioritizes computational efficiency to accommodate the very long (thousands of years) spin-ups necessary for initializing deep firn columns and sensitivity experiments needed to characterize model uncertainty on continental scales. The model is one-way coupled with the atmosphere, which allows the model to be run offline with a diversity of climate forcing but neglects feedback to the atmosphere. GEMB provides numerous parameterization choices for various key processes (e.g., albedo, subsurface shortwave absorption, and compaction), making it well suited for uncertainty quantification and model exploration. The model is evaluated against the current state of the art and in situ observations and is shown to perform well. [ABSTRACT FROM AUTHOR]

This paper provides the first description of version 1.0 of the open-source Glacier Energy and Mass Balance model. GEMB models the ice sheet and glacier surface-atmospheric energy and mass exchange, and firn state. It is a column model (no horizontal communication) of intermediate complexity that includes those processes deemed most relevant to glacier studies with the goal of retaining computational efficiency that can accommodate the very long (thousands of years) spin-ups necessary for initializing deep firn columns and for running sensitivity experiments to characterize model uncertainty on continental scales. The model is one-way coupled with the atmosphere which allows the model to be run off-line with a diversity of climate forcing but neglects feedback to the atmosphere. GEMB provides numerous parameterization choices for various key processes (e.g. albedo, subsurface shortwave absorption, and compaction), making it well suited for uncertainty quantification and model exploration. The model is evaluated against the current state-of-the-art and in situ observations and is shown to perform well. [ABSTRACT FROM AUTHOR]

Estimating the future evolution of the Antarctic Ice Sheet (AIS) is critical for improving future sea level rise (SLR) projections. Numerical ice sheet models are invaluable tools for bounding Antarctic vulnerability; yet, few continental-scale projections of century-scale AIS SLR contribution exist, and those that do vary by up to an order of magnitude. This is partly because model projections of future sea level are inherently uncertain and depend largely on the model's boundary conditions and climate forcing, which themselves are unknown due to the uncertainty in the projections of future anthropogenic emissions and subsequent climate response. Here, we aim to improve the understanding of how uncertainties in model forcing and boundary conditions affect ice sheet model simulations. With use of sampling techniques embedded within the Ice Sheet System Model (ISSM) framework, we assess how uncertainties in snow accumulation, ocean-induced melting, ice viscosity, basal friction, bedrock elevation, and the presence of ice shelves impact continental-scale 100-year model simulations of AIS future sea level contribution. Overall, we find that AIS sea level contribution is strongly affected by grounding line retreat, which is driven by the magnitude of ice shelf basal melt rates and by variations in bedrock topography. In addition, we find that over 1.2 m of AIS global mean sea level contribution over the next century is achievable, but not likely, as it is tenable only in response to unrealistically large melt rates and continental ice shelf collapse. Regionally, we find that under our most extreme 100-year warming experiment generalized for the entire ice sheet, the Amundsen Sea sector is the most significant source of model uncertainty (1032 mm 6σ spread) and the region with the largest potential for future sea level contribution (297 mm). In contrast, under a more plausible forcing informed regionally by literature and model sensitivity studies, the Ronne basin has a greater potential for local increases in ice shelf basal melt rates. As a result, under this more likely realization, where warm waters reach the continental shelf under the Ronne ice shelf, it is the Ronne basin, particularly the Evans and Rutford ice streams, that are the greatest contributors to potential SLR (161 mm) and to simulation uncertainty (420 mm 6σ spread). [ABSTRACT FROM AUTHOR]

Tidewater glacier velocity and mass balance are known to be highly responsive to terminus position change. Yet it remains challenging for ice flow models to reproduce observed ice margin changes. Here, using the Ice Sheet System Model (ISSM; Larour et al., 2012), we simulate the ice velocity and thickness changes of Upernavik Isstrøm (north-western Greenland) by prescribing a collection of 27 observed terminus positions spanning 164 years (1849-2012). The simulation shows increased ice velocity during the 1930s, the late 1970s and between 1995 and 2012 when terminus retreat was observed along with negative surface mass balance anomalies. Three distinct mass balance states are evident in the reconstruction: (1849-1932) with near zero mass balance, (1932-1992) with ice mass loss dominated by ice dynamical flow, and (1998-2012), when increased retreat and negative surface mass balance anomalies led to mass loss that was twice that of any earlier period. Over the multi-decadal simulation, mass loss was dominated by thinning and acceleration responsible for 70% of the total mass loss induced by prescribed change in terminus position. The remaining 30% of the total ice mass loss resulted directly from prescribed terminus retreat and decreasing surface mass balance. Although the method can not explain the cause of glacier retreat, it enables the reconstruction of ice flow and geometry during 1849-2012. Given annual or seasonal observed terminus front positions, this method could be a useful tool for evaluating simulations investigating the effect of calving laws. [ABSTRACT FROM AUTHOR]

Earlier large-scale Greenland ice sheet sea-level projections (e.g. those run during the ice2sea and SeaRISE initiatives) have shown that ice sheet initial conditions have a large effect on the projections and give rise to important uncertainties. The goal of this initMIP-Greenland intercomparison exercise is to compare, evaluate, and improve the initialisation techniques used in the ice sheet modelling community and to estimate the associated uncertainties in modelled mass changes. initMIP-Greenland is the first in a series of ice sheet model intercomparison activities within ISMIP6 (the Ice Sheet Model Intercomparison Project for CMIP6), which is the primary activity within the Coupled Model Intercomparison Project Phase 6 (CMIP6) focusing on the ice sheets. Two experiments for the large-scale Greenland ice sheet have been designed to allow intercomparison between participating models of (1) the initial present-day state of the ice sheet and (2) the response in two idealised forward experiments. The forward experiments serve to evaluate the initialisation in terms of model drift (forward run without additional forcing) and in response to a large perturbation (prescribed surface mass balance anomaly); they should not be interpreted as sea-level projections. We present and discuss results that highlight the diversity of data sets, boundary conditions, and initialisation techniques used in the community to generate initial states of the Greenland ice sheet. We find good agreement across the ensemble for the dynamic response to surface mass balance changes in areas where the simulated ice sheets overlap but differences arising from the initial size of the ice sheet. The model drift in the control experiment is reduced for models that participated in earlier intercomparison exercises. [ABSTRACT FROM AUTHOR]

The mechanical properties of glacier beds play a fundamental role in regulating the sensitivity of glaciers to environmental forcing across a wide range of timescales. Glaciers are commonly underlain by deformable till whose mechanical properties and influence on ice flow are not well understood but are critical for reliable projections of future glacier states. Using synoptic-scale observations of glacier motion in different seasons to constrain numerical ice flow models, we study the mechanics of the bed beneath Hofsjökull, a land-terminating ice cap in central Iceland. Our results indicate that the bed deforms plastically and weakens following incipient summertime surface melt. Combining the inferred basal shear traction fields with a Coulomb-plastic bed model, we estimate the spatially distributed effective basal water pressure and show that changes in basal water pressure and glacier accelerations are non-local and non-linear. These results motivate an idealized physical model relating mean basal water pressure and basal slip rate wherein the sensitivity of glacier flow to changes in basal water pressure is inversely related to the ice surface slope. [ABSTRACT FROM PUBLISHER]

The article focuses on a study conducted by the authors related to models of plan-view marine ice-sheets. It states that they conducted perturbation experiments which specified spatial variation in basal sliding and helped in evolution of grounding lines. It discusses intercomparison of the ice2sea MISMIP3d model. It highlights that examination of normal stresses perpendicular to the grounding lines reveals extension across the grounding lines.

The article presents the Tiling method to couple ice flow models of different orders of complexity. The goal of the method is to determine the spatial extent of where higher-order models are used to lessen the computational cost while retaining the model precision. A geometry for which all models yield similar results is used to examine the consistency of the method and a geometry where a full-Stokes model is needed in the vicinity of the ice front is used. The results reveal that the hybrid models show important improvements over mono-model approaches and lessen computational times.