Beyond equilibrium climate sensitivity

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Abstract

Climate sensitivity, the long-term warming due to doubled atmospheric CO2 levels, is estimated in the range of 1.5 °C to 4.5 °C. A synthesis of work reveals that whether the value falls at the high or low end, future emissions will have to be strongly limited.

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Greenhouse-gas emission targets for limiting global warming to 2 degrees C.

Malte Meinshausen, Nicolai Meinshausen, William Hare … (2009)

More than 100 countries have adopted a global warming limit of 2 degrees C or below (relative to pre-industrial levels) as a guiding principle for mitigation efforts to reduce climate change risks, impacts and damages. However, the greenhouse gas (GHG) emissions corresponding to a specified maximum warming are poorly known owing to uncertainties in the carbon cycle and the climate response. Here we provide a comprehensive probabilistic analysis aimed at quantifying GHG emission budgets for the 2000-50 period that would limit warming throughout the twenty-first century to below 2 degrees C, based on a combination of published distributions of climate system properties and observational constraints. We show that, for the chosen class of emission scenarios, both cumulative emissions up to 2050 and emission levels in 2050 are robust indicators of the probability that twenty-first century warming will not exceed 2 degrees C relative to pre-industrial temperatures. Limiting cumulative CO(2) emissions over 2000-50 to 1,000 Gt CO(2) yields a 25% probability of warming exceeding 2 degrees C-and a limit of 1,440 Gt CO(2) yields a 50% probability-given a representative estimate of the distribution of climate system properties. As known 2000-06 CO(2) emissions were approximately 234 Gt CO(2), less than half the proven economically recoverable oil, gas and coal reserves can still be emitted up to 2050 to achieve such a goal. Recent G8 Communiqués envisage halved global GHG emissions by 2050, for which we estimate a 12-45% probability of exceeding 2 degrees C-assuming 1990 as emission base year and a range of published climate sensitivity distributions. Emissions levels in 2020 are a less robust indicator, but for the scenarios considered, the probability of exceeding 2 degrees C rises to 53-87% if global GHG emissions are still more than 25% above 2000 levels in 2020.

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Irreversible climate change due to carbon dioxide emissions.

Susan Solomon, Gian-Kasper Plattner, Reto Knutti … (2009)

The severity of damaging human-induced climate change depends not only on the magnitude of the change but also on the potential for irreversibility. This paper shows that the climate change that takes place due to increases in carbon dioxide concentration is largely irreversible for 1,000 years after emissions stop. Following cessation of emissions, removal of atmospheric carbon dioxide decreases radiative forcing, but is largely compensated by slower loss of heat to the ocean, so that atmospheric temperatures do not drop significantly for at least 1,000 years. Among illustrative irreversible impacts that should be expected if atmospheric carbon dioxide concentrations increase from current levels near 385 parts per million by volume (ppmv) to a peak of 450-600 ppmv over the coming century are irreversible dry-season rainfall reductions in several regions comparable to those of the "dust bowl" era and inexorable sea level rise. Thermal expansion of the warming ocean provides a conservative lower limit to irreversible global average sea level rise of at least 0.4-1.0 m if 21st century CO(2) concentrations exceed 600 ppmv and 0.6-1.9 m for peak CO(2) concentrations exceeding approximately 1,000 ppmv. Additional contributions from glaciers and ice sheet contributions to future sea level rise are uncertain but may equal or exceed several meters over the next millennium or longer.

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The use of the multi-model ensemble in probabilistic climate projections.

Claudia Tebaldi, Reto Knutti (2007)

Recent coordinated efforts, in which numerous climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multi-model ensembles sample initial condition, parameter as well as structural uncertainties in the model design, and they have prompted a variety of approaches to quantify uncertainty in future climate in a probabilistic way. This paper outlines the motivation for using multi-model ensembles, reviews the methodologies published so far and compares their results for regional temperature projections. The challenges in interpreting multi-model results, caused by the lack of verification of climate projections, the problem of model dependence, bias and tuning as well as the difficulty in making sense of an 'ensemble of opportunity', are discussed in detail.

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Author and article information

Journal

Title: Nature Geoscience

Abbreviated Title: Nature Geosci

Publisher: Springer Nature

ISSN (Print): 1752-0894

ISSN (Electronic): 1752-0908

Publication date Created: September 4 2017

Publication date (Print): September 4 2017

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DOI: 10.1038/ngeo3017

SO-VID: 841e99c0-035d-42a6-8fcf-f18119c82e80

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Beyond equilibrium climate sensitivity

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PLOS Climate

Greenhouse-gas emission targets for limiting global warming to 2 degrees C.

Irreversible climate change due to carbon dioxide emissions.

The use of the multi-model ensemble in probabilistic climate projections.

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