This dataset comprises gridded limb ozone monthly zonal mean profiles from the MIPAS instrument on the ENVISAT satellite. The data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean. The monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file "ESACCI-OZONE-L3-LP-MIPAS_ENVISAT-MZM-2008-fv0001.nc“ contains monthly zonal mean data for MIPAS in 2008.

These ancillary datasets were used in the production of the "Active", "Passive" and "Combined" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v02.2 Soil Moisture CCI data. For further information on these and the references associated with them please see the Product Specification Document (PSD), a link to which is provided in the documentation section. The "Active" "Passive" and "Combined" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website or within the Product Specification Document.

This data set is part of the ESA Sea Ice Climate Change Initiative (CCI) project. The dataset provides sea ice concentration for the Arctic region, derived from the AMSR-E satellite instrument. It consists of daily gridded SIC fields based on Passive Microwave Radiometer measurements from the AMSR-E instrument with a 25km grid spacing, along with the total standard error (uncertainty) and quality control flags. It has been built upon the algorithms and processing software originally developed at the EUMETSAT OSI SAF for their SIC dataset. Please note, in the sea ice concentration data set - on purpose - no weather filter has been applied to eliminate weather-induced spurious ice in the open ocean along the ice edge in order to avoid discarding regions with a real sea ice cover. Users are advised to read the product user guide and the publication by Ivanova et al. [2015] (see documentation section). A second sea ice dataset has also been produced from the SSM/I instrument, and these should be regarded as individual datasets and not combined without further investigations about the compatibility. The project team warns potential users that the AMSR-E SIC time-series is less mature than the SSM/I one, and that the former should be used with extra care, possibly after visual inspection or comparison to other data sources (such as the SSM/I time series during the overlap period).

This dataset comprises gridded limb ozone monthly zonal mean profiles from the OSIRIS instrument on the ODIN satellite. The data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean. The monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-OSIRIS_ODIN-MZM-2008-fv0001.nc” contains monthly zonal mean data for OSIRIS in 2008.

This dataset consists of a gridded composite of limb ozone profile data, combining data from a range of instruments. The data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean. The merged monthly zonal mean data (MMZM) include merged ozone profiles in 10° latitude zones for each month, on the ozone-CCI pressure grid from 250 hPa to 1 hPa, and the parameters which characterize the uncertainty of the merged profiles. In Phase I of the ESA CCI Programme, the dataset has been created for 2 years, 2007 and 2008. The merged monthly zonal mean data are structured into monthly netcdf files with self-explanatory names. For example, the file “ESACCI-OZONE-L3-LP-MERGED-MZM-200801-fv0002.nc” contains merged monthly zonal mean data for January 2008. In addition to the variables of the merged data, the profiles from individual instruments with their uncertainty parameters are also included (for the altitude range 250-1 hPa used in data merging).

This dataset comprises gridded limb ozone monthly zonal mean profiles from the ACE FTS instrument on the SCISAT satellite. The data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean. The monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-ACE_FTS_SCISAT-MZM-2008-fv0001.nc” contains monthly zonal mean data for ACE in 2008.

This dataset comprises gridded limb ozone monthly zonal mean profiles from the GOMOS instrument. The data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean. The monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-GOMOS_ENVISAT-MZM-2008.nc” contains monthly zonal mean data for GOMOS in 2008.

The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the "Active" and "Passive" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. The v03.3 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document. The data set should be cited using all three of the following references: 1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001 2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070 3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014

This dataset consists of a gridded composite of limb ozone profile data, combining data from a range of instruments. The Merged Semi-Monthly Mean (MSMM) dataset is created using measurements from limb sensors participating in Ozone_cci project, for years 2007-2008. First, the ozone profiles from individual instruments are averaged in 10° x 20° latitude-longitude zones over half-month time intervals, and then merged. The merged semi-monthly mean ozone profiles are structured into yearly netcdf files with self-explanatory names. For example, the file “ESACCI-OZONE-L3-LP-SMM-2008-fv0002.nc” contains the semi-monthly mean ozone profiles for January 2008. In addition to the variables of the merged data, the profiles from individual instruments with their uncertainty parameters are also included (for the altitude range 250-1 hPa used in data merging).

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 XCH4 GOS PR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). 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). This version of the proxy product (version 6.0) has been generated using the OCPR University of Leicester Full-Physics Retrieval Algorithm, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra baseline algorithm. This algorithm has been designated the baseline algorithm for the GHG CCI proxy methane retrievals. A second product has also been generated from the TANSO-FTS data using an alternative algorithm, the RemoTeC Proxy algorithm. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the OCPR baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage. The product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further details on the product, including the UoL-PR algorithm and the TANSO-FTS 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/