Abstract
El Niño—Southern Oscillation (ENSO) is regarded as the main driver of phytoplankton inter-annual variability. Remotely sensed surface chlorophyll-a (Chl-a), has made it possible to examine phytoplankton variability at a resolution and scale that allows for the investigation of climate signals such as ENSO. We provide empirical evidence of an immediate and lagged influence of ENSO on SeaWiFS and MODIS-Aqua derived global Chl-a concentrations. We use 13 years of Chl-a remotely sensed observations along with sea surface temperature (SST) observations across the Tropical and South Pacific to isolate and examine the spatial development of Chl-a anomalies during ENSO: its canonical or eastern Pacific (EP) mode, and El Niño Modoki or central Pacific (CP) mode, using the extended empirical orthogonal function (EEOF) technique. We describe how an EP ENSO phase transition affects Chl-a, and identify an interannual CP mode of variability induced spatial pattern. We argue that when ENSO is analysed as a propagating signal by the EEOF, CP ENSO is found to be more influential on Chl-a interannual to decadal variability than the canonical EP ENSO. Our results cannot confirm the independence of the two ENSO modes but clearly demonstrate that both ENSO flavors manifest a distinct biological response.
Highlights
IntroductionOur understanding of changes in global phytoplankton was relatively poor
Prior to satellite observations, our understanding of changes in global phytoplankton was relatively poor
This specific lag was chosen to target Chl-a variability related to eastern Pacific (EP) El Niño—Southern Oscillation (ENSO), the leading mode significantly relates to central Pacific (CP) ENSO variability, and EEOF2 to EP ENSO
Summary
Our understanding of changes in global phytoplankton was relatively poor. Since the advent of satellite remote sensing of surface chlorophyll-a (Chl-a) concentrations in the late 1970s, it has been possible to estimate surface phytoplankton biomass at near global scales. Remote sensing tools have proven to overcome the greatest limitations that classical observational methods suffer by providing global coverage and a continuous temporal sampling rate. Sensors such as the recently terminated SeaWiFS and the on-going MODIS-Aqua are passive ocean color instruments that measure surface water radiance that can be converted into near-surface Chl-a concentrations. The one to two day revisit cycle of the ocean color sensors on board these polar orbiting satellite platforms is ideal for large-scale quantitative studies of the spatial and temporal ocean productivity rates, and its relationship with climate modes of variability
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