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NSF Award from the Arctic Sciences Division

Model Studies of Surface Meltwater Lakes of the Greenland Ice Sheet

  • Principal Investigators: Douglas MacAyeal, PhD, Professor, Geophysical Sciences; and
    Jeremy Bassis, Assistant Professor, Geological Sciences
  • Start Date: September 1, 2009
  • Total Award Amount: $366,039

Project Description

Funds are provided to develop a better understanding of the processes and consequences of surface meltwater production on the Greenland ice sheet, particularly the development of surface lakes and their subsequent drainage to the subglacial bed, with the aid of numerical models designed to simulate the evolution of meltwater lakes on the Greenland Ice Sheet. The work effort will focus on: (a) establishing a self-consistent thermodynamic treatment that explicitly treats radiative forcing using a surface energy balance model, and (b) investigating new approaches to the dynamics of englacial water conduits that cause lake drainage to the subglacial bed.

The surface energy balance formulation will specify the downward radiation from sun, clouds and clear sky in all the important wavelength bands (e.g., shortwave and longwave), use bulk transfer formulations to parameterize sensibleand latent-heat fluxes, and explicitly model heat transfer processes below the surface. The new approaches to englacial water conduit dynamics proposed will involve stochastic processes involved in activation of pre-existing crack systems assumed to have spatial density and orientations described by probability density functions.

Two products will result from the model development and experimentation: (i) a series of numerical simulations designed to address basic questions concerning the formation of surface lakes on the Greenland Ice Sheet and their drainage to the ice-sheet bed and (ii) the development of a framework of diverse model approaches and their application to the sub-grid-scale parameterization of large-scale ice-sheet models, thereby coupling them to climate models.

This award is funded under the American Recovery and Reinvestment Act of 2009, NSF Award number: 0907834


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