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Climate of the Past An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 2 | Copyright
Clim. Past, 14, 139-155, 2018
https://doi.org/10.5194/cp-14-139-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 05 Feb 2018

Research article | 05 Feb 2018

Signal detection in global mean temperatures after “Paris”: an uncertainty and sensitivity analysis

Hans Visser1, Sönke Dangendorf2, Detlef P. van Vuuren1,3, Bram Bregman4, and Arthur C. Petersen5 Hans Visser et al.
  • 1PBL Netherlands Environmental Assessment Agency, Bilthoven, the Netherlands
  • 2Research Institute for Water and Environment, University Siegen, Siegen, Germany
  • 3Faculty of Geosciences, University Utrecht, Utrecht, the Netherlands
  • 4Institute for Science, Innovation and Society, Radboud University, Nijmegen, the Netherlands
  • 5STEaPP, University College London, London, UK

Abstract. In December 2015, 195 countries agreed in Paris to hold the increase in global mean surface temperature (GMST) well below 2.0°C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5°C. Since large financial flows will be needed to keep GMSTs below these targets, it is important to know how GMST has progressed since pre-industrial times. However, the Paris Agreement is not conclusive as regards methods to calculate it. Should trend progression be deduced from GCM simulations or from instrumental records by (statistical) trend methods? Which simulations or GMST datasets should be chosen, and which trend models? What is pre-industrial and, finally, are the Paris targets formulated for total warming, originating from both natural and anthropogenic forcing, or do they refer to anthropogenic warming only? To find answers to these questions we performed an uncertainty and sensitivity analysis where datasets and model choices have been varied. For all cases we evaluated trend progression along with uncertainty information. To do so, we analysed four trend approaches and applied these to the five leading observational GMST products. We find GMST progression to be largely independent of various trend model approaches. However, GMST progression is significantly influenced by the choice of GMST datasets. Uncertainties due to natural variability are largest in size. As a parallel path, we calculated GMST progression from an ensemble of 42 GCM simulations. Mean progression derived from GCM-based GMSTs appears to lie in the range of trend–dataset combinations. A difference between both approaches appears to be the width of uncertainty bands: GCM simulations show a much wider spread. Finally, we discuss various choices for pre-industrial baselines and the role of warming definitions. Based on these findings we propose an estimate for signal progression in GMSTs since pre-industrial.

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In December 2015, 195 countries agreed in Paris to hold the increase in global temperature well below 2.0 °C. However, the Paris Agreement is not conclusive as regards methods to calculate it. To find answers to these questions we performed an uncertainty and sensitivity analysis where datasets, model choices, choices for pre-industrial and warming definitions have been varied. Based on these findings we propose an estimate for signal progression in global temperature since pre-industrial time.
In December 2015, 195 countries agreed in Paris to hold the increase in global temperature well...
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