Dr. Ieda Pscheidt
Institute of Geosciences, Meteorology, University of Bonn
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Advanced methods of detection and attribution of climate change by anthropogenic influences using a Bayesian statistical approach
This project is part of the ClimXtreme project funded by the German Federal Ministry of Education and Research (BMBF-Bundesministerium für Bildung und Forschung) and aims to answer the question of whether detected single extreme events of heatwaves can be attributed to anthropogenic climate change.
Detection is defined as "the process of demonstrating that an observed change is significantly different from a change that can be explained by the natural internal variability" (IPCC, 2001; Mitchell et al., 2001). The attribution of the detected change to an external forcing, such as anthropogenic activities is performed by "assessing evidence that shows the change is unlikely to be due to internal variability alone, consistent with the estimated responses to the given combination of anthropogenic and natural forcing, and not consistent with alternative" (IPCC 2001; Mitschell et al., 2001).
In practice, detection and attribution studies of climate change signals are conducted by comparing climate model simulations with the observations using different statistical methods. Here, a Bayesian approach is used for the detection and attribution study of single heatwave events in Germany to anthropogenic activities.
A set of simulation data from the long term (1850 - 2005) CMIP5 historical full forcing, historical natural forcing and historical anthropogenic simulations, as well as the preindustrial control run, is used to compare different factual (historic full forcing, historic anthropogenic) with different counterfactual (preindustrial control, historic natural) scenarios in the Bayesian sense. The observations are from radiosonde stations.
Project members:
Andreas Hense, Ieda Pscheidt, Christian Ohlwein
BMBF (ClimXtreme)