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j-atkins merged 1 commit into from
Feb 18, 2026
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Fix broken docs link #293

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2 changes: 1 addition & 1 deletion docs/paper/paper.md
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Expand Up @@ -75,7 +75,7 @@ Moreover, the data ingestion system relies on Analysis-Ready and Cloud-Optimized

The package opens space for many other research applications. It can support real-life expedition planning by letting users test sampling routes before going to sea. It also provides tooling to explore real-time adaptive strategies in which sampling plans shift as forecasts or observations update. The same workflow can also be used to investigate sampling efficiency, for example, examining how waypoint number or spacing shapes the ability to capture features of interest. Moreover, the software is well-suited for developing Observation System Simulation Experiments (OSSEs; e.g. @Errico2013) to test and optimise observational strategies in a cost- and time-efficient manner. This framework further enables instrument design experiments that are relevant to autonomous observing systems. There is potential for users to prototype and test control strategies for gliders, REMUS vehicles, and Saildrones, as well as explore concepts for new instruments at early stages of development. Future tutorials could demonstrate how to define custom instruments within the VirtualShip framework.

Both the customisability of the `VirtualShip` platform and the exciting potential for new ARCO-based data hosting services in domains beyond oceanography (e.g., [atmospheric science](https://climate.copernicus.eu/work-progress-our-data-stores-turn-arco)) means there is potential to extend VirtualShip (or "VirtualShip-like" tools) to other domains in the future. Furthermore, as the `Parcels` underpinnings themselves continue to evolve, with a future (at time of writing) [v4.0 release](https://docs.oceanparcels.org/en/v4-dev/v4/) focusing on alignment with [Pangeo](https://pangeo.io/) standards and `Xarray` data structures [@Hoyer2017], `VirtualShip` will also benefit from these improvements, further enhancing its capabilities, extensibility and compatability with modern cloud-based data pipelines.
Both the customisability of the `VirtualShip` platform and the exciting potential for new ARCO-based data hosting services in domains beyond oceanography (e.g., [atmospheric science](https://climate.copernicus.eu/work-progress-our-data-stores-turn-arco)) means there is potential to extend VirtualShip (or "VirtualShip-like" tools) to other domains in the future. Furthermore, as the `Parcels` underpinnings themselves continue to evolve, with a future (at time of writing) [v4.0 release](https://docs.oceanparcels.org/en/main/v4/) focusing on alignment with [Pangeo](https://pangeo.io/) standards and `Xarray` data structures [@Hoyer2017], `VirtualShip` will also benefit from these improvements, further enhancing its capabilities, extensibility and compatability with modern cloud-based data pipelines.

# AI usage disclosure

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