Remote Sensing Data-Based Modelling for Analyzing Green Tide Proliferation Drivers in the Yellow Sea

Since 2007, green tides have recurrently occurred in the Yellow Sea during spring and summer, with a massive outbreak recorded in 2021. Given the critical significance of green tide monitoring and prediction for marine ecological security and sustainable development, this study developed a satellite remote sensing-validated coupled simulation system for green tide drift and growth, by integrating multi-source satellite remote sensing data and oceanographic reanalysis datasets. Leveraging this system, we systematically analyzed the spatiotemporal evolution characteristics and underlying driving mechanisms of both routine green tide processes in 2014–2015 and the extreme 2021 event. Satellite images with low cloud cover and extensive green tide distribution were screened to confirm the accuracy of green tide drift trajectories and distribution ranges for validating the model’s reliability, and the results demonstrated the spatial consistency between simulation results and satellite observations. The validated model was used to track the drift and growth–decline processes of green tides and investigate the underlying cause of high-biomass appearance in 2021. Combined with environmental parameters, our analyses revealed that variations in attachment substrates alter wind resistance coefficients, thereby potentially accelerating the northward drift velocity of green tides. Furthermore, substrate properties may exert a significant regulatory effect on the attachment, germination, and biomass accumulation of Ulva prolifera spores, which could be a leading factor driving the massive green tide outbreak.