The National Centre for Earth Observation (NCEO): Monthly global Particulate Organic Carbon (POC) dataset contains POC concentrations gridded on both sinusoidal (SIN) and geographic (GEO) grid projections at 4 km spatial resolution for 1997-2020. The POC dataset has been produced using the Ocean Colour Climate Change Initiative Remote Sensing Reflectance (Rrs) products, Version 4.2. The dataset includes the Rrs at 443 nm and 555 nm with pixel-by-pixel uncertainty estimates for each wavelength. For more details on the algorithm and its validation, please see papers by Stramski et al. (2008) and Evers-King et al. (2017). Please note that the validation of the POC algorithm is a continuing process. To increase the accuracy of POC algorithms, further in situ POC data need to be collected with high spatial and temporal resolution.

The BICEP/NCEO: Monthly global Particulate Organic Carbon (POC) v5 datasets contain POC concentrations (mg m^-3) with per pixel uncertainties estimates gridded on both geographic and sinusoidal projections at 4 km spatial resolution for the period of 1997 to 2020. The POC products were generated as part of the European Space Agency (ESA) Biological Pump and Carbon Exchange Processes (BICEP) project with support from the National Centre of Earth Observation (NCEO). The POC datasets have been produced by using a modified empirical band ratio algorithm by Stramski et al. (2008): 292*Rrs(490)/Rrs(560)^-1.49. Additional variables that were used for the calculation of the POC products are also provided in the datasets, including the Remote Sensing Reflectance (Rrs) at 490 nm and 560 nm obtained from the ESA Ocean Colour Climate Change Initiative version 5 dataset (OC-CCI v5). For more details on the algorithm and its validation, please see the BICEP Algorithm Theoretical Basis Document (ATBD) and validation report (https://bicep-project.org/Home). A related dataset based on the ESA Ocean Colour Climate Change Initiative v4.2 data is also available (see link in the related records section).

The BICEP/NCEO: Monthly global Particulate Organic Carbon (POC) v4.2 datasets contain POC concentrations (mg m^-3) with per pixel uncertainties estimates gridded on both geographic and sinusoidal projections at 4 km spatial resolution for the period of 1997 to 2020. The POC products were generated as part of the European Space Agency (ESA) Biological Pump and Carbon Exchange Processes (BICEP) project with support from the National Centre of Earth Observation (NCEO). The POC concentrations were estimated using an empirical Remote Sensing Reflectance (Rrs) band ratio algorithm by Stramski et al. (2008): 203.2*Rrs(443)/Rrs(555)^-1.034. This algorithm has shown a relatively good performance in the recent global inter-comparison study conducted by Evers-King et al. (2017). Additional variables that were used for the calculation of the POC products are also provided in the datasets, including the Rrs at 443 nm and 555 nm obtained from the ESA Ocean Colour Climate Change Initiative version 4.2 dataset (OC-CCI v4.2)(Sathyendranath et al., 2020). In addition to the papers by Stramski et al. (2008) and Evers-king et al. (2017), for more details on the algorithm and its validation, please see the BICEP Algorithm Theoretical Basis Document (ATBD) and validation report (https://bicep-project.org/Home). This version of the dataset is an updated version of the previous 'NCEO: Monthly global Particulate Organic Carbon (POC) (produced from the Ocean Colour Climate Change Initiative, Version 4.2 dataset)'. A related product based on the Ocean Colour Climate Change Initiative v5.0 data is also available (see the link in the related records section).

The COAPEC (Coupled Ocean-Atmosphere Processes and European Climate) programme was a 5 year NERC thematic programme designed to examine the variability of the Earth's climate. Interactions between the oceans and the atmosphere play a major role in governing this variability. The goal of COAPEC was to determine the impact on climate, especially European climate, of the coupling between the Atlantic Ocean and the atmosphere, including the influence of ENSO on this coupling. To aid researchers within the COAPEC programme, datasets have been retrieved from a variety of coupled models. * 100 years (2079 - 2178) monthly means of all atmospheric and oceanic fields derived from the control run of the Hadley Centre HadCM3 model. * 1000 years (1849-2849) of monthly means of selected parameters from the HadCM3 control run. * 50 years (1950-2000) of MOM (GFDL Modular Ocean Model) data. * Output from the 100 year HadCM3 control integration produced using UM4.5 on the BADC Beowulf Cluster. * Surface flux climatology data from SOC If using the 100 year dataset from the Hadley Centre, please be aware that the run was restarted part of the way through. This means that there is a difference in the indicated date of origin in the data files, and can cause a discontinuity if not corrected for during analysis. The 1000 year HadCM3 dataset has been extracted from the Met Office and these data have been added to the archive. The data from a 500 year HadCM3 control integration performed on a linux Beowulf cluster using UM version 4.5 at the BADC has been included in the archive. Please see the README.txt for more information.

The VOCALS [VAMOS (Variability of the American Monsoon System) Ocean Cloud Atmosphere Land Study Regional Experiment] campaign was a large multi-national field campaign that has been established to investigate the coupled processes that control the climate of the South-East Pacific region. This includes the variety of interactions between the ocean surface, the overlying atmosphere and the neighbouring land. A particular focus for the Facility for Airborne Atmospheric Measurements (FAAM) aircraft studies was the sources of natural and anthropogenic aerosol and an understanding of their physical and chemical properties and a study of the interactions of this aerosol with the persistent stratocumulus cloud in the maritime atmospheric boundary layer. The campaign made use of instruments on board the FAAM BAe-146 aircraft to determine the strength and temperature dependence.

This dataset contains global spatially predicted sea-surface iodide concentrations at a monthly resolution for the year 1970. It was developed as part of the NERC project Iodide in the ocean:distribution and impact on iodine flux and ozone loss (NE/N009983/1), which aimed to quantify the dominant controls on the sea surface iodide distribution and improve parameterisation of the sea-to-air iodine flux and of ozone deposition. This dataset is the output used in the published paper 'A machine learning based global sea-surface iodide distribution' ( https://doi.org/10.5194/essd-2019-40). The main ensemble prediction ("Ensemble_Monthly_mean ") is provided in a NetCDF file as a single variable (1). A second file (2) is provided which includes all of the predictions and the standard deviation on the prediction. (1) predicted_iodide_0.125x0.125_Ns_Just_Ensemble.nc (2) predicted_iodide_0.125x0.125_Ns_All_Ensemble_members.nc For ease of use, this output has been re-gridded to various commonly used atmosphere and ocean model resolutions (see table SI table A5 in paper). These re-gridded files are included in the folder titled "regridded_data". Additionally, a further file (3) is provided including the prediction made included data from the Skagerak dataset. As stated in the paper referenced above, it is recommended to use the use the core files (1,2) or their re-gridded equivalents. (3) predicted_iodide_0.125x0.125_All_Ensemble_members.nc As new observations are made, this global data product will be updated through a "living data" model. The dataset versions follow semantic versioning (https://semver.org/). This dataset contains the first publicly released version v0.0.1 and supersedes the pre-review dataset named v0.0.0, Please refer to the paper referenced above for the current version number and information on this. Updates for v0.0.1 vs. v0.0.0 - Additional files included of the core data re-gridded for 0.5x0.5 degree and 0.25x0.25 degree horizontal resolution. - Minor updates were applied to all metadata in NetCDF files. - Updates were made to coordinate grids used for regriding files from 1x1 degree to 4x5 degree.

This dataset contains global spatially predicted sea-surface iodide concentrations at a monthly resolution. This dataset was developed as part of the NERC project Iodide in the ocean:distribution and impact on iodine flux and ozone loss (NE/N009983/1), which aimed to quantify the dominant controls on the sea surface iodide distribution and improve parameterisation of the sea-to-air iodine flux and of ozone deposition. The main ensemble prediction ("Ensemble Monthly mean ") is provided in a NetCDF (1) file as a single variable. A second file (2) is provided which includes all of the predictions and the standard deviation on the prediction. (1) predicted_iodide_0.125x0.125_Ns_Just_Ensemble.nc (2) predicted_iodide_0.125x0.125_Ns_All_Ensemble_members.nc This is the output of the paper 'A machine learning based global sea-surface iodide distribution' (see related documentation). For ease of use, this output has been re-gridded to various commonly used atmosphere and ocean model resolutions (see table SI table A5 in paper). These re-gridded files are included in the folder titled "regridded_data". Additionally, a file (3) is provided including the prediction made included data from the Skagerak dataset. As stated in the paper referenced above, it is recommended to use the use the core files (1,2) or their re-gridded equivalents. (3) predicted_iodide_0.125x0.125_All_Ensemble_members.nc As new observations are made, we will update the global dataset through a "living data" model. The dataset versions archived here follow semantic versioning (https://semver.org/). The pre-review dataset is achieved in the folder named v0.0.0, with the with publically released versions numbered starting from v1.0.0. Please refer to the referenced paper (see related documentation) for the current version number and information on this.

This dataset collection contains global spatially predicted sea-surface iodide concentrations at a monthly resolution for the year 1970. It was developed as part of the NERC project Iodide in the ocean:distribution and impact on iodine flux and ozone loss (NE/N009983/1), which aimed to quantify the dominant controls on the sea surface iodide distribution and improve parameterisation of the sea-to-air iodine flux and of ozone deposition. As new observations are made, this global data product will be continually added to and updated through a "living data" model. The datasets follows semantic versioning (https://semver.org/) and holds different versions of this. Please refer to the paper referenced for the current version number and information on this (see related documentation).

We present the significant ocean surface wave heights in the Arctic and Southern Oceans from CryoSat-2 data. We use a semi-analytical model for an idealised synthetic aperture satellite radar or pulse-limited radar altimeter echo power. We develop a processing methodology that specifically considers both the Synthetic Aperture and Pulse Limited modes of the radar that change close to the sea ice edge within the Arctic Ocean. All CryoSat-2 echoes to date were matched by our idealised echo revealing wave heights over the period 2011-2019. Our retrieved data were contrasted to existing processing of CryoSat-2 data and wave model data, showing the improved fidelity and accuracy of the semi-analytical echo power model and the newly developed processing methods. We contrasted our data to in situ wave buoy measurements, showing improved data retrievals in seasonal sea ice covered seas. We have shown the importance of directly considering the correct satellite mode of operation in the Arctic Ocean where SAR is the dominant operating mode. Our new data are of specific use for wave model validation close to the sea ice edge and is available at the link in the data availability statement. NERC NE/R000654/1 Towards a marginal Arctic sea ice cover.

The ocean surface height is constantly varying under the effects of gravity, density and the Earth''s rotation. Information on the Ocean surface elevation in polar regions is available from the CryoSat2 Radar instrument. We compare ocean surface elevation to a static geoid product (GOCO03s) to give the part of the ocean surface elevation accountable due to surface currents, the Dynamic Ocean Topography (DOT). This measurement is smoothed over 100 km and gives monthly surface currents. NERC NE/R000654/1 Towards a marginal Arctic sea ice cover.