The 4-year, calibrated SeaWiFS data set provides a means to determine seasonal and other sources of phytoplankton variability on global scales, which is an important component of the total variability associated with ocean biological and biogeochemical processes. We used empirical orthogonal function (EOF) analysis on a 4-year time series of global SeaWiFS chlorophyll a measurements to quantify the major seasonal (as well as the late El Niño and La Niña phase of the 1997-1998 ENSO) signals in phytoplankton biomass between 50°S and 50°N, and then a second analysis to quantify summer patterns at higher latitudes. Our results help place regional satellite chlorophyll variability within a global perspective. Among the effects we resolved are a 6-month phase shift in maximum chlorophyll a concentrations between subtropical (winter peaks) and subpolar (spring-summer peaks) waters, greater seasonal range at high latitudes in the Atlantic compared to the Pacific, an interesting phasing between spring and fall biomass peaks at high latitudes in both hemispheres, and the effects of the 1998 portion of the 1997-1998 ENSO cycle in the tropics. Our EOF results show that dominant seasonal and ENSO effects are captured in the first six of a possible 184 modes, which explain 67% of the total temporal variability associated with the global mean phytoplankton chlorophyll pattern in our smoothed data set. The results also show that the time (seasonal)/space (zonal) patterns between the ocean basins and between the hemispheres are similar, albeit with some key differences. Finally, the dominant global patterns are consistent with the results of ocean models of seasonal dynamics based on seasonal changes to the heating and cooling (stratification/destratification) cycles of the upper ocean. Copyright 2003 by the American Geophysical Union.
CITATION STYLE
Yoder, J. A., & Kennelly, M. A. (2003). Seasonal and ENSO variability in global ocean phytoplankton chlorophyll derived from 4 years of SeaWiFS measurements. Global Biogeochemical Cycles, 17(4). https://doi.org/10.1029/2002gb001942
Mendeley helps you to discover research relevant for your work.