Ocean Surface Current Analyses Real-time (OSCAR) is a global surface current database and NASA funded research project. OSCAR ocean mixed layer velocities are calculated from satellite-sensed sea surface height gradients, ocean vector winds, and sea surface temperature gradients using a simplified physical model for geostrophy, Ekman, and thermal wind dynamics. Daily averaged surface currents are provided on a global 0.25 x 0.25 degree grid as an average over an assumed well-mixed top 30 m of the ocean from 1993 to present day. OSCAR currents are provided at three quality levels: final, interim and nrt with a respective latency of each of approximately 1 year, 1 month, and 2 days. OSCAR is generated by Earth & Space Research (ESR) https://www.esr.org/research/oscar/. More details on the source datasets, file structure, and methodology can be found in oscarv2guide.pdf.

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POCLOUD Short Name: OSCAR_L4_OC_FINAL_V2.0 Version ID: 2.0 Unique ID: C2098858642-POCLOUD

Ocean Surface Current Analyses Real-time (OSCAR) is a global surface current database and NASA funded research project. OSCAR ocean mixed layer velocities are calculated from satellite-sensed sea surface height gradients, ocean vector winds, and sea surface temperature gradients using a simplified physical model for geostrophy, Ekman, and thermal wind dynamics. Daily averaged surface currents are provided on a global 0.25 x 0.25 degree grid as an average over an assumed well-mixed top 30 m of the ocean from 1993 to present day. OSCAR currents are provided at three quality levels: final, interim and nrt with a respective latency of each of approximately 1 year, 1 month, and 2 days. OSCAR is generated by Earth & Space Research (ESR) https://www.esr.org/research/oscar/. More details on the source datasets, file structure, and methodology can be found in oscarv2guide.pdf.

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POCLOUD Short Name: OSCAR_L4_OC_INTERIM_V2.0 Version ID: 2.0 Unique ID: C2102959417-POCLOUD

This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Along-Track Scanning Radiometer (ATSR-2) on European Remote-sensing Satellite 2 (ERS-2). Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.Daytime and nighttime temperatures are provided in separate files corresponding to the morning and evening ERS-2 equator crossing times which are 10:30 and 22:30 local solar time.Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length.Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.The dataset coverage is near global over the land surface. Small regions were not covered due to downlinking constraints (most noticeably a track extending southwards across central Asia through India – further details can be found on the ATSR project webpages at https://artefacts.ceda.ac.uk/frozen_sites/www.atsr.rl.ac.uk/documentation/docs/userguide/index.shtml).LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. ATSR-2 achieves full Earth coverage in 3 days so the daily files have gaps where the surface is not covered by the satellite swath on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.Dataset coverage starts on 1st June 1995 and ends on 22nd June 2003. There are two gaps of several months in the dataset: no data were acquired from ATSR-2 between 23 December 1995 and 30 June 1996 due to a scan mirror anomaly; and the ERS-2 gyro failed in January 2001, data quality was less good between 17th Jan 2001 and 5th July 2001 and are not used in this dataset. There are minor interruptions (1-2 days) during satellite/instrument maintenance periods.Version 4.00 uses data from the 4th reprocessing of the ATSR L1B archive. The emissivities used in the retrieval come from the Combined ASTER and MODIS Emissivity over Land (CAMEL) Version 2 database; in Version 4.00 a climatology is used since there are temporal instabilities in the CAMEL time series.The dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.The dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards.

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• 030157c0dda24ae28fc0f56d39cf1ed1

FEDEO Short Name: 030157c0dda24ae28fc0f56d39cf1ed1 Version ID: NA Unique ID: C4017534714-FEDEO

The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.The v05.2 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 2019-12-31. 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 website.The data set should be cited using all three of the following references:1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-20192. 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.2017.07.0013. 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

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FEDEO Short Name: 057dd6c36f0741d3b97f9eee688b7835 Version ID: NA Unique ID: C2548143472-FEDEO

This dataset is a monthly mean gridded total ozone data record (level 3) produced by the ESA Ozone Climate Change Initiative project (Ozone CCI). The dataset is a prototype of a merged harmonised ozone data record combining ozone data from the GOME instrument on ERS-2, the SCIAMACHY instrument on ENVISAT and the GOME-2 instrument on METOP-A, and covers the period between April 1996 to June 2011.

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• 0d2260ad4e2c42b6b14fe5b3308f5eaa

FEDEO Short Name: 0d2260ad4e2c42b6b14fe5b3308f5eaa Version ID: NA Unique ID: C2548143081-FEDEO