4 research outputs found

    Opportunities and challenges in using remaining carbon budgets to guide climate policy

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    The remaining carbon budget represents the total amount of CO2 that can still be emitted in the future while limiting global warming to a given temperature target. Remaining carbon budget estimates range widely, however, and this uncertainty can be used to either trivialize the most ambitious mitigation targets by characterizing them as impossible, or to argue that there is ample time to allow for a gradual transition to a low-carbon economy. Neither of these extremes is consistent with our best understanding of the policy implications of remaining carbon budgets. Understanding the scientific and socio-economic uncertainties affecting the size of the remaining carbon budgets, as well as the methodological choices and assumptions that underlie their calculation, is essential before applying them as a policy tool. Here we provide recommendations on how to calculate remaining carbon budgets in a traceable and transparent way, and discuss their uncertainties and implications for both international and national climate policies

    An integrated approach to quantifying uncertainties in the remaining carbon budget

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    The remaining carbon budget quantifies the future CO2 emissions to limit global warming below a desired level. Carbon budgets are subject to uncertainty in the Transient Climate Response to Cumulative CO2 Emissions (TCRE), as well as to non-CO2 climate influences. Here we estimate the TCRE using observational constraints, and integrate the geophysical and socioeconomic uncertainties affecting the distribution of the remaining carbon budget. We estimate a median TCRE of 0.44 °C and 5–95% range of 0.32–0.62 °C per 1000 GtCO2 emitted. Considering only geophysical uncertainties, our median estimate of the 1.5 °C remaining carbon budget is 440 GtCO2 from 2020 onwards, with a range of 230–670 GtCO2, (for a 67–33% chance of not exceeding the target). Additional socioeconomic uncertainty related to human decisions regarding future non-CO2 emissions scenarios can further shift the median 1.5 °C remaining carbon budget by ±170 GtCO2

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

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    Integrated assessment models (IAMs) project future anthropogenic emissions which can be used as input for climate models. However, the full list of climate-relevant emissions is lengthy and most IAMs do not model all of them. Here we present Silicone, an open-source Python package which infers anthropogenic emissions of unmodelled species based on other reported emissions projections. 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 found in other scenarios. Infilling 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). This paper presents a variety of infilling options and outlines their suitability for different cases. We recommend certain infilling techniques as good defaults but emphasise that considering the specifics of the model being infilled will produce better results. We demonstrate the package's utility with three examples: infilling all required gases for a pathway with data for only one emission species, splitting up a Kyoto emissions total into separate gases, and complementing a set of idealised emissions curves to provide a complete, consistent emissions portfolio. The code and notebooks explaining details of the package and how to use it are available on GitHub (https://github.com/GranthamImperial/silicone, last access: 2 November 2020). The repository with this paper's examples and uses of the code to complement existing research is available at https://github.com/GranthamImperial/silicone_example
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