Abstract

The behavior of the Greenland Ice Sheet, which is considered a major contributor to sea level changes, is best understood on century and longer time scales. However, on decadal time scales, its response is less predictable due to the difficulty of modeling surface climate, as well as incomplete understanding of the dynamic processes responsible for ice flow. Therefore, it is imperative to understand how modeling advancements, such as increased spatial resolution or more comprehensive ice flow equations, might improve projections of ice sheet response to climatic trends. Here we examine how a finely resolved climate forcing influences a high‐resolution ice stream model that considers longitudinal stresses. We simulate ice flow using a two‐dimensional Shelfy‐Stream Approximation implemented within the Ice Sheet System Model (ISSM) and use uncertainty quantification tools embedded within the model to calculate the sensitivity of ice flow within the Northeast Greenland Ice Stream to errors in surface mass balance (SMB) forcing. Our results suggest that the model tends to smooth ice velocities even when forced with extreme errors in SMB. Indeed, errors propagate linearly through the model, resulting in discharge uncertainty of 16% or 1.9 Gt/yr. We find that mass flux is most sensitive to local errors but is also affected by errors hundreds of kilometers away; thus, an accurate SMB map of the entire basin is critical for realistic simulation. Furthermore, sensitivity analyses indicate that SMB forcing needs to be provided at a resolution of at least 40 km.

Highlights

  • [2] The Greenland Ice Sheet is a major source of future sea level rise, as it is vulnerable to warming trends, marginal ablation, and consequential retreat [e.g., Ridley et al, 2005; Mikolajewicz et al, 2007; Vizcaino et al, 2010; Huybrechts et al, 2011]

  • The climatic sensitivity of this area is of great interest, as thinning has been observed at Zachariæ Isstrøm since 1999 [Rignot et al, 2001], and an annual aerial survey based on Moderate Resolution Imaging Spectroradiometer (MODIS) images ranks this glacier third only to Humboldt and Petermann glaciers in terms of area of ice lost per year during the 21st century [Box and Decker, 2011]

  • [29] Sampling analysis allows us to quantify the uncertainty propagated through a forward model in response to random errors in model inputs, in this case surface mass balance (SMB) forcing over a 22 year period

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Summary

Introduction

[2] The Greenland Ice Sheet is a major source of future sea level rise, as it is vulnerable to warming trends, marginal ablation, and consequential retreat [e.g., Ridley et al, 2005; Mikolajewicz et al, 2007; Vizcaino et al, 2010; Huybrechts et al, 2011]. Using the established ISSM framework, we assess temporally integrated errors in model output as ice thickness and velocity evolve over time These errors are affected by the feedback between the mass transport and mechanical models as the ice flow responds to forcing. To investigate these processes, we quantify how the location of errors impact mass flux through a specified flux gate by imposing a 0.1% change in SMB to a different partition per each individual run, resulting in one 22 year simulation per partition. We refer the reader to Larour et al [2012b] for a discussion about the propagation of errors through a static ice flow model, associated assumptions, as well as the calculations of mass flux output and response sensitivities using a forward model. Sensitivity values over the entire domain sum to unity, so they can be used to compare the relative contribution of model inputs

Methods
Uncertainty Quantification Methods
Results
Discussion
Conclusion
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