Satellite-derived measurements of spatial and temporal chlorophyll-a variability in Funka Bay, southwestern Hokkaido, Japan

Chlorophyll-a (chl-a) concentration has an important economic effect in coastal and marine environments on fisheries resources and marine aquaculture development. Monthly climatologies the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) derived chl-a from February 1998 to August 2004 around Funka Bay were used to investigate the spatial and temporal variability of chl-a concentrations. SeaWiFS-derived suspended sediment, MODIS derived sea surface temperature (SST), solar radiation and wind data were also analyzed. Results showed two distinct chlorophyll blooms in spring and autumn. Chl-a concentrations were relatively low (<0.3 mg m⁻³) in the bay during summer, with high concentrations occurring along the coast, particularly near Yakumo and Shiraoi. In spring, chl-a concentrations increased, and a large (>2 mg m⁻³) phytoplankton bloom occurred. The spatial and temporal patterns were further confirmed by empirical orthogonal function (EOF) analysis. About 83.94% of the variability could be explained by the first three modes. The first chl-a mode (77.93% of the total variance) explained the general seasonal cycle and quantified interannual variability in the bay. The spring condition was explained by the second mode (3.89% of the total variance), while the third mode (2.12% of the total variance) was associated with autumn condition. Local forcing such as the timing of intrusion of Oyashio water, wind condition and surface heating are the mechanisms that controlled the spatial and temporal variations of chlorophyll concentrations. Moreover, the variation of chlorophyll concentration along the coast seemed to be influenced by suspended sediment caused by resuspension or river discharge.     

Development of a Neural Network Algorithm for Retrieving Concentrations of Chlorophyll, Suspended Matter and Yellow Substance from Radiance Data of the Ocean Color and Temperature Scanner

An algorithm is presented to retrieve the concentrations of chlorophyll a, suspended pariclulate matter and yellow substance from normalized water-leaving radiances of the Ocean Color and Temperature Sensor (OCTS) of the Advanced Earth Observing Satellite (ADEOS). It is based on a neural network (NN) algorithm, which is used for the rapid inversion of a radiative transfer procedure with the goal of retrieving not only the concentrations of chlorophyll a but also the two other components that determine the water-leaving radiance spectrum. The NN algorithm was tested using the NASA's SeaBAM (SeaWiFS Bio-Optical Mini-Workshop) test data set and applied to ADEOS/OCTS data of the Northwest Pacific in the region off Sanriku, Japan. The root-mean-square error between chlorophyll a concentrations derived from the SeaBAM reflectance data and the chlorophyll a measurements is 0.62. The retrieved chlorophyll a concentrations of the OCTS data were compared with the corresponding distribution obtained by the standard OCTS algorithm. The concentrations and distribution patterns from both algorithms match for open ocean areas. Since there are no standard OCTS products available for yellow substance and suspended matter and no in situ measurements available for validation, the result of the retrieval by the NN for these two variables could only be assessed by a general knowledge of their concentrations and distribution patterns. This revised version was published online in July 2006 with corrections to the Cover Date.     

Distribution and seasonal variation of concentrations of particulate carbohydrates and uronic acids in the northern Indian Ocean

Suspended particulate matter (SPM) samples were collected from the surface seawaters at 31 stations, and from various depths (2 to 1000 m) at 9 locations in the northern Indian Ocean during various seasons. SPM samples were analyzed for total particulate carbohydrate (TPCHO), total particulate uronic acid (TPURA) and total particulate neutral carbohydrate (TPNCHO) concentrations and composition. Strong spatial, temporal and depth related variations were evident in the distribution of these compounds. In surface waters, concentrations of TPCHO, TPNCHO, and TPURA varied from 0.57 to 3.58 μM C, 0.11 to 2.34 μM C, and from 0.01 to 0.31 μM C, respectively, and accounted for 2.6 to 34.6%, 2 to 24.5%, and 0.2 to 6.3% of POC, respectively, whereas the TPURA accounted for 4.7 to 22.7% of TPCHO. Concentrations and yields of both TPNCHO and TPURA decreased rapidly in the upper 100 m of the water column suggesting their utilization by heterotrophic organisms. Glucose was the most abundant constituent of the TPNCHO. Glucose mole fraction decreased while that of other monosaccharides, especially galactose, arabinose, mannose, rhamnose and fucose increased in the upper 100 m water. Below this depth, mole fraction of glucose increased while that of other sugars decreased with the increasing water depth. Generally, high C:N ratios were associated with low yields of carbohydrates and uronic acids. Inverse correlation between the mole fractions of arabinose plus xylose and rhamnose plus fucose indicates the importance of biogenic and terrestrial organic matter input to the Bay of Bengal. TPURA are surface-active in nature and thus may play an important role in coagulation of particles and macromolecules. The observed spatial and seasonal variations of these compounds may be due to differences in phytoplankton biomass, nutrient status, and the influence of terrestrial material.