Phytoplankton functional types observation from space in the Fram Strait (2002-2020)
Phytoplankton in the sunlit layer of the ocean act as the base of the marine food web fueling fisheries, and also regulate key biogeochemical processes. Phytoplankton composition structure varies in ocean biomes and different phytoplankton groups drive differently the marine ecosystem and biogeochem...
| Main Authors: | , , , , , , |
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| Format: | Conference Object |
| Language: | unknown |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://epic.awi.de/id/eprint/55868/ https://epic.awi.de/id/eprint/55868/1/Xi_et_al_OceanCarbonSpace2022_long_term_satellite_PFT_hxi_poster_clean.pdf https://hdl.handle.net/10013/epic.29ceca54-2573-4f33-bebe-b0eb25abd89c |
| Summary: | Phytoplankton in the sunlit layer of the ocean act as the base of the marine food web fueling fisheries, and also regulate key biogeochemical processes. Phytoplankton composition structure varies in ocean biomes and different phytoplankton groups drive differently the marine ecosystem and biogeochemical processes. Because of this, variations in phytoplankton composition influence the entire ocean environment, specifically the ocean energy transfer and the export of organic carbon to the deep ocean. As one of the algorithms deriving phytoplankton composition from space borne data, within the framework of the EU Copernicus Marine Service (CMEMS), EOF-PFT algorithm was developed using multi-spectral satellite data collocated to an extensive in-situ PFT data set based on HPLC pigments and sea surface temperature data (Xi et al. 2020, 2021; https://marine.copernicus.eu/). By using multi-sensor merged products and Sentinel-3 OLCI data, the algorithm provides global chlorophyll a data with per-pixel uncertainty for diatoms, haptophytes, dinoflagellates, chlorophytes and prokaryotic phytoplankton spanning the period from 2002 until today. Due to different lifespans and radiometric characteristics of the ocean color sensors, the consistency of the PFTs is evaluated to provide quality-assured data for a consistent long-term monitoring of the phytoplankton community structure. As current commonly used phytoplankton carbon estimation methods rely mostly on the backscattering property of phytoplankton, which could vary dramatically for different phytoplankton taxa, as a perspective of this study, phytoplankton carbon may be better estimated in a way that accounts for phytoplankton taxonomy. |
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