edu.ucar.opensky::articles:21118 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-26T02:21:41.675110 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d78c9zt5 https://doi.org/10.5066/F7542KMD https Related Dataset #1 GIS Features of the Geospatial Fabric for National Hydrologic Modeling https://doi.org/10.5065/D6G73C3Q https Related Dataset #2 Catchment attributes for large-sample studies https://doi.org/10.5066/F7WM1BF7 https Related Dataset #3 Preliminary spatial parameters for PRMS based on the Geospatial Fabric, NLCD2001, and SSURGO https://doi.org/10.5065/D6MW2F4D https Related Dataset #4 A large-sample watershed-scale hydrometeorological dataset for the contiguous USA The CAMELS data set: catchment attributes and meteorology for large-sample studies 2017-10-20T00:00:00Z publication https://n2t.org/ark:/85065/d78c9zt5 https://doi.org/10.5194/hess-21-5293-2017 Addor, Nans author Newman, Andrew J. author Mizukami, Naoki author Clark, Martyn P. author UCAR/NCAR - Library publisher We present a new data set of attributes for 671 catchments in the contiguous United States (CONUS) minimally impacted by human activities. This complements the daily time series of meteorological forcing and streamflow provided by Newman et al. (2015b). To produce this extension, we synthesized diverse and complementary data sets to describe six main classes of attributes at the catchment scale: topography, climate, streamflow, land cover, soil, and geology. The spatial variations among basins over the CONUS are discussed and compared using a series of maps. The large number of catchments, combined with the diversity of the attributes we extracted, makes this new data set well suited for large-sample studies and comparative hydrology. In comparison to the similar Model Parameter Estimation Experiment (MOPEX) data set, this data set relies on more recent data, it covers a wider range of attributes, and its catchments are more evenly distributed across the CONUS. This study also involves assessments of the limitations of the source data sets used to compute catchment attributes, as well as detailed descriptions of how the attributes were computed. The hydrometeorological time series provided by Newman et al. (2015b, https://doi.org/10.5065/D6MW2F4D) together with the catchment attributes introduced in this paper (https://doi.org/10.5065/D6G73C3Q) constitute the freely available CAMELS data set, which stands for Catchment Attributes and MEteorology for Large-sample Studies. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright Author(s) 2017. This work is distributed under the Creative Commons Attribution 3.0 License None eng geoscientificInformation