<p>Chlorophyll <i>a</i> (Chl <i>a</i>) is a key photosynthetic pigment and an essential indicator of phytoplankton biomass. Accurate Chl <i>a</i> measurements are crucial for understanding marine biogeochemical processes. China launched the Chinese Ocean Color and Temperature Scanner (COCTS) aboard the HY-1D satellite in 2020, yet its Chl <i>a</i> products require further validation in complex coastal waters. This study assesses HY-1D Chl <i>a</i> products in the Bohai and Yellow Seas, two optically complex coastal regions, using <i>in situ</i> data collected during multiple cruises. Additionally, we compare HY-1D Chl <i>a</i> products with those from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS). We observed that although Chl <i>a</i> products from HY-1D are generally consistent with those from the MODIS and VIIRS in spatial distribution, there are still significant errors when compared with <i>in situ</i> data. Therefore, we developed a new blended algorithm to improve the accuracy of HY-1D Chl <i>a</i> products. The algorithm distinguishes between turbid and relatively clean waters using a classification index based on the ratio of remote sensing reflectance (<i>R</i>_rs(<i>λ</i>)). After the initial classification, we developed targeted algorithms based on the optical properties of different water bodies. The new model shows a significant improvement, reducing the mean absolute percentage error (MAPE) from 43.1% to 24.3%. Additionally, merging Chl <i>a</i> data from HY-1D, MODIS, and VIIRS maintains good accuracy, with HY-1D Chl <i>a</i> products significantly enhancing data coverage and robustness. This research provides important support for producing high-quality HY-1D Chl <i>a</i> products for coastal waters.</p>