Articles | Volume 12, issue 11
https://doi.org/10.5194/bg-12-3641-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-12-3641-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
11 Jun 2015
Research article |
| 11 Jun 2015
Synoptic-scale analysis of mechanisms driving surface chlorophyll dynamics in the North Atlantic
A. S. A. Ferreira
CORRESPONDING AUTHOR
Centre for Ocean Life, National Institute of Aquatic Resources, Technical University of Denmark, Copenhagen, Denmark
H. Hátún
Environmental Department, Faroe Marine Research Institute, Nóatún 1, P.O. Box 3051, FO 110 Tórshavn, Faroe Islands
F. Counillon
Nansen Environmental and Remote Sensing Center, Thormóhlensgate 47, Bergen, Norway
M. R. Payne
Centre for Ocean Life, National Institute of Aquatic Resources, Technical University of Denmark, Copenhagen, Denmark
A. W. Visser
Centre for Ocean Life, National Institute of Aquatic Resources, Technical University of Denmark, Copenhagen, Denmark
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Cited
17 citations as recorded by crossref.
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- Abiotic control of phytoplankton blooms in temperate coastal marine ecosystems: A case study in the South Atlantic Ocean P. Bermejo et al. 10.1016/j.scitotenv.2017.08.176
- Twenty-One Years of Phytoplankton Bloom Phenology in the Barents, Norwegian, and North Seas E. Silva et al. 10.3389/fmars.2021.746327
- A regional correction model for satellite surface chlorophyll concentrations, based on measurements from sea water samples collected around Iceland K. Guðmundsson et al. 10.1016/j.mio.2016.05.004
- Episodic Summer Chlorophyll‐a Blooms Driven by Along‐Front Winds at Aotearoa's Southeast Shelf Break Front E. Johnson et al. 10.1029/2022JC019609
- Patterns and drivers of phytoplankton phenology off SW Iberia: A phenoregion based perspective L. Krug et al. 10.1016/j.pocean.2018.06.010
- Probabilistic models for harmful algae: application to the Norwegian coast E. Silva et al. 10.1017/eds.2024.11
- Detection of climate change‐driven trends in phytoplankton phenology S. Henson et al. 10.1111/gcb.13886
- Climate change impacts on mismatches between phytoplankton blooms and fish spawning phenology R. Asch et al. 10.1111/gcb.14650
- Phenology and time series trends of the dominant seasonal phytoplankton bloom across global scales K. Friedland et al. 10.1111/geb.12717
- The Faroe shelf spring bloom onset explained by a ‘Critical Volume Hypothesis’ S. Eliasen et al. 10.1016/j.jmarsys.2019.02.005
- Winter‐mixing preconditioning of the spring phytoplankton bloom in the Bay of Biscay R. González‐Gil et al. 10.1002/lno.10769
- Impact of assimilating a merged sea-ice thickness from CryoSat-2 and SMOS in the Arctic reanalysis J. Xie et al. 10.5194/tc-12-3671-2018
- Seasonal strategies in the world’s oceans A. Visser et al. 10.1016/j.pocean.2020.102466
- Are surface temperature and chlorophyll in a large deep lake related? An analysis based on satellite observations in synergy with hydrodynamic modelling and in-situ data D. Bouffard et al. 10.1016/j.rse.2018.02.056
- Spring blooms and annual cycles of phytoplankton: a unified perspective S. Chiswell et al. 10.1093/plankt/fbv021
- Environmental and climactic effects of chlorophyll-a variability around Iceland using reconstructed satellite data fields N. McGinty et al. 10.1016/j.jmarsys.2016.06.005
15 citations as recorded by crossref.
- Revealing environmental synchronicity that enhances anchovy recruitment in the Mediterranean Sea F. Quattrocchi & G. Garofalo 10.1038/s41598-022-09418-z
- Abiotic control of phytoplankton blooms in temperate coastal marine ecosystems: A case study in the South Atlantic Ocean P. Bermejo et al. 10.1016/j.scitotenv.2017.08.176
- Twenty-One Years of Phytoplankton Bloom Phenology in the Barents, Norwegian, and North Seas E. Silva et al. 10.3389/fmars.2021.746327
- A regional correction model for satellite surface chlorophyll concentrations, based on measurements from sea water samples collected around Iceland K. Guðmundsson et al. 10.1016/j.mio.2016.05.004
- Episodic Summer Chlorophyll‐a Blooms Driven by Along‐Front Winds at Aotearoa's Southeast Shelf Break Front E. Johnson et al. 10.1029/2022JC019609
- Patterns and drivers of phytoplankton phenology off SW Iberia: A phenoregion based perspective L. Krug et al. 10.1016/j.pocean.2018.06.010
- Probabilistic models for harmful algae: application to the Norwegian coast E. Silva et al. 10.1017/eds.2024.11
- Detection of climate change‐driven trends in phytoplankton phenology S. Henson et al. 10.1111/gcb.13886
- Climate change impacts on mismatches between phytoplankton blooms and fish spawning phenology R. Asch et al. 10.1111/gcb.14650
- Phenology and time series trends of the dominant seasonal phytoplankton bloom across global scales K. Friedland et al. 10.1111/geb.12717
- The Faroe shelf spring bloom onset explained by a ‘Critical Volume Hypothesis’ S. Eliasen et al. 10.1016/j.jmarsys.2019.02.005
- Winter‐mixing preconditioning of the spring phytoplankton bloom in the Bay of Biscay R. González‐Gil et al. 10.1002/lno.10769
- Impact of assimilating a merged sea-ice thickness from CryoSat-2 and SMOS in the Arctic reanalysis J. Xie et al. 10.5194/tc-12-3671-2018
- Seasonal strategies in the world’s oceans A. Visser et al. 10.1016/j.pocean.2020.102466
- Are surface temperature and chlorophyll in a large deep lake related? An analysis based on satellite observations in synergy with hydrodynamic modelling and in-situ data D. Bouffard et al. 10.1016/j.rse.2018.02.056
2 citations as recorded by crossref.
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Latest update: 04 Nov 2024
Short summary
Our main objective was to assess which bottom-up processes can best predict changes in phytoplankton surface spring blooms in the North Atlantic. We applied new phenology algorithms to satellite-derived data and compared four different metrics based on physical drivers of phytoplankton. We show that there is a dominant physical mechanism - mixed layer shoaling - and that different regions are governed by different physical phenomena.
Our main objective was to assess which bottom-up processes can best predict changes in...
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