While the use of satellite data has revolutionised our ability to study the Arctic, there are significant limitations in the ability to estimate changes in biological processes, biodiversity and ecosytem functions.The development of algorithms for remote sensing of water quality, including productivity and phytoplankton community composition, requires a large amount of in situ data, such as pigment data, to calibrate and validate. However, there is a shortage of in situ data published, and those existing for the Arcitc that can match up in situ pigment data with satellite measurements are very limited due to high cloud cover in this region. This study explores the value of a large, previously unpublished, dataset of historical phytoplankton pigment data from the Arctic region collected over the 2000-2022 period and analyzed by High-Performance Liquid Chromatography (HPLC). A total of 900 sets of pigment data were used in the analyses which compares the spatio-temporal variability in the distribution of  phytoplankton functional types in the Arctic between 2000-2005 and 2014-2022. By acquiring an unprecedented number of match-ups with satellite ocean colour measurements, we provide preliminary results from relating the observed patterns in pigment data with patterns detected from large scale satellite-based estimates of phytoplankton biomass and sea surface temperature among other environmental variables. The newly available dataset with satellite match-ups exhibits potential for significantly improving existing capacity to model changing distributions of phytoplankton functional types from space.

Primary Presenter: Katarzyna Dragańska-Deja, Institute of Oceanology Polish Academy of Science (katarzynadraganska@gmail.com)

Authors:

Katarzyna Dragańska-Deja, Institute of Oceanology Polish Academy of Sciences  (katarzyna@iopan.pl)

Joanna Stoń-Egiert, Institute of Oceanology Polish Academy of Sciences  (aston@iopan.pl)

Artur Palacz, Institute of Oceanology Polish Academy Scieces  (a.palacz@ioccp.org)