Conditional Simulation of Precipitation Time Series Using Phase Annealing

Precipitation is one of the main inputs for hydrological models. For design purposes observed precipitation at high temporal resolution is often not available. In this case weather generators can be used to simulate realistic precipitation. Synthetic precipitation time series are often produced directly from observed time series using the stochastic methods which are able to reproduce the properties of the observed time series. The main difference and advantage of this research is to generate time series by focusing on the specific properties of the observed time series and trying to obtain these properties indirectly by conducting through investigation on the phases and power spectra and their individual effects using the phase annealing method.

Phase annealing is mainly based on annealing the phases of precipitation time series which are obtained from Fourier transform in order to meet the desired properties. These are obtained from observed time series and defined in the objective function. The outcome is synthetic time series with altered phases while the power spectrum is kept intact yielding new precipitation time series with properties matching those of the observed time series.