A Comparison of Stochastic and Deterministic Downscaling in Eddy Resolving Ocean Modelling: The Lakshadweep Sea Case Study

This study compares the skills of two numerical models at same horizontal resolution but based on different principles in representing meso- and sub-mesoscale ocean features. The first model, titled LD20-NEMO, was solving primitive equations dynamics. second LD20-SDD, used a newer stochastic–deterministic downscaling (SDD) method. Both had 1/20° resolution, meteo forcing, outputs from data assimilating global model 1/12° available Copernicus Marine Service (CMEMS). LD20 did not assimilate observational were physically aware observations via parent model. LD20-NEMO only 2D set CMEMS as lateral boundary conditions. LD20-SDD consumed full 3D exploited stochastic properties these to generate downscaled field variables higher than three assessed against remotely sensed situ for four-year period 2015–2018. showed similar reproducing temperature salinity, however SDD version performed slightly better NEMO, more computationally efficient by large margin.