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  • 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 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.

  • 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 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.

  • 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.

  • 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/

  • Part of the European Space Agency's (ESA) Greenhouse Gases (GHG), the XCH4 EMMA product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced by applying the ensemble median algorithm EMMA to level 2 data of several different retrieval products from the Japanese Greenhouse gases Observing Satellite (GOSAT) This is therefore a merged GOSAT XCH4 Level 2 product, primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). For further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR) 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 the Climate Research Data Package Number 3 (CRDP#3), the BESD XCO2 SCIAMACHY 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 SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. This product has been produced with the Bremen Optimal Estimation DOAS (BESD) algorithm, a full physics algorithm which uses measurements in the O2-A absorption band to retrieve scattering information of clouds and aerosols. This is the GHG CCI baseline algorithm for deriving SCIAMACHY XCO2 data: A product has also been generated from the SCIAMACHY data using an alternative algorithm: the WFMD algorithm. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the BESD baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage in the documentation section. For further information on the product, including details of the BESD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents 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/

  • 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.

  • 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/