Merge pull request #44 from OceanParcels/update_CMS_paper

Updates to the JOSS paper submission

Author: michaeldenes

docs/paper/paper.bib

@@ -29,25 +29,6 @@ @article{Large1994
  year = {1994}
 }
 
-@misc{Allen1999,
- title = {{Review of leeway: field experiments and implementation. USCG R&D center technical report CG-D-08-99}},
- author = {Allen, A.A., Plourde, J.V.},
- year = {1999},
- month = {April},
- howpublished = {Available via: https://ntrl.ntis.gov/NTRL/},
- note = {{Accessed: 18 April 2024}}
-}
-
-
-@misc{Allen2005,
- title = {{Leeway divergence. USCG R&D center technical report CG-D-05-05}},
- author = {Allen, A.A.},
- year = {2005},
- month = {January},
- howpublished = {Available via: https://ntrl.ntis.gov/NTRL/},
- note = {{Accessed: 18 April 2024}}
-}
-
 @article{Grawe2012,
  author = {Gräwe, Ulf and Deleersnijder, Eric and Shah, Syed Hyder Ali Muttaqi and Heemink, Arnold Willem},
  doi = {10.1007/s10236-012-0523-y},
@@ -63,8 +44,6 @@ @article{Grawe2012
  year = {2012}
 }
 
-
-
 @article{Lebreton2012,
  author = {Lebreton, L.C.-M. and Greer, S.D. and Borrero, J.C.},
  doi = {10.1016/j.marpolbul.2011.10.027},
@@ -419,10 +398,3 @@ @article{Kaandorp2023
  volume = {16},
  year = {2023}
 }
-
-@misc{CMS,
- title = {{Copernicus Marine Service}},
- howpublished = {https://marine.copernicus.eu/},
- note = {{Accessed: 27 March 2024}},
- year = {2024}
-}

docs/paper/paper.md

@@ -23,7 +23,7 @@ link-bibliography: false
 # Summary
 `plasticparcels` is a python package for simulating the transport and dispersion of plastics in the ocean. The tool is based on `v3.0.3` of the `parcels` computational Lagrangian ocean analysis framework [@Lange2017; @Delandmeter2019], providing a modular and customisable collection of methods, notebooks, and tutorials for advecting virtual plastic particles with a wide range of physical properties. The tool applies a collection of physical processes to the virtual particles, such as Stokes drift, wind-induced drift, biofouling, and turbulent mixing, via custom particle behaviour programmed in the form of `Kernels`. In addition to the fine-scale physics parameterisations, `plasticparcels` provides global particle initialisation maps that represent best estimates for plastic pollution emissions along coastlines [@Jambeck2015], from river sources [@Meijer2021], and in the open-ocean from fishing-related activities [@Kroodsma2018], as well as a current best estimate of buoyant plastic concentrations globally [@Kaandorp2023]. We envisage `plasticparcels` as a tool for easy-to-run plastic dispersal simulations; as well as for rapid prototyping, development, and testing of new fine-scale physics parameterisations.
 
-The current version supports nano- and microplastic behaviour, with support for macroplastics planned in the near-future. It has been designed for use with hydrodynamic and biogeochemical data from the Copernicus Marine Service [@CMS], providing new plastic modelling capabilities as part of the NECCTON project. `plasticparcels` is easily adapted to run on local machines and high-performance computing (HPC) architecture with various hydrodynamic, biogeochemical, and other model fields as input. A future goal is to embed `plasticparcels` within a cloud platform to allow for even more rapid prototyping, development, and simulations.
+The current version supports nano- and microplastic behaviour, with support for macroplastics planned in the near-future. It has been designed for use with hydrodynamic and biogeochemical data from the [Copernicus Marine Service](https://marine.copernicus.eu/), providing new plastic modelling capabilities as part of the NECCTON project. `plasticparcels` is easily adapted to run on local machines and high-performance computing (HPC) architecture with various hydrodynamic, biogeochemical, and other model fields as input. A future goal is to embed `plasticparcels` within a cloud platform to allow for even more rapid prototyping, development, and simulations.
 
 
 # Statement of need