This dataset contains global, monthly marine phytoplankton primary production products (in mg C m-2 d-1) for the period of 1998 to 2018 at 9 km spatial resolution. Data are provided in NetCDF format. Primary production by marine phytoplankton was modelled using ocean-colour remote sensing products and a spectrally-resolved primary production model that incorporates the vertical structure of phytoplankton and simulates changes in photosynthesis as a function of irradiance using a two-parameter photosynthesis versus irradiance (P-I) function (see Kulk et al. 2020, Sathyendranath et al. 2020a, and references therein for details). Chlorophyll-a products were obtained from the European Space Agency (ESA) Ocean Colour Climate Change Initiative (OC-CCI v4.2 dataet). Photosynthetic Active Radiation (PAR) products were obtained from the National Aeronautics and Space Administration (NASA) and were corrected for inter-sensor bias in products. In situ datasets of chlorophyll-a profile parameters and P-I parameters were incorporated as described in Kulk et al. (2020). The primary production products were generated as part of the ESA Living Planet Fellowship programme ‘Primary production, Index of Climate Change in the Ocean: Long-term Observations’ (PICCOLO). Support from the Simons Foundation grant ‘Computational Biogeochemical Modeling of Marine Ecosystems’ (CBIOMES, number 549947), from the ESA Biological Pump and Carbon Exchange Processes (BICEP) project and from the National Centre of Earth Observation (NCEO) is acknowledged. Data are provided as netCDF files containing global, monthly marine phytoplankton primary production products (in mg C m-2 d-1) for the period of 1998 to 2020 at 9 km spatial resolution. References: Kulk, G.; Platt, T.; Dingle, J.; Jackson, T.; Jönsson, B.F.; Bouman, H.A., Babin, M.; Doblin, M.; Estrada, M.; Figueiras, F.G.; Furuya, K.; González, N.; Gudfinnsson, H.G.; Gudmundsson, K.; Huang, B.; Isada, T.; Kovac, Z.; Lutz, V.A.; Marañón, E.; Raman, M.; Richardson, K.; Rozema, P.D.; Van de Poll, W.H.; Segura, V.; Tilstone, G.H.; Uitz, J.; van Dongen-Vogels, V.; Yoshikawa, T.; Sathyendranath S. Primary production, an index of climate change in the ocean: Satellite-based estimates over two decades. Remote Sens. 2020, 12, 826. doi:10.3390/rs12050826 Sathyendranath, S.; Platt, T.; Žarko K.; Dingle, J.; Jackson, T.; Brewin, R.J.W.; Franks, P.; Nón, E.M.; Kulk, G.; Bouman, H. Reconciling models of primary production and photoacclimation. Appl. Opt. 2020a, 59, C100-C114. doi.org/10.1364/AO.386252.

Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 8 for Co-ordinated Airborne Studies in the Tropics (CAST) project.

WCRP CMIP5: Institut Pierre-Simon Laplace (IPSL) IPSL-CM5A-LR model output for the aqua planet plus 4K anomaly (aqua4K) experiment. These data cover the following realms: aerosol, atmos, land and ocean; at the following frequencies: 3hr, 6hr, day, fx and mon. The runs included the ensemble members: r0i0p0, r1i1p1 and r2i1p1. The WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5).

ARSF project GB08/19: Investigating the Urban Energy Balance of London. Led by: Prof. Martin Wooster, Environmental Monitoring & Modelling Research Group, Department of Geography, King's College London, Strand, London, WC2R 2LS, UK. Location: London, UK.

The European Arctic Stratospheric Ozone Experiment is a European Commission (EC) measurement campaign undertaken in the Northern Hemisphere winter of 1991-92 to study ozone chemistry and dynamics. This dataset contains ozone and meteorology measurements.

WCRP CMIP5: National Centers for Environmental Prediction (NCEP) CFSv2-2011 model output for the 10-year hindcast/prediction initialized in year 1985 (decadal1985) experiment. These data cover the following realms: atmos, land, landIce, ocean and seaIce; at the following frequencies: fx and mon. The runs included the ensemble members: r0i0p0, r1i1p1, r2i1p1, r3i1p1 and r4i1p1. The WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5).

Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 12 for BORTAS: Quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites project.

The European Arctic Stratospheric Ozone Experiment is a European Commission (EC) measurement campaign undertaken in the Northern Hemisphere winter of 1991-92 to study ozone chemistry and dynamics. This dataset contains vertical column measurements of NO2 and O3.

The BGS Debris Flow Susceptibility Model for Great Britain v6.1 is a 1:50 000 scale raster dataset of Great Britain providing 50 m ground resolution information on the potential of the ground, at a given location, to form a debris flow. It is based on a combination of geological, hydrogeological and geomorphological data inputs and is primarily concerned with potential ground stability related to natural (rather than man-made) geological conditions and slopes. The dataset is designed for those interested specifically in debris flow susceptibility at a regional or national planning scale such as those involved in construction or maintenance of infrastructure networks (road or rail or utilities), or other asset managers such as for property (including developers and home owners), loss adjusters, surveyors or local government. The dataset builds on research BGS has conducted over the past 15 years investigating debris flows. The model was designed to identify potential source-areas for debris flows rather than locate where material may be deposited following a long-run-out failure i.e. the track and flow of debris. This work focuses on natural geological and geomorphological controls that are likely to influence the initiation of debris flows. It therefore, does not consider the influence of land use or land cover factors.

This is version v3.4.0.2023f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data. This update (v3.4.0.2023f) to HadISD corrects a long-standing bug which was discovered in autumn 2023 whereby the neighbour checks (and associated [un]flagging for some other tests) were not being implemented. For more details see the posts on the HadISD blog: https://hadisd.blogspot.com/2023/10/bug-in-buddy-checks.html & https://hadisd.blogspot.com/2024/01/hadisd-v3402023f-future-look.html The 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. The 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_19310101-20230101_v3.4.1.2023f.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. To keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS. For more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/ References: When 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) : Dunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note. Dunn, 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. Dunn, 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 Smith, 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 For a homogeneity assessment of HadISD please see this following reference Dunn, 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.