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|Created:||Sep 22, 2020 at 9:10 p.m.|
|Last updated:|| Sep 22, 2020 at 9:19 p.m.
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This dataset contains gridded monthly Standardized Precipitation Index (SPI) at 10 timescales: 1-, 3-, 6-, 9-, 12-, 18-, 24-, 36-, 48-, and 60-month intervals from 1920 to 2012 at 250 m resolution for seven of the eight main Hawaiian Islands (18.849°N, 154.668°W to 22.269°N, 159.816°W; the island of Ni‘ihau is excluded due to lack of data). The gridded data use a World Geographic Coordinate System 1984 (WGS84) and are stored as individual GeoTIFF files for each month-year, organized by SPI interval, as indicated by the GeoTIFF file name. Thus, for example, the file “spi3_1999_11.tif” would contain the gridded 3-month SPI values calculated for the month of November in the year 1999. Currently, the data are available from 1920 to 2012, but the datasets will be updated as new gridded monthly rainfall data become available.SPI is a normalized drought index that converts monthly rainfall totals into the number of standard deviations (z-score) by which the observed, cumulative rainfall diverges from the long-term mean. The conversion of raw rainfall to a z-score is done by fitting a designated probability distribution function to the observed precipitation data for a site. In doing so, anomalous rainfall quantities take the form of positive and negative SPI z-scores. Additionally, because distribution fitting is based on long-term (>30 years) precipitation data at that location, SPI score is relative, making comparisons across different climates possible.The creation of a statewide Hawai‘i SPI dataset relied on a 93-year (1920-2012) high resolution (250 m) spatially interpolated monthly gridded rainfall dataset . This dataset is recognized as the highest quality precipitation data available  for the main Hawaiian Islands. After performing extensive quality control on the monthly rainfall station data (including homogeneity testing of over 1,100 stations [1,3]) and a geostatistical method comparison, ordinary kriging was using to generate a time series of gridded monthly rainfall from January 1920 to December 2012 at 250 m resolution . This dataset was then used to calculate monthly SPI for 10 timescales (1-, 3-, 6-, 9-, 12-, 18-, 24-, 36-, 48-, and 60-month) at each grid cell. A 3-month SPI in May 2001, for example, represents the March-April-May (MAM) total rainfall in 2001 compared to the MAM rainfall in the entire time series. The resolution of the gridded rainfall dataset provides a more precise representation of drought (and pluvial) events compared to the other available drought products.Frazier, A.G.; Giambelluca, T.W.; Diaz, H.F.; Needham, H.L. Comparison of geostatistical approaches to spatially interpolate month-year rainfall for the Hawaiian Islands. Int. J. Climatol. 2016, 36, 1459–1470, doi:10.1002/joc.4437.Giambelluca, T.W.; Chen, Q.; Frazier, A.G.; Price, J.P.; Chen, Y.-L.; Chu, P.-S.; Eischeid, J.K.; Delparte, D.M. Online Rainfall Atlas of Hawai‘i. B. Am. Meteorol. Soc. 2013, 94, 313–316, doi:10.1175/BAMS-D-11-00228.1.Frazier, A.G.; Giambelluca, T.W. Spatial trend analysis of Hawaiian rainfall from 1920 to 2012. Int. J. Climatol. 2017, 37, 2522–2531, doi:10.1002/joc.4862.
In 2016, University of Hawai‘i launched the Hawai‘i EPSCoR ‘Ike Wai project supported by the National Science Foundation (Award # OIA-1557349) The five-year project uses integrated research, education, and community engagement efforts aimed to ensure Hawai‘i’s future water security and promote resource management within the state that is sustainable, responsible, and data-driven.
To save space on Hydroshare, all ‘Ike Wai project files are stored at the University of Hawai‘i and linked here. Please use the following link(s) to see the files for this resource.
Self Potential (SP)
the self-potential is a difference of electrical potential naturally occurring in the ground, measured between two electrodes placed at the surface of the Earth or in boreholes. SP can be generated by redox potentials associated with ore bodies or contaminant plumes that are rich in organic matter. A second source of self-potential anomalies is the thermoelectric effect associated directly with a gradient of the temperature affecting the chemical potential gradient of charge carriers. A third source is related to gradients of the chemical potential of the ionic charge carriers at constant temperature. A fourth source of self-potential signals is the streaming potential contribution related to the flow of the pore water relative to the mineral grain framework in saturated and unsaturated conditions.
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|National Science Foundation||‘Ike Wai: Securing Hawaii’s Water Future Award||OIA-1557349|
|USDA||Hatch Research Grant||1143H|
|Pacific Islands Climate Adaptation Science Center|
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
|Thomas Giambelluca||University of Hawaii at Manoa|
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/