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Data · dataset · 2026

Machine learning-based detection of atmospheric rivers in CESM1.3

Listed in National Center for Atmospheric Research

These data are the results of high resolution simulations with the Community Earth System Model, version 1.3 (CESM1.3).

Description

These data form the basis of a publication analyzing machine learning based-detection of atmospheric rivers and associated precipitation. The CESM1.3 data include simulations with historical (years 2000-2005), RCP2.6 (years 2006-2015), and RCP8.5 (years 2086-2100) climate forcing.

The temporal resolution is 3-hourly, the horizontal resolution is 0.25 degree, and the spatial domain is global. Preprint: doi.org/10.22541/essoar.15005316/v1

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Catalogue records · 1

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Inferred from text
Atmospheric sciences 74%
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
National Center for Atmospheric Researchcf6e4484-b318-410a-913a-8ae244e34fb612 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:group:3701enrichment · data ucar edutaxonomy-embedding@1.1.0title+keywords+description (74%)
concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0