Predicting Melt Pond Coverage on Arctic Sea Ice From Pre‐Melt Surface Topography DOI Creative Commons
Niels Fuchs, Gerit Birnbaum, Niklas Neckel

et al.

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(9)

Published: May 8, 2025

Abstract Sea‐ice melt ponds form in the depressions of pre‐melt surface topography, a process widely accepted yet lacking larger‐scale evaluation through explicit comparisons. During MOSAiC, we collected multi‐dimensional aerial data to examine relationship between topography and pond evolution across an entire Arctic ice floe. Using hydrological models, analyze correlation potential meltwater accumulation areas identified winter spring topographies, available meltwater, observed coverage. Our findings demonstrate strong connection, revealing 72% accuracy matching low ponds, with 98% basins deeper than 0.5 m transforming into ponds. Incorporating assumptions regarding availability improve predictions fraction highlight key factors driving extensive lateral runoff networks on No significant differences are first‐ second‐year ice. This study provides valuable ground truth for future modeling measurements formation.

Language: Английский

Predicting Melt Pond Coverage on Arctic Sea Ice From Pre‐Melt Surface Topography DOI Creative Commons
Niels Fuchs, Gerit Birnbaum, Niklas Neckel

et al.

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(9)

Published: May 8, 2025

Abstract Sea‐ice melt ponds form in the depressions of pre‐melt surface topography, a process widely accepted yet lacking larger‐scale evaluation through explicit comparisons. During MOSAiC, we collected multi‐dimensional aerial data to examine relationship between topography and pond evolution across an entire Arctic ice floe. Using hydrological models, analyze correlation potential meltwater accumulation areas identified winter spring topographies, available meltwater, observed coverage. Our findings demonstrate strong connection, revealing 72% accuracy matching low ponds, with 98% basins deeper than 0.5 m transforming into ponds. Incorporating assumptions regarding availability improve predictions fraction highlight key factors driving extensive lateral runoff networks on No significant differences are first‐ second‐year ice. This study provides valuable ground truth for future modeling measurements formation.

Language: Английский

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