Improving model-satellite comparisons of sea ice melt onset with a satellite simulator

• Published in: The Cryosphere
• Main Authors: Smith, A., Jahn, A., Burgard, C., Notz, D.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2022
• Subjects: Arctic; Arctic Ocean; Sea ice; The Cryosphere
• Online Access: http://hdl.handle.net/21.11116/0000-000A-F6EF-4; http://hdl.handle.net/21.11116/0000-000A-F6F1-0; http://hdl.handle.net/21.11116/0000-000A-F6F2-F

Seasonal transitions in Arctic sea ice, such as the melt onset, have been found to be useful metrics for evaluating sea ice in climate models against observations. However, comparisons of melt onset dates between climate models and satellite observations are indirect. Satellite data products of melt onset rely on observed brightness temperatures, while climate models do not currently simulate brightness temperatures, and must therefore define melt onset with other modeled variables. Here we adapt a passive microwave sea ice satellite simulator, the Arctic Ocean Observation Operator (ARC3O), to produce simulated brightness temperatures that can be used to diagnose the timing of the earliest snowmelt in climate models, as we show here using Community Earth System Model version 2 (CESM2) ocean-ice hindcasts. By producing simulated brightness temperatures and earliest snowmelt estimation dates using CESM2 and ARC3O, we facilitate new and previously impossible comparisons between the model and satellite observations by removing the uncertainty that arises due to definition differences. Direct comparisons between the model and satellite data allow us to identify an early bias across large areas of the Arctic at the beginning of the CESM2 ocean-ice hindcast melt season, as well as improve our understanding of the physical processes underlying seasonal changes in brightness temperatures. In particular, the ARC3O allows us to show that satellite algorithm-based melt onset dates likely occur after significant snowmelt has already taken place. © 2022 Authors