Identifying drivers and dynamics of phytoplankton in the Black Sea: application of a neural emulator

We present a spatiotemporal convolutional U-Net emulator model to forecast phytoplankton chlorophyll concentrations and key nutrient fields (nitrate and ammonium) in the Black Sea, using simulation data from 1950–2014. The emulator achieved substantially higher predictive skill compared to baseline...

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Auteurs principaux:	Philip A. H. Smith, Anshul Chauhan, Marilaure Grégoire, Luc Vandenbulcke, Filipe Rodrigues, Asbjørn Christensen, Michael A. St John, Patrizio Mariani
Format:	Artigo
Langue:	Inglês
Publié:	Frontiers Media S.A. 2026-03-01
Collection:	Frontiers in Marine Science
Sujets:	biogeochemical modeling Black Sea chlorophyll deep learning marine ecosystems model emulation
Accès en ligne:	https://www.frontiersin.org/articles/10.3389/fmars.2026.1760162/full
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