Articles | Volume 17, issue 10
https://doi.org/10.5194/gmd-17-4355-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-4355-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
24 May 2024
Model description paper |
| 24 May 2024
| 24 May 2024
VISIR-2: ship weather routing in Python
Gianandrea Mannarini
CORRESPONDING AUTHOR
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Lecce, Italy
Mario Leonardo Salinas
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Lecce, Italy
Lorenzo Carelli
CMCC Foundation – Euro-Mediterranean Center on Climate Change, Lecce, Italy
Nicola Petacco
DITEN, Università degli Studi di Genova, via Montallegro 1, 16145 Genoa, Italy
Josip Orović
Maritime Department, University of Zadar, Ul. Mihovila Pavlinovića, 23000 Zadar, Croatia
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Cited
25 citations as recorded by crossref.
- Accurate Mediterranean Sea forecasting via graph-based deep learning D. Holmberg et al. https://doi.org/10.1038/s41598-025-31177-w
- Studying the methods of predicting changes in floating speed when facing the wind for use in weather routing algorithm H. karimpour et al. https://doi.org/10.61882/marineeng.21.46.3
- An Isochrone-Based Predictive Optimization for Efficient Ship Voyage Planning and Execution Y. Chen & W. Mao https://doi.org/10.1109/TITS.2024.3416349
- A ferry route in the Skagerrak optimised via VISIR-2 G. Mannarini & M. Leonardo Salinas https://doi.org/10.1088/1742-6596/2867/1/012003
- Enhanced Ship Routing Through Ensemble Wave Forecasting and Causality-Constrained Departure Windows L. Zhang et al. https://doi.org/10.1109/ACCESS.2026.3700613
- Data Assimilated Atmospheric Forecasts for Digital Twin of the Ocean Applications: A Case Study in the South Aegean, Greece A. Parasyris et al. https://doi.org/10.3390/a17120586
- Development of a Reinforcement Learning-Based Ship Voyage Planning Optimization Method Applying Machine Learning-Based Berth Dwell-Time Prediction as a Time Constraint Y. Park et al. https://doi.org/10.3390/jmse14010043
- Capturing system complexity in maritime decarbonization: a multilayer modeling perspective M. Chepeliev et al. https://doi.org/10.1088/1748-9326/ae61ce
- Anomalous Behavior in Weather Forecast Uncertainty: Implications for Ship Weather Routing M. Marjanović et al. https://doi.org/10.3390/jmse13061185
- Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning C. Latinopoulos et al. https://doi.org/10.3390/jmse13050902
- Towards robust intelligent shipping via graph-informed representation, generative routing, and certified maneuvering X. Yin et al. https://doi.org/10.1016/j.oceaneng.2025.123957
- Numerical investigation on the aerodynamic performance of a combined Flettner rotor and U sail system R. Zhang et al. https://doi.org/10.1080/17445302.2025.2487576
- Green Voyage Planning: A Literature Survey on the Role of Sustainable Technologies and Strategies in Maritime Operations R. Fava & G. Satta https://doi.org/10.12716/1001.19.02.36
- Multi-voyage vessel routing and scheduling under nonlinear metocean-induced speed variation: A bidirectional A* and genetic-algorithm-embedded label-correcting framework G. Wu et al. https://doi.org/10.1016/j.oceaneng.2026.126565
- Vessel Trajectory Data Mining: A Review A. Troupiotis-Kapeliaris et al. https://doi.org/10.1109/ACCESS.2025.3525952
- Route and speed optimisation of a general cargo ship using extreme gradient boosting and enhanced Deep Q-Network approaches Y. Zhou et al. https://doi.org/10.1016/j.tre.2025.104555
- HADAD: Hexagonal A-Star with Differential Algorithm Designed for weather routing J. Jiménez de la Jara et al. https://doi.org/10.1016/j.oceaneng.2024.120050
- State-of-the-art optimization algorithms in weather routing — ship decision support systems: challenge, taxonomy, and review Y. Chen et al. https://doi.org/10.1016/j.oceaneng.2025.121198
- Waypoint-Sequencing Model Predictive Control for Ship Weather Routing Under Forecast Uncertainty M. Marjanović et al. https://doi.org/10.3390/jmse14020118
- Towards Improved Ship Weather Routing Through Multi-Objective Optimization with High Performance Computing Support M. Abdalsalam & J. Szlapczynska https://doi.org/10.12716/1001.19.01.12
- Long-term prediction of ship responses considering global scale wave forecast uncertainty and applications for container ships W. Fujimoto et al. https://doi.org/10.1016/j.oceaneng.2025.122072
- Design of global climate routing software (case study of crossing the Pacific Ocean) M. Alimohammadi et al. https://doi.org/10.66224/marineeng.21.47.8
- Robust Multi-Output AIS–Metocean Forecasting With Transformers: Closed-Form Weighting, Hybrid GWO–SA, and Post-Hoc Calibration A. Widodo et al. https://doi.org/10.1109/ACCESS.2026.3656919
- Optimal operational method for hybrid propulsion ships using operation data Y. Jang & K. Kim https://doi.org/10.1016/j.ijnaoe.2026.100761
- Recent Advancements and Challenges in Artificial Intelligence for Digital Twins of the Ocean V. Metheniti et al. https://doi.org/10.3390/cli14010003
25 citations as recorded by crossref.
- Accurate Mediterranean Sea forecasting via graph-based deep learning D. Holmberg et al. https://doi.org/10.1038/s41598-025-31177-w
- Studying the methods of predicting changes in floating speed when facing the wind for use in weather routing algorithm H. karimpour et al. https://doi.org/10.61882/marineeng.21.46.3
- An Isochrone-Based Predictive Optimization for Efficient Ship Voyage Planning and Execution Y. Chen & W. Mao https://doi.org/10.1109/TITS.2024.3416349
- A ferry route in the Skagerrak optimised via VISIR-2 G. Mannarini & M. Leonardo Salinas https://doi.org/10.1088/1742-6596/2867/1/012003
- Enhanced Ship Routing Through Ensemble Wave Forecasting and Causality-Constrained Departure Windows L. Zhang et al. https://doi.org/10.1109/ACCESS.2026.3700613
- Data Assimilated Atmospheric Forecasts for Digital Twin of the Ocean Applications: A Case Study in the South Aegean, Greece A. Parasyris et al. https://doi.org/10.3390/a17120586
- Development of a Reinforcement Learning-Based Ship Voyage Planning Optimization Method Applying Machine Learning-Based Berth Dwell-Time Prediction as a Time Constraint Y. Park et al. https://doi.org/10.3390/jmse14010043
- Capturing system complexity in maritime decarbonization: a multilayer modeling perspective M. Chepeliev et al. https://doi.org/10.1088/1748-9326/ae61ce
- Anomalous Behavior in Weather Forecast Uncertainty: Implications for Ship Weather Routing M. Marjanović et al. https://doi.org/10.3390/jmse13061185
- Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning C. Latinopoulos et al. https://doi.org/10.3390/jmse13050902
- Towards robust intelligent shipping via graph-informed representation, generative routing, and certified maneuvering X. Yin et al. https://doi.org/10.1016/j.oceaneng.2025.123957
- Numerical investigation on the aerodynamic performance of a combined Flettner rotor and U sail system R. Zhang et al. https://doi.org/10.1080/17445302.2025.2487576
- Green Voyage Planning: A Literature Survey on the Role of Sustainable Technologies and Strategies in Maritime Operations R. Fava & G. Satta https://doi.org/10.12716/1001.19.02.36
- Multi-voyage vessel routing and scheduling under nonlinear metocean-induced speed variation: A bidirectional A* and genetic-algorithm-embedded label-correcting framework G. Wu et al. https://doi.org/10.1016/j.oceaneng.2026.126565
- Vessel Trajectory Data Mining: A Review A. Troupiotis-Kapeliaris et al. https://doi.org/10.1109/ACCESS.2025.3525952
- Route and speed optimisation of a general cargo ship using extreme gradient boosting and enhanced Deep Q-Network approaches Y. Zhou et al. https://doi.org/10.1016/j.tre.2025.104555
- HADAD: Hexagonal A-Star with Differential Algorithm Designed for weather routing J. Jiménez de la Jara et al. https://doi.org/10.1016/j.oceaneng.2024.120050
- State-of-the-art optimization algorithms in weather routing — ship decision support systems: challenge, taxonomy, and review Y. Chen et al. https://doi.org/10.1016/j.oceaneng.2025.121198
- Waypoint-Sequencing Model Predictive Control for Ship Weather Routing Under Forecast Uncertainty M. Marjanović et al. https://doi.org/10.3390/jmse14020118
- Towards Improved Ship Weather Routing Through Multi-Objective Optimization with High Performance Computing Support M. Abdalsalam & J. Szlapczynska https://doi.org/10.12716/1001.19.01.12
- Long-term prediction of ship responses considering global scale wave forecast uncertainty and applications for container ships W. Fujimoto et al. https://doi.org/10.1016/j.oceaneng.2025.122072
- Design of global climate routing software (case study of crossing the Pacific Ocean) M. Alimohammadi et al. https://doi.org/10.66224/marineeng.21.47.8
- Robust Multi-Output AIS–Metocean Forecasting With Transformers: Closed-Form Weighting, Hybrid GWO–SA, and Post-Hoc Calibration A. Widodo et al. https://doi.org/10.1109/ACCESS.2026.3656919
- Optimal operational method for hybrid propulsion ships using operation data Y. Jang & K. Kim https://doi.org/10.1016/j.ijnaoe.2026.100761
- Recent Advancements and Challenges in Artificial Intelligence for Digital Twins of the Ocean V. Metheniti et al. https://doi.org/10.3390/cli14010003
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Short summary
Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and verifiable research. The Python-refactored VISIR-2 model considers currents, waves, and wind to optimise routes. The model was validated, and its computational performance is quasi-linear. For a ferry sailing in the Mediterranean Sea, VISIR-2 yields the largest percentage emission savings for upwind navigation. Given the vessel performance curve, the model is generalisable across various vessel types.
Ship weather routing has the potential to reduce CO2 emissions, but it currently lacks open and...
