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from dagshub.streaming import DagsHubFilesystem
fs = DagsHubFilesystem(".", repo_url="https://dagshub.com/DagsHub-Datasets/surftemp-sst-dataset")
fs.listdir("s3://surftemp-sst")
Global daily-mean sea surface temperatures, presented on a 0.05° latitude-longitude grid, with gaps between available daily observations filled by statistical means, spanning late 1981 to recent time. Suitable for large-scale oceanographic meteorological and climatological applications, such as evaluating or constraining environmental models or case-studies of marine heat wave events. Includes temperature uncertainty information and auxiliary information about land-sea fraction and sea-ice coverage. For reference and citation see: www.nature.com/articles/s41597-019-0236-x.
Global daily-mean sea surface temperatures, presented on a 0.05° latitude-longitude grid, with gaps between available daily observations filled by statistical means, spanning late 1981 to recent time. Suitable for large-scale oceanographic meteorological and climatological applications, such as evaluating or constraining environmental models or case-studies of marine heat wave events. Includes temperature uncertainty information and auxiliary information about land-sea fraction and sea-ice coverage. For reference and citation see: www.nature.com/articles/s41597-019-0236-x.
yearly
https://www.reading.ac.uk/met/
aws-pds, earth observation, oceans, climate, environmental, global, geospatial
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