1/10th of a degree observation-based dataset

URL: http://data.southcentralclimate.org/RedRiver/Downscaled/Livneh/

Historical 1/10th of a degree (~10 km) observations. The data is based on Livneh's 1/16th of a degree dataset. The folder contains daily maximum and minimum temperature, and daily precipitation over the Red River Basin (South Central region of the U.S.). These datasets were used to produce statistically downscaled time series from the three Global Climate Models used in the project (MPI-ESM-LR, CCSM4 and MIROC5).

Please go to the main directory: http://data.cybercommons.org/dataset/downscaling-red-river-basin for a detailed description of the datasets in this collection (spatial and temporal resolution, Global Climate Models used, downscaling methods implemented, and climate variables in the dataset).

NetCDF files can be opened and visualized using open source software like R, Python, Panoply and Ferret. The NetCDF files contain additional metadata and can be used to geo-reference the time series. This functionality allows the users to open the NetCDF files using GIS software. For more information "Mapping and Modeling Weather and Climate with GIS", a book from Esri Press, offers a wealth of information for atmospheric research methods.

Reference of the 1/16th of a degree dataset: Ben Livneh, Eric A. Rosenberg, Chiyu Lin, Bart Nijssen, Vimal Mishra, Kostas M. Andreadis, Edwin P. Maurer, and Dennis P. Lettenmaier, 2013: A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States: Update and Extensions*. J. Climate, 26, 9384–9392. doi:10.1175/JCLI-D-12-00508.1

Official Download site: ftp://ftp.hydro.washington.edu/pub/blivneh/CONUS

The datasets can be downloaded as NetCDF or .zip files (Browse and Download tabs, respectively).


Additional Information

Field Value
Data last updated February 11, 2016
Metadata last updated February 11, 2016
Created February 11, 2016
Format NetCDF
License Creative Commons Attribution
createdover 3 years ago
has viewsTrue
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