Snow on sea ice in the Arctic Archipelago

• Main Author: Dawson, John
• Other Authors: Mäkynen, Marko, Skourup, Henriette, Insinööritieteiden korkeakoulu, Rautiainen, Miina, Aalto-yliopisto, Aalto University
• Format: Master Thesis
• Language: English
• Published: 2022
• Subjects: Canadian Arctic Archipelago; snow on sea ice; snow depth climatology; landfast ice; Arctic; Arctic Ocean; Canada; Arctic Archipelago; Sea ice
• Online Access: https://aaltodoc.aalto.fi/handle/123456789/116372

Snow depth on sea ice is an important control of sea ice growth and uncertainties in snow depth are one of the largest sources of uncertainties in estimating sea ice thickness with satellite based remote sensing methods. Currently the standard snow depth estimation product is a modified Warren 1999 snow depth climatology. The warren 1999 climatology was constructed from Soviet in situ snow depth measurements in the Arctic with no measurements procured in the Canadian Arctic Archipelago; resulting in a need for improved estimates of snow depth in the Canadian Arctic Archipelago. The Canadian Arctic Archipelago is an area of great importance being projected to be part of the last area to have year ­round ice and is underrepresented in pan­Arctic data products. A number of snow depth climatologies were created for this thesis from in situ snow depth measurements taken on landfast sea ice along the coasts of Canada for the months of October through April. These Climatologies showed promising results for the Canadian Arctic Archipelago and the northeastern coast of mainland Canada, but does not show as promising results beyond the edges of the Canadian Arctic Archipelago into the Arctic Ocean, When compared to the modified Warren 1999 snow depth climatology and the SnowModel­ LG, the interpolation methods created in this thesis produced lower snow depth estimates in the autumn and early winter and greater snow depth later in the winter and in the spring for the Canadian Arctic Archipelago. The snow depth accumulation rates were found by these interpolation methods to be more evenly distributed through the months studied than what was found by the w99m climatology and the SnowMode-LG