Effects of sea ice model characteristics on Arctic marine primary production

Abstract

The Arctic environment is rapidly changing and drastic declines in sea ice extent and thickness have been observed over the past decades. The thinning of the ice pack affects its dynamics and makes it more susceptible to form fractal features such as leads and ridges at scales of meters to kilometres, as well as larger openings known as polynyas of tens to tens of thousands of square kilometres. Observations show that their presence influences polar phytoplankton communities and productivity, pointing at the importance of representing such sea ice features in biogeochemical ocean modelling. The following study investigates how Arctic primary production and carbon export simulated with the biogeochemical model HYCOM-ECOSMO are affected by different sea ice models. Three simulations are available; one coupled to the Los Alamos sea ice model (CICE) with an elastic-viscous-plastic rheology. Two other simulations were run with the next generation sea ice model (neXtSIM) with a brittle rheology that better represents features such as leads and ridges. The neXtSIM(NOlight) simulation was run with the standard neXtSIM code and does not allow for light flux through the ice. In the neXtSIM(light) simulation, the light flux was parameterised to go through the young ice class with the objective to investigate the effect of refreezing leads on phytoplankton growth. Sea ice properties and key biogeochemical fields were analysed for the Chukchi Sea. We found that the choice of sea ice model rheology caused differences in the spring-bloom timing via sea ice concentration (SIC) and associated light availability. This further affected the timing of spring carbon export. The light flux through ice in CICE and neXtSIM(light) increased the light availability particularly during late spring and summer, and affected SIC in neXtSIM(light) compared to neXtSIM(NOlight). These findings suggest that the choice of sea ice model affects simulated primary production in HYCOM-ECOSMO, and that a better representation of mechanical damage in sea ice models is relevant for primary production and carbon export estimates in Arctic Ocean biogeochemical models.