Result List
Get a list of Result objects. Results have a 1:1 mapping with Observations.
GET /api/v3/results/?format=api&offset=10900
{ "count": 11555, "next": "https://api.catalogue.ceda.ac.uk/api/v3/results/?format=api&limit=100&offset=11000", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/results/?format=api&limit=100&offset=10800", "results": [ { "ob_id": 43319, "uuid": "7d5a23b3efa744d699c5a779795ddfc3", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/desnz-cs-now/data/gridded-proj-river-flows", "numberOfFiles": 3195, "volume": 420233173964, "fileFormat": "NetCDF and BADC-CSV", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 41555, "uuid": "cf66055440344d7eb9b6f834e81736c6", "short_code": "ob", "title": "CS-NOW: Gridded future projections of natural and artificially influenced river flows (1980 to 2080)", "abstract": "The Grid-to-Grid (G2G) river flow model projections comprise an ensemble of natural and artificially influenced (AI) estimates of daily mean river flows (m3s-1). These flow projections are for a historical and future period spanning 1st December 1980 to 30th November 2080 and reflect scenarios of change in both climate and artificial (anthropogenic) influences (abstractions and discharges).\r\nThe historical and future projections are available in two formats: \r\n(i) 1 km × 1 km gridded daily mean river flows (m3s-1) for two spatial regions: Natural river flows across Great Britain, and Artificially influenced river flows across England\r\n(ii) Time series of daily flows for 626 catchments across England\r\nThe climate projections consist of an ensemble of bias-corrected UKCP18 Regional Climate Model (RCM) output. A further 4 hydrological connectivity datasets provide flow directions, upstream areas and coastal/gauged locations. Further details are provided in a linked Data Document.\r\n\r\n Three future scenarios of artificial influences are considered: \r\n(a) Sustainability (SUS), \r\n(b) Business as usual (BAU) and \r\n(c) Economic Growth (EG). \r\n\r\nThe dataset is an output from the CS-NOW project (Climate services for a Net Zero resilient world - GOV.UK (www.gov.uk)) commissioned by the UK Department for Energy Security and Net Zero (DESNZ). Publication of these data is also supported by the Natural Environment Research Council award number NE/X019063/1 as part of the Hydro-JULES programme delivering National Capability." }, "onlineresource_set": [] }, { "ob_id": 43320, "uuid": "e17b59ef813f4b51a6a81274a060b698", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/desnz-cs-now/data/gridded-actual-flows", "numberOfFiles": 13, "volume": 166445191, "fileFormat": "NetCDF and BADC-CSV", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43175, "uuid": "18886f95ba84447f997efac96df456ad", "short_code": "ob", "title": "Gridded actual groundwater, surface water and tidal water abstraction, discharge and Hands-off Flow datasets for England (1999 to 2014)", "abstract": "This dataset contains recorded or ‘actual’ abstraction and discharge data for sites across England that have been transformed into 1 km × 1 km resolution gridded data along with surface water Hands-off Flow (HoF) conditions, and are available in CSV and/or NetCDF formats. It includes:\r\n \r\n(i)\tMonthly abstractions (m3 month-1) from 1999 to 2014 for each source (Groundwater, Surface Water or Tidal Water)\r\n(ii)\tMean monthly abstractions (m3 month-1) over the period 2010 to 2014 for each source (Groundwater, Surface Water or Tidal Water)\r\n(iii)\tDaily rate of Consented Dry Weather flow (CDWF)and Recent Actual (RACT) discharges (m3 day-1) based on information from a 6-year period ending in 2017\r\n(iv)\tHands-off Flow (HoF) conditions (m3 day-1) for 2022\r\n\r\nFurther details, including caveats about usage, are provided in the linked Data Document.\r\n\r\nThese data were sourced from the Environment Agency (EA) monthly groundwater, surface water and tidal water abstraction data from 1999 to 2014, and annual discharges and surface water Hands-off Flow (HoF) conditions were obtained from the EA’s Water Resources Geographic Information System (WRGIS 2017 and 2022 versions respectively). \r\n\r\nThis data publication is supported by the Natural Environment Research Council award number NE/X019063/1 as part of the Hydro-JULES programme delivering National Capability. The dataset is also linked with the Climate Services for a Net Zero Resilient World (CS-N0W) project." }, "onlineresource_set": [] }, { "ob_id": 43350, "uuid": "907362199dbd4858af6a3535861d7499", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/eocis/data/global_and_regional/land_surface_temperature/SENTINEL3A_SLSTR/L3C/0.01/v4.00/daily/", "numberOfFiles": 6165, "volume": 3263133501777, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43087, "uuid": "a784eeb9287b43bcb63ccae59e6af82e", "short_code": "ob", "title": "EOCIS: Daily land surface temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3A, level 3 collated (L3C) global product, version 4.00", "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3A. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel-3A equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. SLSTRA achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 1st May 2016 and continues until 31st December 2024. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the UK Earth Observation Climate Information Service (EOCIS) and is based on development funded under ESA CCI with additional funding from NCEO. The EOCIS dataset includes and continues the CCI v4 CDR (currently under development)." }, "onlineresource_set": [] }, { "ob_id": 43351, "uuid": "339e76c757614a038fc4ff6b32018b74", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/eocis/data/global_and_regional/land_surface_temperature/SENTINEL3B_SLSTR/L3C/0.01/v4.00/daily/", "numberOfFiles": 4395, "volume": 2291469072425, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43088, "uuid": "fc0bc3d5887d441296091a8025f8f45d", "short_code": "ob", "title": "EOCIS: Daily land Surface Temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3B, level 3 collated (L3C) global product , version 4.00", "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3B. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel 3B equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. SLSTRB achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 17th November 2018 and continues until 31st December 2024. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the UK Earth Observation Climate Information Service (EOCIS) and is based on development funded under ESA CCI with additional funding from NCEO. The EOCIS dataset includes and continues the CCI v4 CDR (currently under development)." }, "onlineresource_set": [] }, { "ob_id": 43352, "uuid": "cecfa0ace0394f24bd95bf678ff00e1d", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2024/Flight-Matched-Contrails", "numberOfFiles": 21, "volume": 40082084, "fileFormat": ".csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43238, "uuid": "f45a1a95ddcc480784640da6f3001904", "short_code": "ob", "title": "Flight matched contrails in ground based camera imagery over London between November 2021 and April 2022", "abstract": "This dataset provides aircraft flight path information and ground-based camera imagery to support the evaluation of models of contrail formation and persistence. \r\n\r\nCamera imagery and corresponding flight path information were collected for 5 separate days where contrail formation was identified over London between November 2021 and April 2022, leading to 16 hours of observation. The camera observations were made every 5 seconds, looking to the East of Imperial College London (where the camera was based).\r\n\r\nThis dataset contains flight path telemetry data used to derive aircraft trajectories intersecting the camera's field of view." }, "onlineresource_set": [] }, { "ob_id": 43353, "uuid": "f69e298f69eb48e7a2eb9c0a51e43970", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/deposits01/soc240662", "numberOfFiles": 7002, "volume": 30799081980, "fileFormat": "JPG", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43355, "uuid": "4bfed57aaa324847b5df139b7114e32c", "short_code": "ob", "title": "Benthic images collected by Remotely Operated Vehicle during expedition JC241 in the UK-1 area of the Clarion-Clipperton Zone, Pacific Ocean, 2023", "abstract": "A collection of 7000 benthic still images was obtained using a downward-looking camera mounted on the UK ISIS Remotely Operated Vehicle (ROV), dive 413, deployed from RRS James Cook during cruise JC241 in the abyssal plain (~4100 m depth) of the northern part of the UK-1 exploration area of the Clarion-Clipperton Zone, Pacific Ocean, in 2023. The ROV was piloted to survey the seafloor across seven 2 km transect lines. The Grasshopper2 GS2-GE-50S5C camera system mounted on the ROV collected downward-looking still images at a target altitude of 3 m above the seabed. Images were colour corrected to enhance visual fidelity based on known sediment and nodule colours and converted from original 8-bit RAW to JPG images. Overlap among images was removed based on automated computer vision, and was later validated with human verification of overlap between successive images. The image set was subsequently annotated using the online platform BIIGLE (Bio-Image Indexing and Graphical Labelling Environment) to derive ecological understanding on seabed community composition under natural dynamics. The data were collected by scientists from the National Oceanography Centre, Southampton, UK as part of the NERC-funded Seabed Mining And Resilience To EXperimental impact (SMARTEX) project (NE/T003537/1)." }, "onlineresource_set": [] }, { "ob_id": 43354, "uuid": "e73c3d23593f40b5b9525d747f1ba973", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/deposits01/soc240663", "numberOfFiles": 1829, "volume": 6343823700, "fileFormat": "JPG", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43356, "uuid": "38b8f36f312549f88a4b0faa72d6a15b", "short_code": "ob", "title": "Benthic images collected by Autonomous Underwater Vehicle during expedition JC257 in the UK-1 area of the Clarion-Clipperton Zone, Pacific Ocean, 2024", "abstract": "A collection of 1828 benthic still images was obtained using a downward-looking camera mounted on the UK Autosub5 Autonomous Underwater Vehicle (AUV), mission number: AS5M091, deployed from RRS James Cook during cruise JC257 in the abyssal plain (~4100 m depth) of northern part of the UK-1 exploration area of the Clarion-Clipperton Zone, Pacific Ocean, in 2024. The AUV was programmed to replicate five 2 km long transect lines that were previously surveyed in 2023 during cruise JC241 using the UK ISIS Remotely Operated Vehicle (ROV). The Grasshopper2 GS2-GE-50S5C camera mounted on the AUV collected downward-looking still images at a target altitude of 3 m above the seabed, with one image being captured per second. These images were colour corrected to enhance visual fidelity and converted from original 8-bit RAW to JPG images. The final image set was inspected for overlap, which was non-existent. The image set was subsequently annotated using the online platform BIIGLE (Bio-Image Indexing and Graphical Labelling Environment) to derive ecological understanding on seabed community composition under natural dynamics. The data were collected by scientists from the National Oceanography Centre, Southampton, UK as part of the NERC-funded Seabed Mining And Resilience To EXperimental impact (SMARTEX) project (NE/T003537/1)." }, "onlineresource_set": [] }, { "ob_id": 43375, "uuid": "2eace8364f0b4e16a72d671da1ef1c15", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2025/UM_water_tracer_precip", "numberOfFiles": 2, "volume": 10195197, "fileFormat": "Data is NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43217, "uuid": "10ae416c4ccb4a90bdb5da0bbf68d4f9", "short_code": "ob", "title": "Water tracer precipitation output from the Met Office Unified Model (GAL9.0) for 1985-2014", "abstract": "This dataset contains global water tracer precipitation from a historical simulation of the Met Office Unified Model (UM) for the 30 year period, 1985 to 2014. The water tracer data can be used to track the source evaporative properties of the model's precipitation and is used in the following paper:\r\n\r\nMcLaren, A. J., Sime, L. C., Wilson, S., Ridley, J., Gao, Q., Gorguner, M., Line, G., Werner, M., and Valdes, P.: Implementation of water tracers in the Met Office Unified Model, Geosci. Model Dev., 18, 8129-8142, https://doi.org/10.5194/gmd-18-8129-2025, 2025.\r\n\r\nThe simulation is atmosphere only, with prescribed sea surface temperature and sea ice starting in 1979. The ‘N96’ horizontal resolution version of the UM is used which has 192 longitude points by 144 latitude points, with a mid-latitude resolution of 135km. There are 85 vertical levels with 50 levels below 18km and a fixed model lid at 85km above sea level. The scientific configuration is GAL9.0 and the UM version is 13.3. \r\n\r\nIn the dataset, the different water tracers have an associated 'water tracer number'. These are:\r\n1 = Total precipitation\r\n2 = Precipitation that has been sourced from Northern Hemisphere (NH) sea ice sublimation\r\n3 = Precipitation that has been sourced from Southern Hemisphere (SH) sea ice sublimation\r\n4 = Precipitation that has been sourced from NH open ocean evaporation\r\n5 = Precipitation that has been sourced from SH open ocean evaporation\r\n6 = Precipitation that has been sourced from NH land evapotranspiration\r\n7 = Precipitation that has been sourced from SH (north of 60S) land evapotranspiration\r\n8 = Precipitation that has been sourced from SH (south of 60S) land evapotranspiration\r\n9-23 = Scaled flux water tracer precipitation (see McLaren et al. 2025 for details)\r\nThese are fully documented in McLaren et al. (2025). \r\nGlobal climatological seasonal means for the 30 year period, 1985 - 2014, are provided." }, "onlineresource_set": [] }, { "ob_id": 43376, "uuid": "7e88bffd19be430a953139414f69a7f1", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2020/vol-clim/Marshall_et_al_2024", "numberOfFiles": 14, "volume": 20462394, "fileFormat": "Data are NetCDF and CSV formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43273, "uuid": "756571adbea845f3a78e75e2aef9d968", "short_code": "ob", "title": "Vol-Clim data for Marshall et al. 2024", "abstract": "Data from the Vol-Clim experiments as described in Marshall et al. 2024. This was collected as part of the NERC Reconciling Volcanic Forcing and Climate Records throughout the Last Millennium (Vol-Clim) project, which aims to resolve the discrepancy between climate model simulations and data on the magnitude of temperature changes caused by large-magnitude volcanic eruptions.\r\n\r\nThe 9 NetCDF files provide 10 years of zonal mean, monthly-mean 1.5m air temperature data and the top of atmosphere outgoing longwave and shortwave fluxes for 9 UKESM1.0 realisations. Additionally, the \"emissions\" files for the stated eruption years provide the Stratospheric Aerosol Optical Depth (SAOD) at 550nm.\r\n\r\nThe CSV files provide monthly-mean, global mean or northern-hemispheric mean data for UKESM1, CESM2 (WACCM6ma), MPI-ESM1-2-LR, MRI-ESM2, MIROC-ES2L, and IPSL-CM6A-LR. We provide SAOD at 550nm for UKESM, CESM2, and MRI, with all models providing 1.5 air temperature.\r\n\r\nMarshall, L. R., Schmidt, A., Schurer, A. P., Abraham, N. L., Lücke, L. J., Wilson, R., Anchukaitis, K., Hegerl, G., Johnson, B., Otto-Bliesner, B. L., Brady, E. C., Khodri, M., and Yoshida, K.: Last Millennium Volcanic Forcing and Climate Response using SO2 Emissions, EGUsphere, https://doi.org/10.5194/egusphere-2024-1322, 2024." }, "onlineresource_set": [] }, { "ob_id": 43380, "uuid": "29a0ea0d3004438f8c635eb3f98e21bf", "short_code": "result", "curationCategory": "B", "dataPath": "/neodc/aatsr_multimission/atsr2-v4/data/AT_1_RBT", "numberOfFiles": 71851, "volume": 31724639715529, "fileFormat": "ESA SAFE", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43344, "uuid": "dcad505a8203486e8a3b530a6dff00ca", "short_code": "ob", "title": "ATSR-2: Multimission land and sea surface temperature data. Fourth Reprocessing (v4) AT_1_RBT", "abstract": "The Along Track Scanning Radiometer2 (ATSR2) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThe ERS2 ATSR2 Level 1B Brightness Temperature/Radiance product (RBT) contains top of atmosphere (TOA) brightness temperature (BT) values for the infra-red channels and radiance values for the visible channels, on a 1-km pixel grid. Values for each channel and for the nadir and oblique views occupy separate NetCDF files within the Sentinel-SAFE format, along with associated uncertainty estimates. Additional files contain cloud flags, land and water masks, and confidence flags for each image pixel, as well as instrument and ancillary meteorological information.\r\n\r\nThis A/ATSR product [ENV_AT_1_RBT] in NetCDF format stemming from the 4th AATSR reprocessing, is a continuation of ERS ATSR data and a precursor of Sentinel-3 SLSTR data. It has replaced the former L1B product [ATS_TOA_1P] in Envisat format from the 3rd reprocessing. Users with Envisat-format products are recommended to move to the new Sentinel-SAFE like/NetCDF format products. \r\n\r\nThe 4th reprocessing of Envisat AATSR data was completed in 2022." }, "onlineresource_set": [] }, { "ob_id": 43390, "uuid": "8ca26363989944efa838db7a1f8015a3", "short_code": "result", "curationCategory": "", "dataPath": "/badc/name_nwp/data/global/UMG_Mk9/", "numberOfFiles": 151527, "volume": 4824673004321, "fileFormat": "Packed PP format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43389, "uuid": "2bb4d76ed2fa4fc2af3fbbca6eb80965", "short_code": "ob", "title": "Global NWP meteorological data for Met Office NAME dispersion model (Mk9: July 2015 - 2017)", "abstract": "This dataset contains Numerical Weather Prediction (NWP) global meteorological data produced by the Met Office Unified Model. The files in the dataset have been processed into a form suitable for use in the Met Office NAME (Numerical Atmospheric-dispersion Modelling Environment) dispersion model. NAME uses the Met Office Numerical Weather Prediction model outputs as its source for weather data to be able to predict movement of atmospheric parcels forwards and backwards in time.\r\n\r\nThe files contain a basic collection of model-level fields (3-d winds, temperature, etc.) and a selection of single-level fields including mean sea level pressure, cloud and precipitation. Fields are split into various geographical regions (referred to as \"parts\" or \"PTs\" in NAME) with separate files for each \"part\". Data are provided at 3-hourly resolution. All files are in packed PP format.\r\n\r\nThe NWP data used by NAME is different from other forms of Met Office NWP as follows:\r\n- It has been split into spatial partitions (i.e. different parts of the world/domain are in different files)\r\n- It has been reformatted into PP format\r\n\r\nHowever, from the perspective of the raw data, this dataset of global gridded NWP meteorological data is generically useful for a whole range of scientific research and applications." }, "onlineresource_set": [] }, { "ob_id": 43391, "uuid": "407b84b1f88b402eb61ebed09945cee3", "short_code": "result", "curationCategory": "", "dataPath": "/badc/nahosmip", "numberOfFiles": 742, "volume": 321590934226, "fileFormat": "Data are in gridded NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43305, "uuid": "07bc349e42f94117b83e6f8289834eb7", "short_code": "ob", "title": "North Atlantic Hosing Model Intercomparison Project (NAHosMIP) Data", "abstract": "This dataset contains output from 5 climate model experiments conducted as part of the North Atlantic Hosing Model Intercomparison Project. The experiments use idealised forcing, including adding hosing (additional surface fresh water) over the North Atlantic and Arctic. These experiments are:\r\n•\tu03-hos - constant uniform hosing of 0.3 Sv. \r\n•\tu03-r50 - experiment with no hosing initialised 50 years into u03-hos\r\n•\tu03-r70 - experiment with no hosing initialised 70 years into u03-hos\r\n•\tu03-r100 - experiment with no hosing initialised 100 years into u03-hos\r\n•\tg01-hos – hosing around Greenland of 0.1Sv\r\n\r\nEight CMIP6 global coupled climate models took part (note that only some have conducted u03-r70 and u03-r100). The data is presented in gridded netcdf format with the intention of providing standardised data following the CMIP6 data request and CF metadata convention. The equivalent data with no hosing is available from the preindustrial control simulations from the CMIP6 database" }, "onlineresource_set": [] }, { "ob_id": 43404, "uuid": "b68bf388fdc941c1bcf85187e0a278e9", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/malaysia/SEP-11/", "numberOfFiles": 620084, "volume": 955683556035, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archived document /neodc/forestscan/data/malaysia/SEP-11/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43405, "uuid": "37b039605e9b4bb5a89371fd7f5b7ba1", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-03: Kabili-Sepilok, Malaysian Borneo 1ha plot SEP-11, March 2017", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Malaysia during March 2017 by Mathias Disney using a Riegl VZ-400 scanner. Data collection assistance was provided by postdocs Dr Phil Wilkes, Dr Andy Burt and Dr Toby Jackson and a local team of field assistants. Data processing was performed by Dr Cecilia Chavana-Bryant with assistance provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates\r\n.\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the three FBRMS plots is found within plot directories: SEP-11, SEP-12 and SEP-30. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2017-03-14.001.riproject) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/malaysia/SEP-11/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43409, "uuid": "7301dbf14e004c2e8a7c20b0340e7bf5", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/malaysia/SEP-12/", "numberOfFiles": 403054, "volume": 793422011307, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archived document /neodc/forestscan/data/malaysia/SEP-12/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43408, "uuid": "bb81c82352524df99ddd411f6ca2ec81", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-03: Kabili-Sepilok, Malaysian Borneo 1ha plot SEP-12, March 2017", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Malaysia during March 2017 by Mathias Disney using a Riegl VZ-400 scanner. Data collection assistance was provided by postdocs Dr Phil Wilkes, Dr Andy Burt and Dr Toby Jackson and a local team of field assistants. Data processing was performed by Dr Cecilia Chavana-Bryant with assistance provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates. \r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the three FBRMS plots is found within plot directories: SEP-11, SEP-12 and SEP-30. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2017-03-02.001.riproject) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/malaysia/SEP-12/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43411, "uuid": "92b81d8bf76247449190b1e43050c7a2", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/malaysia/SEP-30/", "numberOfFiles": 1063004, "volume": 913343172832, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archived document /neodc/forestscan/data/malaysia/SEP-30/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43410, "uuid": "ff217c783e3f4c66a4891d2b5807ee6e", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-03: Kabili-Sepilok, Malaysian Borneo 1ha plot SEP-30, March 2017", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Malaysia during March 2017 by Mathias Disney using a Riegl VZ-400 scanner. Data collection assistance was provided by postdocs Dr Phil Wilkes, Dr Andy Burt and Dr Toby Jackson and a local team of field assistants. Data processing was performed by Dr Cecilia Chavana-Bryant with assistance provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2). \r\n\r\nData for each of the three FBRMS plots is found within plot directories: SEP-11, SEP-12 and SEP-30. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2017-03-20.001.riproject) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/malaysia/SEP-30/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43413, "uuid": "7e1332758acc414493e41afc62f15877", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/french_guiana/paracou/ALS-Paracou-2022-PerPlot", "numberOfFiles": 6, "volume": 168157094, "fileFormat": "Storage format is las 1.2 (terrestrial laser scanner)", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 40853, "uuid": "7bef89a9dc404683a46642625a024a4b", "short_code": "ob", "title": "ForestScan: Aerial Laser Scanning (ALS) of FBRMS-01: Paracou, French Guiana, November 2022", "abstract": "This Aerial Laser Scanning (ALS) campaign was conducted in November 2022. The ALS data corresponding to plots FG5c1, FG6c2, FG8c4 and IRD-CNES also scanned by Terrestrial LiDAR Scanning (TLS) in October or November 2022 as part of the ForestScan Project are provided in four separate laz files.\r\n\r\nThe covered area: 3*2.16 ha + 1*1.44 ha; Pulse density: ~200 m2; Scanner type: VQ 780II RIEGL; Scanner wavelength: 1064 nm; Beam divergence: <=0.25 mrad (1/e2); Vehicle: Airplane BN2; Operator: Altoa. Acquisition parameters: swath angle: +/-20 degrees; PRR (channel type): ~ 1000 kHz; Ground footprint size of pulse: ~0.16 m; Flight height: 650m terrain follow mode (AGL); Acquisition mode: Full waveform, RGB camera on board but no orthomosaïc made." }, "onlineresource_set": [] }, { "ob_id": 43419, "uuid": "d734071a810d42d492f64ff757827799", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/sentinel2c/data/L1C_MSI/", "numberOfFiles": 9193, "volume": 1493448486908, "fileFormat": "These data are JPG 2000 formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43418, "uuid": "7f7eef8be52a47aa97021f79f81a5f08", "short_code": "ob", "title": "Sentinel 2C Multispectral Instrument (MSI) Level 1C data", "abstract": "This dataset contains Top-of Atmosphere (TOA) reflectances in cartographic geometry (level 1C) processed data, from the Multispectral Instrument (MSI) aboard the European Space Agency (ESA) Sentinel 2C satellite. Sentinel 2C was launched on 5th September 2024 and provides multispectral images of the earth’s surface as a continuation and enhancement of the Landsat and SPOT missions. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user.\r\n\r\nCEDA have switched to provide Sentinel 2 data for the UK and Dependencies along with data needed per project basis as of April 2019. Please contact us if you need data outside these areas and we will see what we can do." }, "onlineresource_set": [] }, { "ob_id": 43425, "uuid": "d0f9abb2550d4d7b90cb1a3553ba8043", "short_code": "result", "curationCategory": "B", "dataPath": "/badc/ukmo-cet/data/daily", "numberOfFiles": 78, "volume": 1565592, "fileFormat": "ASCII", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [ 88347 ] }, { "ob_id": 43438, "uuid": "a8d437827176417282db827c5b7ddbb5", "short_code": "result", "curationCategory": "", "dataPath": "/badc/ccmi/data/post-cmip6/ccmi-2022/MIROC/MIROC-ES2H/senD2-fix/", "numberOfFiles": 2620, "volume": 117918740701, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43437, "uuid": "ee70a9639a364aea845ef3b84ffa8be2", "short_code": "ob", "title": "CCMI-2022: senD2-fix data produced by the MIROC-ES2H model from MIROC", "abstract": "This dataset contains model data for CCMI-2022 experiment senD2-fix produced by the MIROC-ES2H model which is based on a global climate model MIROC (Model for Interdisciplinary Research on Climate). This has been cooperatively developed by JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan).\r\n\r\nIt used a baseline (SSP2-45) with a modified specified stratospheric aerosol distribution using a repeated annual cycle of the WACCM-calculated Surface Area Density (SAD) for 2025 (the WACCM background before stratospheric aerosol injection was initiated) and with specified SSTs/sea-ice as in senD2-sai.\r\n\r\nThe senD2-sai simulation is based on the refD2 experiment but with a modified specified stratospheric aerosol distribution reflecting increased stratospheric aerosol amounts from stratospheric aerosol injection (SAI). Sea ice and sea surface temperatures (SSTs) are specified to follow a repeating annual cycle taken from those used by the same model for their refD2 experiment over 2020 - 2030, the period when SAI is assumed to have been initiated.\r\n\r\nThe refD2 experiment is the baseline projection for updated projections of ozone recovery. Specified forcings largely following the same specifications as for the SSP2-4.5 scenario of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), with the exception of the near-surface mixing ratio of Ozone Depleting Substances which follow the baseline projection from WMO (2018).\r\n\r\nSSP2-4.5 is a Shared Socio-economic Pathway scenario that follows socio-economic storyline SSP2 with intermediate mitigation and adaptation challenges and climate forcing pathway RCP4.5 which leads to a radiative forcing of 4.5 Wm-2 by the year 2100.\r\n\r\nWMO-2018 refers to the Scientific Assessment of Ozone Depletion: 2018.\r\n\r\nThe CCMI-2022 Chemistry-climate model initiative is a set of model experiments focused on the stratosphere, with the goals of providing updated projections towards the future evolution of the ozone layer and improving our understanding of chemistry-climate interactions from models.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n- Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI)\r\n- A new set of Chemistry-Climate Model Initiative (CCMI) Community Simulations to Update the Assessment of Models and Support Upcoming Ozone Assessment Activities, David Plummer and Tatsuya Nagashima and Simone Tilmes and Alex Archibald and Gabriel Chiodo and Suvarna Fadnavis and Hella Garny and Beatrice Josse and Joowan Kim and Jean-Francois Lamarque and Olaf Morgenstern and Lee Murray and Clara Orbe and Amos Tai and Martyn Chipperfield and Bernd Funke and Martin Juckes and Doug Kinnison and Markus Kunze and Beiping Luo and Katja Matthes and Paul A. Newman and Charlotte Pascoe and Thomas Peter (2021), SPARC Newsletter, volume 57, pp 22-30" }, "onlineresource_set": [] }, { "ob_id": 43440, "uuid": "0c85b5b3d32147149a5b869dcc725a65", "short_code": "result", "curationCategory": "", "dataPath": "/badc/ccmi/data/post-cmip6/ccmi-2022/NIES/CCSRNIES-MIROC32/senD2-fix/", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43439, "uuid": "fdbdbc9212fa47bdb5e60855d714851c", "short_code": "ob", "title": "CCMI-2022: senD2-fix data produced by the CCSR-NIES MIROC3.2 model at NIES", "abstract": "This dataset contains model data for CCMI-2022 experiment senD2-fix produced by the CCSR-NIES MIROC3.2 model run by the modelling team at NIES (National Institute for Environmental Studies) in Japan.\r\nIt used a baseline (SSP2-45) with a modified specified stratospheric aerosol distribution using a repeated annual cycle of the WACCM-calculated Surface Area Density (SAD) for 2025 (the WACCM background before stratospheric aerosol injection was initiated) and with specified SSTs/sea-ice as in senD2-sai.\r\n\r\nThe senD2-sai simulation is based on the refD2 experiment but with a modified specified stratospheric aerosol distribution reflecting increased stratospheric aerosol amounts from stratospheric aerosol injection (SAI). Sea ice and sea surface temperatures (SSTs) are specified to follow a repeating annual cycle taken from those used by the same model for their refD2 experiment over 2020 - 2030, the period when SAI is assumed to have been initiated.\r\n\r\nThe refD2 experiment is the baseline projection for updated projections of ozone recovery. Specified forcings largely following the same specifications as for the SSP2-4.5 scenario of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), with the exception of the near-surface mixing ratio of Ozone Depleting Substances which follow the baseline projection from WMO (2018).\r\n\r\nSSP2-4.5 is a Shared Socio-economic Pathway scenario that follows socio-economic storyline SSP2 with intermediate mitigation and adaptation challenges and climate forcing pathway RCP4.5 which leads to a radiative forcing of 4.5 Wm-2 by the year 2100.\r\n\r\nWMO-2018 refers to the Scientific Assessment of Ozone Depletion: 2018.\r\n\r\nThe CCMI-2022 Chemistry-climate model initiative is a set of model experiments focused on the stratosphere, with the goals of providing updated projections towards the future evolution of the ozone layer and improving our understanding of chemistry-climate interactions from models.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n- Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI)\r\n- WMO (World Meteorological Organization), Scientific Assessment of Ozone Depletion: 2018, Global Ozone Research and Monitoring Project – Report No. 58, 588 pp., Geneva, Switzerland, 2018.\r\n- A new set of Chemistry-Climate Model Initiative (CCMI) Community Simulations to Update the Assessment of Models and Support Upcoming Ozone Assessment Activities, David Plummer and Tatsuya Nagashima and Simone Tilmes and Alex Archibald and Gabriel Chiodo and Suvarna Fadnavis and Hella Garny and Beatrice Josse and Joowan Kim and Jean-Francois Lamarque and Olaf Morgenstern and Lee Murray and Clara Orbe and Amos Tai and Martyn Chipperfield and Bernd Funke and Martin Juckes and Doug Kinnison and Markus Kunze and Beiping Luo and Katja Matthes and Paul A. Newman and Charlotte Pascoe and Thomas Peter (2021), SPARC Newsletter, volume 57, pp 22-30" }, "onlineresource_set": [] }, { "ob_id": 43441, "uuid": "8e7d7c596643423897ceff2b70821013", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/deposits01/soc240713", "numberOfFiles": 2063, "volume": 11321165883, "fileFormat": "JPG", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43442, "uuid": "c8fc3efdd6264b42ac84749b88219d95", "short_code": "ob", "title": "Benthic images collected over different terrain features by Autonomous Underwater Vehicle during expedition JC257, 30 km south from the northern border of the UK-1 area of the Clarion-Clipperton Zone, Pacific Ocean, 2024", "abstract": "A collection of 2061 benthic still images was obtained using a downward-looking camera mounted on the UK Autosub5 Autonomous Underwater Vehicle (AUV), deployed from RRS James Cook during cruise JC257 in the abyssal plain (~4100 m depth) of the UK-1 exploration area of the Clarion-Clipperton Zone, Pacific Ocean, in 2024. During mission AS5M097, the AUV was programmed to replicate 21 parallel 1 km long transect lines in a site located 30 km South from the northern border of the UK-1 exploration area. The Grasshopper2 GS2-GE-50S5C camera mounted on the AUV collected vertically orientated still images at a target altitude of 3 m above the seabed, with one image being captured per second. Terrain features exhibiting different slope were delimited and images within each feature were randomly subsampled. These images were colour corrected to enhance visual fidelity and converted from original 8-bit RAW to JPG images. The final image set was inspected for overlap, which was non-existent. The image set was subsequently annotated using the online platform BIIGLE to derive ecological understanding on the influence of seabed topography on seabed community composition. The data were collected by scientists from the National Oceanography Centre, Southampton, UK as part of the NERC-funded Seabed Mining And Resilience To EXperimental impact (SMARTEX) project (NE/T003537/1)." }, "onlineresource_set": [] }, { "ob_id": 43460, "uuid": "a677a5dbce8a406ea385ae554ecd1392", "short_code": "result", "curationCategory": "", "dataPath": "/badc/cmip6/data/CMIP6Plus/RAMIP/MRI/MRI-ESM2-0/ssp370-sas126aer", "numberOfFiles": 1060, "volume": 702241201045, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 43462, "uuid": "8724b4149b4e447fbf8f192207cb0397", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2025/SEANA/seana_faroes_voc_2020/", "numberOfFiles": 3, "volume": 567131, "fileFormat": "data are BADC-CSV formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43397, "uuid": "cda8f167a71c48978837a22b9eb3265e", "short_code": "ob", "title": "Isoprene and DMS concentration measurements in the Faroe Islands in summer-autumn 2020", "abstract": "This dataset contains the time series of isoprene and dimethyl sulfate (DMS) concentrations measured in the Faroe Islands from June to October 2020 as part of the the NERC-funded Shipping Emissions in the Arctic and North Atlantic atmosphere (SEANA) project.\r\n\r\nThe data was collected using two iDirac gas chromatographs (one for isoprene, one for DMS), deployed at the Havnardalur remote air quality station (62.017036°N, 6.857356 °W, 160 m a.s.l.), run by the Faroese Environment Agency on the island of Streymoy, the largest of the Faroe Islands.\r\n\r\nIsoprene and DMS represent two of the largest natural emissions of volatile organic compounds into the atmosphere, with direct effects on regional atmospheric composition and climate.\r\n\r\nThis data is openly accessible for research purposes. Please do contact the authors if you plan to use this data for publications." }, "onlineresource_set": [] }, { "ob_id": 43465, "uuid": "63fdd798729148e1835f72ffabc3a0fa", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2025/Kaboi_Lake_drone_imagery/", "numberOfFiles": 599, "volume": 4611244664, "fileFormat": "BADC-CSV and JPEG format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43434, "uuid": "98692ec457ee431cacc4027820e46411", "short_code": "ob", "title": "Aboveground carbon (AGC) drone imagery and field data for Kaboi Lake 2021", "abstract": "Drone imagery and field data for aboveground carbon (AGC) measurements at Kaboi Lake, Sabah, Malaysia. \r\nData consist of 597 jpeg files of a small forest stand collected by a drone and one csv for field measurements of 24 tree heights. \r\nDrone imagery covering the 2 ha site was collected in March 2021, with field data collected concurrently. \r\nThe drone used was a DJI Phantom 4 Pro V2.0 quadcopter equipped with a 20 megapixel optical camera. \r\nThe data were used to compare drone- and field-based measurements of AGC over small sites, and to inform best practices for calculating baseline AGC for small-scale, community-based forest restoration projects. \r\nData were collected by members of Cardiff University and the Danau Girang Field Centre. Data interpretation by B Newport, University of Bristol." }, "onlineresource_set": [] }, { "ob_id": 43466, "uuid": "869c4ae6f8644262a484c4f45c6821a0", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2025/Southern_Ocean_Clouds/dms_rothera", "numberOfFiles": 2, "volume": 685812, "fileFormat": "BADC-CSV", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43401, "uuid": "a0fa32d5872545bb93c5e9616aa020d4", "short_code": "ob", "title": "DMS concentrations in the Antarctic Peninsula", "abstract": "This dataset contains the time series of dimethyl sulfate (DMS) concentrations measured at East Beach Hut near the British Antarctic Survey (BAS) Rothera station off the coast of the Antarctic peninsula since late Feb 2022, as part of the Southern Ocean Clouds (SOC) project.\r\n\r\nThe data was collected using an iDirac gas chromatograph. DMS is naturally emitted from the oceans into the atmosphere, and has a direct effect on climate through cloud formation.\r\n\r\nThis data is openly accessible for research purposes. Please do contact the authors if you plan to use this data for publications." }, "onlineresource_set": [] }, { "ob_id": 43482, "uuid": "6276e700761e41c1b94d3c9c6e24ffe9", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/desnz-cs-now/data/UKESM-simulation-cs-n0w/", "numberOfFiles": 83856, "volume": 238942143576, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43415, "uuid": "7637a16b099544c2b761175e1de02894", "short_code": "ob", "title": "UKESM1 simulations in support of the CS-N0W programme", "abstract": "The UK Earth System Model (UKESM1) has been used to produce two simulations for the Climate Services for a Net Zero Resilient World (CS-N0W) research programme. The first simulation (\"no overshoot\" or NO) was designed to fix global-mean annual-mean surface temperature to 1.5C above pre-Industrial levels from 2010-2100, and the second simulation (\"very high overshoot\" or VHO) was a scenario where global-mean annual-mean surface temperature was allowed to rise above 1.5C during the century but return to 1.5C by 2100. Four ensemble members were run for each scenario.\r\n\r\nThese are based on the UKESM1-0-LL model. Forcings followed the SSP2-4.5 Shared Socio-economic Pathway, except for chemistry and aerosol emissions which followed SSP1-1.9. CO2 and N2O concentrations were calculated used the TIMES Integrated Assessment Model at University College London (TIAM-UCL) model, which was also used to calculated CH4 for the NO simulation. CH4 in the VHO simuation used SSP1-1.9." }, "onlineresource_set": [] }, { "ob_id": 43484, "uuid": "381f417abc824bf0a0f8fae6e0bf36cb", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/deposits01/soc250721", "numberOfFiles": 15, "volume": 47926427961, "fileFormat": ".mp4 and .csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43485, "uuid": "c701076b44c14a918f7cdb9641bf2d78", "short_code": "ob", "title": "Benthic images recorded by a Remotely Operated Vehicle video camera during cruise JC241 in the eastern Clarion-Clipperton Zone (Pacific Ocean, 2023)", "abstract": "A collection of video images was obtained using an oblique-looking camera mounted on the UK ISIS Remotely Operated Vehicle (ROV), deployed from the RRS James Cook during cruise JC241 in the abyssal plain (~4700 m depth) of the Clarion-Clipperton Zone, Pacific Ocean, in 2023. The images were obtained in an area that included a site disturbed by a deep-sea mining machine in 1979. The mining machine (9 m wide, 14 m long, 4.5 m high) was operated by the Ocean Minerals Company (OMCO) from the ship Hughes Glomar Explorer on the seafloor between 15 and 18 March 1979 at a site centred 13°44'N 126°13.5'W. The videos show the disturbance caused by the past mining activities. The data were collected by scientists from the National Oceanography Centre, Southampton, UK as part of the NERC-funded Seabed Mining And Resilience To EXperimental impact (SMARTEX) project (NE/T003537/1)." }, "onlineresource_set": [] }, { "ob_id": 43487, "uuid": "df979fd4dd02404683ab4c26ce029841", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/gebco/global/gebco_2024/ice_surface_elevation/netcdf/", "numberOfFiles": 8, "volume": 7466666900, "fileFormat": "Data: .nc\r\nDocumentation and metadata: .pdf, .csv, .xlsx, .txt", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43489, "uuid": "5ec6949356de45c2a3b3565d297a80fa", "short_code": "ob", "title": "The GEBCO_2024 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2024 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions largely outside of the Arctic Ocean area, the grid uses as a base Version 2.6 of the SRTM15_plus data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2024 Grid represents all data within the 2024 compilation. The compilation of the GEBCO_2024 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a ‘remove-restore’ blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2024 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute (AWI), Germany; Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research (NIWA), New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory (LDEO), Columbia University, USA; Arctic and North Pacific Oceans - jointly hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43490, "uuid": "24654e4fd1ae47e6a48d64535b0d8375", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/sea_surface_salinity/data/v05.5/NHv5.5/7days/", "numberOfFiles": 5105, "volume": 9871220205, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43291, "uuid": "5b48a34fb4134bbd99acace7767e5b3e", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product for the Northern Hemisphere on a 25km EASE grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a NH polar 25km EASE (Equal Area Scalable Earth) grid with 1 day of time sampling. This product is also available separately on a regular lat/lon grid. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "onlineresource_set": [] }, { "ob_id": 43491, "uuid": "07da640984f840e79b3784375e5d5559", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/sea_surface_salinity/data/v05.5/GLOBALv5.5/7days/", "numberOfFiles": 5105, "volume": 28126458548, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43290, "uuid": "4321d9b540fe48f8943179aa3ef06c79", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product on a 0.25 degree global grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a 0.25 degree grid and 1 day of time sampling. This product is also available separately on polar 25km EASE (Equal Area Scalable Earth) grids. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "onlineresource_set": [] }, { "ob_id": 43492, "uuid": "7b983414c38b4d0cad7333c891995999", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/sea_surface_salinity/data/v05.5/SHv5.5/7days/", "numberOfFiles": 5105, "volume": 11696581616, "fileFormat": "Data are in NetCDF format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43289, "uuid": "c302b1dceb8a4c39a31d18b60f236d09", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product for the Southern Hemisphere on a 25km EASE grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a SH polar 25km EASE (Equal Area Scalable Earth) grid with 1 day of time sampling. This product is also available separately on a regular lat/lon grid. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "onlineresource_set": [] }, { "ob_id": 43493, "uuid": "3ed11e6ca7a04272b57e4b51b5af6b8c", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/sea_surface_salinity/data/v05.5/GLOBALv5.5/30days/", "numberOfFiles": 336, "volume": 1905563660, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43288, "uuid": "3339dec1fbd94599802aba7f1c665679", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product on a 0.25 degree global grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a 0.25 degree grid and 15 days of time sampling. This product is also available separately on polar 25km EASE (Equal Area Scalable Earth) grids. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "onlineresource_set": [] }, { "ob_id": 43494, "uuid": "d0d195c1518b4df299227ec7637df9f6", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/sea_surface_salinity/data/v05.5/SHv5.5/30days/", "numberOfFiles": 336, "volume": 785193298, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43287, "uuid": "0397ca6f625e47f489684bad2bd533bb", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product for the Southern Hemisphere on a 25km EASE grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a SH polar 25km EASE (Equal Area Scalable Earth) grid with 15 days of time sampling. This product is also available separately on a regular lat/lon grid. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "onlineresource_set": [] }, { "ob_id": 43495, "uuid": "5232ab92ebd54bd9a4a34756c64929b3", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/sea_surface_salinity/data/v05.5/NHv5.5/30days/", "numberOfFiles": 336, "volume": 657473105, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43286, "uuid": "3d3e52e597fe40b0ab5984cc0ee82de3", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product for the Northern Hemisphere on a 25km EASE grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a NH polar 25km EASE (Equal Area Scaleable Earth) grid with 15 days of time sampling. This product is also available separately on a regular lat/lon grid. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "onlineresource_set": [] }, { "ob_id": 43502, "uuid": "c007760a318842029cdc9f5ae69c3344", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/deposits01/soc250724", "numberOfFiles": 337, "volume": 1576736905, "fileFormat": ".jpg", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43503, "uuid": "cf65717536994466976cf260ae8f7fe2", "short_code": "ob", "title": "Highlight seabed images taken by ROV in the Ocean Minerals Company (OMCO) during expedition JC241 in the Clarion-Clipperton Zone (Pacific Ocean, 2023)", "abstract": "A collection of benthic still images was obtained using an oblique-looking camera mounted on the UK ISIS Remotely Operated Vehicle (ROV), deployed from the RRS James Cook during cruise JC241 in the abyssal plain (~4700 m depth) of the Clarion-Clipperton Zone, Pacific Ocean, in 2023. The images were obtained in an area that included a site disturbed by a deep-sea mining machine in 1979. The mining machine (9 m wide, 14 m long, 4.5 m high) was operated by the Ocean Minerals Company (OMCO) from the ship Hughes Glomar Explorer on the seafloor between 15 and 18 March 1979 at a site centred 13°44'N 126°13.5'W. The images show the seabed covered by polymetallic nodules and the disturbance caused by the past mining activities. The data were collected by scientists from the National Oceanography Centre, Southampton, UK as part of the NERC-funded Seabed Mining And Resilience To EXperimental impact (SMARTEX) project (NE/T003537/1)." }, "onlineresource_set": [] }, { "ob_id": 43510, "uuid": "14aeff33341f46f9957e645ddef17ed2", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/ghg/data/cci_plus/CO2_OC2_FOCA/v11.0", "numberOfFiles": 3255, "volume": 67226763806, "fileFormat": "netcdf", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43488, "uuid": "198d56f5fbbf4144b8fd4932328be462", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 11.0", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2) data, generated using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data (v11) was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg).\r\nThe FOCAL OCO-2 XCO2 retrieval development, data processing and analysis has received co-funding from ESA’s Climate Change Initiative (CCI+) via project GHG-CCI+ (contract 4000126450/19/I-NB, https://climate.esa.int/en/projects/ghgs) EUMETSAT via the FOCAL-CO2M study (contract EUM/CO/19/4600002372/RL), the European Union via the Horizon 2020 (H2020) projects VERIFY (Grant Agreement No. 776810, http://verify.lsce.ipsl.fr) and CHE (Grant Agreement No. 776186, https://www.che-project.eu) and by the State and the University of Bremen.\r\n\r\nWhen citing this data, please also cite the following peer-reviewed publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017" }, "onlineresource_set": [] }, { "ob_id": 43522, "uuid": "490dae796f484741b8ab8944caf4dd2b", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2023/ice_surface_elevation/netcdf", "numberOfFiles": 6, "volume": 7466363848, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43496, "uuid": "bb0e44f6520f415e9a07601bb21ac3c8", "short_code": "ob", "title": "The GEBCO_2023 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2023 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.5.5 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2023 Grid represents all data within the 2023 compilation. The compilation of the GEBCO_2023 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a 'remove-restore' blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2023 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43523, "uuid": "be640aa87e47413398967db83f113520", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2022/ice_surface_elevation/netcdf", "numberOfFiles": 6, "volume": 7466348665, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43497, "uuid": "4ea04d633ecc43e195520fb65256cd5e", "short_code": "ob", "title": "The GEBCO_2022 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43524, "uuid": "51a03c6548fa4b248ba4eff7cb2ad0ee", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2022/ice_surface_elevation/netcdf", "numberOfFiles": 5, "volume": 7466347826, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 43525, "uuid": "6da3aa684da340d9acad463feafc0942", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2021/ice_surface_elevation/netcdf", "numberOfFiles": 5, "volume": 7466238602, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 43526, "uuid": "24e5ee2011f241f3973767645832de60", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2021/ice_surface_elevation/netcdf", "numberOfFiles": 6, "volume": 7466239441, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43498, "uuid": "eb4f211ef57745919dddb8a93518db00", "short_code": "ob", "title": "The GEBCO_2021 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2021 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2021 Grid represents all data within the 2021 compilation. The compilation of the GEBCO_2021 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2021 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43527, "uuid": "a243c19bdeba4fb5bc671f7963b6e40d", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2020/ice_surface_elevation/netcdf", "numberOfFiles": 8, "volume": 7466474042, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43499, "uuid": "4ad3e42245174dee86ca27f8e1bb2e87", "short_code": "ob", "title": "The GEBCO_2020 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43528, "uuid": "841bb061b42f4eba81269604b133e80a", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2019/ice_surface_elevation/netcdf", "numberOfFiles": 5, "volume": 11723667350, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43500, "uuid": "2920b2ea41d244cd9bfd95be0f4dc4a9", "short_code": "ob", "title": "The GEBCO_2019 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA)." }, "onlineresource_set": [] }, { "ob_id": 43529, "uuid": "c2a191c684de4cddb14be5e1582d125a", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2024", "numberOfFiles": 118, "volume": 110659007521, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43504, "uuid": "591c8f9d03ea45ce9053a8d67d65eb56", "short_code": "ob", "title": "The GEBCO_2024 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2024 Grid Collection is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2024 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2024 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2024 grid (standard grid of ice surface elevation) available in NetCDF format. In regions largely outside of the Arctic Ocean area, the GEBCO_2024 grid uses as a base Version 2.6 of the SRTM15_plus data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2024 Grid represents all data within the 2024 compilation. The compilation of the GEBCO_2024 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a ‘remove-restore’ blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2024 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute (AWI), Germany; Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research (NIWA), New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory (LDEO), Columbia University, USA; Arctic and North Pacific Oceans - jointly hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43530, "uuid": "47d5c003fe6d41b6b29f449e10cb05c0", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2023", "numberOfFiles": 114, "volume": 107903394711, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43505, "uuid": "c25d585d8c314cbba6faebb4f21ff4a3", "short_code": "ob", "title": "The GEBCO_2023 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2023 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2023 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2023 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2023 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.5.5 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2023 Grid represents all data within the 2023 compilation. The compilation of the GEBCO_2023 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a 'remove-restore' blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2023 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43531, "uuid": "390a06cebf4a49caa650cf2be69f55bc", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2022", "numberOfFiles": 116, "volume": 109887838662, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43506, "uuid": "b5a93cb47d934f5295e2784313ecfb00", "short_code": "ob", "title": "The GEBCO_2022 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2022 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2022 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2022 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43532, "uuid": "565c4581b319406ea2b56c75dd1df784", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2021", "numberOfFiles": 108, "volume": 108470395279, "fileFormat": "NetCDF, ESRI ASCII raster, data GeoTIFF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43507, "uuid": "b978db2f6e4e4bc49ca8ca026495aaac", "short_code": "ob", "title": "The GEBCO_2021 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2021 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2021 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2021 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2021 grid (standard grid of ice surface elevation) available in NetCDF format.\r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2021 Grid represents all data within the 2021 compilation. The compilation of the GEBCO_2021 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2021 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43533, "uuid": "03950655bdd3407fa69dc8e30b5c3231", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2020", "numberOfFiles": 15, "volume": 11294459725, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43508, "uuid": "74583b230b1343d9b4b302b8fbb5414f", "short_code": "ob", "title": "The GEBCO_2020 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2020 Grid Collection comprises the following data types: the standard grid (ice surface elevation), and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2020 Grid Collection is delivered in NetCDF format only. This data collection also contains the published and citable GEBCO_2020 grid (standard grid of ice surface elevation) available in NetCDF format.\r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "onlineresource_set": [] }, { "ob_id": 43534, "uuid": "e4f1dabc57f5429c8d182c3dacb731c0", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2019", "numberOfFiles": 15, "volume": 19487610783, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43509, "uuid": "cefbb8b5fc874bfc84f75169a611de4f", "short_code": "ob", "title": "The GEBCO_2019 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2019 Grid Collection, comprises the following data types: the standard grid (ice surface elevation), the Source Identifier Grid (SID), and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2019 Grid Collection is available in NetCDF format only. This data collection also contains the published and citable GEBCO_2019 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nThe grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA)." }, "onlineresource_set": [] }, { "ob_id": 43537, "uuid": "02e5ef337ca249e8b618b952ee3b4bc9", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_one_minute_2008", "numberOfFiles": 6, "volume": 756309650, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43536, "uuid": "e7b366a8516240b7a023edb25fdaf1bf", "short_code": "ob", "title": "The GEBCO_2008 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2008 Grid is a global continuous terrain model for ocean and land with a spatial resolution of one arc-minute. The GEBCO_2008 Grid, comprises the one minute grid in NetCDF format only, alongside accompanying terms of use and documentation. Please note that the GEBCO 2008 One Minute Grid is a legacy dataset that has been superseded by subsequent releases of the GEBCO grid." }, "onlineresource_set": [] }, { "ob_id": 43538, "uuid": "50ac745a72b94148a4440d6b04f26e02", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/global/gebco_2014", "numberOfFiles": 9, "volume": 4948804328, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43535, "uuid": "0c9dfec287bf4b6c84435d1182825389", "short_code": "ob", "title": "The GEBCO_2014 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2014 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 30 arc-seconds. The GEBCO_2019 Grid Collection, comprises the following data types: the standard grid (ice surface elevation), and the Source Identifier Grid (SID). The GEBCO_2014 Grid Collection is available in NetCDF format only. Please note the GEBCO 2014 grid is a legacy dataset that has been superseded by more recent releases." }, "onlineresource_set": [] }, { "ob_id": 43541, "uuid": "6b3f7e44f4fb485b9130327399367249", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/ibcao/ibcao_v1", "numberOfFiles": 41, "volume": 1309572300, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43513, "uuid": "8e50690c2ac84e249cbc2cba2e95f5e5", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 1", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 1.0 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. The IBCAO Version 1 Grid was released in July 2001.\r\n\r\nThe bathymetric grid released in IBCAO Version 1 is available in NetCDF or Esri ASCII raster format. The grid is available as a geographic grid (one arc-minute intervals), or in a polar stereographic projection (2500 x 2500 m grid interval, true scale 75°N, WGS 84 datum). Postscript plots in polar stereographic projection are also available in IBCAO Version 1, showing shaded relief and contours. Shaded relief imagery is also provided in JPEG format. A Source Identifier Grid is delivered as a Postscript plot for IBCAO Version 1, to provide information on the source data sets included in the IBCAO grid." }, "onlineresource_set": [] }, { "ob_id": 43542, "uuid": "4a1edd7a9fde49599fc365f4137b729c", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/ibcao/ibcao_v2_23", "numberOfFiles": 20, "volume": 825460525, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43514, "uuid": "1e69e123a0c04e2a83539dec43f1bfdb", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 2.23", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 2.23 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. The IBCAO Version 2.23 Grid was released in March 2008.\r\n\r\nThe bathymetric grid released in IBCAO Version 2.23 is available in NetCDF or Esri ASCII raster format. The grid is available as a geographic grid (one arc-minute or two arc-minute intervals), or in a polar stereographic projection (2000 x 2000 m grid interval, true scale 75°N, WGS 84 datum). The one-minute geographic grid imagery is also available in KMZ format for Google Earth. A Source Identifier Grid is delivered as a JPEG image for IBCAO version 2.23, to provide information on the source data sets included in the IBCAO grid." }, "onlineresource_set": [] }, { "ob_id": 43543, "uuid": "139379ed7fdb46968e5b341ad3c4d0d0", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/ibcao/ibcao_v3", "numberOfFiles": 32, "volume": 10612304945, "fileFormat": "ESRI ASCII raster, data GeoTIFF, NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43515, "uuid": "ca9e188d6141435eb7d851d40416a645", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 3.0", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 3.0 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. The IBCAO Version 3.0 Grid was released in June 2012.\r\n\r\nAt the time of its publication, IBCAO Version 3.0 represented the largest improvement in the data set since 1999. Taking advantage of new data sets collected by the circum-Arctic nations, opportunistic data collected from fishing vessels, data acquired from US Navy submarines and from research ships of various nations.\r\n\r\nBuilt using an improved gridding algorithm, the grid is on a 500 meter spacing, revealing much greater details of the Arctic seafloor than IBCAO Version 1.0 (2.5 km) and Version 2.0 (2.0 km). The area covered by multibeam surveys has increased from ~6 % in Version 2.0 to ~11% in Version 3.0.\r\n\r\nThe bathymetric grid released in IBCAO Version 3.0 is available in NetCDF, Esri ASCII or data GeoTIFF raster format. The IBCAO V3 data are built using the WGS84 horizontal datum, where the vertical datum is referenced to Mean Sea Level. Elevation values are provided in metres (negative below the sea surface). The IBCAO V3 dataset comprises polar stereographic grids at 500 x 500m grid intervals, true scale 75°N, in both smoothed (SM) and remove-restore (RR) method formats. The IBCAO V3 dataset also comprises geographic grids at 30 arc-second resolution in both smoothed (SM) and remove-restore (RR) method formats." }, "onlineresource_set": [] }, { "ob_id": 43544, "uuid": "92b621c8b57745e288cd2df54283434f", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/ibcao/ibcao_v4.1", "numberOfFiles": 102, "volume": 59631521711, "fileFormat": "ESRI ASCII raster, data GeoTIFF, NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43516, "uuid": "ae9cfa35e2454137a672f15ca00d0e64", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.1", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.1 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.1 Grid was released in July 2021, updated from IBCAO Version 4 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.1 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.1 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.1 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." }, "onlineresource_set": [] }, { "ob_id": 43545, "uuid": "f39109750c134f77a63d26b56e033ec2", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/ibcao/ibcao_v4.2", "numberOfFiles": 102, "volume": 59659683940, "fileFormat": "ESRI ASCII raster, data GeoTIFF, NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43517, "uuid": "c46755ee7d604d8591fee4dc5f56b9e3", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.2 Grid was released in August 2022, updated from IBCAO Version 4.1 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.2 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.2 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.2 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." }, "onlineresource_set": [] }, { "ob_id": 43546, "uuid": "4ef509d0455e46cda59bb8fc8a891a3a", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/ibcao/ibcao_v4.2.13", "numberOfFiles": 101, "volume": 59409906321, "fileFormat": "ESRI ASCII raster, data GeoTIFF, NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43518, "uuid": "5846574e36e942a29b778534980280b9", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2.13", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2.13 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.2.13 Grid was released in August 2022, updated from IBCAO Version 4.2 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.2.13 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.2.13 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.2.13 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." }, "onlineresource_set": [] }, { "ob_id": 43547, "uuid": "c61b573725c04855938d422a0c733a20", "short_code": "result", "curationCategory": "", "dataPath": "/bodc/gebco/ibcao/ibcao_v5", "numberOfFiles": 69, "volume": 169755069833, "fileFormat": "ESRI ASCII raster, data GeoTIFF, NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43519, "uuid": "3bc493d393a843ee9422f9c610fcd437", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 5", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 5 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 5 Grid was released in 2024, updated from IBCAO Version 4.2.13 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 5 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 5 dataset comprises a grid with Greenland ice sheet data at 100 m, 200 m and 400 m grid cell spacing. A Version 5 grid without Greenland ice sheet data is also available. IBCAO Version 5 imagery is also provided in .tiff format at 100m grid cell spacing. \r\n\r\nAlongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 100 m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." }, "onlineresource_set": [] }, { "ob_id": 43548, "uuid": "a5dc2fb56d27462a81dba914740639aa", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2025/AQREAN", "numberOfFiles": 225, "volume": 52620806507, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43429, "uuid": "7d44ef2a9e9346e79863f53193db189e", "short_code": "ob", "title": "UK Air Quality Reanalysis (AQREAN): Bias Corrected Surface Level", "abstract": "The UK Air Quality Reanalysis (AQREAN) combines an air quality forecast model with a bias-correction post-processing system, incorporating ground-based pollutant observations, to give an improved estimate of pollutant levels for the UK. \r\n\r\nThe data covers the UK at the surface level on a 0.1degree horizontal grid, at hourly time resolution. \r\n\r\nThis dataset contains the following species:\r\n\t• Particulate matter, with diameter < 2.5 µm (PM2.5)\r\n\t• Particulate matter, with diameter < 10 µm (PM10)\r\n\t• Ozone (O3)\r\n\t• Nitrogen Monoxide (NO)\r\n\t• Nitrogen Dioxide (NO2)\r\n\t• Sulphur Dioxide (SO2)\r\n\t• Carbon Monoxide (CO)\r\n\r\nThe Daily Air Quality Index (DAQI) is also included, along with the species-specific DAQI for the contributing pollutants. \r\n\r\nNote: \r\n• AQREAN is only representative of ambient background pollutant concentrations. \r\n• Data is masked to include only land-based locations as no observations are included to support the bias corrections over the ocean." }, "onlineresource_set": [] }, { "ob_id": 43549, "uuid": "1519222bbc044eeb85fc6991d687d450", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/ghg/data/cci_plus/CH4_S5P_WFMD/v1.8_extended_june2024", "numberOfFiles": 2379, "volume": 142178270863, "fileFormat": "netcdf", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43540, "uuid": "2b8c6a8f1abd40a6b0ce07c40b1c57ff", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.8, November 2017 - June 2024", "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.8, and covers the period from November 2017 - June 2024. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThese data were produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project.\r\n\r\nWhen citing this dataset, please also cite the following peer-reviewed publication: \r\nSchneising, O., Buchwitz, M., Hachmeister, J., Vanselow, S., Reuter, M., Buschmann, M., Bovensmann, H., and Burrows, J. P.: Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm, Atmos. Meas. Tech., 16, 669–694, https://doi.org/10.5194/amt-16-669-2023, 2023." }, "onlineresource_set": [] }, { "ob_id": 43550, "uuid": "0e5171fe0bff46aeb3adce414e2808d4", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2024/lgm_oscillations_convadv/", "numberOfFiles": 116, "volume": 9051796032, "fileFormat": "NetCDF and CSV", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43174, "uuid": "1f4ebb2944ec43a39ce6c69a8f1942fb", "short_code": "ob", "title": "HadCM3 simulation data and model inputs supporting the manuscript \"Simulated millennial-scale climate variability driven by a convection-advection oscillator\"", "abstract": "This record contains Hadley Centre Coupled Model, version 3 (HadCM3) simulation data produced for the manuscript \"Simulated millennial-scale climate variability driven by a convection-advection oscillator\" by Y.M. Rome et al, submitted to Climate Dynamics https://doi.org/10.1007/s00382-025-07630-x\r\n\r\nThis paper introduces the convection-advection oscillator mechanism to explain the millennial-scale oscillations observed in a set of HadCM3 general circulation model simulations forced with snapshots of deglacial meltwater history. The oscillating simulation was compared to different simulations using a different meltwater forcing and model parametrisation to extract the main components at stake in the establishment of the oscillations. This record also includes a rerun of the primary oscillating simulation with additional salinity tendencies diagnostic included.\r\n\r\nThis results in six HadCM3 simulations of the Last Glacial Maximum (21,000 years ago) integrated over 3,000 to 10,000 years. The model outputs were saved as netcdf files, and the data were cropped to only include the fields relevant to the figures of the paper. This dataset can be used as the input of the companion scripts accessible using the following DOI: 10.5281/zenodo.13710877. The dataset also includes some of the model inputs, namely the land-sea mask, basin files, meltwater forcing and waterfix, necessary for the reproducibility of the results." }, "onlineresource_set": [] }, { "ob_id": 43556, "uuid": "cd610d777df44716993d017b190867ce", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG5c1/", "numberOfFiles": 1282074, "volume": 1467542700932, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archive /neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG5c1/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 40874, "uuid": "656ac8ee1d42443f9addcbce28c1b137", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-01: Paracou, French Guiana 1ha plot FG5c1, September to October 2022", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in French Guiana from September to October 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. Data collection assistance was provided by UCL PhD student Wanxin Yang and a local team of field assistants, data processing assistance was provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing terrestial (TLS), unpiloted airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the three FBRMS plots is found within plot directories: FG5c1, FG6c2 and FG8c4. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-10-10_FG5c1.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG5c1/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43560, "uuid": "e25150fc9630405ea4530e2854ac833d", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG6c2/", "numberOfFiles": 768701, "volume": 1522120454888, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the in the following directory /neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG6c2/.ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 40875, "uuid": "931973db09af41568853702efe135f29", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-01: Paracou, French Guiana 1ha plot FG6c2, September to October 2022", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in French Guiana from September to October 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the three FBRMS plots is found within plot directories: FG5c1, FG6c2 and FG8c4. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-10-18_FG6c2.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG6c2/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43561, "uuid": "be86b6caacc44d8aa94b1a9e45b02943", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG8c4/", "numberOfFiles": 1025581, "volume": 1511278928546, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the following archived document /neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG8c4/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 40876, "uuid": "40f0f38023ac40f6b40bbf96e4dc5258", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-01: Paracou, French Guiana 1ha plot FG8c4, September to October 2022", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in French Guiana from September to October 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the three FBRMS plots is found within plot directories: FG5c1, FG6c2 and FG8c4. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-09-26_FG8c4.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/french_guiana/paracou/TLS_Plot_FG8c4/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43562, "uuid": "b19eb07911734f3bacaff0779ef49da8", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/gabon/lope/TLS_lope_2022/LPG-01/", "numberOfFiles": 424132, "volume": 1066178163790, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archive document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/LPG-01/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43029, "uuid": "8ea2c697ee53430a84825384bfdcf06a", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-02: Station d’Etudes des Gorilles et Chimpanzés, Lopé National Park, Gabon 1ha plot LPG-01, June to July 2022", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Gabon from June to July 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. Data collection assistance was provided by Heddy O. Milamizokou Napo, Luna Soenens, Virginie Daelemans and Löic Makaga, data processing assistance was provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the four FBRMS plots is found within plot directories: LPG-01, OKO-01, OKO-02 and OKO-03. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-06-24_LPG-01.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/LPG-01/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43566, "uuid": "9e77b16a49de4429afdbd6aa19633c3e", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-01", "numberOfFiles": 816262, "volume": 1410567879717, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-01/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 40878, "uuid": "45ae3437f82f4e4fb75f9a5c26a194ba", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-02: Station d’Etudes des Gorilles et Chimpanzés, Lopé National Park, Gabon 1ha plot OKO-01, June to July 2022", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Gabon from June to July 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. Data collection assistance was provided by UCL postdoc Dr Phil Wilkes and a local team of field assistants, data processing assistance was provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the four FBRMS plots is found within plot directories: LPG-01, OKO-01, OKO-02 and OKO-03. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-06-04_OKO-01.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-01/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43567, "uuid": "8f9d1243b2194e66b0624f96acfab5da", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-02/", "numberOfFiles": 831131, "volume": 1527859727292, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-02/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 40879, "uuid": "ff4b43475c9641cca1dad2c8be8dadaf", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-02: Station d’Etudes des Gorilles et Chimpanzés, Lopé National Park, Gabon 1ha plot OKO-02, June to July 2022", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Gabon from June to July 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. Data collection assistance was provided by Heddy O. Milamizokou Napo, Luna Soenens and Virginie Daelemans, data processing assistance was provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the four FBRMS plots is found within plot directories: LPG-01, OKO-01, OKO-02 and OKO-03. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-06-10_OKO-02.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-02/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets" }, "onlineresource_set": [] }, { "ob_id": 43568, "uuid": "5dc050fb4b0143f4bd7e13dd046a958e", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-03/", "numberOfFiles": 682452, "volume": 1252104515880, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-03/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 40880, "uuid": "8ed3ddec76b8470285bdb2ea643f54bc", "short_code": "ob", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-02: Station d’Etudes des Gorilles et Chimpanzés, Lopé National Park, Gabon 1ha plot OKO-03, June to July 2022", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Gabon from June to July 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. Data collection assistance was provided by Heddy O. Milamizokou Napo, Luna Soenens and Virginie Daelemans, data processing assistance was provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the four FBRMS plots is found within plot directories: LPG-01, OKO-01, OKO-02 and OKO-03. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-07-04_OKO-03.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/OKO-03/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets." }, "onlineresource_set": [] }, { "ob_id": 43570, "uuid": "6f13d8e0867a4210876c75ead9272f9f", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/eocis/data/global_and_regional/arctic_sea_ice/arctic_sea_ice_thickness_grids/L3C/monthly/v1.0/", "numberOfFiles": 100, "volume": 1356759727, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43329, "uuid": "4c246cb11aa04651a0182b2d329a84f9", "short_code": "ob", "title": "EOCIS: Arctic Sea Ice Thickness Grids, v1.00", "abstract": "This dataset contains Arctic Sea Ice Thickness data produced within the Earth Observation Climate Information Service (EOCIS) project.\r\n\r\nThe sea ice products provide a 5x5 km grid of Arctic sea ice thickness (for the whole Arctic region and of 17 sub-regions), delivered as NetCDF files. \r\n\r\nEOCIS sea ice thickness NetCDF products are generated monthly by the Centre for Polar Observation and Modelling (CPOM) from radar altimetry measurements taken from the ESA CryoSAT-2 satellite during the winter months (Oct-Apr).\r\n\r\nSea ice thickness is only reliably measured from satellite radar altimetry during the winter months. During summer, melt ponds can form on the sea ice floes making it difficult for the satellite to differentiate between floes and leads, and hence calculate sea ice freeboard (and subsequently thickness). Measurement during summer months using radar altimetry is an area of active research (Landy et al, 2022) but is not yet operationally processed.\r\n\r\nFor future updates to this dataset, see the EOCIS CPOM page in the related documents section." }, "onlineresource_set": [] }, { "ob_id": 43571, "uuid": "258ae48263184472ab9376fa9e9229ca", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/eocis/data/global_and_regional/arctic_sea_ice/arctic_sea_ice_timeseries/monthly/v1.0/", "numberOfFiles": 2, "volume": 63583, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43252, "uuid": "b59bd616e0b24388b8b57a195ea4d538", "short_code": "ob", "title": "EOCIS: Time Series of Arctic Sea Ice Thickness, Volume & Mass V1.00", "abstract": "This dataset contains Sea Ice Arctic Thickness, Volume and Mass data produced within the Earth Observation Climate Information Service (EOCIS) project.\r\n\r\nThe sea ice products provide a time series of Arctic sea ice thickness, volume and mass (for the whole Arctic region and of 17 sub-regions), delivered in NetCDF files, where thickness, volume and mass are each variables. \r\n\r\nEOCIS sea ice thickness, volume and mass NetCDF products are generated monthly by the Centre for Polar Observation and Modelling (CPOM) from radar altimetry measurements taken from the ESA CryoSAT-2 satellite during the winter months (Oct-Apr).\r\n\r\nSea ice thickness is only reliably measured from satellite radar altimetry during the winter months. During summer, melt ponds can form on the sea ice floes making it difficult for the satellite to differentiate between floes and leads, and hence calculate sea ice freeboard (and subsequently thickness). Measurement during summer months using radar altimetry is an area of active research (Landy et al, 2022) but is not yet operationally processed.\r\n\r\nFor future updates to this dataset, see the EOCIS CPOM page in the related documents section." }, "onlineresource_set": [] }, { "ob_id": 43575, "uuid": "4fe0e3310db54e3ea5d3005e4b7a88bb", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2025/NW_European_Seasonal_Weather_Prediction/", "numberOfFiles": 9, "volume": 741480, "fileFormat": "csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43574, "uuid": "358b4a19d1c44f6f8948edea4cae7f9b", "short_code": "ob", "title": "Northwest European Seasonal Weather Prediction from Complex Systems Modelling for Summer and Winter from 1940 to 2023 (NERC grant NE/V001787/1)", "abstract": "This dataset provides Northwest European seasonal weather predictions from complex systems modelling for Summer and Winter from 1940 to 2023. \r\n\r\nTime series of standardised anomalies with respect to the normalisation period 1981-2010 were obtained for each dataset, covering sea ice cover, sea surface temperatures, tropical precipitation, sea level pressure, the stratospheric polar vortex, snow cover, sunspot activity, volcanic activity and carbon dioxide concentrations. In addition, using 500 hPa geopotential height data from the ERA5 reanalysis, time series of jet speed and latitude were derived and the top three principal empirical orthogonal functions of atmospheric circulation variability for the North Atlantic and European sector.\r\n\r\nThe datasets are sets of standardised values and anomalies for different predictors of atmospheric circulation variability, which can be fed into NARMAX machine learning models to generate forecasts of the three leading empirical orthogonal functions of atmospheric circulation variability - roughly corresponding to the North Atlantic Oscillation (NAO), East Atlantic Pattern (EA) and Scandinavian Pattern (SCA). In the SF-NARMAX project these values were used to generate NARMAX forecasts for June, for July/August, and for meteorological winter (December/January/February), which were then compared with actual outcomes, to help assess the reliability of the NARMAX models.\r\n\r\nThe datasets used for generating the predictor datasets for both winter and summer can be found alongside supporting documentation. These datasets relate to NERC grant: NE/V001787/1." }, "onlineresource_set": [] }, { "ob_id": 43577, "uuid": "245588ab05034d50ac30f851c1036851", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2025/Urban_Atmosphere_Particle_Formation/", "numberOfFiles": 10, "volume": 941740923, "fileFormat": "csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43467, "uuid": "128cb0c2cf1c43c8a5f0b7ffe58325d0", "short_code": "ob", "title": "Measurements of particle number size distributions, sulfuric acid, and oxygenated organic molecules at five sites", "abstract": "These files contain measurements of the particle number size distribution (PNSD) taken with a suite of instruments explained below, as well as gas phase sulfuric acid (H2SO4), gas phase sulfuric acid (H2SO4 dimer), and oxygenated organic molecules (OOMs) as measured by Nitrate CIMS (Chemical Ionisation Mass Spectrometer).\r\n\r\nThe data were taken at five urban site across Europe. At an urban background site in Manchester, UK (MAN_UB), one at an urban background site and one at a roadside site in Leipzig, Germany (LEJ_UB, LEJ_RS ), one at an urban background site and one at a roadside site in Barcelona, Spain (BCN_UB, BCN_RS)." }, "onlineresource_set": [] }, { "ob_id": 43587, "uuid": "7313226db48d48e88b83c6e8245755e4", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/sea_ice/data/sea_ice_concentration/L3C/esmr/25km/v1.1", "numberOfFiles": 2275, "volume": 8142797329, "fileFormat": "Data are in NetCDF format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43483, "uuid": "8978580336864f6d8282656d58771b32", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Nimbus-5 ESMR Sea Ice Concentration, version 1.1", "abstract": "This dataset provides Sea Ice Concentration (SIC) for the polar regions, derived from the Nimbus-5 Electrical Scanning Microwave Radiometer (ESMR), which operated between 1972 and 1977. It is processed with an algorithm using the single channel ESMR data (19.35 GHz), and has been gridded at 25 km grid spacing. This is the second version of the product, v1.1.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project." }, "onlineresource_set": [] }, { "ob_id": 43594, "uuid": "fe7d784ba0f44c098f353d169095d1ab", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/eocis/data/CHUK/geospatial_information/v1.1/", "numberOfFiles": 59, "volume": 11372121174, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43348, "uuid": "b766867ceadb409da64d480bdbe4057d", "short_code": "ob", "title": "EOCIS: Geospatial Information Files V1.1", "abstract": "This dataset contains categorical geographical information data files for the UK to enable the effective translation of climate data into new forms of actionable information. \r\n\r\nThese datasets have been created as part of the Earth Observation Climate Information Service (EOCIS) project, following the specific format and nature of the EOCIS Climate information at Hi-res for the UK (CHUK) grid, as specified by NCEO. \r\n\r\nThe information files cover the following attributes: \r\n* land and permanent water\r\n* tags for the devolved nation of the UK (also Eire, France, etc)\r\n* tags for the county / council / unitary authority / metropolitan or London borough\r\n* tags for the parish / community / town council\r\n* tags for the UK postcode sector \r\n* tags for appropriate administrative boundaries relating to the National Health Service \r\n* tags for appropriate administrative boundaries relating to the Fire Service\r\n* land classification \r\n* built and paved area fractions \r\n* presence of roads, railway tracks and transmission network \r\n* socioeconomic data of population, income, and educational attainment" }, "onlineresource_set": [] }, { "ob_id": 43615, "uuid": "07d58c9b9d02438aaeb9c16a10610512", "short_code": "result", "curationCategory": "", "dataPath": "/badc/ccmi/data/post-cmip6/ccmi-2022/NASA-GSFC/GEOSCCM/refD2/", "numberOfFiles": 885, "volume": 573826845723, "fileFormat": "Files are Net-CDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43613, "uuid": "07d609ca7d7942278d8f324a642535c0", "short_code": "ob", "title": "CCMI-2022: refD2 data produced by the GEOSCCM model at NASA-GSFC", "abstract": "This dataset contains model data for CCMI-2022 experiment refD2 produced by the GEOSCCM model run by the modelling team at NASA-GSFC (NASA Goddard Space Flight Center) in the USA.\r\n\r\nThe refD2 experiment is the baseline projection for updated projections of ozone recovery. Specified forcings largely following the same specifications as for the SSP2-4.5 scenario of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), with the exception of the near-surface mixing ratio of Ozone Depleting Substances which follow the baseline projection from WMO (2018).\r\n\r\nThe CCMI-2022 Chemistry-climate model initiative is a set of model experiments focused on the stratosphere, with the goals of providing updated projections towards the future evolution of the ozone layer and improving our understanding of chemistry-climate interactions from models.\r\n\r\nWMO-2018 refers to the Scientific Assessment of Ozone Depletion: 2018.\r\n\r\nSSP2-4.5 is a Shared Socio-economic Pathway scenario that follows socio-economic storyline SSP2 with intermediate mitigation and adaptation challenges and climate forcing pathway RCP4.5 which leads to a radiative forcing of 4.5 Wm-2 by the year 2100.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n- Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI)\r\n- A new set of Chemistry-Climate Model Initiative (CCMI) Community Simulations to Update the Assessment of Models and Support Upcoming Ozone Assessment Activities, David Plummer and Tatsuya Nagashima and Simone Tilmes and Alex Archibald and Gabriel Chiodo and Suvarna Fadnavis and Hella Garny and Beatrice Josse and Joowan Kim and Jean-Francois Lamarque and Olaf Morgenstern and Lee Murray and Clara Orbe and Amos Tai and Martyn Chipperfield and Bernd Funke and Martin Juckes and Doug Kinnison and Markus Kunze and Beiping Luo and Katja Matthes and Paul A. Newman and Charlotte Pascoe and Thomas Peter (2021), SPARC Newsletter, volume 57, pp 22-30\r\n\r\n- Chemical mechanisms and their applications in the Goddard Earth Observing System (GEOS) earth system model. Nielsen, J. E., Pawson, S., Molod, A., Auer, B., da Silva, A. M., Douglass, A. R., ... Wargan, K. (2017). Journal of Advances in Modeling Earth Systems, 9, 3019–3044. https://doi.org/10.1002/2017MS001011\r\n- Change in tropospheric ozone in the recent decades and its contribution to global total ozone. Liu, J., Strode, S. A., Liang, Q., Oman, L.D., Colarco, P. R., Fleming, E. L., et al. (2022). Journal of Geophysical Research: Atmospheres, 127, e2022JD037170. https://doi.org/10.1029/2022JD037170" }, "onlineresource_set": [] }, { "ob_id": 43616, "uuid": "14894c566ef541a7a4792e3bbc668281", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/dcmex/data/DCMEX_UM_CASIM", "numberOfFiles": 21818, "volume": 3222360333423, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43614, "uuid": "b850297a4de4493b8ff048f574811e25", "short_code": "ob", "title": "UM-CASIM Simulation Data for campaign cases from the DCMEX Project", "abstract": "This dataset contains output from the Unified Model - Cloud AeroSol Interacting Microphysics (UM-CASIM) model simulations of campaign case studies carried out as part of the Deep Convective Microphysics Experiment (DCMEX) project.\r\nThe simulation is designed to investigate cloud microphysics and convective processes under varying atmospheric conditions. It includes 1.5km gridded data of cloud and radiative properties, along with a number of other variables of potential interest such as precipitation and lightning. It is intended to support both process-level studies and model validation efforts. \r\nSingle level data is provided in files with suffixes \"pa000\" (time-averages) and \"px\" (instantaneous). Pressure level data is provided in files with suffixes \"pw\". Model level data is provided files with suffixes \"pz\".\r\nThese simulations utilise data collected during the DCMEX measurement campaign in July and August 2022, New Mexico, USA. https://dx.doi.org/10.5285/B1211AD185E24B488D41DD98F957506C\r\nThis research has been supported by the Natural Environment Research Council (grant nos. NE/T006420/1). Paul Field (UK Met Office) supported the simulation setup and experiment design." }, "onlineresource_set": [] }, { "ob_id": 43620, "uuid": "f82d6736bca647b4b0b5f86c6d1fb745", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/uk-decc-network/data/v25.01", "numberOfFiles": 129, "volume": 3419857009, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43618, "uuid": "040f19261fa24683988bff79b255f0a8", "short_code": "ob", "title": "Atmospheric trace gas observations from the UK Deriving Emissions linked to Climate Change (DECC) Network and associated data - Version 25.01", "abstract": "This version 25.01 dataset collection consists of atmospheric trace gas observations made as part of the UK Deriving Emissions linked to Climate Change (DECC) Network. It includes core DECC Network measurements, funded by the UK Government Department for Energy Security and Net Zero (TRN1028/06/2015, TRN1537/06/2018, TRN5488/11/2021 and prj_1604) and through the National Measurement System at the National Physical Laboratory, supplemented by observations funded through other associated projects. The core DECC network consists of five sites in the UK and Ireland measuring greenhouse and ozone-depleting gases.\r\n\r\nThe four UK-based sites (Ridge Hill, Herefordshire; Tacolneston, Norfolk; Bilsdale, North Yorkshire; and Heathfield, East Sussex) sample air from elevated inlets on tall telecommunications towers. Mace Head, situated on the west coast of Ireland, samples from an inlet within 10 metres of ground level and is ideally situated to intercept baseline air from the North Atlantic Ocean. The measurement site at Weybourne, Norfolk, funded by the National Centre for Atmospheric Science (NCAS) and operated by the University of East Anglia, is also affiliated with the network. Mace Head and Weybourne data are archived separately - see links in documentation. Data from the UK DECC network are used to assess atmospheric trends and quantify UK emissions, and feed into other international research programs, including the Integrated Carbon Observation System (ICOS) and Advanced Global Atmospheric Gases Experiment (AGAGE) networks." }, "onlineresource_set": [] }, { "ob_id": 43623, "uuid": "8092a1b4cb0f4537b4031c0cdce5413f", "short_code": "result", "curationCategory": "B", "dataPath": "/neodc/aatsr_multimission/atsr1-v4/data/AT_1_RBT", "numberOfFiles": 46785, "volume": 16464847690224, "fileFormat": "AT_1_RBT ESA SAFE Format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43622, "uuid": "6822dc77dcd34c85b015d5f8b40b4ce9", "short_code": "ob", "title": "ATSR-1: Multimission land and sea surface temperature data, 4th Reprocessing (v4) AT_1_RBT", "abstract": "The Along Track Scanning Radiometer1 (ATSR1) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThe ERS1 ATSR1 Level 1B Brightness Temperature/Radiance product (RBT) contains top of atmosphere (TOA) brightness temperature (BT) values for the infra-red channels on a 1-km pixel grid. Values for each channel and for the nadir and oblique views occupy separate NetCDF files within the Sentinel-SAFE format, along with associated uncertainty estimates. Additional files contain cloud flags, land and water masks, and confidence flags for each image pixel, as well as instrument and ancillary meteorological information.\r\n\r\nThis A/ATSR product [ENV_AT_1_RBT] in NetCDF format stemming from the 4th AATSR reprocessing, is a continuation of ERS ATSR data and a precursor of Sentinel-3 SLSTR data. It has replaced the former L1B product [_TOA_1P] in Envisat format from the 3rd reprocessing. Users with Envisat-format products are recommended to move to the new Sentinel-SAFE like/NetCDF format products. \r\n\r\nThe 4th reprocessing of ERS-1 ATSR-1 data was completed in 2023." }, "onlineresource_set": [] }, { "ob_id": 43628, "uuid": "cc04d6ec9b584736975a9d10ef2b5422", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ukmo-cet/data/v2.0.0.0/adjustments/", "numberOfFiles": 8, "volume": 16163, "fileFormat": "Data are BADC-CSV formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43592, "uuid": "1d2020153f84407ba2852acfd8579886", "short_code": "ob", "title": "Mean, Minimum and Maximum Central England Temperature (HadCET) series post 1973 static adjustments, v2.0.0.0", "abstract": "The Central England Temperature (HadCET) daily mean series is anchored to Gordon Manley’s original temperature record prior to 1973. Between 1848 and 1878, adjustments are applied to account for periods when only a single station was in use.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nFrom 1973 onwards, multiple adjustments ensure continuity with Manley’s series, homogenise the current station selection with Manley’s original dataset, and correct for the effects of increasing urbanisation.\r\n \r\nThese static adjustments are calculated on a monthly basis and are applied uniformly to all daily values within each month from 1973 to the present. \r\n \r\nUrbanisation adjustments remain static from November 2004 onward, while adjustments between 1974 and October 2004 are graded to reflect a progressive increase in urbanisation effects over time.\r\n \r\nThis dataset contains the post-Manley extended adjustments, station homogenisation adjustments, and static urban corrections.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n\r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "onlineresource_set": [] }, { "ob_id": 43629, "uuid": "d449117727e14fc98f1c3264a4ad2994", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ukmo-cet/data/v2.0.0.0/daily/", "numberOfFiles": 4, "volume": 3070938, "fileFormat": "Data are BADC-CSV formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43589, "uuid": "0363d592dd3548febaa6fc4056a618a9", "short_code": "ob", "title": "Daily Mean, Minimum and Maximum Central England Temperature series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) daily series start in 1772 for mean temperature and 1878 for minimum and maximum temperature.\r\n \r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nPrior to 1973, the daily mean temperature series is anchored to the mean temperature series constructed by Gordon Manley, with the daily minimum and maximum temperature series adjusted to the mean temperature series to ensure values are consistent.\r\n \r\nAlthough the station selection has changed through time, the series is homogenised and adjusted to ensure consistency with Manley's selection and for periods when only a single station value was used.\r\n \r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nFor more information on the change in station selection, please refer to the papers supplied with the data collection.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "onlineresource_set": [] }, { "ob_id": 43630, "uuid": "d3eaeb59dd2a446ba2b8f3261791fba0", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ukmo-cet/data/v2.0.0.0/monthly/", "numberOfFiles": 7, "volume": 149125, "fileFormat": "Data are BADC-CSV formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43590, "uuid": "6d41468a8cd4462e923b4fc4f28b2dda", "short_code": "ob", "title": "Monthly Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) monthly series start in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe monthly temperature series are derived as the mean of the daily temperature series values.\r\n \r\nFor mean temperature, the monthly values from 1659 to 1771 are derived directly from Gordon Manley's monthly mean values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "onlineresource_set": [] }, { "ob_id": 43631, "uuid": "552fbbdebde548a7a3aa98ba44c8a3b3", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ukmo-cet/data/v2.0.0.0/seasonal/", "numberOfFiles": 7, "volume": 67625, "fileFormat": "Data are BADC-CSV formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43591, "uuid": "06f14deceb27463c86f350ad278245ca", "short_code": "ob", "title": "Seasonal Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) seasonal series starts in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe seasonal temperature series are derived as the mean of the monthly temperature series values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "onlineresource_set": [] }, { "ob_id": 43634, "uuid": "463a254361114864923b38a083f2b0ae", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/tls/data/raw/malaysia/MLA-01/2018-07-17.001.riproject", "numberOfFiles": 2115, "volume": 112925085258, "fileFormat": "Point cloud data in RIEGL proprietry .rxp format, image data in .jpg format and matrix data in text file.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43635, "uuid": "844bd5c5bc9940d6b04cd35bd9c8b956", "short_code": "ob", "title": "TLS-ARCH terrestrial laser scanner data: Maliau Basin (MLA-01), July 2018", "abstract": "This dataset is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at Plot MLA-01 (Belian) is part of the Global Ecosystem Monitoring (GEM) network and is located in the rainforests of Malaysian Borneo.\r\n\r\nTLS data was collected on a 10 m x 10 m grid where at each position the scanner captured data in an upright and tilted position. The scanner was set to an angular step of 0.04 degrees and 0.02 degress for upright and tilted scans respectively. In between each scan position a set of retro-reflective targets were positioned to be used as tie-points between scans. For more information on TLS acquisition refer to Wilkes et al. (2017). Scan data was coregistered using RiSCAN Pro, the 4x4 rotation transformation matrices to trasnform the point cloud data into a common reference coordinate system can be found in the \"matrix\" directory." }, "onlineresource_set": [] }, { "ob_id": 43648, "uuid": "686a5c08e803446c9e5c93db1acae3d5", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/forestscan/data/gabon/lope/UAV_PointCloudData_lope_2022", "numberOfFiles": 151, "volume": 15795008315, "fileFormat": "Point cloud data .las files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 40868, "uuid": "7a4649cabd3e4afb8cd31cfd7d95ac8e", "short_code": "ob", "title": "ForestScan project: Unpiloted Aerial Vehicle LiDAR Scanning (UAV-LS) data of FBRMS-02: Station d’Etudes des Gorilles et Chimpanzés, Lopé National Park, Gabon, June 2022", "abstract": "This dataset contains point cloud data (a set of data points in a 3D coordinate system) which were collected using a RIEGL miniVUX1-DL LiDAR scanner mounted on a DELAIR DT26X Unpiloted Aerial Vehicle (UAV). The data was collected in June 2022 as part of the ForestScan project. The person responsible for the data collection was Dr. Iain McNicol from the University of Edinburgh, who collected and processed the data." }, "onlineresource_set": [] }, { "ob_id": 43655, "uuid": "ef368695b9094ce4ba7d9b967573cf90", "short_code": "result", "curationCategory": "", "dataPath": "/badc/deposited2025/FAMOUS-BISICLES_data", "numberOfFiles": 486, "volume": 56194513174, "fileFormat": "net-CDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43573, "uuid": "4ce75927eab444b89b5439e33ecf1a80", "short_code": "ob", "title": "FAMOUS-BISICLES simulation data with interactive Northern Hemisphere ice sheets (21ka and 140ka)", "abstract": "This dataset contains model inputs and outputs from ensembles of simulations and sensitivity tests performed by FAMOUS-BISICLES of the Last Glacial Maximum (LGM; 21 kilo annum before present (ka BP)) and the Penultimate Glacial Maximum (PGM; 140 ka BP), as used in the publication Patterson et al., 2025 (https://doi.org/10.5194/egusphere-2024-3896) \r\n\r\nThese data were used to explore the sensitivity of the ice sheets to uncertain model parameters. The output of 120 ensemble members varying climate and ice sheet model parameters for each of the LGM and PGM are included as well as the results of sensitivity tests varying the spatial resolution and till water drainage rate. These simulations were created using the atmospheric general circulation model FAMOUS coupled to the BISICLES ice sheet model under LGM and PGM climate boundary conditions, including greenhouse gas concentrations and orbital parameters outlined in the PMIP4 (Paleoclimate Modelling Intercomparison Project - Phase 4) protocols (Kageyama et al., 2017 and Menviel et al., 2019)." }, "onlineresource_set": [] }, { "ob_id": 43665, "uuid": "0198fe379fec4fea90f1cfbd8cd6641f", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2025/BLEACH_York_TILDAS_Bermuda/", "numberOfFiles": 4, "volume": 29680, "fileFormat": "badc-csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43656, "uuid": "c5545d7d3b7b405e8607afb8b2e581f2", "short_code": "ob", "title": "Bermuda boundary Layer Experiment: Gas phase hydrogen chloride measurements from TILDAS instrument", "abstract": "This dataset contains hydrochloride concentration measurements from the University of York's Tunable Infrared Laser Direct Absorption Spectrometer (TILDAS). This instrument is situated on top of a 10-metre high tower at the Bermuda Institute of Ocean Sciences (BIOS) Tudor Hill Marine Atmospheric Observatory (THMAO) in Bermuda during the Bermuda boundary Layer Experiment of the Atmospheric Chemistry of Halogens (BLEACH) campaigns. The summer BLEACH campaign took place during June 2022 and the Winter BLEACH campaign took place during January/Febrauary 2023. \r\nTILDAS 1hz data have been averaged to hourly intervals, associated with the timestamp at the start of the hour, and filtered to exclude periods impacted by instrument issues and power outages. A background correction method has been applied to account for issues with background measurements.\r\nThese measurements will provide a quantitative observational constraint for the dependence of reactive halogen abundances on pollution levels, as well as allow us to assess the model's representation of the abundance and speciation of reactive halogens at a tropical, marine location and their interactions with one another." }, "onlineresource_set": [] }, { "ob_id": 43673, "uuid": "760e091bfc90471ea62d62c90902540b", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISD/subdaily/HadISDTable/r1/v3-4-1-2024f/", "numberOfFiles": 9972, "volume": 57206088098, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43669, "uuid": "2a01faf75de64308b2bf4c7b43d393ef", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2024, v3.4.1.2024f", "abstract": "This is version v3.4.1.2024f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20250101_v3.4.1.2024f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, "onlineresource_set": [] }, { "ob_id": 43686, "uuid": "07c8af4f754941f0b52067e7738b5380", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ncas-mobile/data/ncas-mobile-x-band-radar-1/20230525_woest/", "numberOfFiles": 44022, "volume": 2212414678710, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43685, "uuid": "7746b6b9a5b044ddbc0d2a172b9a8b5f", "short_code": "ob", "title": "WOEST: Scan data from the NCAS mobile X-band radar unit 1 deployed at MOD Lyneham, v1.0.0 (20230525-20230908)", "abstract": "Scan data from the National Centre for Atmospheric Science Atmospheric Measurement and Observation Facility's mobile X-band radar unit 1 deployed at MOD Lyneham, near Swindon, Wiltshire, UK (51.5071N, -2.00547E) from May to September 2023. These observations were taken as part of the WesCon - Observing the Evolving Structures of Turbulence (WOEST) project between 20230525 and 20230908.\r\n\r\nData products from this deployment include: volume scans (vol) and vertical cross sections (rhi). The radar performed two sets of volume scans, alternating approximately every 5 minutes, using different parameters for targeting the boundary layer and clouds. Following the volume scans the radar performed a single vertical cross-section. The whole cycle repeated every 10 minutes. \r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "onlineresource_set": [] }, { "ob_id": 43703, "uuid": "4af3d0bd8261485ca6a6fabc4ab5c39e", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/land-surface-derived", "numberOfFiles": 6, "volume": 76819799, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43643, "uuid": "19c5dc39bb8c4c40a5643678c31168e7", "short_code": "ob", "title": "Met Office Cardington: Land surface model (LSM) meteorological driving data, 2005-2024", "abstract": "The Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024, compiled a forcing meteorological dataset for the Cardington site to drive the JULES standalone land surface model (LSM) that covers the whole year 2005-2024 data record, albeit only based on 30 min temporal resolution. JULES is the UK community LSM that is used in the Met Office Unified Model (MetUM) from short-range weather forecasts through to climate predictions, from global coverage down to a single point. JULES requires the following seven atmospheric input variables at every time step for it to able to run using prescribed meteorology from field observations: downwelling shortwave irradiance, downwelling longwave irradiance, rainfall, air temperature, mean horizontal wind, surface barometric pressure, and specific humidity. \r\n\r\nThe drive dataset is a NetCDF file for each of the four drive heights (2, 10, 25 and 50 m), such that temperature, wind and humidity drive variables are taken from the different mast heights, with the pressure, radiation and rainfall remaining unchanged as they were only available from fixed levels (i.e. pressure at 1.2 m, downwelling radiation at 4 m, upwelling radiation at 2 m, and rainfall at the surface).\r\n\r\nThe corresponding 4 files have the following temporal ranges:\r\n\r\n - 2 m drive height: 20120101-0000 to 20241231-2330\r\n - 10 m drive height: 20050101-0000 to 20241231-2330\r\n - 25 m drive height: 20050101-0000 to 20241231-2330\r\n - 50 m drive height: 20050101-0000 to 20241231-2330\r\n\r\nTimes are in UTC.\r\n\r\nThe 2 m level is limited to the whole years 2012–2024. Although the netCDF drive dataset has been configured to run with JULES, it should be straightforward to apply the data within it to other LSMs that can be run offline and forced by prescribed meteorology for a single point.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "onlineresource_set": [] }, { "ob_id": 43704, "uuid": "8bdf994c46c840f19d8ed412577fa42f", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/disdrometer/thies", "numberOfFiles": 1533, "volume": 4269163190, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43602, "uuid": "5d8997e0cd974835999a8d8ba677b26f", "short_code": "ob", "title": "Met Office Cardington: precipitation measurements from a Thies disdrometer, 2019-2024", "abstract": "The Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024, operated the Thies laser disdrometer, a laser optical device used for the measurement of diameter and fall velocity of hydrometeors, from 2019 to 2024. From such measurements, it is possible to classify different types of precipitation, such as drizzle, rain, hail, snow, and mixed precipitation, quantify precipitation in a time interval, and derive size and velocity joint distribution. Thies laser disdrometer can in addition detect fine drizzle, drop fall speed and drop size distribution.\r\n\r\nThe disdrometer is the most sophisticated precipitation instrument deployed at Cardington.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset." }, "onlineresource_set": [] }, { "ob_id": 43705, "uuid": "c78b3c61d08f4cb99e299065b9c32802", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/lidar/halo-lidar-01", "numberOfFiles": 11056, "volume": 194670361799, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43603, "uuid": "ba87087355ed4e748d1650d012adc4ef", "short_code": "ob", "title": "Met Office Cardington: vertical wind profiles and backscatter measurements from Halo Doppler Lidar unit 01, 2009-2021", "abstract": "The Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024, operated three Halo Photonics Streamline Doppler lidars, denoted by unit numbers 01, 30 and 35. This dataset covers data from unit 01.\r\n\r\nAll three Halo systems were based on a 1565 nm laser emitting linearly polarised pulsed light through an 8 cm diameter lens with a heterodyne detector. Laser beam returns from the atmosphere are range-gated velocity and back-scattered power. The Halo systems are capable of full hemispheric scanning of the backscatter coefficient and radial velocity as a function of beam range.\r\n\r\nThe usual operation at Cardington was vertical stares (zenith angle=0°) with periodic wind scans that invoked various options of off-axis views. Wind profiles performed every 30 min was the default operation for wind scans. Most profiles of horizontal wind within the dataset are based on DBS (Doppler beam swinging) scans which use a tri-axis azimuthally orthogonal technique using the single lidar beam to retrieve horizontal mean wind components. This scan was chosen for the bulk of the time because it only takes about 21 s to complete, which leaves 98% of the available time to vertical stares if one wind scan is completed every 30 min. More recent scans in the dataset have used multi-axis VAD (velocity azimuth display) scans, which are a more involved version of the DBS scans and use 6 or 12 point off-zenith views. The vertical stares, DBS and VAD wind scans produced separate archived netCDF files.\r\n\r\nAlthough depolarisation capability was possible with #35, this was only switched on occasionally during certain weather conditions.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "onlineresource_set": [] }, { "ob_id": 43706, "uuid": "1f80b2aadbb54215ad17858a98cb6bae", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/lidar/halo-lidar-30", "numberOfFiles": 7630, "volume": 1040145624066, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43604, "uuid": "6ebd987dac6f4d1692d878258bf7112c", "short_code": "ob", "title": "Met Office Cardington: vertical wind profiles and backscatter measurements from Halo Doppler Lidar unit 30, 2011-2022", "abstract": "The Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024, operated three Halo Photonics Streamline Doppler lidars, denoted by unit numbers 01, 30 and 35. This dataset covers data from unit 30.\r\n\r\nAll three Halo systems were based on a 1565 nm laser emitting linearly polarized pulsed light through an 8 cm diameter lens with a heterodyne detector. Laser beam returns from the atmosphere are range-gated velocity and back-scattered power. The Halo systems are capable of full hemispheric scanning of the backscatter coefficient and radial velocity as a function of beam range.\r\n\r\nThe usual operation at Cardington was vertical stares (zenith angle=0°) with periodic wind scans that invoked various options of off-axis views. Wind profiles performed every 30 min was the default operation for wind scans. Most profiles of horizontal wind within the dataset are based on DBS (Doppler beam swinging) scans which use a tri-axis azimuthally orthogonal technique using the single lidar beam to retrieve horizontal mean wind components. This scan was chosen for the bulk of the time because it only takes about 21 s to complete, which leaves 98% of the available time to vertical stares if one wind scan is completed every 30 min. More recent scans in the dataset have used multi-axis VAD (velocity azimuth display) scans, which are a more involved version of the DBS scans and use 6 or 12 point off-zenith views. The vertical stares, DBS and VAD wind scans produced separate archived netCDF files.\r\n\r\nAlthough depolarisation capability was possible with #35, this was only switched on occasionally during certain weather conditions.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "onlineresource_set": [] }, { "ob_id": 43707, "uuid": "b35117a21f6849c6a5abd5059f33f762", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/lidar/halo-lidar-35", "numberOfFiles": 7165, "volume": 856666272579, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43617, "uuid": "77bef4103ec2426281a5e74ccc0ba5c7", "short_code": "ob", "title": "Met Office Cardington: vertical wind profiles and backscatter measurements from Halo Doppler Lidar unit 35, 2012-2024", "abstract": "The Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024, operated three Halo Photonics Streamline Doppler lidars, denoted by unit numbers 01, 30 and 35. This dataset covers data from unit 35.\r\n\r\nAll three Halo systems were based on a 1565 nm laser emitting linearly polarized pulsed light through an 8 cm diameter lens with a heterodyne detector. Laser beam returns from the atmosphere are range-gated velocity and back-scattered power. The Halo systems are capable of full hemispheric scanning of the backscatter coefficient and radial velocity as a function of beam range.\r\n\r\nThe usual operation at Cardington was vertical stares (zenith angle=0°) with periodic wind scans that invoked various options of off-axis views. Wind profiles performed every 30 min was the default operation for wind scans. Most profiles of horizontal wind within the dataset are based on DBS (Doppler beam swinging) scans which use a tri-axis azimuthally orthogonal technique using the single lidar beam to retrieve horizontal mean wind components. This scan was chosen for the bulk of the time because it only takes about 21 s to complete, which leaves 98% of the available time to vertical stares if one wind scan is completed every 30 min. More recent scans in the dataset have used multi-axis VAD (velocity azimuth display) scans, which are a more involved version of the DBS scans and use 6 or 12 point off-zenith views. The vertical stares, DBS and VAD wind scans produced separate archived netCDF files.\r\n\r\nAlthough depolarisation capability was possible with #35, this was only switched on occasionally during certain weather conditions.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "onlineresource_set": [] }, { "ob_id": 43708, "uuid": "0b0e102a48e1431abccda61c58cadc64", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/microwave-radiometer/wvr1100", "numberOfFiles": 6858, "volume": 4360834295, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43606, "uuid": "21c423889e6a4035ac7f4761e467de2b", "short_code": "ob", "title": "Met Office Cardington: column integrations of liquid water and water vapour from a Radiometrics WVR-1100 microwave radiometer, 2002-2022", "abstract": "The Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024, operated the Radiometrics WVR-1100 passive microwave radiometer measuring the atmospheric emissions at two frequencies (23.8 and 31.4 GHz) which provided brightness temperature at these channels, retrieve column integrations of liquid water path and integrated water vapour.\r\n\r\nThe WVR-1100 used a bi-linear regression method based on local radiosonde launches to retrieve column integrations of liquid water and water vapour. The WVR-1100 in addition performed ‘tipping curve’ observations using off-zenith slant scans where the optical depth for each frequency varies in a known way with atmospheric geometrical thickness. Tipping curves assume the atmosphere is horizontally homogeneous. The overall error in liquid water path is estimated to be 0.015 kg m-2. Water vapour and liquid water column amounts were logged typically every 9-10 s. Absolute calibrations for the absorbing channels were done periodically using an external black body cooled with liquid nitrogen.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "onlineresource_set": [] }, { "ob_id": 43709, "uuid": "200f7025d92f4861a47f82718f972c05", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/microwave-radiometer/humpro", "numberOfFiles": 1904, "volume": 23699537696, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43605, "uuid": "9bf50847dd4d49a281d5663d512e1646", "short_code": "ob", "title": "Met Office Cardington: humidity profiles, liquid water paths and integrated water vapour measurement from a RPG Humpro microwave radiometer, 2016-2024", "abstract": "The Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024, operated the RPG Humpro profiling microwave radiometer retrieving humidity profiles in addition to the liquid water paths and integrated water vapour paths using brightness temperatures measured at seven microwave frequencies between 22.24 and 31.4 GHz (this band in general being sensitive to water vapour and cloud). The liquid and vapour water path retrievals used a supplied neural network algorithm (which is trained with radiosonde data using a radiative transfer scheme). Two archived files are available, based on the time series (water vapour and liquid water) and profile (humidity) data.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "onlineresource_set": [] }, { "ob_id": 43716, "uuid": "0e2651e9a052470cb2a5cd8ad5670b73", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/microwave-radiometer/wvp-3000", "numberOfFiles": 556, "volume": 1959573316, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43642, "uuid": "d44b15c8f183404ca47291bc677f93e0", "short_code": "ob", "title": "Met Office Cardington: column integrations of liquid water and water vapour from a Radiometrics TP/WVP-3000 microwave radiometer, 2011-2016", "abstract": "The Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024, operated the Radiometrics TP/WVP-3000 microwave radiometer using a neural network to retrieve profiles of water vapour and temperature. The TP/WVP-3000 was set up to take readings in the vertical approximately every 8 s. Regular tipping curve scans were done over a range of zenith angles (30, 45, 90, 135, 150 degrees) to compare the atmospheric radiances to that of known values at relatively opaque water vapour frequencies (with the opacity being a linear function of the slant path), in addition using frequent views of an internal temperature-controlled black body. Absolute calibrations for the absorbing channels were done periodically using a black body cooled with liquid nitrogen.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "onlineresource_set": [] }, { "ob_id": 43722, "uuid": "c07a1dce38eb4c89a26d83900a530aeb", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ncas-mobile/data/ncas-radar-x-band-2/20230525_woest/v1.0.0", "numberOfFiles": 47126, "volume": 2041828389830, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43721, "uuid": "0affc94eb312459e840d957d4401018e", "short_code": "ob", "title": "WOEST: Scan data from the NCAS mobile X-band radar unit 2 deployed at from Chilbolton Atmospheric Observatory, v1.0.0 (20230525-20230913)", "abstract": "Scan data from the National Centre for Atmospheric Science Atmospheric Measurement and Observation Facility's mobile X-band radar unit 2 deployed at Chilbolton Atmospheric Observatory, near Andover, Hampshire, UK from May to September 2023. These observations were taken as part of the (WesCon) experiment - Observing the Evolving Structures of Turbulence (WOEST) project between 20230525 and 20230913.\r\n\r\nData products from this deployment include: volume scans (vol) and vertical cross sections (rhi). The radar performed two sets of volume scans, alternating approximately every 5 minutes, using different parameters for targeting the boundary layer and clouds. Following the volume scans the radar performed a single vertical cross-section. The whole cycle repeated every 10 minutes. \r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "onlineresource_set": [] }, { "ob_id": 43744, "uuid": "ed4d385a64684059b806e0777eca2915", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-cardington/data/complete-collection/sonde/vaisala", "numberOfFiles": 1892, "volume": 695754351, "fileFormat": "Data are NetCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43607, "uuid": "5934d2a5706c4a3c9caa15188d9ed24b", "short_code": "ob", "title": "Met Office Cardington: vertical profile measurements from Vaisala radiosonde ascents, 1996-2024", "abstract": "This repository provides data from all radiosondes launched at Cardington between 1996-2024.\r\nThe sonde unit was operated by the Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England.\r\n\r\nSonde launches were performed with a mean ascent rate of 2.5 m s-1. The slower ascent rate compared to an operational sonde ascent rate enables improved vertical sampling resolution in the atmospheric boundary layer whilst maintaining a sufficient ventilation rate over the sensors. From 1996-2002, a RS80 device was used with ThermoCap, HumiCap, BaroCap sensors, and between 2006-2014 a RS92-SGPB device was used with ThermoCap, HumiCap, capacitive pressure sensors. Sonde launches from 2014-2024 used an RS41-SG(P) device with PRT, silicon capacitive pressure (SGP), and HumiCap sensors.\r\n\r\nThe launches of radiosondes were performed on a project related basis only and all available ascent data has been provided from the Cardington facility. Please note that there were no ascents in 2022.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "onlineresource_set": [] }, { "ob_id": 43752, "uuid": "415369ec1d134465a657512985e802e2", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ncas-mobile/data/ncas-radar-wind-profiler-1/20020711_capel-dewi/v8.0", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 43754, "uuid": "a0e2736f5e23401f96062513f558af7e", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ncas-mobile/data/ncas-radar-wind-profiler-1/20020711_capel-dewi/v8.0", "numberOfFiles": 13, "volume": 8153235, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 43753, "uuid": "b3438d6d5f634c39af57335df1febe6f", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the NCAS Capel Dewi Atmospheric Observatory (CDAO), v8.0 (20020711-20020726)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the NCAS Capel Dewi Atmospheric Observatory (CDAO). These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20020711 and 20020726.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "onlineresource_set": [] } ] }