POSTER Session 4

RE-EVALUATING METHODOLOGIES FOR ESTIMATING MARINE PRIMARY PRODUCTIVITY IN THE LABRADOR SEA USING SATELLITE AND IN SITU OBSERVATIONS

Marine primary productivity (PP), a crucial component to assess the biological carbon pump (BCP), may be monitored using satellite ocean color remote sensing. However, satellite detection is limited to the first optical depth of the water column (few 10s meters), thus failing to accurately capture productivity beyond this depth. In high-latitude areas, satellite coverage is further hindered by cloud cover and low irradiance during winter. In addition, the variety of PP models poses a challenge to compile a comprehensive estimate of global primary productivity due to significant disparities among estimates. For instance, Bisson et al. (2018) highlighted the significant impact of PP model selection and data sources on the estimation of BCP export. This study aims at assessing two satellite-based methodologies of estimating Net primary production (NPP) by comparison with an in-situ NPP time series, which is derived from in-situ daily bio-optical observations from a moored profiler in the subpolar Northwest Atlantic (56.8°N, 52.2°W) between May and November 2016. The primary objectives are: (1) to evaluate the importance of regional tuning for satellite-derived chlorophyll-a concentration in high-latitude regions on NPP estimates, (2) to assess three chlorophyll-based productivity models using different data sources, model configurations, and extrapolation techniques for subsurface structure from satellite data, and (3) to compare satellite-derived NPP time series against in-situ measurements. Through this reassessment, we aim to enhance the accuracy of NPP estimates in high-latitude regions and contribute to a better understanding of oceanic carbon dynamics.

*Ka Ki Kam, Dalhousie University, Canada, [email protected], https://orcid.org/0000-0002-0572-9488

Emmanuel Devred, Fisheries and Oceans Canada, Bedford Institute of Oceanography, Canada, [email protected], https://orcid.org/0000-0001-9446-0005

Stephanie Clay, Fisheries and Oceans Canada, Bedford Institute of Oceanography, Canada, [email protected], https://orcid.org/0000-0001-5113-2378

Mohammad Amirian, Department of Mathematics and Statistics, Dalhousie University, Canada, [email protected], https://orcid.org/0000-0002-8402-5779

Dariia Atamanchuk, Department of Oceanography, Dalhousie University, Canada, [email protected]

Douglas Wallace, Department of Oceanography, Dalhousie University, Canada, [email protected]

Andrew Irwin, Department of Mathematics and Statistics, Dalhousie University, Canada, [email protected], https://orcid.org/0000-0001-7784-2319

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