Articles | Volume 3, issue 1
https://doi.org/10.5194/ascmo-3-33-2017
https://doi.org/10.5194/ascmo-3-33-2017
09 Jun 2017
 | 09 Jun 2017

Estimating trends in the global mean temperature record

Andrew Poppick, Elisabeth J. Moyer, and Michael L. Stein

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Cited articles

Aldrin, M., Holden, M., Guttorp, P., Skeie, R. B., Myhre, G., and Berntsen, 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.
Armour, K. C., Bitz, C. M., and Roe, G. H.: Time-varying climate sensitivity from regional feedbacks, J. Climate, 26, 4518–4534, 2013.
Arrhenius, S.: On the influence of carbonic acid in the air upon the temperature of the ground, Philos. Mag. 5, 41, 237–276, 1896.
Beran, J., Feng, Y., Ghosh, S., and Kulik, R.: Long-memory processes, Springer, New York, 2013.
Bloch-Johnson, J., Pierrehumbert, R. T., and Abbot, D. S.: Feedback temperature dependence determines the risk of high warming, Geophys. Res. Lett., 42, 4973–4980, 2015.
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Short summary
We show that ostensibly empirical methods of analyzing trends in the global mean temperature record, which appear to de-emphasize assumptions, can nevertheless produce misleading inferences about trends and associated uncertainty. We illustrate how a simple but physically motivated trend model can provide better-fitting and more broadly applicable results, and show the importance of adequately characterizing internal variability for estimating trend uncertainty.
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