A Visibility Risk-Assessment Tool for Maritime Operations

Fog and smog reduce visibility at sea, greatly impacting ship navigation and safety. Although ships underway in fog tend to slow and proceed with caution, collisions with other ships and rocks occur frequently every year. Impacts of low-visibility marine conditions impact commerce via decreased speed and safety in movement of commercial fleets, and increased costs through poor fuel load planning. The COVID-19 pandemic has underscored the necessity of maritime shipping to the supply chain; therefore, decreasing its associative cost and risk are of utmost importance.

Applied Ocean Sciences (AOS) is creating a visibility risk-assessment tool for maritime operations. Previously, AOS has successfully developed analogous risk assessment code (RAC) for applications of Arctic maritime waypoint planning, anti-submarine warfare, and the use of autonomous maritime systems for Intelligence, Surveillance, and Reconnaissance (ISR) operations. A maritime operations risk-assessment tool will consider meteorologic, oceanographic, and bathymetric conditions and safety thresholds to create discretized spatial risk maps. Visibility prediction must consider precipitation, lighting conditions, low clouds, and smog. AOS is creating a diagnostic model for fog prediction using publicly available ensemble weather forecast model output. Smog will be modeled from satellite particle concentration observations and diffusion-advection ensemble wind models. Hindcast validation will be used to calibrate these atmospheric models. Ensemble ocean models will be used for waves and currents. NOAA nautical charts will be used for navigational considerations along with historical information about vessel density and speed. AOS personnel have experience conducting navigational risk assessments for proposed maritime facilities for the US Coast Guard and are familiar with metrics for parameterizing risk of vessel collision (kinetic energy density, etc.), and will build on these tools in the development of the RACs for this project.

RACs developed by AOS use joint distributions of environmental forecast states to estimate the probabilities of exceeding key variable thresholds, such as those rules describing safe maritime vessel transit. The rules governing the RAC can integrate criteria derived from multiple variables and consider forecast quality for each parameter. Once spun up, the user can query the RAC with current or future conditions and parameters. The RAC analysis then computes the probabilities of risk at the locations and times of interest, producing automatic analysis maps at each forecast snapshot. The RAC will be validated with historical maritime accident reports. Initially, AOS is testing all models over the Gulf of Mexico due to the importance of that area to US commerce and recreation.