A data-driven framework for attainable ship speed uncertainty under stochastic weather conditions
Volume
77
Issue number
1
Article number
77108
Received
10 August 2025
Received in revised form
16 September 2025
Accepted
3 October 2025
Available online
8 October 2025
Authors
Marijana Marjanović1*, Marko Valčić1,2, Jasna Prpić-Oršić1, Mate Barić2
1 University of Rijeka, Faculty of Engineering, Vukovarska 58, 51000 Rijeka, Croatia
2 University of Zadar, Maritime Department, Mihovila Pavlinovića 1, 23000 Zadar, Croatia
Corresponding author email
Abstract
This paper presents a data-driven framework for quantifying attainable ship speed uncertainty considering weather forecast uncertainty. The methodology integrates two parallel workflows: weather forecast processing and ship performance simulation. Weather forecast data from NOAA and GFS sources are collected at multiple lead times (0-24h, 24-72h, 72-120h, 120-168h). The data undergo spatial discretisation over a North Atlantic rectangular grid, extracting the main meteorological variables, including significant wave height, peak period, wave direction, wind speed, and wind direction. Ship performance simulations were done using Wärtsilä NaviTrainer NTPRO 5000 and HydroComp NavCad to generate attainable ship speed lookup tables under varying conditions: intended speeds (14.5, 13.5, 12.0 kn), wave heights (0-14 m according to WMO Sea State Codes 0-8), and wave encounter angles (0°-180°). Multiple metrics were used for uncertainty quantification, including RMSE, MAE, Bias, UGR, CRPS, IoA, and FSS for meteorological variables, alongside CMAE for directional parameters. These metrics are subsequently applied to estimated attainable ship speeds, establishing response variable uncertainties. Correlation analysis was conducted between the uncertainty of meteorological variables and the uncertainty in attainable ship speed, providing important insights for estimated time of arrival (ETA) calculations and voyage planning under weather uncertainty.
Keywords
Attainable Ship Speed, Weather Uncertainty, Ship Speed Uncertainty, Data-driven modelling, Voyage Planning