SURF: A Relocatable Platform for On-Demand High-Resolution Ocean Modelling for the Digital Twins

In today’s world, the accessibility of operational large-scale regional ocean models from platforms like the Copernicus Marine Environment Monitoring Service (CMEMS), combined with advanced computing infrastructures such as cloud computing and high-performance computing (HPC), is enabling the creation of high-resolution, on-demand digital representations of the ocean. These advancements are driving international interest in implementing high-resolution shelf-coastal numerical models to deepen our understanding of marine systems and their sensitivities to climate change. Such models are essential for capturing fine-scale processes that coarse-resolution global and regional models cannot resolve. 

The Structured and Unstructured grid Relocatable Ocean platform for Forecasting (SURF) is an innovative, open-source ocean modeling platform designed to set up, execute, and analyze high-resolution nested ocean models in any region within a large-scale Ocean Forecasting, Analysis, and Reanalysis System. SURF integrates two state-of-the-art ocean models:  NEMO: A structured-grid model optimized for open ocean and shelf applications. SHYFEM-MPI: An unstructured-grid model tailored for accurately modeling complex coastal dynamics.

SURF has been successfully implemented and validated in various regions of the world’s oceans, downscaling from large-scale ocean prediction systems, such as global and regional CMEMS products. The nested high-resolution models have shown better performance compared to their parent coarse-resolution models.

SURF provides a high-level, user-friendly interface to conduct an ocean downscaling experiment from start to finish, including input data acquisition and pre-processing, model execution, and post-processing for visualization and analysis of results. The platform is distributed as a Virtual Machine and Container Images, using portable virtualization technology for easy deployment across various computational environments, ensuring accessibility for a wide range of users, including educational institutions and commercial enterprises.

SURF is a valuable tool to supports Decision Support System (DSS) by providing high-resolution ocean forecasts crucial for applications like oil spill monitoring, search and rescue operations, navigation routing, fisheries and tourism.  A recent application was its deployment during the Manila Oil Spill accident on July 24, 2024, where high-resolution ocean circulation fields generated by SURF were integrated with the WITOIL oil spill simulation platform. This integration improved trajectory predictions, accurately depicting the northward drift of the oil slick and closely aligning with satellite observations.

On-demand regional and coastal high-resolution models can be beneficial to diverse end-users, including coastalmanagers, harbour authorities, civil protection agencies and maritime communities. By providing high-resolution ocean forecasts, SURF can play a crucial role in mitigating risks, protecting communities, and reducing potential losses.