Abstract

High-impact ocean weather events and climate extremes can have devastating effects on coastal zones and small islands. Marine Disaster Risk Reduction (DRR) is a systematic approach to such events, through which the risk of disaster can be identified, assessed and reduced. This can be done by improving ocean and atmosphere prediction models, data assimilation for better initial conditions and developing an efficient and sustainable impact forecasting methodology for Early Warnings Systems. A common user request during disaster remediation actions is for high-resolution information, which can be derived from easily deployable numerical models nested into operational larger-scale ocean models. The Structured and Unstructured Relocatable Ocean Model for Forecasting (SURF) enables users to rapidly deploy a nested high-resolution numerical model into larger-scale ocean forecasts. Rapidly downscaling the currents, sea level, temperature, and salinity fields is critical in supporting emergency responses to extreme events and natural hazards in the world’s oceans. The most important requirement in a relocatable model is to ensure that the interpolation of low-resolution ocean model fields (analyses and reanalyses) and atmospheric forcing is tested for different model domains. The provision of continuous ocean circulation forecasts through the Copernicus Marine Environment Monitoring Service (CMEMS) enables this testing. High-resolution SURF ocean circulation forecasts can be provided to specific application models such as oil spill fate and transport models, search and rescue trajectory models, and ship routing models requiring knowledge of meteo-oceanographic conditions. SURF was used to downscale CMEMS circulation analyses in four world ocean regions, and the high-resolution currents it can simulate for specific applications are examined. The SURF downscaled circulation fields show that the marine current resolutions affect the quality of the application models to be used for assessing disaster risks, particularly near coastal areas where the coastline geometry must be resolved through a numerical grid, and high-frequency coastal currents must be accurately simulated.

Highlights

  • Major natural and manmade events can endanger life and property in coastal areas

  • The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation

  • NP fundamental helped in interpretation of modeling results and revising the work

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Summary

INTRODUCTION

Major natural and manmade events can endanger life and property in coastal areas. Such threats are addressed through the Sendai Framework for Disaster Risk Reduction (DRR), which is aimed at reducing the damage caused by natural hazards, such as the beaching of hazardous substances, storm surges, and flooding. Being a relocatable platform SURF has two major advantages over the products outlined above: (i) a robust grid interpolation scheme and lateral boundary constraints (Pinardi et al, 2003); (ii) a direct interface to the CMEMS service products (no need of any reformatting for the ocean fields) that are open and free every day, in every part of the ocean. This makes SURF one of the most complete open-source and freely available relocatable platforms, offering several grid and numerical scheme solutions, nested in an operational global model with high accessibility and trusted repositories. The Lagrangian model is configured to model surface drift using the uppermost model layer currents

Results
SUMMARY AND CONCLUSION
DATA AVAILABILITY STATEMENT

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