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Dataset: b.e13.BRCP85C5CN.ne120_g16.003a.cam.h5.TS.2099010100Z-2099123121Z.bilin.NA.dlfront.nc
Catalog: /thredds/catalog/files/d583105/catalog.html
dataFormatNetCDF
authorityedu.ucar.gdex
featureTypeGRID
dataSize67128448
idfiles/d583105/b.e13.BRCP85C5CN.ne120_g16.003a.cam.h5.TS.2099010100Z-2099123121Z.bilin.NA.dlfront.nc
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ServiceTypeDescription
OpenDAP Data Access Access dataset through OPeNDAP using the DAP2 protocol.
DAP4 Data Access Access dataset using the DAP4 protocol.
NetcdfSubset Data Access A web service for subsetting CDM scientific grid datasets.
CdmRemote Data Access Provides index subsetting on remote CDM datasets, using ncstream.
CdmrFeature Data Access Provides coordinate subsetting on remote CDM Feature Datasets, using ncstream.
WCS Data Access Supports access to geospatial data as 'coverages'.
WMS Data Access Supports access to georegistered map images from geoscience datasets.
HTTPServer Data Access HTTP file download.
ISO Metadata Provide ISO 19115 metadata representation of a dataset's structure and metadata.
NCML Metadata Provide NCML representation of a dataset.
UDDC Metadata An evaluation of how well the metadata contained in the dataset conforms to the NetCDF Attribute Convention for Data Discovery (NACDD)

Viewers:

ViewerTypeDescription
Godiva3 Browser
default_viewer.ipynb Jupyter Notebook The TDS default viewer attempts to plot any Variable contained in the Dataset.
Documentation
Dates
Creators
Publishers

Description:

  • Rights: Freely Available
  • summary: These data are the results of high resolution simulations with the Community Earth System Model, version 1.3 (CESM1.3). These simulations form the basis of a publication analyzing machine learning based-detection of weather fronts and associated extreme 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. Depending on the variables, the temporal resolution is 3-hourly, 6-hourly, or monthly, the horizontal resolution is 0.25 degree or 1 degree, and the spatial domain is global or centered over North America.
  • NCAR GDEX - Machine learning-based detection of weather fronts and associated extreme precipitation in CESM1.3(d583105)

Dates:

  • modified : 2025-06-19T23:16:02.993Z

Creators:

  • UCAR/NCAR/CGD

Publishers:

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