Articles | Volume 13, issue 11
Model description paper
04 Nov 2020
Model description paper |  | 04 Nov 2020

Silicone v1.0.0: an open-source Python package for inferring missing emissions data for climate change research

Robin D. Lamboll, Zebedee R. J. Nicholls, Jarmo S. Kikstra, Malte Meinshausen, and Joeri Rogelj


Interactive discussion

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

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Referee Nomination & Report Request started (24 Aug 2020) by Rolf Sander
RR by Anonymous Referee #2 (02 Sep 2020)
RR by Anonymous Referee #1 (06 Sep 2020)
AR by Svenja Lange on behalf of the Authors (01 Sep 2020)  Author's response
ED: Publish subject to minor revisions (review by editor) (06 Sep 2020) by Rolf Sander
AR by Robin Lamboll on behalf of the Authors (14 Sep 2020)  Author's response    Manuscript
ED: Publish as is (23 Sep 2020) by Rolf Sander
Short summary
Many models project how human activity can lead to more or less climate change, but most of these models do not project all climate-relevant emissions, potentially biasing climate projections. This paper outlines a Python package called Silicone, which can add missing emissions in a flexible yet high-throughput manner. It does this infilling based on more complete literature projections. It facilitates a more complete understanding of the climate impact of alternative emission pathways.