edu.ucar.gdex::d583154 eng; USA utf-8 dataset NSF NCAR Geoscience Data Exchange datahelp@ucar.edu https://gdex.ucar.edu NSF NCAR Geoscience Data Exchange The Geoscience Data Exchange (GDEX), managed by the Computational and Information Systems Laboratory (CISL) at NSF NCAR, contains a large collection of meteorological, atmospheric composition, and oceanographic observations, and operational and reanalysis model outputs, integrated with NSF NCAR High Performance Compute services to support atmospheric and geosciences research. download pointOfContact 2026-04-19T04:57:42Z ISO 19115 Geographic Information - Metadata ISO19115:2003/Cor 1 2006 https://doi.org/10.5065/D6SB44JV Ensemble gridded (1 km) daily rainfall and temperature for the Hawaiian Islands (1990-2014) d583154 2018-01-01 publication Newman, Andrew J. author Clark, Martyn P. author Longman, Ryan J. author Gilleland, Eric author Giambelluca, Thomas W. author Arnold, Jeffrey R. author NSF National Center for Atmospheric Research publisher It is a major challenge to develop gridded precipitation and temperature estimates that adequately resolve the extreme spatial gradients present in the Hawaiian Islands. The challenge is particularly pronounced because the available station networks are irregularly spaced and sparse, creating large uncertainties in gridded spatial meteorological estimates. Here we develop a 100- member, daily ensemble of precipitation and temperature estimates over the Hawaiian Islands for the period 1990-2014 at 1 km grid resolution. We first develop an intermediary ensemble estimate of the monthly climatological precipitation and temperature and use the climatological surfaces to inform daily anomaly interpolation. This Climatologically Aided Interpolation (CAI) method extends our initial ensemble system developed for the continental United States (CONUS). For Hawaii, we show that daily interpolation using only daily data is inferior to the CAI methodology, particularly over longer time periods (years to decades). Daily interpolation has more value for short time periods (e.g. 1-month or less) or when the precipitation distribution substantially diverges from climatology. The CAI ensemble is able to reproduce observed precipitation and temperature patterns, including the probability of precipitation. Leave-one-out cross-validation results illustrate that the ensemble has: 1) minimal biases, 2) reasonable mean absolute errors, 3) good representation of daily precipitation intensity variability, and 4) good reliability and discrimination. Additionally, the ensemble is able to reasonably reproduce the tails (e.g. 99.9th percentile) of the daily precipitation and temperature distributions, with increasing uncertainty for higher percentiles. completed datahelp@ucar.edu pointOfContact notPlanned dataset https://gdex.ucar.edu/images/ds_logos/default_200_200.png Logo thumbnail from URL png HDF5/NetCDF4 dataset Resource Type 2021-03-30 revision 4.4 DataCite Metadata Working Group orginator resourceTypeGeneral WEATHER STATIONS > WEATHER STATIONS U.S. National Aeronautics and Space Administration Global Change Master Directory GCMD 2026-04-15 revision 23.7 NASA Global Change Master Directory orginator Valids List: Platforms EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE > SURFACE TEMPERATURE > MAXIMUM/MINIMUM TEMPERATURE EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > PRECIPITATION AMOUNT U.S. National Aeronautics and Space Administration Global Change Master Directory GCMD 2026-04-15 revision 23.7 NASA Global Change Master Directory orginator Valids List: Science and Services Keywords Creative Commons Attribution 4.0 International License None eng utf-8 climatologyMeteorologyAtmosphere 1900-01-01 2014-12-31 NSF NCAR Geoscience Data Exchange datahelp@ucar.edu https://gdex.ucar.edu distributor 161214.52 https://gdex.ucar.edu/datasets/d583154/ https Dataset Description Related Link information https://gdex.ucar.edu/datasets/d583154/dataaccess/ https Data Access Related Link download none asNeeded