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Comparison of geostatistical approaches to spatially interpolate month‐year rainfall for the Hawaiian Islands
Author(s) -
Frazier Abby G.,
Giambelluca Thomas W.,
Diaz Henry F.,
Needham Heidi L.
Publication year - 2015
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.4437
Subject(s) - kriging , interpolation (computer graphics) , covariate , elevation (ballistics) , climatology , geostatistics , multivariate interpolation , physical geography , environmental science , statistics , geology , spatial variability , geography , mathematics , computer science , animation , computer graphics (images) , geometry , bilinear interpolation
The Hawaiian Islands have one of the most spatially diverse rainfall patterns on earth. Knowledge of these patterns is critical for a variety of resource management issues and, until now, only long‐term mean monthly and annual rainfall maps have been available for Hawai‘i. In this study, month‐year rainfall maps from January 1920 to December 2012 were developed for the major Hawaiian Islands. The maps were produced using climatologically aided interpolation ( CAI ), where the station anomalies were interpolated first, and then combined with the mean maps. A geostatistical method comparison was performed to choose the best interpolation method. The comparison focuses on three kriging algorithms: ordinary kriging (OK), ordinary cokriging (OCK), and kriging with an external drift (KED). Two covariates, elevation and mean rainfall, were tested with OCK and KED. The combinations of methods and covariates were compared using cross‐validation statistics, where OK produced the lowest error statistics. Station anomalies for each month were interpolated using OK and combined with the mean monthly maps to produce the final month‐year rainfall maps.