Snowmelt onset in the Arctic: Insights from a thermodynamic sea ice model, ice mass balance buoys, and passive microwave remote sensing

Abstract The timing of snowmelt onset (SMO) is a critical climate indicator in the Arctic. However, spaceborne, in-situ measurements, and model simulations yield different estimates for the timing. Understanding these discrepancies is essential for identifying the physical mechanisms driving SMO. In this study, SMO, snow, and sea ice thermodynamics were simulated using a single-column snow/ice model (HIGHTSI) along trajectories of 42 ice mass balance buoys operating in the period of 2010 to 2015. The results were compared with passive microwave remote sensing and ice mass balance observations. The modeled surface-SMO has a high inter-annual correlation (0.94) with the ice mass balance-derived results but occurred on average 5 days earlier than observations. The remote-sensing-derived Early-SMO was 12 days before the ice mass balance-derived surface-SMO, while the Continuous-SMO showed a 5 day lag. The modeled average snow depth, ice thickness, and snow/ice temperature captured the recorded seasonal variations. The modeled snow/ice temperature showed seasonal biases of 0.4°C/0.5°C between May–September, and −2.7°C/−4.6°C between October–April, respectively. The corresponding biases for average snow depth and ice thickness were −0.05 m/−0.15 m and 0.03 m/0.14 m, respectively. Accurate representation of air temperature forcing and solar radiation absorption is crucial for realistic simulation of SMO.