Uncertainty in an emissions-constrained world


Our study focuses on uncertainty in greenhouse gas (GHG) emissions from anthropogenic sources, including land use and land-use change activities. We aim to understand the relevance of diagnostic (retrospective) and prognostic (prospective) uncertainty in an emissions-temperature setting that seeks to constrain global warming and to link uncertainty consistently across temporal scales. We discuss diagnostic and prognostic uncertainty in a systems setting that allows any country to understand its national and near-term mitigation and adaptation efforts in a globally consistent and long-term context. Cumulative emissions are not only constrained and globally binding but exhibit quantitative uncertainty; and whether or not compliance with an agreed temperature target will be achieved is also uncertain. To facilitate discussions, we focus on two countries, the USA and China. While our study addresses whether or not future increase in global temperature can be kept below 2, 3, or 4 °C targets, its primary aim is to use those targets to demonstrate the relevance of both diagnostic and prognostic uncertainty. We show how to combine diagnostic and prognostic uncertainty to take more educated (precautionary) decisions for reducing emissions toward an agreed temperature target; and how to perceive combined diagnostic and prognostic uncertainty-related risk. Diagnostic uncertainty is the uncertainty contained in inventoried emission estimates and relates to the risk that true GHG emissions are greater than inventoried emission estimates reported in a specified year; prognostic uncertainty refers to cumulative emissions between a start year and a future target year, and relates to the risk that an agreed temperature target is exceeded.

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Fig. 1
Fig. 2


  1. 1.

    The four parameters in WBGU’s “historical responsibility” approach are (i) 1990, (ii) 2050, (iii) 25 %, and (iv) 1990; and (i) 2010, (ii) 2050, (iii) 33 %, and (iv) 2010 in its “future responsibility” approach. In both approaches, the probability of exceeding the 2  ºC temperature target refers to cumulative emission constraints for 2000–2049.

  2. 2.

    IIASA’s World Population Program reports 7.8 and 9.9 for the 10th and 90th percentiles.

  3. 3.

    Note that applying the 2 °C Check Tool as described in Section 2.3 but to a cumulative emissions constraint for 2000–2050 of 1800, instead of 1500 Pg CO2-eq, does not encounter any limitations, which is why the risk interval is minimal for maximal uncertainty in p/c emissions and consists of a single value only.

  4. 4.

    Ito (2011) provides a historical meta-analysis of global NPP (1860s–2000s) which allows Haberl and Erb’s HANPP concept with reference to 2000 to be put into a long-term temporal perspective.

  5. 5.

    Haberl et al. (2007: Tab. 1) estimate total HANPP in 2000 to be 57.2 Pg CO2 (including human-induced fires), of which about 6.2 Pg CO2 is internationally transferred (net transfer) according to Erb et al. (2009b: Tab. 2) (about 7.2 Pg CO2 according to the data communicated to us).

  6. 6.

    See http://unfccc.int/parties_and_observers/parties/annex_i/items/2774.php for Annex I countries to the UNFCCC.

  7. 7.

    Respectively, carbon dioxide, methane, nitrous oxide, hydrofluorocarbon, sulfur hexafluoride, perfluorocarbon

  8. 8.

    We employ a total uncertainty in relative terms of 7.5 % (representing the median of the relative uncertainty class 5–10 %) for reporting the emissions of the six Kyoto GHGs excluding emissions from land use and land-use change in both reference and target year; and 0.75 for the correlation in these uncertainties (Jonas et al. 2010b).

  9. 9.

    Respectively, Global Trade and Environment Model; Integrated Model to Assess the Greenhouse Effect; Prospective Outlook on Long-term Energy Systems (model)


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This study was financially supported by the Austrian Climate Research Programme (B068706).

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Correspondence to Matthias Jonas.

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This article is part of a Special Issue on “Third International Workshop on Uncertainty in Greenhouse Gas Inventories” edited by Jean Ometto and Rostyslav Bun.

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Jonas, M., Marland, G., Krey, V. et al. Uncertainty in an emissions-constrained world. Climatic Change 124, 459–476 (2014). https://doi.org/10.1007/s10584-014-1103-6

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  • Diagnostic Uncertainty
  • Cumulative Emission
  • Terrestrial Biosphere
  • Target Path
  • Cumulative Constraint