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Metadata: Particle tracking model output simulating floating marine litter in the Bay of Bengal, 2018 to 2019
Abstract:
These data are particle positions and dates/times which are output from an OceanParcels particle tracking model simulating likely pathways of floating marine macro-litter in the Bay of Bengal between 1st June 208 – 30th September 2019, saved as NetCDF files. The model incorporated advection due to ocean, wind, and Stokes drift velocities, horizontal diffusion, and particle beaching behaviours. Two different hydrodynamic data sets were used to force the particles’ trajectories: a high-resolution ocean velocity hindcast (ROMS – Regional Oceanic Modelling System) and a lower-resolution dataset which included data assimilation (CMEMS - Copernicus Marine Environment Monitoring Service). Sensitivity tests were run to determine whether hourly or daily forcing resulted in significantly different particle end locations and validation simulations were run to compare with undrogued drifter tracks for the same period and region. All model output is stored in NetCDF files. This is data to accompany a manuscript submitted to Ocean Science entitled ‘Monsoonal influence on floating marine litter pathways in the Bay of Bengal’ (Preprint: `EGUsphere - Monsoonal influence on floating marine litter pathways in the Bay of Bengal`_). These experiments aimed to determine source-to-sink connectivity between countries surrounding the Bay of Bengal. .. _`egusphere - monsoonal influence on floating marine litter pathways in the bay of bengal`: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3096/
Data holder:
Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS)
| Other details | ||
| Internal code | Internally assigned metadata identifier | 11059 |
| Title | The title is used to provide a brief and precise description of the dataset such as 'Date', 'Originating organisation/programme', 'Location' and 'Type of survey'. All acronyms and abbreviations should be reproduced in full. | Particle tracking model output simulating floating marine litter in the Bay of Bengal, 2018 to 2019 |
| File Identifier | The File Identifier is a code, preferably a GUID, that is globally unique and remains with the same metadata record even if the record is edited or transferred between portals or tools. | CEFASee9b441a-b04d-4013-92fe-56f5eab85b2f |
| Resource Identifier | This is the code assigned by the data owner. | CEFAS22047 |
| Resource type | The resource type will likely be a dataset but could also be a series (collection of datasets with a common specification) or a service. | dataset |
| Start date | This describes the date the resource starts. This may only be the year if month and day are not known | 2018-06-01 |
| End date | This describes the date the resource ends. This may only be the year if month and day are not known | 2019-09-30 |
| Frequency of updates | This describes the frequency with which the resource is modified or updated i.e. a monitoring programme that samples once per year has a frequency that is described as 'annually'. | notPlanned |
| Abstract | The abstract provides a clear and brief statement of the content of the resource. | These data are particle positions and dates/times which are output from an OceanParcels particle tracking model simulating likely pathways of floating marine macro-litter in the Bay of Bengal between 1st June 208 – 30th September 2019, saved as NetCDF files. The model incorporated advection due to ocean, wind, and Stokes drift velocities, horizontal diffusion, and particle beaching behaviours. Two different hydrodynamic data sets were used to force the particles’ trajectories: a high-resolution ocean velocity hindcast (ROMS – Regional Oceanic Modelling System) and a lower-resolution dataset which included data assimilation (CMEMS - Copernicus Marine Environment Monitoring Service). Sensitivity tests were run to determine whether hourly or daily forcing resulted in significantly different particle end locations and validation simulations were run to compare with undrogued drifter tracks for the same period and region. All model output is stored in NetCDF files. This is data to accompany a manuscript submitted to Ocean Science entitled ‘Monsoonal influence on floating marine litter pathways in the Bay of Bengal’ (Preprint: `EGUsphere - Monsoonal influence on floating marine litter pathways in the Bay of Bengal`_). These experiments aimed to determine source-to-sink connectivity between countries surrounding the Bay of Bengal. .. _`egusphere - monsoonal influence on floating marine litter pathways in the bay of bengal`: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3096/ |
| Lineage | Lineage includes the background information, history of the sources of data, data quality statements and methods. | The transport of marine litter was modelled using the OceanParcels v2.3.1 Lagrangian particle tracking model (Delandmeter and van Sebille, 2019; Lange and van Sebille, 2017). The model includes several processes which influence the movement of floating, buoyant particles around the domain. Advection of particles via surface ocean currents (detailed below) was included using an inbuilt OceanParcels kernel which uses a fourth-order Runge-Kutta advection scheme. Stokes drift velocities were added to surface currents to account for the movement of particles resulting from wave motions. To account for sub-grid scale processes, diffusion is implemented as a random walk, with a diffusion coefficient of 100 m2/s, chosen based on grid cell size (Peliz et al., 2007), as detailed below. Windage is implemented in the model by applying 1% of the wind velocity to the particles’ trajectories, following analysis of observations of the wind’s effect on drifters by Pereiro et al. (2018), which should account for all but very large items of litter. The final process implemented here was beaching. At the end of each timestep, after advancing each particle’s position, ocean velocities were checked at this new position. If the velocity was less than 10-14 m/s, the particle was considered to be beached (after Delandmeter and van Sebille (2019)) and was no longer tracked. There is no resuspension of particles that have beached; the beached location is considered the final sink location. The advection of particles depends on surface ocean currents taken from two different models which were used to evaluate the transport of particles and help quantify uncertainty in the results. The NEMO-based CMEMS Global Ocean Physics Analysis and Forecast hydrodynamic model (E.U. Copernicus Marine Service Information (CMEMS), Marine Data Store (MDS), 2022a) has a resolution of 1/12°, which is roughly 9.2 km at the latitudes of the Bay of Bengal, and includes data assimilation (Lellouche et al., 2018). Also included was the ROMS-based high-resolution model, configured for the North Indian Ocean as a part of the High-Resolution Operational Ocean Forecast and Reanalysis System (known as NIO-HOOFS) by INCOIS for the Indian Ocean (Francis et al., 2020), which has a much higher resolution of 1/48°, corresponding to approximately 2.3 km at these latitudes, but does not include data assimilation. Additional datasets from CMEMS Global Ocean Wave Analysis and Forecasting model (Ardhuin et al., 2010; E.U. Copernicus Marine Service Information (CMEMS). Marine Data Store (MDS), 2022b) and ERA5 global atmospheric reanalysis (Hersbach et al., 2023) were used to provide Stokes drift velocities and wind fields at a height of 10 m above land, respectively. Particle release locations were uniformly spaced around all major coastlines in the Bay of Bengal. Particles were released on average 6 km from the coastline, with a maximum distance of 18 km in some locations. A particle was released from each of the 500 coastal locations every day for a year, with 182,500 particles released in total. Model simulations covered 1st June 2018 – 30th September 2019 for each case (CMEMS and ROMS). Following some sensitivity tests detailed below, particles were forced with daily-mean ocean, Stokes drift, and wind velocities. A model time step of 15 minutes was used (following Delandmeter and van Sebille (2019)) and particle positions were output daily. We ran separate simulations for each season, with particles released over a season-specific, four-month period: monsoon = 1st June – 30th September 2018; post-monsoon = 1st October 2018 – 31st January 2019; pre-monsoon = 1st February – 30th May 2019 (Anoop et al., 2015). Regardless of the release period, all particles were tracked until the end of September 2019. To assess model performance, the simulated trajectories of floating litter were compared with paths of drifters which had lost their drogues in the Bay of Bengal between June 2018 – September 2019. Within the Global Drifter Program’s quality-controlled 6-hour interpolated dataset (Lumpkin and Centurioni, 2019), five drifters were identified that met these criteria within the spatial and temporal limits of the model. As the separation between the particles and drifter location is expected to increase with time (Tamtare et al., 2021), each drifter trajectory was separated into week-long segments. CMEMS and ROMS simulations were run, using the same input data and parameters described for the main simulations. Starting at midday on the first full day after each drifter lost its drogue, 100 particles were released at the same location as the drifter. For each subsequent week, a further 100 particles were released from the location of the drifter at that time. Each particle was then followed for one week to compare to the relevant drifter trajectory during that time. To decide the required temporal resolution necessary to simulate particle trajectories across the Bay of Bengal, simulations were run to test the sensitivity of sink locations to temporal forcing. Simulations were forced with either CMEMS or ROMS hydrodynamic forcing at either hourly or daily temporal resolution. All four simulations used the same parameters as well as wind and Stokes drift data as detailed above and were run for the month of July 2020 with particles released for the first two weeks only. This study has been conducted using E.U. Copernicus Marine Service Information: `10.48670/moi-00016``10.48670/moi-00017` Anoop, T. R., Kumar, V. S., Shanas, P. R., and Johnson, G.: Surface Wave Climatology and Its Variability in the North Indian Ocean Based on ERA-Interim Reanalysis, Journal of Atmospheric and Oceanic Technology, 32, 1372–1385, `https://doi.org/10.1175/JTECH-D-14-00212.1`_, 2015. Ardhuin, F., Rogers, E., Babanin, A. V., Filipot, J.-F., Magne, R., Roland, A., Westhuysen, A. van der, Queffeulou, P., Lefevre, J.-M., Aouf, L., and Collard, F.: Semiempirical Dissipation Source Functions for Ocean Waves. Part I: Definition, Calibration, and Validation, Journal of Physical Oceanography, 40, 1917–1941, `https://doi.org/10.1175/2010JPO4324.1`_, 2010. Delandmeter, P. and van Sebille, E.: The Parcels v2.0 Lagrangian framework: new field interpolation schemes, Geoscientific Model Development, 12, 3571–3584, `https://doi.org/10.5194/gmd-12-3571-2019`_, 2019. Francis, P. A., Jithin, A. K., Effy, J. B., Chatterjee, A., Chakraborty, K., Paul, A., Balaji, B., Shenoi, S. S. C., Biswamoy, P., Mukherjee, A., Singh, P., Deepsankar, B., Reddy, S. S., Vinayachandran, P. N., Kumar, M. S. G., Bhaskar, T. V. S. U., Ravichandran, M., Unnikrishnan, A. S., Shankar, D., Prakash, A., Aparna, S. G., Harikumar, R., Kaviyazhahu, K., Suprit, K., Shesu, R. V., Kumar, N. K., Rao, N. S., Annapurnaiah, K., Venkatesan, R., Rao, A. S., Rajagopal, E. N., Prasad, V. S., Gupta, M. D., Nair, T. M. B., Rao, E. P. R., and Satyanarayana, B. V.: High-Resolution Operational Ocean Forecast and Reanalysis System for the Indian Ocean, Bulletin of the American Meteorological Society, 101, E1340–E1356, `https://doi.org/10.1175/BAMS-D-19-0083.1`_, 2020. Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), `https://doi.org/10.24381/cds.adbb2d47`_, 2023. Lange, M. and van Sebille, E.: Parcels v0.9: prototyping a Lagrangian ocean analysis framework for the petascale age, Geoscientific Model Development, 10, 4175–4186, `https://doi.org/10.5194/gmd-10-4175-2017`_, 2017. Lellouche, J.-M., Greiner, E., Le Galloudec, O., Garric, G., Regnier, C., Drevillon, M., Benkiran, M., Testut, C.-E., Bourdalle-Badie, R., Gasparin, F., Hernandez, O., Levier, B., Drillet, Y., Remy, E., and Le Traon, P.-Y.: Recent updates to the Copernicus Marine Service global ocean monitoring and forecasting real-time 1/12° high-resolution system, Ocean Science, 14, 1093–1126, `https://doi.org/10.5194/os-14-1093-2018`_, 2018. Lumpkin, R. and Centurioni, L.: Global Drifter Program quality-controlled 6-hour interpolated data from ocean surface drifting buoys. June 2018-September 2019. NOAA National Centers for Environmental Information. [Dataset.] `https://doi.org/10.25921/7ntx-z961`_, 2019, (Accessed 07 July 2023). Peliz, A., Marchesiello, P., Dubert, J., Marta-Almeida, M., Roy, C., and Queiroga, H.: A study of crab larvae dispersal on the Western Iberian Shelf: Physical processes, Journal of Marine Systems, 68, 215–236, `https://doi.org/10.1016/j.jmarsys.2006.11.007`_, 2007. Pereiro, D., Souto, C., and Gago, J.: Calibration of a marine floating litter transport model, Journal of Operational Oceanography, 11, 125–133, `https://doi.org/10.1080/1755876X.2018.1470892`_, 2018. Tamtare, T., Dumont, D., and Chavanne, C.: Extrapolating Eulerian ocean currents for improving surface drift forecasts, Journal of Operational Oceanography, 14, 71–85, `https://doi.org/10.1080/1755876X.2019.1661564`_, 2021. .. _`10.48670/moi-00016`: https://data.marine.copernicus.eu/product/GLOBALANALYSISFORECASTPHY001024/description .. _`10.48670/moi-00017`: https://data.marine.copernicus.eu/product/GLOBALANALYSISFORECASTWAV001027/description .. _`https://doi.org/10.1175/jtech-d-14-00212.1`: https://journals.ametsoc.org/view/journals/atot/32/7/jtech-d-14-00212_1.xml .. _`https://doi.org/10.1175/2010jpo4324.1`: https://doi.org/10.1175/2010JPO4324.1 .. _`https://doi.org/10.5194/gmd-12-3571-2019`: https://doi.org/10.5194/gmd-12-3571-2019 .. _`https://doi.org/10.1175/bams-d-19-0083.1`: https://doi.org/10.1175/BAMS-D-19-0083.1 .. _`https://doi.org/10.24381/cds.adbb2d47`: https://doi.org/10.24381/cds.adbb2d47 .. _`https://doi.org/10.5194/gmd-10-4175-2017`: https://doi.org/10.5194/gmd-10-4175-2017 .. _`https://doi.org/10.5194/os-14-1093-2018`: https://doi.org/10.5194/os-14-1093-2018 .. _`https://doi.org/10.25921/7ntx-z961`: https://doi.org/10.25921/7ntx-z961 .. _`https://doi.org/10.1016/j.jmarsys.2006.11.007`: https://doi.org/10.1016/j.jmarsys.2006.11.007 .. _`https://doi.org/10.1080/1755876x.2018.1470892`: https://doi.org/10.1080/1755876X.2018.1470892 .. _`https://doi.org/10.1080/1755876x.2019.1661564`: https://doi.org/10.1080/1755876X.2019.1661564 |
| Related keywords | ||
| Keyword | General subject area(s) associated with the resource, uses multiple controlled vocabularies | Modelling |
| General subject area(s) associated with the resource, uses multiple controlled vocabularies | Season | |
| General subject area(s) associated with the resource, uses multiple controlled vocabularies | Oceanographic geographical features | |
| General subject area(s) associated with the resource, uses multiple controlled vocabularies | Habitats and biotopes | |
| General subject area(s) associated with the resource, uses multiple controlled vocabularies | Unknown | |
| General subject area(s) associated with the resource, uses multiple controlled vocabularies | Marine Environmental Data and Information Network | |
| General subject area(s) associated with the resource, uses multiple controlled vocabularies | data.gov.uk | |
| Geographical coverage | ||
| North | The northern-most limit of the data resource in decimal degrees | 30 |
| East | The eastern-most limit of the data resource in decimal degrees | 110 |
| West | The western-most limit of the data resource in decimal degrees | 70 |
| Responsible organisations | ||
| Role | The point of contact is person or organisation with responsibility for the creation and maintenance of the metadata for the resource. | pointOfContact |
| Organisation name | Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) | |
| Delivery point | Cefas Lowestoft Laboratory, Pakefield Road | |
| Postal code | NR33 0HT | |
| City | Lowestoft | |
| Administrative area | Suffolk | |
| Country | UK | |
| data.manager@cefas.co.uk | ||
| Role | The originator is the person or organisation who created, collected or produced the resource. | originator |
| Organisation name | Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) | |
| Delivery point | Cefas Lowestoft Laboratory, Pakefield Road | |
| Postal code | NR33 0HT | |
| City | Lowestoft | |
| Administrative area | Suffolk | |
| Country | UK | |
| data.manager@cefas.co.uk | ||
| Role | The custodian is the person or organisation that accepts responsibility for the resource and ensures appropriate care and maintenance. If a dataset has been lodged with a Data Archive Centre for maintenance then this organisation is be entered here. | custodian |
| Organisation name | Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) | |
| Delivery point | Cefas Lowestoft Laboratory, Pakefield Road | |
| Postal code | NR33 0HT | |
| City | Lowestoft | |
| Administrative area | Suffolk | |
| Country | UK | |
| data.manager@cefas.co.uk | ||
| Role | The distributor is the person or organisation that distributes the resource. | distributor |
| Organisation name | Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS) | |
| Delivery point | Cefas Lowestoft Laboratory, Pakefield Road | |
| Postal code | NR33 0HT | |
| City | Lowestoft | |
| Administrative area | Suffolk | |
| Country | UK | |
| data.manager@cefas.co.uk | ||
| Role | The owner is the person or organisation that owns the resource. | owner |
| Organisation name | Department for Environment, Food and Rural Affairs (DEFRA) | |
| defra.helpline@defra.gov.uk | ||
| Resource locators | ||
| Locator URL | Web address (URL) that links to the resource | https://data.cefas.co.uk/view/22047 |
| Locator name | Name of the web resource | Cefas Data Portal |
| Dataset constraints | ||
| 20.1 Limitations on Public Access - Access constraints | This states `otherRestrictions` from ISO vocabulary RestrictionCode and is an INSPIRE/GEMINI requirement. | otherRestrictions |
| 20.2 Limitations on Public Access - Other constraints | noLimitations | |
| 21.1 Conditions for Access and Use - Use constraints | This states `otherRestrictions` from ISO vocabulary RestrictionCode and is an INSPIRE/GEMINI requirement. | otherRestrictions |
| 21.2 Conditions for Access and Use - Other constraints | https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ | |
| Version info | ||
| Date of publication | The publication date of the resource or if previously unpublished the date that the resource was made publicly available via the MEDIN network. | 2024-10-02 |
| Date of last revision | The most recent date that the resource was revised. | 2025-09-25 |
| Date of creation | The date that the resource was created. | 2024-09-25 |
| Harvest date | The date which this record has been (re)harvested from the provider. | 2026-04-12 |
| Metadata date | The date when the content of this metadata record was last updated. | 2025-09-25 |
| Metadata standard name | The name of the metadata standard used to create this metadata | MEDIN |
| Metadata standard version | The version of the MEDIN Discovery Metadata Standard used to create the metadata record | 3.1.1 |