Abstract

The distribution of climatic variance across the frequency spectrum has substantial importance for anticipating how climate will evolve in the future. Here power spectra and power laws (β) are estimated from instrumental, proxy, and climate model data to characterize the hydroclimate continuum in... Show moreThe distribution of climatic variance across the frequency spectrum has substantial importance for anticipating how climate will evolve in the future. Here power spectra and power laws (β) are estimated from instrumental, proxy, and climate model data to characterize the hydroclimate continuum in western North America (WNA). The significance of the estimates of spectral densities and β are tested against the null hypothesis that they reflect solely the effects of local (nonclimate) sources of autocorrelation at the monthly time scale. Although tree-ring-based hydroclimate reconstructions are generally consistent with this null hypothesis, values of β calculated from long moisture-sensitive chronologies (as opposed to reconstructions) and other types of hydroclimate proxies exceed null expectations. Therefore it may be argued that there is more low-frequency variability in hydroclimate than monthly autocorrelation alone can generate. Coupled model results archived as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) are consistent with the null hypothesis and appear unable to generate variance in hydroclimate commensurate with paleoclimate records. Consequently, at decadal-to-multidecadal time scales there is more variability in instrumental and proxy data than in the models, suggesting that the risk of prolonged droughts under climate change may be underestimated by CMIP5 simulations of the future. Show less