10:45 AM - 12:15 PM
[HTT17-P03] Estimation of Phytoplankton Size Class in Ise-Mikawa Bay by Ocean Color Satellite
Keywords:PSC, SGLI, Ise-Mikawa Bay, QAA
Phytoplankton plays an important role on planetary primary production, climate processes, biogeochemical cycles, and marine food chain. Phytoplankton consist of many taxonomic groups, and they are often split into three size classes (i.e., micro- [> 20 μm], nano- [2–20 μm], and pico-phytoplankton [< 2 μm]). The distribution and variation of phytoplankton size class (PSC) significantly affects ocean biogeochemical processes and ecosystems. Ise-Mikawa Bay is a representative semi-enclosed sea and the largest bay located in central area of Japan which has suffered severe eutrophication since 1980s as the urbanization and industrialization. However, distribution and variation of the PSC during and after this period is still unclear. Our research aims to understand these variabilities from SGLI satellite data, and a method was developed to estimate PSC from remote sensing reflectance, Rrs, through phytoplankton absorption coefficient, aph(λ). First, we used seven HPLC diagnostic pigments data in Ise-Mikawa Bay from 2010 to 2019 to calculate PSC. And then in-situ aph(λ) was used to estimate the PSC using a tuned spectral-based PSC model, and finally Quasi-Analytical Algorithm (QAA) was used to estimate aph(λ) from in situ Rrs to derive PSC. Spatial distribution of PSC from the pigments shows that micro-phytoplankton dominants in most of the Ise-Mikawa Bay area especially the coastal and center parts. Nano- and pico-phytoplankton take part in a smaller amount of the phytoplankton biomass. The PSC can be well retrieved from the in-situ aph, but not when it was calculated from in situ Rrs. We will improve the PSC estimation from Rrs, and then apply to the SGLI satellite data to show the variations of both the seasonal and interannual PSC distributions in Ise-Mikawa Bay.