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  • 1
    Publication Date: 2022-05-25
    Description: Author Posting. © American Meteorological Society, 2009. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 22 (2009): 5175–5204, doi:10.1175/2009JCLI2863.1.
    Description: 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.
    Description: This work was supported in part by the Office of Science (BER), U.S. Department of Energy Grants DE-FG02-94ER61937 and DE-FG02-93ER61677, and by the industrial and foundations sponsors of The MIT Joint Program on the Science and Policy of Global Change (http://globalchange.mit.edu/sponsors/ current.html).
    Keywords: Probability forecasts/models ; Climate prediction ; Anthropogenic effects ; Numerical analysis/modeling ; Feedback
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
    Publication Date: 2022-05-25
    Description: Author Posting. © American Meteorological Society, 2010. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 23 (2010): 2230–2231, doi:10.1175/2009JCLI3566.1.
    Description: Corrigendum: Sokolov, A., and Coauthors, 2009: Probabilistic forecast for twenty-first-century climate based on uncertainties in emissions (without policy) and climate parameters. J. Climate, 22, 5175–5204.
    Keywords: Probability forecasts/models ; Climate prediction ; Anthropogenic effects ; Numerical analysis/modeling ; Feedback
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
    Location Call Number Limitation Availability
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  • 3
    Publication Date: 2016-10-08
    Description: Background In-stent hyperplasia (ISH) may develop in regions of low endothelial shear stress (ESS), but the relationship between the magnitude of low ESS, the extent of ISH, and subsequent clinical events has not been investigated. Methods and Results We assessed the association of poststent ESS with neointimal ISH and clinical outcomes in patients treated with percutaneous coronary interventions (PCI). Three-dimensional coronary reconstruction was performed in 374 post-PCI patients at baseline and 6 to 10 months follow-up as part of the PREDICTION Study. Each vessel was divided into 1.5-mm-long segments, and we calculated the local ESS within each stented segment at baseline. At follow-up, we assessed ISH and the occurrence of a clinically indicated repeat PCI for in-stent restenosis. In 246 total stents (54 overlapping), 100 (40.7%) were bare-metal stents (BMS), 104 (42.3%) sirolimus-eluting stents, and 42 (17.1%) paclitaxel-eluting stents. In BMS, low ESS post-PCI at baseline was independently associated with ISH (β=1.47 mm 2 per 1-Pa decrease; 95% CI, 0.38–2.56; P 〈0.01). ISH was minimal in drug-eluting stents. During follow-up, repeat PCI in BMS was performed in 21 stents (8.5%). There was no significant association between post-PCI ESS and in-stent restenosis requiring PCI. Conclusions Low ESS after BMS implantation is associated with subsequent ISH. ISH is strongly inhibited by drug-eluting stents. Post-PCI ESS is not associated with in-stent restenosis requiring repeat PCI. ESS is an important determinant of ISH in BMS, but ISH of large magnitude to require PCI for in-stent restenosis is likely attributed to factors other than ESS within the stent.
    Keywords: Vascular Biology
    Electronic ISSN: 2047-9980
    Topics: Medicine
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