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Advances in Statistical Climatology, Meteorology and Oceanography An international open-access journal on applied statistics
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We present new probabilistic estimates of model parameters in the MIT Earth System Model using more recent data and an updated method. Model output is compared to observed climate change to determine which sets of model parameters best simulate the past. In response to increasing surface temperatures and accelerated heat storage in the ocean, our estimates of climate sensitivity and ocean diffusivity are higher. Using a new interpolation algorithm results in smoother probability distributions.
ASCMO | Articles | Volume 4, issue 1/2
Adv. Stat. Clim. Meteorol. Oceanogr., 4, 19–36, 2018
https://doi.org/10.5194/ascmo-4-19-2018
Adv. Stat. Clim. Meteorol. Oceanogr., 4, 19–36, 2018
https://doi.org/10.5194/ascmo-4-19-2018

  30 Nov 2018

30 Nov 2018

Estimates of climate system properties incorporating recent climate change

Alex G. Libardoni et al.

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Cited articles

Aldrin, M., Holden, M., Guttorp, P., Skeie, R. B., Myhre, G., and Bernstein, T. K.: Bayesian estimation of climate sensitivity based on a simple climate model fitted to observations of hemispheric temperatures and global ocean heat content, Environmetrics, 23, 253–271, 2012. a, b
Andrews, D. G. and Allen, M. R.: Diagnosis of climate models in terms of transient climate response and feedback response time, Atmos. Sci. Lett., 9, 7–12, 2008. a
Andronova, N. G. and Schlesinger, M. E.: Objective estimation of the probability density function for climate sensitivity, J. Geophys. Res., 106, 22605–22612, 2001. a
Bayes, T.: An essay towards solving a problem in the doctrine of chances, Phil. Trans. Roy. Soc., 53, 370–418, 1763. a
Bindoff, N. L., Stott, P. A., AchutaRao, K. M., Allen, M. R., Gillett, N., Gutzler, D., Hansingo, K., Hegerl, G., Gu, Y., Jain, S., Mokhov, I. I., Overland, J., Perlwitz, J., Sebbari, R., and Zhang, X.: Detection and attribution of climate change: From global to regional, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T., Qin, D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P., 867–952, Cambridge University Press, Cambridge, UK and New York, NY, USA, 2013. a
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Short summary
We present new probabilistic estimates of model parameters in the MIT Earth System Model using more recent data and an updated method. Model output is compared to observed climate change to determine which sets of model parameters best simulate the past. In response to increasing surface temperatures and accelerated heat storage in the ocean, our estimates of climate sensitivity and ocean diffusivity are higher. Using a new interpolation algorithm results in smoother probability distributions.
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