Space-time modelling of rainfall using Copulas - a quasi meta-gaussian approach

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Stochastic space time modelling of precipitation is a scientific challenge with great practical importance. There are two key challenges: Firstly, rainfall is highly variable in its spatial and temporal distribution. Secondly, within a rain-field there are locations where the rainfall intensity is zero (a property referred to as “intermittence”). The practical importance lies in the fact that spatially distributed rainfall fields are of key importance for designers and planners for flood protection. Moreover, the field of weather forecasting is more and more interested in correct spatially-distributed rainfall fields to enhance weather forecasts. Currently, there are no methods available which take these two properties adequately into account. We are suggesting the development of a method that can describe the spatial and temporal variability of rain fields and correctly takes intermittence into account. The purpose of this proposal is to develop a novel methodology for multisite precipitation modelling which is based on Copulas. Copulas are the method of choice to describe spatial and temporal dependence structures, because Copulas allow to describe such a dependence in its purest form. This methodology should be applied to different climatic conditions in Germany and in South-Africa. Different climatic conditions imply a different spatial and temporal distribution of rainfall, and applying the proposed model there will be an ultimate test for the model. First step of the development is to create and test the model for the daily time scale using conventional observations. Subsequently, the model will be tested for smaller time steps, as small as one hour. The model should serve both as a precipitation generating procedure and as the basis for an interpolator and a conditional simulator. The research is planned to be conducted bilaterally in Germany and South Africa and is aimed to complement present research activities both on Copulas and precipitation modelling.