9 research outputs found

    Permafrost degradation and methane: low risk of biogeochemical climate-warming feedback

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    Climate change and permafrost thaw have been suggested to increase high latitude methane emissions that could potentially represent a strong feedback to the climate system. Using an integrated earth-system model framework, we examine the degradation of near-surface permafrost, temporal dynamics of inundation (lakes and wetlands) induced by hydro-climatic change, subsequent methane emission, and potential climate feedback. We find that increases in atmospheric CH[subscript 4] and its radiative forcing, which result from the thawed, inundated emission sources, are small, particularly when weighed against human emissions. The additional warming, across the range of climate policy and uncertainties in the climate-system response, would be no greater than 0.1 ° C by 2100. Further, for this temperature feedback to be doubled (to approximately 0.2 ° C) by 2100, at least a 25-fold increase in the methane emission that results from the estimated permafrost degradation would be required. Overall, this biogeochemical global climate-warming feedback is relatively small whether or not humans choose to constrain global emissions.United States. Dept. of Energy (Climate Change Prediction Program Grant DE-PS02-08ER08-05)United States. Dept. of Energy. Office of Science (Biological and Environmental Research

    Data associated with the paper Sokolov et al. (2018): "Description and Evaluation of the MIT Earth System Model (MESM)"

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    Data used to produce figures in the paper "Description and Evaluation of the MIT Earth System Model (MESM)" by Andrei Sokolov, David Kicklighter, Adam Schlosser, Chien Wang, Erwan Monier, Benjamin Brown-Steiner, Ron Prinn, Chris Forest, Xiang Gao, Alex Libardoni and Sebastian Eastham

    Probabilistic Forecast for Twenty-First-Century Climate Based on Uncertainties in Emissions (Without Policy) and Climate Parameters

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    The Massachusetts Institute of Technology (MIT) Integrated Global System Model is used to make probabilistic projections of climate change from 1861 to 2100. Since the model’s first projections were published in 2003, substantial improvements have been made to the model, and improved estimates of the probability distributions of uncertain input parameters have become available. The new projections are considerably warmer than the 2003 projections; for example, the median surface warming in 2091–2100 is 5.1°C compared to 2.4°C in the earlier study. Many changes contribute to the stronger warming; among the more important ones are taking into account the cooling in the second half of the twentieth century due to volcanic eruptions for input parameter estimation and a more sophisticated method for projecting gross domestic product (GDP) growth, which eliminated many low-emission scenarios. However, if recently published data, suggesting stronger twentieth-century ocean warming, are used to determine the input climate parameters, the median projected warming at the end of the twenty-first century is only 4.1°C. Nevertheless, all ensembles of the simulations discussed here produce a much smaller probability of warming less than 2.4°C than implied by the lower bound of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) projected likely range for the A1FI scenario, which has forcing very similar to the median projection in this study. The probability distribution for the surface warming produced by this analysis is more symmetric than the distribution assumed by the IPCC because of a different feedback between the climate and the carbon cycle, resulting from the inclusion in this model of the carbon–nitrogen interaction in the terrestrial ecosystem.United States. Dept. of Energy (Grants DE-FG02-94ER61937 and DE-FG02-93ER61677

    Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

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    Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions
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