This dataset contains raw beaching data computed by marine debris simulations (run using OceanParcels) for a range of physical scenarios (surface currents from GLORYS12V1 (https://doi.org/10.3389/feart.2021.698876), Stokes drift from WAVERYS (https://doi.org/10.1007/s10236-020-01433-w), and surface winds from ERA5 (https://doi.org/10.1002/qj.3803)), as described in the accompanying manuscript. Through postprocessing, debris ‘connectivity’ matrices can be computed, providing predictions for the main terrestrial and marine source regions of plastic debris accumulating at remote islands in the western Indian Ocean. These simulations include beaching and sinking processes, and a set of example matrices is provided here (https://doi.org/10.5287/bodleian:DEdqwXZQw). However, these matrices can be recomputed for different sinking and beaching rates using the scripts archived here (https://doi.org/10.5281/zenodo.7351695), or see here (https://github.com/nvogtvincent/WIO_Marine_Debris/) for the live version with documentation. These predictions will be useful for environmental practitioners in the western Indian Ocean to assess source regions for marine debris accumulating at islands of interest, and when this debris is likely to beach. The data were produced as part of the Marine Dispersal and Retention in the Western Indian Ocean project funded by the Natural Environment Research Council (NERC) grant NE/S007474/1. See linked online references on this record for cited items given above.

A colour LiDAR (Light Detection And Ranging) dataset was obtained at the cliffs at Happisburgh, Norfolk, UK, over a period of 9 months (April 6, 2019 to December 23, 2019). The scans were taken daily for 90% of the study period using a FARO S350 TLS (Terrestrial LiDAR Scanner). Scans were carried out from two locations consecutively, positioned at around 40 m from the cliffs. The full scans are also split into smaller subsets: "slices", 1 m wide bands oriented perpendicular to the shoreline, and "grids", smaller areas of the beach, to assist analysis. The numerical model SWAN (Simulated Waves Nearshore) (v41.31a), run in non-stationary mode, was used to simulate hourly sea states at the study site to aid in the context of environmental conditions. Wind parameters from the ERA5 reanalysis and bathymetry from the OceanWise 1 arc second digital elevation model (DEM) were used to force the SWAN model, and obtained wave parameters in 4x6 km rectangular grid around the scanning site, with a 10m interval, and a 26x26 km square grid encompassing the smaller grid, with a 100 m interval. The LiDAR scans were also projected into both colour and intensity images, viewing the shoreline from above. This research was funded by the UK Natural Environment Research Council (NE/M004996/1; BLUE-coast project). The on-location LiDAR Scanning and Technical R&D operated by ScanLAB Projects Ltd was funded by Innovate UK's Audience of the Future Program (Multiscale 3D Scanning with Framerate for TV and Immersive Applications project). The first 6 months of LiDAR scans (April to September 2019) were funded by Innovate UK, and this project was continued by the NERC BLUE-coast funding for the last 3 months (October to December 2019).

The Global Sea Level Observing System (GLOSS) is an international programme co-ordinated by the Intergovernmental Oceanographic Commission (IOC) for the establishment of high quality global and regional sea level networks for application to climate, oceanographic and coastal sea level research. The programme became known as GLOSS as it provides data for deriving the "Global Level Of the Sea Surface"; a smooth level after averaging out waves, tides and short-period meteorological events. The main component of GLOSS is the Global Core Network (GCN) of 308 sea level stations around the world, which are maintained by 87 countries. The GLOSS network has been designed to observe large-scale sea level variations of global implications, and stations were identified at intervals of approximately 1000 km along the continental coasts and on islands, but generally not closer than 500 km. In selecting individual sites, priority is given to gauges which have been functioning for a long period. All gauges are required to aim for an accuracy of 10 mm in level, and 1 minute in time. All must be linked to bench marks against which their datum is checked regularly. This network monitors sea level changes which could be indicative of global warming, ocean circulation patterns, climate variability, etc., and contributes data to global climate research within the World Climate Research Programme (WCRP) including the Tropical Ocean-Global Atmosphere (TOGA) project, the World Ocean Circulation Experiment (WOCE), Climate Variability and Predictability (CLIVAR) and recent vertical crustal movement studies conducted by the International Union of Geodesy and Geophysics (IUGG) of the International Council of Scientific Unions (ICSU) and UNESCO (International Geological Correlation Programme (IGCP)). It also provides high quality data for practical applications of national importance. The measurements by GLOSS gauges complement satellite altimetry measurements. GLOSS is considered as an important potential element of the Global Ocean Observing System (GOOS) initiated by IOC with the World Meteorological Organisation (WMO), the UN Environmental Programme (UNEP) and ICSU. The elements of GLOSS are: A global network of permanent sea level stations to obtain standardised sea level observations; this forms the primary network to which regional and national sea level networks can be related; Data collection for international exchange with unified formats and standard procedures which includes both near-real-time as well as delayed mode data collection; Data analysis and product preparation for scientific and/or practical applications; Assistance and training for establishing and maintaining sea level stations as part of GLOSS and improving national sea level networks; A selected set of GLOSS tide-gauge bench marks accurately connected to a global geodetic reference system (i.e. the conventional terrestrial frame established by the International Earth Rotation Service). The Permanent Service for Mean Sea Level (PSMSL) collects and archives data from GLOSS stations in the form of monthly mean values, but hourly and daily values are also expected to be made available from all stations by the originators. The GLOSS network consists of 308 sea level stations, which are operated and maintained by 87 countries.