Articles | Volume 3, issue 1
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.
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.