Among the weather-related disasters, drought affects the most people worldwide. In view of an increasing frequency and intensity of drought episodes in many regions of the world including Europe coupled with rising vulnerability, a shift from ad hoc strategies towards mitigation based approaches to drought management is inevitable. The necessary underpinning for these actions is a consistent multivariate spatio-temporal framework for defining, characterizing, backcasting and monitoring drought.
The aim of this project is to develop and apply recent approaches to joint modeling of meteorological variables to enhance the temporal and spatial characterization of drought events, and to validate the impacts of past events on the biosphere. A stepwise modeling approach will be used to model spatial dependency of primary meteorological variables via Gaussian Markow random fields and the multivariate dependency structures of residuals via a new spatial extension of vine copulas to allow for non-symmetric dependence. Novel multiscalar descriptors of drought conditions based on the spatio-temporal dependency structures of primary climatic variables will then be derived from the models.
These drought indices are supposed to supersede existing approaches to drought characterization. The validation of these indices will be facilitated using the response of different systems of the biosphere to identified drought events. Predominantly using proxy data for vegetation response, but also data on atmospheric isotopic composition and archived impact data from various sources, this validation step will be carried out in the temporal and spatial domain alike.