3 research outputs found
Development of a Maximum Specific Photosynthetic Rate Algorithm Based on Remote Sensing Data: a Case Study for the Atlantic Ocean
New regional empirical algorithms were developed to obtain maximum specific photosynthetic
rates of phytoplankton ( ) in the surface layer of the Atlantic Ocean. These algorithms were based on the
dependence of on seawater temperature. Sea Surface Temperature remote sensing data and the PANGAEA
global database of photosynthesis–irradiance parameters were used to test the algorithm. In addition, the
variability in , both spatially (from 60° S to 85° N) and seasonally, (2002–2013) was estimated. The highest
was obtained in December in areas of deep convection and the interaction between the Labrador Current
and the Gulf Stream, while minimum values were observed in the northern and equatorial–tropical parts of
the ocean during the time intervals between the phytoplankton blooms (March to September–October). In
addition, existing and algorithms used in primary production models, as well as the algorithm devel�oped using temperature and chlorophyll a data from AMT-29, which were then tested using the PANGAEA
dataset. The results show that the new algorithm developed using seawater temperature data with region�ally adjusted empirical coefficients correlated best with the in situ data