Preprints
https://doi.org/10.5194/gc-2018-5
https://doi.org/10.5194/gc-2018-5
05 Jun 2018
 | 05 Jun 2018
Status: this discussion paper is a preprint. It has been under review for the journal Geoscience Communication (GC). The manuscript was not accepted for further review after discussion.

STAGE 2.0: Sensitivity Transfer Analysis of Greenhouse Emissions

Peter O. Passenier

Abstract. A simulation tool has been realized with which the sensitivity of the Earth climate system to human interference can be studied. The tool is intended to offer users of the software, e.g. students in higher education, support in gaining insight into critical aspects of the climate system and thus counteracting common misconceptions with regard to the functioning of this system. The conceptual design of the tool is based on the paradigm learning as experimenting, encouraging students to explore climate sensitivity in its various aspects in an active manner. The feasibility of the educational application is demonstrated by exploring possible long-term climate consequences and uncertainties of near-term greenhouse-gas mitigation actions, as an outcome of present-day world-wide negotiations under the UNFCCC umbrella.

Peter O. Passenier
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Peter O. Passenier
Peter O. Passenier

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Short summary
A simulation tool has been realized with which the sensitivity of the Earth climate system to human interference can be studied. The tool is intended to offer users of the software, e.g. students in higher education, support in gaining insight into critical aspects of the climate system and thus counteracting common misconceptions with regard to the functioning of this system. The conceptual design of the tool is based on the paradigm learning as experimenting.
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