C11A-0335:
Distribution of Phytoplankton and Particulate Organic Carbon in the Beaufort Sea during the 2014 Marginal Ice Zone Experiment

Monday, 15 December 2014
Mary Jane Perry1, Craig Lee2, Eun Jin Yang3, Ivona Cetinic1 and Sung-Ho Kang3, (1)University of Maine, Orono, ME, United States, (2)Univ Washington, Seattle, WA, United States, (3)KOPRI Korea Polar Research Institute, Incheon, South Korea
Abstract:
Spatial and temporal distributions of phytoplankton and particulate organic carbon in the newly emerging marginal ice zone in the Beaufort Sea are assessed from autonomous Seaglider surveys in summer 2014 as part of the Marginal Ice Zone (MIZ) Experiment, an international project sponsored by ONR. In late July 2014 four Seagliders were deployed in the Beaufort Sea to follow the retreat of the MIZ. Sampling in open water, through the MIZ and under the ice is expected through mid-September, with gliders navigating under ice from moored acoustic sound sources embedded in the MIZ autonomous observing array. The sensor suite carried by Seagliders include temperature, temperature microstructure, salinity, oxygen, chlorophyll fluorescence, optical backscatter, and multi-spectral downwelling irradiance. A rigorous sensor inter-calibration program with simultaneous ship CTD and glider profiles is an essential component of glider deployment and recovery protocol, as well as during opportunistic glider encounters with the IBRV Araon during August. Ship-based water sampling will allow construction of regional libraries of optical proxies for chlorophyll, pigment spectral absorption coefficient, and particulate organic carbon. Since irradiance under the ice is dependent on ice thickness and presence of melt ponds and leads, phytoplankton distribution is expected to vary spatially. Both the vertical and horizontal distributions of pigment spectral absorption coefficients are expected to play a role in the feedback between phytoplankton and ice melt. Glider data will allow us to apply a light and chlorophyll primary productivity model to estimate and compare phytoplankton productivity under various ice-cover and ice-free conditions.