Extreme precipitation events are expected to intensify in a warming climate. How the characteristics of these events and the associated uncertainties may change is less certain, e.g. if events will cover a larger area, last longer or travel larger distances. To assess changes in such precipitation characteristics, an object-oriented analysis is required: using Lagrangian tracking methods (see image), precipitation events are identified as a collection of objects, whose spatial characteristics are quantified through the lifecycle of the event. To reliably investigate extreme precipitation events – particularly convective events – in a future climate, high-resolution climate models are required. XPreCCC thus uses convection-permitting regional climate models to simulate extreme events in the present, past and future climates and the Lagrangian tracking algorithm is applied to these simulations. Furthermore, in order to assess uncertainty in the changes of precipitation characteristics, ensemble simulations are employed. XPreCCC is also interested in the question of climate attribution, namely, can past changes in the climate explain characteristics of observed present-day extremes. Here, a similar modelling strategy is employed, except that an additional model ensemble representative of a counter-factual pre-industrial climate is also created. In identifying any changes, XPreCCC also seeks to examine if these can be modulated by any local-scale factors and if they sensitive to any warming thresholds.

Website: XPRECCCC
Institution: Institut für Meteorologie, Freie Universität Berlin
Contact: Prof. Dr. H. Rust, Prof. Dr. U. Ulbrich