Wednesday, 13 January 2016
Decadal variability in climate extremes associated with floods is of particular interest for infrastructure development and for insurance programs. In this study, short and long duration extreme rainfall events in the U.S. northeast region are analyzed employing spectral and time decomposition methods to identify the nature of decadal variability and its potential links to large scale climate. Wavelet analysis is applied on time series of annual maximum rainfall and the five dominant large scale models of climate variability (Atlantic Multi-decadal Oscillation, AMO, North Atlantic Oscillation, NAO, Pacific-North American pattern, PNA, Pacific Decadal Oscillation, PDO, and El Niño–Southern Oscillation, ENSO) to identify the inter-annual to decadal to multi-decadal quasi-periodic oscillation. Then, hierarchical clustering is applied on the global wavelet spectrum to identify the grouping of the rainfall stations with the climate indicators at different frequencies. Results indicate that there is clustering in various duration of rainfall extremes at decadal scales. Short duration events have coherence mostly with NAO and partly with PDO while there is no connection with AMO.
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