New diagnostic sea surface current fields to trace floating algae in the Yellow Sea

Area of Science:

• Oceanography
• Marine Biology
• Computational Fluid Dynamics

Background:

• Accurate simulation of floating algae requires precise surface velocity fields.
• Existing reanalysis datasets may have limitations in representing localized ocean dynamics.

Purpose of the Study:

• To derive and validate new diagnostic velocity fields based on Generalized Ekman (GE) theory for tracing floating algae.
• To compare the performance of diagnostic velocity fields against reanalysis datasets in the Yellow Sea (YS).
• To assess the utility of these fields for simulating the transport of specific algae species.

Main Methods:

• Derivation of diagnostic velocity fields using GE theory.
• Validation against drifter observations and comparison with two reanalysis datasets.
• Particle tracking experiments for Ulva prolifera (July 2011) and Sargassum horneri (May 2017).
• Simulation of drifter trajectories and estimation of error accumulation speed.

Main Results:

• Diagnostic velocity fields demonstrated comparable, and sometimes superior, accuracy to reanalysis datasets.
• Simulations using diagnostic fields showed better agreement with satellite imagery and in situ observations.
• Error accumulation speeds were analyzed for each velocity field.

Conclusions:

• Diagnostic velocity fields derived from GE theory are a superior tool for simulating surface-floating substances and organisms.
• This approach provides a computationally efficient alternative to heavy numerical models for ecological forecasting.
• The method is readily applicable for studying algal bloom dynamics and transport in marine environments.