Update December 2021

Scientific publications (peer-reviewed):

Oberpriller, J., Arneth, A., Herschlein, C., Rammig, A. & Hartig, F. (2021 im Druck). Modellunsicher-heiten in Klimafolgeprojektionen – eine Einführung. In: Mitteilungen der Fränkischen Geographischen Gesellschaft Band 67: Herausforderungen des Klimawandels in Bayern. Erlangen.

In preperation:
Oberpriller, J., Trotsiuk, V., Heiland, L., Hülsmann, L. & Hartig, F. (in preparation) Local Adaptation Bayesian Calibration of a physiological forest ecosystem model shows evidence of biological adaptations across Europe

Goals of the subproject

To assess the consequences of mitigation and adaptation strategies, public and private decision-makers need not only detailed forecasts of the most likely impacts of climate change, but also estimates of the uncertainties associated with such forecasts.

What are the uncertainties of various management options under climate change? Subproject 5 calculates forecasting uncertainties for the predictions made by BLIZ. (Photo: Rammig)

Subproject 5 of BLIZ (BayRisk) at the University of Regensburg deals with quantifying  uncertainties in model projections. BayRisk will create uncertainty estimates of the ecological models used in BLIZ, using Monte-Carlo simulations and Bayesian statistical methods. The calculated uncertainties are then used in cooperation with the socio-economic subprojects of BLIZ to derive probability distributions and risks for economically relevant parameters. Hence, BayRisk forms a link between the ecological subprojects 1-3 and the socio-economic subprojects 4 & 6. The latter conduct research on land use decisions and the evaluation of risks and options for action.