The study presents long-term variability in satellite retrieved phytoplankton size classes (PSC) at two coastal sites, off Gopalpur and Visakhapatnam, in the north-western Bay of Bengal. The abundance-based models by Brewin et al. (2010) (B10) and Sahay et al. (2017) (S17), for retrieval of PSC (micro, nano, and picophytoplankton), from satellite data, were validated. Both the models performed well in the retrieval of nano and microphytoplankton. However, B10 performed poorly in retrieving picophytoplankton. The statistical analysis indicated better performance of the S17 model and hence was applied to Moderate Resolution Imaging Spectroradiometer onboard Aqua satellite (MODISA) data to understand the temporal (at monthly climatology) and spatial variability (from nearshore to offshore). The spatial distribution indicated nearshore dominance of micro and offshore dominance of picophytoplankton. In nearshore waters off Gopalpur, microphytoplankton dominated throughout the year except for months of south-west monsoon (June and July) where the dominance of picophytoplankton was observed. All PSC exhibited similar distribution at an annual scale with a primary peak during pre-monsoon (March and April) and a secondary peak during post-monsoon (September–November). However, microphytoplankton concentration during post-monsoon was higher off Gopalpur in comparison to Visakhapatnam. The higher microphytoplankton concentration during pre-monsoon was attributed to recurrent phytoplankton blooms. Whereas, post-monsoon increment could be attributed to enhanced phytoplankton growth by availing nutrients sourced from monsoonal precipitation induced terrigenous influx. The outcome of the present study recommends the use of the S17 model for satellite retrieval of PSC from the north-western Bay of Bengal.

这项研究提出了在孟加拉西北部的Gopalpur和Visakhapatnam附近的两个沿海地点，卫星检索到的浮游植物大小等级（PSC）的长期变化。Brewin等人的基于丰度的模型。（2010）（B10）和Sahay等。（2017）（S17），用于从卫星数据中检索PSC（微米，纳米和浮游植物）的方法得到了验证。两种模型在纳米浮游植物和微浮游植物的检索中均表现良好。但是，B10在恢复浮游浮游生物方面表现不佳。统计分析表明S17模型具有更好的性能，因此被应用于水上卫星中分辨率成像光谱仪（MODISA）数据，以了解时间（每月气候）和空间变化（从近岸到近海）。空间分布表明微浮游植物的近岸优势和浮游植物的近岸优势。在戈帕普尔（Gopalpur）附近的近岸水域中，微浮游植物全年占主导地位，西南季风（6月和7月）除外，在几个月中微浮游植物占主导地位。所有PSC的年均分布均相似，季风前（3月和4月）出现一次高峰，季风后（9月至11月）出现次高峰。然而，与维沙卡帕特南地区相比，季风后微风中浮游植物的浓度更高。季风前较高的浮游植物浓度归因于浮游植物反复开花。然而，季风后的增加可以归因于通过利用季风性降水引起的陆源性涌入而获得的养分，促进了浮游植物的生长。本研究的结果建议使用S17模型从孟加拉西北部湾对PSC进行卫星检索。