edu.ucar.opensky::articles:17757 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-26T02:59:13.756586 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7wh2rf2 https://doi.org/10.5065/D6TH8JR2 https Related Dataset #1 Gridded Ensemble Precipitation and Temperature Estimates over the Contiguous United States https://doi.org/10.7289/V5D21VHZ https Related Dataset #2 Global Historical Climatology Network - Daily (GHCN-Daily), Version 3 https://doi.org/10.5067/6J5LHHOHZHN4 https Related Dataset #3 NLDAS Primary Forcing Data L4 Hourly 0.125 x 0.125 degree, Version 002 https://doi.org/10.5065/D6MW2F4D https Related Dataset #4 A large-sample watershed-scale hydrometeorological dataset for the contiguous USA https://doi.org/10.3334/ORNLDAAC/1219 https Related Dataset #5 Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2 Gridded ensemble precipitation and temperature estimates for the contiguous United States 2015-12-01T00:00:00Z publication https://n2t.org/ark:/85065/d7wh2rf2 https://doi.org/10.1175/JHM-D-15-0026.1 Newman, Andrew J. author Clark, Martyn P. author Craig, Jason author Nijssen, B. author Wood, Andrew author Gutmann, Ethan D. author Mizukami, Naoki author Brekke, L. author Arnold, J. author UCAR/NCAR - Library publisher Gridded precipitation and temperature products are inherently uncertain because of myriad factors, including interpolation from a sparse observation network, measurement representativeness, and measurement errors. Generally uncertainty is not explicitly accounted for in gridded products of precipitation or temperature; if it is represented, it is often included in an ad hoc manner. A lack of quantitative uncertainty estimates for hydrometeorological forcing fields limits the application of advanced data assimilation systems and other tools in land surface and hydrologic modeling. This study develops a gridded, observation-based ensemble of precipitation and temperature at a daily increment for the period 1980–2012 for the conterminous United States, northern Mexico, and southern Canada. This allows for the estimation of precipitation and temperature uncertainty in hydrologic modeling and data assimilation through the use of the ensemble variance. Statistical verification of the ensemble indicates that it has generally good reliability and discrimination of events of various magnitudes but has a slight wet bias for high threshold events (>50 mm). The ensemble mean is similar to other widely used hydrometeorological datasets but with some important differences. The ensemble product produces a more realistic occurrence of precipitation statistics (wet day fraction), which impacts the empirical derivation of other fields used in land surface and hydrologic modeling. In terms of applications, skill in simulations of streamflow in 671 headwater basins is similar to other coarse-resolution datasets. This is the first version, and future work will address temporal correlation of precipitation anomalies, inclusion of other data streams, and examination of topographic lapse rate choices. 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 2015 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be "fair use" under Section 107 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Law (17 USC, as revised by P.L. 94-553) does not require the Society's permission. Republication, systematic reproduction, posting in electronic form on servers, or other uses of this material, except as exempted by the above statements, requires written permission or license from the AMS. Additional details are provided in the AMS Copyright Policies, available from the AMS at 617-227-2425 or amspubs@ametsoc.org. Permission to place a copy of this work on this server has been provided by the AMS. The AMS does not guarantee that the copy provided here is an accurate copy of the published work. None eng geoscientificInformation