Journal cover Journal topic
Climate of the Past An interactive open-access journal of the European Geosciences Union
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
06 Jul 2017
Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Climate of the Past (CP) and is expected to appear here in due course.
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 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, Great Britain
Abstract. Abstract. In December 2015, 195 countries agreed in Paris to hold the increase in global mean surface temperature (GMT) 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 GMTs below these targets, it is important to know how GMT has progressed since pre-industrial times, taking short-term and long-term (decadal) natural variability into account. However, the Paris Agreement is not conclusive as for methods to calculate it. Should trend progression be deduced from GCM simulations or from instrumental records by (statistical) trend methods? Which trend model should be chosen and what is pre-industrial? Does trend progression depend on the specific GMT dataset chosen? 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 since pre-industrial, along with uncertainty information. To do so, we analysed four trend approaches and applied these to the five leading GMT products. As a parallel path, we calculated GMT progression from an ensemble of 106 GCM simulations, corrected for natural variability. We find GMT progression to be largely independent of various trend model approaches. However, GMT progression is significantly influenced by the choice of GMT datasets. Both sources of uncertainty are dominated by natural variability. Mean progression derived from GCM-based GMTs appears to lie within the range of the trend-dataset combinations. A difference between both approaches lies in the width of uncertainty bands: bands for GCMs are much wider. Results appear to be robust as for specific choices for pre-industrial. Our Paris policy recommendation would be to choose a spline or IRW trend model and estimate it on the average of the five leading GMT datasets, where 1880 is taken as base year. Given this choice trend progression for 2016 accounts for 1.01 ± 0.13 °C (2-σ).

Citation: Visser, H., Dangendorf, S., Van Vuuren, D. P., Bregman, B., and Petersen, A. C.: Signal detection in global mean temperatures after Paris: an uncertainty and sensitivity analysis, Clim. Past Discuss.,, in review, 2017.
Hans Visser et al.
Hans Visser et al.


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