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Estimating uncertainty associated with the standardized precipitation index
Author(s) -
Carbone Gregory J.,
Lu Junyu,
Brunetti Michele
Publication year - 2018
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.5393
Subject(s) - precipitation , outlier , confidence interval , climatology , environmental science , statistics , index (typography) , range (aeronautics) , resampling , econometrics , mathematics , meteorology , geography , computer science , geology , materials science , world wide web , composite material
ABSTRACT We investigate methodological uncertainties associated with the standardized precipitation index (SPI) that result from limited record length, trends, and outliers. We use long, homogenous records from 14 Italian stations to investigate how specific features in the precipitation record affect construction of an underlying gamma probability function. We apply a resampling scheme to the long records in order to estimate confidence intervals associated with a range of precipitation characteristics. Stability in parameter estimation increases nonlinearly as record length increases. The resulting SPI estimates for 30‐year reference periods have considerably more uncertainty than those made from 60‐year records. In general, increasing record length beyond 60‐years has limited benefits and, in the presence of a trend, may increase uncertainty. Extreme events also have significant influence on SPI estimates, even for records exceeding 60 years. Despite using stations from different geographic regions, each with unique precipitation characteristics, we find consistent confidence interval estimates across stations. These confidence intervals can be applied to specific time series to identify how trends, changes in variability, and outliers during a particular reference period influence SPI values.