Preprints
https://doi.org/10.5194/egusphere-2023-2060
https://doi.org/10.5194/egusphere-2023-2060
16 Nov 2023
 | 16 Nov 2023
Status: this preprint is open for discussion.

VISIR-2: ship weather routing in Python

Gianandrea Mannarini, Mario Leonardo Salinas, Lorenzo Carelli, Nicola Petacco, and Josip Orović

Abstract. Ship weather routing, which involves suggesting low-emission routes, holds potential for contributing to the decarbonisation of maritime transport. However, its quantitative impact has been explored only to a limited extent, also for a lack of readily deployable open-source and open-language computational models.

As a response, the VISIR model has been refactored in Python, incorporating new features. The velocity composition with currents has been refined, now encompassing leeway as well. For motor vessels, the angle of attack of waves has been considered, while sailboats now account for the combined effects of wind and sea currents. A least-CO2 algorithm in presence of dynamic graph edge weights has been implemented and validated, proving a quasi-linear computational performance which outperforms VISIR-1. The software suite’s modularity has been significantly improved, alongside a thorough validation against arious benchmarks.

The resulting VISIR-2 model has been employed in numerical experiments within the Mediterranean Sea for the entire 2022, utilising meteo-oceanographic analysis fields. For a 125-meter-long ferry, the distribution of carbon dioxide savings follows a bi-exponential distribution. Two-digit CO2 savings were possible for more than ten days in a year. Largest savings were achieved in avoiding upwind sailing and using the lowest engine load. In the case of an 11-meter sailboat, time savings increase with the extent of path elongation, particularly during upwind sailing. The sailboat’s routes were approximately 3 % shorter thanks to optimisation, and there was potential for additional savings when favourable currents were in play. The impact of leeway was minor, but disregarding it would result in a systematic underestimation of route durations.

VISIR-2 is a collaborative model with the capacity to harness knowledge from oceanography, ocean engineering, and computer science, to contribute to the decarbonisation efforts in the shipping industry.

Gianandrea Mannarini et al.

Status: open (until 11 Jan 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Gianandrea Mannarini et al.

Data sets

Raw data for replicating VISIR-2 runs of this manuscript Mario Salinas https://zenodo.org/record/8321216

Intermediate products (routes) to expedite reproduction of both figures and tables in Sect.5 of this manuscript Mario Salinas https://zenodo.org/record/8233874

Model code and software

Source code of VISIR-2 Mario Salinas, Lorenzo Carelli, Gianandrea Mannarini https://zenodo.org/record/8305527

Video supplement

Ferry optimal routes for whole 2022 Mario Salinas https://av.tib.eu/media/62912

Sailboat optimal routes for whole 2022 Mario Salinas https://av.tib.eu/media/62913

Gianandrea Mannarini et al.

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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 now quasi-linear. VISIR-2 yields, for more than ten days in a year, two-digit savings for a ferry sailing in the Mediterranean Sea. Sailboat routes with wind and currents can be optimised as well.