The influence of ENSO, PDO and PNA on secular rainfall variations in Hawai‘i
2018
Over the last century, significant declines in rainfall across the state of Hawai‘i have been observed, and it is unknown whether these declines are due to natural variations in climate, or manifestations of human-induced climate change. Here, a statistical analysis of the observed rainfall variability was applied as first step towards better understanding causes for these long-term trends. Gridded seasonal rainfall from 1920 to 2012 is used to perform an
empirical orthogonal function(
EOF) analysis. The leading
EOFcomponents are correlated with three indices of natural climate variations (
El Nino-Southern Oscillation(ENSO),
Pacific Decadal Oscillation(PDO), and Pacific North American (PNA)), and multiple linear regression (MLR) is used to model the leading components with climate indices. PNA is the dominant mode of
wet season(November–April) variability, while ENSO is most significant in the
dry season(May–October). To assess whether there is an anthropogenic influence on rainfall, two methods are used: a linear trend term is included in the MLR, and pattern correlation coefficients (PCC) are calculated between recent rainfall trends and future changes in rainfall projected by downscaling methods. PCC results indicate that recent observed rainfall trends in the
wet seasonare positively correlated with future expected changes in rainfall, while
dry seasonPCC results do not show a clear pattern. The MLR results, however, show that the trend term adds significantly to model skill only in the
dry season. Overall, MLR and PCC results give weak and inconclusive evidence for detection of anthropogenic signals in the observed rainfall trends.
Keywords:
-
Correction
-
Source
-
Cite
-
Save
65
References
15
Citations
NaN
KQI