English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

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

MPS-Authors
/persons/resource/persons204594

Burgard,  Clara       
Max Planck Research Group The Sea Ice in the Earth System, The Ocean in the Earth System, MPI for Meteorology, Max Planck Society;

/persons/resource/persons37281

Notz,  Dirk       
Max Planck Research Group The Sea Ice in the Earth System, The Ocean in the Earth System, MPI for Meteorology, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

tc-16-3235-2022.pdf
(Publisher version), 7MB

Supplementary Material (public)

tc-16-3235-2022-supplement.pdf
(Supplementary material), 2MB

Citation

Smith, A., Jahn, A., Burgard, C., & Notz, D. (2022). Improving model-satellite comparisons of sea ice melt onset with a satellite simulator. The Cryosphere, 16, 3235-3248. doi:10.5194/tc-16-3235-2022.


Cite as: https://hdl.handle.net/21.11116/0000-000A-F6EF-4
Abstract
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