Idealized Models of Arctic Sea Ice Melt Ponds
As Arctic sea ice starts to melt in the summer, melt ponds form on its surface and, in a matter of days, cover large portions of the ice. Due to their low reflectivity, melt ponds greatly accelerate ice melt. Despite their importance, they are poorly understood due the many processes that control th...
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| Format: | Text |
| Language: | English |
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The University of Chicago
2020
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| Online Access: | https://doi.org/10.6082/uchicago.2180 http://knowledge.uchicago.edu/record/2180 |
| Summary: | As Arctic sea ice starts to melt in the summer, melt ponds form on its surface and, in a matter of days, cover large portions of the ice. Due to their low reflectivity, melt ponds greatly accelerate ice melt. Despite their importance, they are poorly understood due the many processes that control their evolution, which operate on widely separated length-scales. In this thesis, we use idealized models of melt ponds with a goal to provide a fundamental understanding of their evolution. First, we study the case of late-summer ponds that exist on highly permeable first-year sea ice. Assuming that ice is fully permeable, we show that pond coverage evolution can be approximately determined by solving two uncoupled ordinary differential equations (ODEs) in which the rate of change of pond coverage fraction is a function of itself, of the initial ice surface hypsographic curve, and of average melt rates of different regions of the ice. In this way, we show that it is possible to greatly reduce the complexity of pond evolution on permeable ice and to summarize all of the environmental conditions with only a few aggregate parameters. Second, we show that melt pond geometry on both first and multi-year ice can be accurately captured by a simple geometric model where ponds are represented as voids that surround randomly sized and placed circles that represent snow dunes. There are only two model parameters: the characteristic circle radius and the pond coverage fraction. We set these parameters by matching two correlation functions, which determine the typical pond size and their connectedness, between the model and aerial photographs of melt ponds. With parameters calibrated in this way, we reproduce the previously-observed pond size distribution and fractal dimension as a function of pond size over the entire observational range of more than 6 orders of magnitude. Surprisingly, by further studying the correlation functions, we find that late-summer ponds are organized close to the critical percolation threshold. Moreover, ... |
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