Abstract
Abstract. The latest development of the ship-routing model published in Mannarini et al. (2016a) is VISIR-1.b, which is presented here. The new version of the model targets large ocean-going vessels by considering both ocean surface gravity waves and currents. To effectively analyse currents in a graph-search method, new equations are derived and validated against an analytical benchmark. A case study in the Atlantic Ocean is presented, focussing on a route from the Chesapeake Bay to the Mediterranean Sea and vice versa. Ocean analysis fields from data-assimilative models (for both ocean state and hydrodynamics) are used. The impact of waves and currents on transatlantic crossings is assessed through mapping of the spatial variability in the tracks, an analysis of their kinematics, and their impact on the Energy Efficiency Operational Indicator (EEOI) of the International Maritime Organization. Sailing with or against the main ocean current is distinguished. The seasonal dependence of the EEOI savings is evaluated, and greater savings with a higher intra-monthly variability during winter crossings are indicated in the case study. The total monthly mean savings are between 2 % and 12 %, while the contribution of ocean currents is between 1 % and 4 %. Several other ocean routes are also considered, providing a pan-Atlantic scenario assessment of the potential gains in energy efficiency from optimal tracks, linking them to regional meteo-oceanographic features.
Highlights
The strongest water flows are generally observed in western ocean boundary currents, in tidal currents, in the circulation of straits and fjords, in inland waterways, and in the vicinity of river runoffs (Apel, 1987)
This is indicated by ocean drifter data, which are affected by wind (Maximenko et al, 2012), satellite altimetry, which just provides the geostrophic component of the currents (Pascual et al, 2006), and model computations, whose capacity to represent mesoscale variability depends on spatial discretisation along with other factors (Fu and Smith, 1996; Sandery and Sakov, 2017)
The results are difficult to compare because (i) they are not validated against exact solutions, (ii) with some exceptions, they do not declare the computational performance, (iii) generally, their model source codes are not openly accessible, (iv) they are limited to case study analyses on a specific date, without any assessment of seasonal and geographical variability in their quantitative conclusions, and (v) they generally cannot account for both surface gravity waves and ocean currents
Summary
The strongest water flows are generally observed in western ocean boundary currents, in tidal currents, in the circulation of straits and fjords, in inland waterways, and in the vicinity of river runoffs (Apel, 1987). In the contexts of robust control and dynamic positioning, currents and other environmental fields, such as gravity waves and winds, are regarded as a disturbance that needs to be compensated for such an objective to be achieved, such as keeping the vessel’s position and heading To achieve this task, numerical schemes typically assume that such disturbance is constant in time (Fossen, 2012) or at least slowly varying with respect to the signal of interest related to the vessel’s internal dynamics (Loria et al, 2000). The level-set approach was extended to deal with energy minimisation by Subramani and Lermusiaux (2016), showing the potential of intentional speed reduction in a dynamic flow This method appears to be quite promising, though it has not as of yet been embedded into an operational service. It is one of the main instruments for mitigating the contribution of maritime transportation to climate change (Bazari and Longva, 2011)
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