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.

Time-mean Sea Level Projections for the UK produced by the Met Office for UK Climate Projections 2018 (UKCP2018). Data has been produced by standard and exploratory methods.

The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 historical simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 1970 to 2005, and applies to the UK coast.

The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 RCP8.5 simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 2007 to 2099, and applies to the UK coast.

Historical and future simulations of sea surface elevation for UK waters for 1970-2100 produced by the Met Office for UK Climate Projections 2018 (UKCP2018). The data is available at hourly temporal resolution.

MarQUEST was led by Prof Andrew Watson (UEA), with 15 co-investigators at UEA/BAS, the Universities of Southampton, Essex, and Reading, and from the Plymouth Marine Laboratory and Proudman Oceanographic Laboratory. This dataset collection contains ocean optical, chemical and plankton model measurements from SeaWiFS/SeaStar Level 3 products. MarQUEST developed new methods of validating ocean biogeochemistry models, making use of remote sensing ocean colour data, in situ data sets and ongoing observations from the major European programmes CarboOcean and EUR-OCEANS. In the past, ocean biogeochemical models represented biological processes in very simple or rigid ways (e.g., single nutrient limitation, a single generic primary producer), limiting understanding of the role of ecosystems in the climate system. Increasing the complexity of models has presented new challenges for their validation; it is also not clear what the ‘optimal’ complexity of a model should be for any given real-world problem. QUEST scientists cooperated in comparing various models, and examining more fundamental (physiological) approaches to understanding the planktonic ecoystem. MarQUEST also developed a module to simulate coastal ecosystems usable in global ocean biogeochemical simulations. Finally, the project team generated an accurate physical simulation of the North Atlantic guided by data assimilation, into which ecosystem simulations can be embedded. This allows the variation in air-sea fluxes of gases (CO2, oxygen and dimethyl sulphide) from ocean to atmosphere to be quantified for the contemporary period.

Short event case studies for UK waters produced by the Met Office for UK Climate Projections 2018 (UKCP2018). Data is available at 6-minute and 15-minute temporal resolution.

MarQUEST was led by Prof Andrew Watson (UEA), with 15 co-investigators at UEA/BAS, the Universities of Southampton, Essex, and Reading, and from the Plymouth Marine Laboratory and Proudman Oceanographic Laboratory. This dataset contains monthly inherent optical absorption properties for 1998-2007 calculated from SeaWiFS/SeaStar Level 3 products. QUEST scientists cooperated in comparing various models, and examining more fundamental (physiological) approaches to understanding the planktonic ecoystem. MarQUEST also developed a module to simulate coastal ecosystems, usable in global ocean biogeochemical simulations. Finally, the project team generated an accurate physical simulation of the North Atlantic guided by data assimilation, into which ecosystem simulations can be embedded. This allows the variation in air-sea fluxes of gases (CO2, oxygen and dimethyl sulphide) from ocean to atmosphere to be quantified for the contemporary period. This data was produced by Takafumi Hirata, Plymouth Marine Laboratory, Plymouth, UK as part of NERC Programmes: Centre for the observation of Air-Sea Interaction and fluXes (CASIX), National Centre for Earth Observation (NCEO) and Quantifying and Understanding the Earth System (QUEST).

The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 RCP8.5 simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 2007 to 2099, and applies to the UK coast.

The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone. The data were produced by the Met Office Hadley Centre. The data were produced to investigate the impact of simulated mean sea level increase on UK coastal tides. To produce the data, the CS3 continental shelf model was used to simulate the tides under various different amounts of mean sea level increase (simulated by simply increasing the bathymetry). The data are the resulting simulated sea surface elevations above the mean sea level. The data covers a period of about 28 days (one spring-neap cycle), and applies to the UK coast.