The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance.

This dataset contains satellite-derived atmospheric column-average dry-air mole fractions of carbon dioxide (XCO2), and is a Level 3 gridded product in Obs4MIPs format. It has been derived by the Greenhouse Gases CCI (GHG_cci) project as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme, and has been obtained from an ensemble of individual Level 2 (i.e. swath) XCO2 products, retrieved from the satellite sensors SCIAMACHY / ENVISAT and TANSO-FTS / GOSAT. The versions of the Level 2 GHG_cci data products used as input for this product are those of the GHG_cci "Climate Research Data Package No. 3" (CRDP#3). This Level 3 Obs4MIPs XCO2 product has been specifically generated for comparisons with climate model output in the context of the CMIP5/CMIP6/IPCC experiments.

Data produced in support of the NERC project Poles Apart (2014 - 2017) that investigated the atmospheric drivers of changes in surface wind forcing using the UK Chemistry and Aerosols (UKCA) model. Ten HadGEM3 model simulations were undertaken. Monthly model data was taken from the final 30 years of each simulation and a number of variables of interest, e.g. temperature and precipitation were extracted and analysed. The temporal range for the perturbed simulations is 1980-2013, and the control simulations are valid between 1841-1900. See the detailed experiment documentation for the Unified Model experiment ids and their corresponding description (these have been used to organise the data).

This dataset contains satellite-derived atmospheric column-average dry-air mole fractions of methane (XCH4), and is a Level 3 gridded product in Obs4MIPs format. It has been derived by the Greenhouse Gases CCI (GHG_cci) project as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme, and was obtained from an ensemble of individual Level 2 (i.e. swath) XCH4 products, retrieved from the satellite sensors SCIAMACHY / ENVISAT and TANSO-FTS / GOSAT. The versions of the Level 2 GHG-CCI data products used as input for this product are those of the GHG_cci "Climate Research Data Package No. 3" (CRDP#3). This Level 3 Obs4MIPs XCH4 product has been specifically generated for comparisons with climate model output in the context of the CMIP5/CMIP6/IPCC experiments.

Datasets collected as part of the NERC project Poles Apart Why has Antarctic sea ice increased and why don't coupled climate models reproduce observations? (NE/K012150/1, NE/K011561/1). The aim of this project was to model atmospheric drivers of changes in surface wind forcing. The project began in June 2014 and completed at the end of June 2017.

The Greenhouse Gases Climate Change Initiative (GHG_cci) data products are near-surface-sensitive dry-air column-averaged mole fractions (mixing ratios) of methane (CH4) and carbon dioxide (CO2), created as part of the European Space Agency's (ESA) Greenhouses Gases Essential Climate Variable (ECV) CCI project. Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). The products have each been generated from individual sensors, a single merged product not having yet been created "combining" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. Typically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. For further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section.

Data from two laboratory-based studies, both investigating the interactive effects of abiotic and biotic controls on peatland carbon cycling. Data comprise carbon dioxide and methane fluxes in peat, litter mass remaining and respiration rate data from litter bags on peat mesocosms, and biochemical and physical properties of peat. Data was collected in from the first laboratory study, which focused on identifying the interactive effects of small-scale temperature change, water table level and plant functional type legacy effects in peat on carbon dioxide (CO2) and methane (CH4) fluxes from peat collected from Black Law Wind Farm, Lanarkshire, Scotland. Data includes CO2 and CH4 fluxes from peat mesocosms (sampled in May 2011), measured six times from October 2011 to September 2012. Data collected from the second laboratory study between October 2012 and October 2013 focused on identifying the interactive effects of small-scale temperature change and plant functional type legacy effects in peat and litter on decomposition in peatlands, and included litter mass remaining (% of initial litter mass) and respiration rate data from litter bags on peat mesocosms. Peat and litter used in this laboratory study were collected from blanket bog peatland at Black Law Wind Farm, Lanarkshire, Scotland in October 2012. Peat and litter used in both studies were analysed for their biochemical and physical properties. Biochemical and physical properties data for the first laboratory study includes bulk density, pH, total carbon (C) content, total nitrogen (N) content, ratio of C to N, C stock, N stock, total phospholipid fatty acids (PLFAs), total fungal PLFAs, total bacterial PLFAs, ratio of fungal to bacterial PLFAs, total gram-positive bacterial PLFAs, total gram-negative bacterial PLFAs and ratio of gram-positive to gram-negative bacterial PLFAs of peat. Biochemical and physical properties data for the second laboratory study include total carbon (C) content, total nitrogen (N) content and the ratio of C to N for peat and litter. Biochemical and physical data properties for peat and litter were used to better understand the effects of plant functional type legacy on greenhouse gas fluxes and litter decomposition. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/e15fbbab-1cdd-4509-81a3-aa050e927dd0

The data consists of nitrogen (N) offtake, N emissions and soil N parameters, and herbage quality parameters from a three-cut silage plot trial located at two grassland sites within the UK collected between April and October 2016. The sites were Rothamsted Research at North Wyke in Devon and Bangor University at Henfaes Research Station in North Wales. At each site measurements were taken from 16 plots, organised within a randomised complete block design. Fertiliser was applied three times and three cuts were performed, all parameters measured were following a fertiliser application. Nitrogen parameters measured were crude protein (CP) of herbage, ammonia (NH3) emissions, nitrous oxide (N2O) emissions, and soil ammonium (NH4) and nitrate (NO3). Herbage quality parameters measured were dry matter, acid-digestible fibre (ADF), ash, CP, metabolizable energy (ME), and non-digestible fibre (NDF) and digestibility (D) was calculated. Nitrogen offtake, losses and fluxes were measured to determine the N use efficiency and the economic viability of different N fertilisers. Measurements were undertaken by members of staff from Bangor University, School of Environment, Natural Resources & Geography and Rothamsted Research, Sustainable Agricultural Sciences – North Wyke. Data was collected for the Newton Fund project "UK-China Virtual Joint Centre for Improved Nitrogen Agronomy". Funded by Biotechnology and Biological Sciences Research Council (BBSRC) and NERC - Ref BB/N013468/1 Full details about this dataset can be found at https://doi.org/10.5285/4c7d4b3c-88f7-43ab-a50f-b6804474e568

Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project, the XCO2 GOSAT product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). The University of Leicester Full-Physics Retrieval Algorithm has been applied to the TANSO-FTS data, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra. A second product, generated using the SRFP algorithm, is also available. The XCO2 product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further information, including details of the OCFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) in the documentation section. The GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/

Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and Climate Research Data Package Number 2 (CRDP#3), the XCO2 GOSAT product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). In this case, the RemoTeC Full Physics (SRFP) algorithm, jointly developed at SRON and KIT, has been applied to the TANSO-FTS data. A second product, generated using the OCFP (University of Leicester Full Physics) algorithm, is also available. The data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key standard products, i.e. the retrieved column averaged dry air mixing ratio XCO2 with bias correction, averaging kernels and quality flags, as well as secondary products specific for the RemoTeC algorithm. For further information, including details of the SRFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section. The GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/