About Us

We are a network of different research institutions in Germany with the common goal to advance research on extreme events in the context of climate change. With the framework programme Research for Sustainable Development (FONA3), the Federal Ministry of Education and Research (BMBF) aims to support sustainability research in Germany. Understanding the occurrence of extreme weather and climate events will help to deal with them more effectively. What are the pressing questions?
How are dynamical processes affecting the intensity, frequency and spatial distribution of extreme events?
Are particular extreme events in the course of climate change already changing their characteristics?
What will be the impact of extreme events in the course of future climate change?

Our Mission

Our mission is to improve the assessment of extreme weather events and their changes, uncertainties and impacts in Central Europe both in the past and in the coming decades. We focus in particular on the hazard types heat waves, droughts, heavy precipitation, including hail, and storms. Since this raises a wide range of research questions, how do we approach them? The entire project is divided into four modules, which form a well-connected research network.

A Research Network


The overall objective of Module A is to significantly improve the understanding of scale interactions and links between atmospheric circulation, their natural variability and the resulting extreme events. This comprises identifying large-scale atmospheric patterns associated with the extreme weather events and understanding whether these large-scale attributes are consistent with changes in the planetary circulation and with the identified dynamics. This analysis is required for a robust estimate of future changes.

Module B aims at detecting and classifying extreme weather events under past and future climate change. With statistical approaches the modified  intensity and frequency for clearly defined spatio-temporal scales, which are derived together with module A or defined by the impact from module C, will be assessed. Furthermore, the attribution of man-made changes in the statistics of extreme events will be investigated. This includes various extreme indices, statistical significance of changes, influence of large-scale anomalies as well as advanced detection and attribution methods.

Module C focuses on extreme events that have an impact on socio-economic systems. This means that it is not only a local extreme value of a meteorological parameter that is of interest, but the combination of specific environmental attributes that make it impact relevant. This may include the spatial extent of extremes, nonlinearities in dependencies, the combination of meteorological parameters, so-called compound events, the influence of non-climatic human factors or vulnerability and exposure.

The overall objective of Module D is to provide support to the scientific activities in the  modules A, B, and C through the coordination of the modelling, data  and software management activities. In addition, the work within module D also includes the development of a common central evaluation system, the provision and evaluation of fundamental datasets for the assessment of climate extreme events, as well as an infrastructure for the climXtreme research community based on achievements of previous BMBF programs.


Module A
A1: SEVERE (Scale Dependent Process Representation)
Scale Dependent Process Representation and Sensitivity Analysis for Most Extreme Events
The project SEVERE investigates the physics, processes and scale dependency of very extreme precipitation events. Very extreme precipitation events with very long return periods (e.g. 100 years) can potentially cause large damages, especially when followed by regional or large scale flooding. This is crucial in a warming climate since atmospheric physics shows that warmer air contains more water than colder air (as described in the Clausius-Clapeyron equation). Hence a larger water content in the air masses brings an increased potential for precipitation extremes. However, this effect is not the only factor since the future development depends as well on the large and regional scale evaporation, atmospheric stability conditions
and large-dynamics dynamics. The period, for which reliable observations exist (~ 50 years), is too short to derive robust estimates on longer time-scales. Therefore, SEVERE will use the data from existing large ensembles of regional climate simulations from German and International projects (MiKlip, CMIP-5/6, CORDEX). The project is structured into three phases: i) The characterization of intensity, extension and duration of observed extreme precipitation events over Europe with respect to their temporal and spatial distribution. ii) Evaluation of the potential of climate simulations to reproduce the relevant features of extreme precipitation as well as the large and
regional scale processes. iii) The results will then be applied to the existing large ensembles of climate simulations to identify a sufficient number of very extreme precipitation events.
Module C
C1: C00 (Coordination, Index Clustering)
Module C coordination and index clustering
The project aims to build and continuously expand an integrated database on damaging weatherconditions on the basis of past and recent observational datasets (reanalysis data) as well as recent and future climate model projections. This starts from well-established extreme indices and integrating novel extreme indices through collaboration with the other projects from Module C focusing on impacts of multiple hazards considered in Module C. The project COO coordinates Module C and will integrate individual Module C work package results to build the database for damaging weather conditions in central Europe. As a key scientific question, the project will address clustering of damaging weather events which are particularly relevant in the (re)insurance context since clustering of damaging events can have severe economic implications.
Module B
B1.1: COORD (Coordination, Detection/Attribution)
Module Coordination and Advanced Detection/Attribution Studies
This project concentrates upon two major lines of tasks. First, the coordination of ClimXtreme in concert with the coordinators of Module A, C and D together with the coordination of the sixteen subprojects within Module B. Scientifically, B1.1 will contribute to the advanced methods of detection and attribution of climate change by anthropogenic influences using a Bayes statistical approach. The methods will include a single event attribution based on an explicit Bayesian likelihood modelling for observed heatwave and wind storm cases given the factual and counterfactual scenario. The data basis will be given by the MiKliP decadal prediction system which can be combined into a 75 member lagged ensemble for about 50 years. Additionally, a set of simulation data will come from the long term (1880 – 2010) historical full forcing, historical natural forcing and historical anthropogenic CMIP5 simulations besides the preindustrial control run to compare different factual scenario (historic full forcing, historic anthropogenic) with different counterfactual (preindustrial control, historic natural) simulations in the Bayesian sense. Observations will be taken from station data and the regional reanalyses REA6.
Project Website: Website
Participating Institutions: Institute of Geosciences, University of Bonn
Contact: Dr. Ieda Pscheidt
Module D
D1: CoDax (Data Management)
Coordination of Data Management in ClimXtreme
To support the scientific activities in ClimXtreme, module D takes over the coordination of software and data management. The priority of the data-related work in CoDaX is to support the ClimXtreme partners in the evaluation and application of new data products by providing and integrating them into a central evaluation system. One highly relevant data source are ground-based meteorological observations for analyzing the extremes of the last decades, especially when looking at centennial time scales. Second, for the assessment of regional extremes in Europe and Germany regional reanalyses have come up as opportunity for a detailed analysis of extreme events. Besides, several gridded data sets as well as global products are considered and will be made available to all ClimXtreme members. In addition to provision and integration, the development of methods for the evaluation and assessment of the data sets with regard to extreme events will be part of CoDax as well. CoDaX will support ClimXtreme by identifying relevant definitions of extreme events and testing the suitability of the station data and reanalysis data for the analysis of extremes based on these definitions.