Pfrommer, T.; Goeschl, T.; Proelss, A.; Carrier, M.; Lenhard, J.; Martin, H. et al. (2019): Establishing causation in climate litigation. Admissibility and reliability. In: Climatic Change 421 (6926), S. 891. DOI: 10.1007/s10584-018-2362-4.

"Climate litigation has attracted renewed interest as a governance tool. A key challenge in climate litigation is to assess the factual basis of causation. Extreme weather attribution, specifically the Fraction of Attributable Risk (FAR), has been proposed as a way to tackle this challenge. What remains unclear is how attribution science interacts with the legal admissibility of evidence based on climate models. "

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Bonetti, F.; McInnes, C. (2018): Multiple input control strategies for robust and adaptive climate engineering in a low-order 3-box model. In: Proceedings. Mathematical, physical, and engineering sciences 474 (2217), S. 20180447. DOI: 10.1098/rspa.2018.0447.

"A low-order 3-box energy balance model for the climate system is employed with a multivariable control scheme for the evaluation of new robust and adaptive climate engineering strategies using solar radiation management. The climate engineering measures are deployed in three boxes thus representing northern, southern and central bands. It is shown that, through heat transport between the boxes, it is possible to effect a degree of latitudinal control through the reduction of insolation."

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Duan, L.; Cao, L.; Bala, G.; Caldeira, K. (2018): Comparison of the Fast and Slow Climate Response to Three Radiation Management Geoengineering Schemes. In: J. Geophys. Res. Atmos. DOI: 10.1029/2018JD029034.

"Geoengineering has been proposed as a backup approach to rapidly cool the Earth and avoid damages associated with anthropogenic climate change. In this study, we use the NCAR Community Earth System Model (CESM) to conduct a series of slab‐ocean and prescribed sea‐surface‐temperature simulations to investigate the climate response to three proposed radiation management geoengineering schemes: stratospheric aerosol increase (SAI), marine cloud brightening (MCB), and cirrus cloud thinning (CCT)."

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Oschlies, A. (2018): Bewertung von Modellqualität und Unsicherheiten in der Klimamodellierung. In: Janich N.; Rhein L. (Hg.): Unsicherheit als Herausforderung für die Wissenschaft: Peter Lang D. DOI: 10.3726/b14379

"The chapter discusses sources of uncertainties in climate models and their possible impacts on the model results. The three criteria “adequacy”, “consistency” and “representativeness” are suggested for a comprehensive assessment of the quality of climate models. The fit to data determines the model’s representativeness. For many climate variables, such as precipitation, cloudiness and the climate sensitivity, this has not significantly improved from the second-to-last to the last assessment report of the Intergovernmental Panel on Climate Change (IPCC)."

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