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Silicone is an open-source Python package which infers anthropogenic emissions of missing species based on other known emissions. For example, it can infer nitrous oxide emissions in one scenario based on carbon dioxide emissions from that scenario plus the relationship between nitrous oxide and carbon dioxide emissions in other scenarios. This broadens the range of IAMs available for exploring projections of future climate change and hence Silicone forms part of the open-source pipeline for assessments of the climate implications of IAM scenarios, led by the Integrated Assessment Modelling Consortium (IAMC). A paper describing the model in detail can be found at https://gmd.copernicus.org/articles/13/5259/2020/gmd-13-5259-2020.html (https://doi.org/10.5194/gmd-13-5259-2020) and more recent code developments can be found at https://github.com/GranthamImperial/silicone
IAM, infilling
IAM, infilling
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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