Articles | Volume 19, issue 4
https://doi.org/10.5194/os-19-973-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-19-973-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Jul 2023
Research article |
| 06 Jul 2023
| 06 Jul 2023
Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
Gotzon Basterretxea
CORRESPONDING AUTHOR
Department of Marine Ecology, Instituto Mediterráneo de
Estudios Avanzados, IMEDEA (UIB-CSIC), Miquel Marqués 21, 07190
Esporles, Illes Balears, Spain
Joan S. Font-Muñoz
Department of Marine Ecology, Instituto Mediterráneo de
Estudios Avanzados, IMEDEA (UIB-CSIC), Miquel Marqués 21, 07190
Esporles, Illes Balears, Spain
Ismael Hernández-Carrasco
Department of Oceanography and Global Change, Instituto
Mediterráneo de Estudios Avanzados, IMEDEA (UIB-CSIC), Miquel
Marqués 21, 07190 Esporles, Illes Balears, Spain
Sergio A. Sañudo-Wilhelmy
Department of Biological Sciences and Department of Earth Sciences,
University of Southern California, Marine Biology and Biological
Oceanography, Los Angeles, California 90089-0371, United States
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Short summary
We examine global ocean color data and modeling outputs of nutrients using SOM analysis to identify characteristic spatial and temporal patterns of HNLC regions and their association with different climate modes. HNLC regions in polar and subpolar areas have experienced an increase in phytoplankton biomass over the last decades, particularly in the Southern Ocean. Our study finds that chlorophyll variations in HNLC regions respond to major climate variability signals.
We examine global ocean color data and modeling outputs of nutrients using SOM analysis to...
