Satellite views of Pacific chlorophyll variability: Comparisons to physical variability, local versus nonlocal influences and links to climate indices

Concurrent satellite-measured chlorophyll (CHL), sea surface temperature (SST), sea level anomaly (SLA) and model-derived wind vectors from the 13þ year SeaWiFS period September 1997–December 2010 quantify time and space patterns of phytoplankton variability and its links to physical forcing in the Pacific Ocean. The CHL fields are a metric of biological variability, SST represents vertical mixing and motion, often an indicator of nutrient availability in the upper ocean, SLA is a proxy for pycnocline depths and surface currents while vector winds represent surface forcing by the atmosphere and vertical motions driven by Ekman pumping. Dominant modes of variability are determined using empirical orthogonal functions (EOFs) applied to a nested set of domains for comparison: over the whole basin, over the equatorial corridor, over individual hemispheres at extra-tropical latitudes (4201) and over eastern boundary current (EBC) upwelling regions. Strong symmetry exists between hemispheres and the EBC regions, both in seasonal and non-seasonal variability. Seasonal variability is strongest at mid latitudes but non-seasonal variability, our primary focus, is strongest along the equatorial corridor. Non-seasonal basin-scale variability is highly correlated with equatorial signals and the strongest signal across all regions in the study period is associated with the 1997–1999 ENSO cycle. Results quantify the magnitude and geographic pattern with which dominant basin-scale signals are expressed in extra-tropical regions and the EBC upwelling areas, stronger in the Humboldt Current than in the California Current. In both EBC regions, wind forcing has weaker connections to non-seasonal CHL variability than SST and SLA, especially at mid and lower latitudes. Satellite-derived dominant physical and biological patterns over the basin and each sub-region are compared to indices that track aspects of climate variability in the Pacific (the MEI, PDO and NPGO). We map and compare the local CHL footprint associated with each index and those of local wind stress curl, showing the dominance in most areas of the MEI and its similarity to the PDO. Principal estimator patterns quantify the linkage between dominant modes of forcing variability (wind, SLA and SST) and CHL response, comparing local interactions within EBC regions with those imposed by equatorial signals and mapping equatorial forcing on extra-tropical CHL variability. & 2012 Elsevier Ltd. All rights reserved.