Copula-based downscaling of spatial rainfall: a proof of concept

摘要

Fine-scale rainfall data is important for many hydrological applications.However, often the only data available is at a coarse scale. To bridge thisgap in resolution, stochastic disaggregation methods can be used. Suchmethods generally assume that the distribution of the field is stationary,i.e. the distribution for the entire (fine-scale) field is the same as thedistribution of a smaller region within the field. This assumption isgenerally incorrect and we provide a proof of concept of a method to estimatethe distribution of a smaller region. In this method, a copula is used toconstruct a bivariate distribution describing the relation between thescales. This distribution is then used to estimate the distribution of thefine-scale rainfall within a single coarse-scale pixel, by conditioning onthe coarse-scale rainfall depth.