A stochastic weather generation method for temporal precipitation simulation

Abstract

Disaggregation methods are designed to produce finer temporal scale data from coarser temporal scale data. An example of this need is the modification of monthly scale precipitation data to drive dynamic hydrological models operated at daily scale. Such issues occur for dynamic hydrological forecasts in which the General Circulation Models (GCMs) are used to generate the required precipitation data but the GCM outputs are only be reliable at coarser temporal scales. Stochastic weather generation methods together with simple adjustment of the total amounts provide a simple and efficient way for data disaggregation. However, the success of stochastic weather generation depends critically on wh..