Sea ice as a source of sea salt aerosol to Greenland ice cores: a model-based study

• Published in: Atmospheric Chemistry and Physics
• Main Authors: Rhodes, Rachael H., Yang, Xin, Wolff, Eric W., McConnell, Joseph R., Frey, Markus M.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus publications 2017
• Subjects: 01 - Climate Change and Earth-Ocean Atmosphere Systems; Arctic; Greenland; Climate change; Greenland ice core; Greenland ice cores; ice core; Sea ice
• Online Access: http://eprints.esc.cam.ac.uk/4042/; http://eprints.esc.cam.ac.uk/4042/1/acp-17-9417-2017.pdf; http://eprints.esc.cam.ac.uk/4042/7/acp-17-9417-2017-supplement.zip; https://doi.org/10.5194/acp-17-9417-2017

Growing evidence suggests that the sea ice surface is an important source of sea salt aerosol and this has significant implications for polar climate and atmospheric chemistry. It also suggests the potential to use ice core sea salt records as proxies for past sea ice extent. To explore this possibility in the Arctic region, we use a chemical transport model to track the emission, transport, and deposition of sea salt from both the open ocean and the sea ice, allowing us to assess the relative importance of each. Our results confirm the importance of sea ice sea salt (SISS) to the winter Arctic aerosol burden. For the first time, we explicitly simulate the sea salt concentrations of Greenland snow, achieving values within a factor of two of Greenland ice core records. Our simulations suggest that SISS contributes to the winter maxima in sea salt characteristic of ice cores across Greenland. However, a north–south gradient in the contribution of SISS relative to open-ocean sea salt (OOSS) exists across Greenland, with 50 % of winter sea salt being SISS at northern sites such as NEEM (77° N), while only 10 % of winter sea salt is SISS at southern locations such as ACT10C (66° N). Our model shows some skill at reproducing the inter-annual variability in sea salt concentrations for 1991–1999, particularly at Summit where up to 62 % of the variability is explained. Future work will involve constraining what is driving this inter-annual variability and operating the model under different palaeoclimatic conditions.