Preprints
https://doi.org/10.5194/egusphere-2025-187
https://doi.org/10.5194/egusphere-2025-187
10 Feb 2025
 | 10 Feb 2025
Status: this preprint is open for discussion and under review for The Cryosphere (TC).

A low-cost, autonomous system for distributed snow depth measurements on sea ice

Ian A. Raphael, Donald K. Perovich, Christopher M. Polashenski, and Robert L. Hawley

Abstract. Snow is a critical component of the Arctic sea ice system. With its low thermal conductivity and high albedo, snow moderates energy transfer between the atmosphere and ocean during both winter and summer, thereby playing a significant role in determining the magnitude, timing, and variability of sea ice growth and melt. The depth of snow on Arctic sea ice is highly variable in space and time, and accurate measurements of snow depth and variability are central to improving our basic understanding, model representation, and remote sensing observations of the Arctic system. Our ability to collect those measurements has hitherto been limited by the high cost and large size of existing autonomous snow measurement systems. We designed a new system called SnoTATOS (the Snow Thickness and Temperature Observation System) to address this gap. SnoTATOS is a radio-networked, distributed snow depth observation system that is 95 % less expensive and 93 % lighter than existing systems. In this manuscript, we describe the technical specifications of the system and present results from a case study deployment of four SnoTATOS networks (each with ten observing nodes) in the Lincoln Sea between April 2024 and January 2025. The study demonstrates SnoTATOS’ utility in collecting distributed, in situ snow depth, accumulation, and surface melt data. While surface melt varied within each network by up to 38 %, mean surface melt between networks varied by only up to 9 %. Similarly, whereas initial snow depth varied by up to 42 % within each network, a comparison of mean initial snow depth between networks showed a maximum difference of only 26 %. This indicates that floe-scale measurements made using SnoTATOS provide more representative data for regional intercomparisons than existing single station systems. We conclude by recommending further research to determine the optimal number and arrangement of autonomous stations needed to capture the variability of snow depth on Arctic sea ice.

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Ian A. Raphael, Donald K. Perovich, Christopher M. Polashenski, and Robert L. Hawley

Status: open (until 31 Mar 2025)

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Ian A. Raphael, Donald K. Perovich, Christopher M. Polashenski, and Robert L. Hawley

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SnoTATOS snow depth and surface melt observations from the 2024 ARCSIX campaign Ian Raphael, Donald Perovich, and Christopher Polashenski https://doi.org/10.18739/A2RX93G1Q

Ian A. Raphael, Donald K. Perovich, Christopher M. Polashenski, and Robert L. Hawley

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Short summary
Snow plays competing roles in the sea ice cycle by reflecting sunlight during summer (reducing melt) and insulating the ice from the cold atmosphere during winter (reducing growth). Observing where, when, and how much snow accumulates on sea ice is thus central to understanding the Arctic. Here, we describe a new snow depth observation system that is substantially cheaper and lighter than existing tools, and present a study demonstrating its potential to improve snow measurements on sea ice.
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