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EartH2Observe brings together the findings from European FP projects DEWFORA, GLOWASIS, WATCH, GEOWOW and others. It will integrate available global earth observations (EO), in-situ datasets and models and will construct a global water resources re-analysis dataset of significant length (several decades). The resulting data will allow for improved insights on the full extent of available water and existing pressures on global water resources in all parts of the water cycle. The project will support efficient and globally consistent water management and decision making by providing comprehensive multi-scale (regional, continental and global) water resources observations. It will test new EO data sources, extend existing processing algorithms and combine data from multiple satellite missions in order to improve the overall resolution and reliability of EO data included in the re-analysis dataset. The resulting datasets will be made available through an open Water Cycle Integrator data portal https://wci.earth2observe.eu/ : the European contribution to the GEOSS/WCI approach. The datasets will be downscaled for application in case-studies at regional and local levels, and optimized based on identified European and local needs supporting water management and decision making . Actual data access: https://wci.earth2observe.eu/data/group/earth2observe
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>>>!!!<<< Stated 2018-11-05: The ECDS database is being migrated to SND https://www.re3data.org/repository/r3d100010146 . You can still search for climate and environmental data here, but to publish data and metadata visit SND - Describe and deposit https://snd.gu.se/en/describe-and-deposit-data . When the migration is complete, search and download services will be provided through SND. All ecds.se urls and identifiers (eg. DOI) will, however, continue to links to the correct data sets when migration is complete. >>>!!!<<<
The IRI/LDEO Climate Data Library is a collection of climate data sets with the focus of climate change monitoring and mitigation. Browse data by category and source, navigate and analyze datasets using maps, and the Ingrid Data Analysis Language. The IRI/LDEO also includes web tutorials.