Stochastic Generation of Plausible Hydroclimate Futures Using Climate Teleconnections for Southeastern Australia

Abstract

Abstract Generating plausible future climate time series is needed for bottom-up climate impact modeling, as well as downscaling climate model output for hydrological applications. A novel method for generating multisite daily stochastic climate series is developed based on 1) linear regression between climate teleconnection time series (e.g., IPO/SOI) and annual rainfall, 2) clustered method of fragments for subannual disaggregation, and 3) a regression-based approach to daily potential evapotranspiration (PET) for hydrological modeling. We demonstrate that bias (i.e., oversampling) occurs with the standard method of fragments disaggregation in the multisite context and show that selection of an analog year from clustered rainfall amounts provides better sampling properties than the standard method of fragments. Using hydrological data for southeastern Australia, we model runoff from observed and simulated rainfall and PET using the GR4J (Génie Rural à 4 paramètres Journalier) model. Simulated annual and daily rainfall and runoff characteristics from the new method are similar to existing methods, with improvements demonstrated in wet–wet transition probabilities and spatial (between-site) correlations. Significance Statement In this paper we develop a novel method for generating multisite daily stochastic climate series regressing climate teleconnections (e.g., ENSO, IPO) to annual site rainfall, and disaggregation using a clustered version of the method of fragments. The modular nature of the method also allows for the possibility of the generation of replicates from GCM output of climate teleconnections, as well as perturbed climate futures for scenario-neutral modeling. Results demonstrate that rainfall and runoff metrics of interest for water resource modeling are reproduced well using the model.