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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Tavoni, Massimo; Bosetti, Valentina; Shayegh, Soheil; Drouet, Laurent; Emmerling, Johannes; Fuss, Sabine et al. (2017): Challenges and Opportunities for Integrated Modeling of Climate Engineering. Fondazione Eni Enrico Mattei (FEEM). Milan (Nota di Lavoro, 38.2017).

"By reviewing the existing literature and reporting the views of experts, we identify research gaps and priorities for improving the integrated assessment of climate engineering. Results point to differentiated roles of CDR and SRM as complementary strategies to the traditional ones, as well as diverse challenges for an adequate representation in integrated assessment models. We identify potential synergies for model development which can help better represent mitigation and adaptation challenges, as well as climate engineering."

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Oschlies, A.; Held, H.; Keller, D.; Keller, K.; Mengis, N.; Quaas, M. et al. (2016): Indicators and Metrics for the Assessment of Climate Engineering. In Earth's Future. DOI 10.1002/2016EF000449

"We here propose that such an effort should be facilitated by a more decision-oriented approach and an iterative procedure in close interaction between academia, decision makers and stakeholders. Specifically, synergies and trade-offs between social objectives reflected by individual indicators, as well as decision-relevant uncertainties should be considered in the development of metrics, so that society can take informed decisions about climate policy measures under the impression of the options available, their likely effects and side effects, and the quality of the underlying knowledge base."

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Dorr, Adam (2016): Technological change and climate scenarios. In Nature Climate change. DOI 10.1038/nclimate2981.

"Thecarbon and climate problem is a crisis today, regardless of what tomorrow may bring. Moreover, the risk of ‘mitigation
obstruction’ and complacency associated with the anticipation of geoengineering ‘techno-fixes’ remains a legitimate
concern."

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