Stochastic generation of plausible hydroclimate futures using climate teleconnections for South-Eastern Australia

Generating plausible future climate timeseries is needed for bottom-up climate impact modelling, 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 timeseries (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 modelling. 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 analogue year from clustered rainfall amounts provides better sampling properties than the standard method of fragments. Using hydrological data for south-eastern Australia, we model runoff from observed and simulated rainfall and PET using the GR4J 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.