The Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application to the Yellow Sea green tide

Abstract. Massive floating macroalgal blooms in the ocean result many ecological consequences. Tracking their drifting pattern and predicting biomass are essential for effective marine management. In this study, a physical–ecological model, Floating Macroalgal Growth Drift Model (FMGDM), was developed. Based on tracking, replication, extinction of Lagrangian particles, FMGDM is capable determining dynamic growth drift macroalgae, with position, velocity, quantity, represented particles being updated synchronously between tracking modules. The particle driven by flows sea surface wind, process controlled temperature, irradiation, nutrients. flow turbulence fields were provided unstructured grid Finite-Volume Community Ocean (FVCOM), biological parameters specified based culture experiment Ulva prolifera, phytoplankton species causing largest worldwide bloom green tide Yellow Sea, China. applied to simulate around Sea 2014 2015. model results, e.g., distribution, tide, validated using remote-sensing observation data. Given prescribed spatial initialization from observations, robust enough reproduce temporal developments its early spring late summer, an accurate prediction 7–8 d. With support hydrodynamic macroalgae data, can serve as tool forecast other regions.