Spectral and spatial interpolation of precipitation for daily and hourly time series

Generating synthetic precipitation for weather generators were always a challenging issue in hydro-climate simulations because of its high variability in time and space. We present a spectral method for generating the synthetic precipitation time series which is in accordance with the observed precipitation statistical characteristics not only for the observed points, but also for any desired location by interpolating the time series spectrum. In this regard, time series spectra derived from the observed signal converting from its time domain to the corresponding frequency domain using the Fourier transform.

The main problem for spectral interpolation of precipitation time series is highly occurrence of non-rainy days which can be even more inaccurate for the finer resolutions such as hourly and sub-hourly data. In order to overcome the highly frequent occurrence of non-rainy days, transformation between indicator and normal correlation has been taken into account.

This method enables us to generate synthetic time series with same statistical characteristics for the observed points and also for any point of interests rather than the observed points. The introduced so called spectral and spatial interpolation method applied for daily and hourly precipitation time series for the selected stations in state Baden-Württemberg, Germany.