EGU23-854, updated on 22 Feb 2023
https://doi.org/10.5194/egusphere-egu23-854
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Variability and predictability of surface chlorophyll in the Atlantic upwelling systems 

Elena Calvo Miguélez1,2, Belén Rodríguez-Fonseca1,2, and Iñigo Gómara3
Elena Calvo Miguélez et al.
  • 1Complutense University of Madrid, Faculty of physical sciences, Geophysics and Meteorology department, Madrid, Spain (elenca03@ucm.es)
  • 2Instituto de Geociencias (IGEO), UCM-CSIC, Madrid, Spain
  • 3University of Valladolid, Applied Mathematics department, Segovia, Spain

Chlorophyll-a surface concentration is partially determined by environmental conditions and its variability, as the highest concentrations are generally found in wind-driven oceanic upwelling regions. These wind regimes that affect upwelling strength can be determined by local and remote drivers, such as sea surface temperature (SST) anomaly patterns (e.g., Pacific and Atlantic Niños/Niñas) that trigger tropical basin interactions.

By performing a Maximum Covariance Analysis (MCA) between chlorophyll-a concentration from Copernicus Satellite data and SST anomalies from OISST (January 1998-December 2019), we here identify the individual SST patterns and the associated atmospheric responses that lead to an increase in chlorophyll concentration in two regions of the tropical Atlantic: the Senegalese coast and the equator during their seasonal maxima (February to May and June to September, respectively). The present study shows how an Atlantic El Niño is capable of promoting a Pacific La Niña, whose atmospheric response affects either the tropical north Atlantic and the equatorial Atlantic, producing an SST cooling in early spring in the former and in summer in the latter, both related to an increase of chlorophyll concentration.

A cross-validated hindcast based on Maximum Covariance Analysis (MCA) is used to assess chlorophyll predictability through these individual SST variability modes.

Key words: chlorophyll-a concentration, SSTs, atmospheric responses, statistical prediction.

How to cite: Calvo Miguélez, E., Rodríguez-Fonseca, B., and Gómara, I.: Variability and predictability of surface chlorophyll in the Atlantic upwelling systems , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-854, https://doi.org/10.5194/egusphere-egu23-854, 2023.