Long-range persistence in climatological and hydrological time series: analysis, modeling and application to drought hazard assessment

Abstract

We present power spectra of time-series data for tree ring width chronologies, atmospheric temperatures, river discharges and precipitation averaged over hundreds of stations worldwide. The average power spectrum S for each of these phenomena is found to have a power-law dependence on frequency with exponent − 1 2 : S(f) ∝f − 1 2 . An advection-diffusion model of the vertical transport of heat and water vapor in the atmosphere is presented as a first-order model of climatic and hydrological variability. The model generates variability with the observed spectrum. The model is validated with a correlation analysis of temperature and water vapor concentration measurements from the TIROS operational vertical sounder (TOVS). Drought frequency analyses based on synthetic lognormal streamflows with the above power spectrum are presented. We show that the presence of long memory as implied by the power-law power spectrum has a significant effect on the likelihood of extended droughts compared with the drought hazard implied from standard autoregressive models with short memory.