Title of article :
Patterns of seasonal dynamics of remotely sensed chlorophyll and physical environment in the Newfoundland region
Author/Authors :
Afanasyev، نويسنده , , Yakov D and Nezlin، نويسنده , , Nikolay P and Kostianoy، نويسنده , , Andrey G، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2001
Abstract :
The patterns of seasonal variation of surface plant pigment concentration (Chl) in the Newfoundland region were studied using remotely sensed data from the coastal zone color scanner (CZCS) (1978–1986) and sea-viewing wide field-of-view sensor (SeaWiFS) radiometers (from September 1997 to October 1999). Sea surface temperature (SST) data obtained from AVHRR radiometers and sea surface height (SSH) data obtained from TOPEX/POSEIDON altimeter were then used to interpret the observed patterns in terms of physical factors which influence the growth of phytoplankton. Stable seasonal cycles of both SST and Chl were observed in all parts of the region under study (Labrador Current, Newfoundland Bank, Flemish Pass, frontal zone between Gulf Stream and Labrador Current). The SST values in the summer season during the 2 years under study (September 1997–October 1999) were up to 3°C higher as compared to climatologically averaged values. The seasonal pattern of Chl in the Labrador Current zone was typical of Arctic regions (one maximum in summer); in the Gulf Stream zone, it was typical of subtropical regions (smoothed maximum during winter); and in between these zones, the pattern was typical of mid-latitudes (two maxima, in spring and autumn). Over the Grand Newfoundland Bank, the seasonal pattern had one spring maximum, typical of shallow regions. The patterns of seasonal phytoplankton cycles resulted mainly from the meteorological factors influencing water stratification; the latter seems to be a crucial factor in either light or nutrient limitation of phytoplankton growth.
Keywords :
Phytoplankton seasonal cycle , Physical Environment
Journal title :
Remote Sensing of Environment
Journal title :
Remote Sensing of Environment