Preliminary modeling work simulating N-ICE snow distributions and the associated impacts on: 1)sea ice growth; 2)the formation of melt ponds; and 3)the.

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Presentation transcript:

Preliminary modeling work simulating N-ICE snow distributions and the associated impacts on: 1)sea ice growth; 2)the formation of melt ponds; and 3)the penetration of solar radiation through the snow, ponds, and ice. Glen Liston, Colorado State University

There are two kinds of snow accumulation and erosion features in this sea ice “landscape”: 1)snowdrifts behind pressure ridges, and 2)snow dunes on the relatively flat surfaces.

Snowdrifts behind pressure ridges

5 meters Snow dunes form during winter as part of blowing snow processes. Melt ponds form between the snow dunes. The snow dunes and melt ponds control the Arctic albedo evolution and surface energy budget. (Sturm and Liston 2003)(Polashenski)

Conceptual model of snow-drift evolution on lake ice. (Sturm and Liston 2003)

So all we need is a turbulent wind field. I get that from a large-eddy simulation model.

LANCE For Leg-1, I created ice topography and thickness distributions using one of Jari’s radar images.

LANCE Leg-1 SnowModel simulations of snowdrifts behind pressure ridges, and snow-dunes in the flat-ice areas. These model simulations were performed on a 3- m grid. Final simulations will use a 1-m grid to adequately resolve the snow-dune features.

Visual comparison of simulated (white, left panel) and observed (white, right panel) snow dunes. (These features are not displayed at the same scale)

A zoom-in showing ice- block topography, snow drifts behind the ice blocks, and snow dunes. The next slide shows the snow-depth profile for the line at the bottom of this figure. N-ICE observations are required to validate these distributions and profiles.

Snowdrift profile simulated by SnowModel, for the bottom black line in the slide below.

A key goal of this project is to use N-ICE observations to drive and verify a 3-D, time- evolving model of all of the relevant features, properties, processes, and fluxes. sea ice snow ocean

3-D Thermodynamic Ice Growth Model

(Liston et al. 2016, following Bitz and Lipscomb 1999)

Snow dune topography controls pond formation. Ponds form between the snow dunes. (Surface heights measured from repeat lidar scans. Polashenski et al. 2012)

Ultimate Goal of This Work: Develop a subgrid snow and sea-ice heat flux parameterization for use in Earth System models. Additional required model simulations include quantifying what is missed by assuming only 1-D heat transfers, compared to the full 3-D fluxes.

Additional Contributions For pan-Arctic applications, the following have been implemented within SnowModel: 1)Ice dynamics handled using the incremental remapping model of Lipscomb and Hunke (2004). 2)Daily ice motion vectors defined using NASA remote sensing products. 3)Daily ice concentration defined using NASA products.

Data needs for this modeling project include: 1) Snow dune length scales from MagnaProbes. 2) Sea ice thickness from EM31. 3) Ice surface topography. 4) Snowdrift profile from laser-level survey. 5) Meteorological forcing. 6) Snow property data from snow pits. 7) Salinity profiles in the sea ice. 8) Ice-ocean interface heat flux. 9) Time evolution of everything.