Linking observations of Arctic summer sea ice thickness and melt ponds to model simulations

Melt ponds on Arctic sea ice play a critical role in the ice-albedo feedback, influencing the Arctic energy budget and climate. While satellite-derived products provide broad-scale estimates of melt pond fraction, detailed information on individual pond properties and direct high-resolution comparisons with other sea ice properties remain limited. In this study, we combine airborne observations of melt ponds and sea ice thickness with model output to evaluate the representation of melt ponds in Arctic sea ice simulations.

Melt pond properties, in particular pond fraction, along flight tracks are derived using high-resolution RGB imagery, while coincident ice thickness measurements are obtained using the EM-Bird, a tethered electromagnetic sensor. These observations are analyzed to explore the relationship between melt pond fraction, ice thickness, and surface morphology, providing a comprehensive observational perspective. This relationship is then compared to simulations from the Los Alamos Sea Ice Model (CICE) and its column physics module, Icepack, which include melt pond parameterizations based on sea ice thickness categories and the distribution of level and deformed ice within these categories. By examining how observed relationships between melt pond fraction and ice thickness agree with model results, this study aims to evaluate models in realistically simulating melt pond properties and processes on Arctic sea ice.