Update JOSS paper title

docs/paper/paper.bib

@@ -107,7 +107,7 @@ @article{Errico2013
 number = {674},
 pages = {1162-1178},
 keywords = {OSSE, data assimilation, atmospheric observations},
-doi = {https://doi.org/10.1002/qj.2027},
+doi = {10.1002/qj.2027},
 url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.2027},
 eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2027},
 abstract = {Abstract Initial design and validation of baseline Observing System Simulation Experiments (OSSEs) at NASA's Global Modeling and Assimilation Office (GMAO) are described. The OSSEs mimic the procedures used to analyze global observations for specifying states of the atmosphere. As simulations, however, OSSEs are not only confined to already existing observations and they provide a perfect description of the true state being analyzed. These two properties of the simulations can be exploited to improve both existing and envisioned observing systems and the algorithms to analyze them. Preliminary to any applications, however, the OSSE framework must be adequately validated. This first version of the simulated observations is drawn from a 13 month simulation of nature produced by the European Center for Medium-Range Weather Forecasts. These observations include simulated errors of both instruments and representativeness. Since the statistics of analysis and forecast errors are partially determined by these observational errors, their appropriate modelling can be crucial for validating the realism of the OSSE. That validation is performed by comparing the statistics of the results of assimilating these simulated observations for one summer month compared with the corresponding statistics obtained from assimilating real observations during the same time of year. The assimilation system is the three-dimensional variational analysis (GSI) scheme used at both the National Centers for Environmental Prediction and GMAO. Here, only statistics concerning observation innovations or analysis increments within the troposphere are considered for the validation. In terms of the examined statistics, the OSSE is validated remarkably well, even with some simplifications currently employed. In order to obtain this degree of success, it was necessary to employ horizontally correlated observation errors for both atmospheric motion vectors and some satellite observed radiances. The simulated observations with added observation errors appear suitable for some initial OSSE applications.},
@@ -122,7 +122,7 @@ @article{Lumpkin2017
    volume = "9",
    number = "Volume 9, 2017",
    pages = "59-81",
-   doi = "https://doi.org/10.1146/annurev-marine-010816-060641",
+   doi = "10.1146/annurev-marine-010816-060641",
    url = "https://www.annualreviews.org/content/journals/10.1146/annurev-marine-010816-060641",
    publisher = "Annual Reviews",
    issn = "1941-0611",
@@ -143,6 +143,7 @@ @article{Jayne2017
  journal = {Oceanography},
  number = {2},
  pages = {18--28},
+ doi = "10.5670/oceanog.2017.213",
  publisher = {Oceanography Society},
  title = {The Argo Program: Present and Future},
  urldate = {2025-12-17},
@@ -181,7 +182,7 @@ @article{Kostaschuk2005
 year = {2005},
 note = {Fluid Flow and Sediment Transport Process in Geomorphology},
 issn = {0169-555X},
-doi = {https://doi.org/10.1016/j.geomorph.2004.07.012},
+doi = {10.1016/j.geomorph.2004.07.012},
 url = {https://www.sciencedirect.com/science/article/pii/S0169555X04002879},
 author = {Ray Kostaschuk and Jim Best and Paul Villard and Jeff Peakall and Mark Franklin},
 keywords = {Acoustic Doppler current profiler, Flow velocity, Bed load velocity, Sediment transport},
@@ -196,7 +197,7 @@ @article{Gordon2014
 number = {7},
 pages = {4251-4263},
 keywords = {Kuroshio, NEC bifurcation, Lamon Bay, Philippines},
-doi = {https://doi.org/10.1002/2014JC009882},
+doi = {10.1002/2014JC009882},
 url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2014JC009882},
 eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2014JC009882},
 abstract = {Abstract A northward flowing current, emanating from the North Equatorial Current (NEC) bifurcation at the Philippine margin, enters Lamon Bay along Luzon's eastern coast. There the NEC tropical water masses merge with subtropical water of the western North Pacific to form the Kuroshio. A northward flowing western boundary current is first observed near 16.5°N, marking the initiation of the Kuroshio. The current feeding into the nascent Kuroshio of Lamon Bay is bracketed by an anticyclonic dipole to its northeast and a cyclonic dipole to its southwest. Ship-based observational programs in the spring seasons of 2011 and 2012 detect a shift of the Lamon Bay thermohaline stratification with marked enrichment of NEC tropical thermocline water in 2012 relative to a dominant western North Pacific subtropical stratification of 2011. Temperature-salinity time series from moorings spanning the two ship-based observations identify the timing of the transition as December 2011. The NEC bifurcation was further south in May 2012 than in May 2011. We suggest that the more southern bifurcation in May 2012 induced increased NEC thermocline water injection into Lamon Bay and nascent Kuroshio, increasing the linkage of the western North Pacific subtropical and tropical thermoclines. This connection was reduced in May 2011 as the NEC bifurcation shifted into a more northerly position and western North Pacific subtropical thermocline dominated Lamon Bay stratification.},

docs/paper/paper.md

@@ -1,5 +1,5 @@
 ---
-title: "VirtualShip for simulating oceanographic fieldwork in the global ocean"
+title: "VirtualShip: A Python package for simulating oceanographic fieldwork in the global ocean"
 tags:
   - Python
   - oceanography
@@ -45,10 +45,12 @@ bibliography: paper.bib
 
 Marine science relies on fieldwork for data collection, yet sea-going opportunities are limited due to financial costs, logistical constraints, and environmental burdens. We present an alternative means, namely `VirtualShip`, for training scientists to conduct oceanographic fieldwork in an authentic manner, to plan future expeditions and deployments, and to directly compare observational and instrumentational strategies with model data.
 
-`VirtualShip` goes beyond simply extracting grid-cell values from model output. Instead, it uses programmable behaviours and sophisticated interpolation techniques (with `Parcels` underpinnings) to access data in exact locations and timings, as if they were being collected by real-world instruments. `VirtualShip` shares some functionality with existing tools, such as `OceanSpy` [@Almansi2019] and `VirtualFleet` [@Maze2023], but extends capabilities to mesh many different instrument deployments into a unified expedition simulation framework. Moreover, `VirtualShip` exploits readily available, streamable data via the Copernicus Marine Data Store, removing the need for users to download and manage large datasets locally and/or arrange for access to remote servers. `VirtualShip` can also integrate coordinate files exported from the [Marine Facilities Planning](https://www.marinefacilitiesplanning.com/cruiselocationplanning#) (MFP) tool, giving users the option to define expedition waypoints via an intuitive web-based mapping interface.
-
 `VirtualShip` simulates the deployment of virtual instruments commonly used in oceanographic fieldwork, with emphasis on realism in how users plan and execute expeditions. For example, users must consider ship speed and instrument deployment/recovery times to ensure their expedition is feasible within given time constraints. Possible instrument selections include surface `Drifter` [@Lumpkin2017], `CTD` (Conductivity-Temperature-Depth; @Johnson2007), `Argo float` [@Jayne2017], `XBT` (Expendable Bathythermograph; @Goni2019), underway `ADCP` (Acoustic Doppler Current Profiler; @Kostaschuk2005), and underway `temperature/salinity` [@Gordon2014] probes. More detail on each instrument is available in the [documentation](https://virtualship.readthedocs.io/en/latest/user-guide/assignments/Research_proposal_intro.html#Measurement-Options).
 
+# State of the field
+
+`VirtualShip` goes beyond simply extracting grid-cell values from model output. Instead, it uses programmable behaviours and sophisticated interpolation techniques (with `Parcels` underpinnings) to access data in exact locations and timings, as if they were being collected by real-world instruments. `VirtualShip` shares some functionality with existing tools, such as `OceanSpy` [@Almansi2019] and `VirtualFleet` [@Maze2023], but extends capabilities to mesh many different instrument deployments into a unified expedition simulation framework. By way of further innovation, `VirtualShip` exploits readily available, streamable data via the Copernicus Marine Data Store, removing the need for users to download and manage large datasets locally and/or arrange for access to remote servers. `VirtualShip` can also integrate coordinate files exported from the [Marine Facilities Planning](https://www.marinefacilitiesplanning.com/cruiselocationplanning#) (MFP) tool, giving users the option to define expedition waypoints via an intuitive web-based mapping interface.
+
 # Software design
 
 The software can simulate complex multidisciplinary expeditions. One example is a virtual expedition across the Agulhas Current and the South Eastern Atlantic that deploys a suite of instruments to sample physical and biogeochemical properties (\autoref{fig:fig1}). Key circulation features appear early in the expedition track, with enhanced ADCP speeds marking the strong Agulhas Current (\autoref{fig:fig1}b) and drifters that turn back toward the Indian Ocean indicating the Agulhas Retroflection (\autoref{fig:fig1}c). The CTD profiles capture the vertical structure of temperature and oxygen along the route, including the warmer surface waters of the Agulhas region (\autoref{fig:fig1}d, early waypoints) and the Oxygen Minimum Zone in the South Eastern Atlantic (\autoref{fig:fig1}e, final waypoints).