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This work reviews the literature on an alleged global warming 'pause' in global mean surface temperature (GMST) to determine how it has been defined, what time intervals are used to characterise it, what data are used to measure it, and what methods used to assess it. We test for 'pauses', both in the normally understood meaning of the term to mean no warming trend, as well as for a 'pause' defined as a substantially slower trend in GMST. The tests are carried out with the historical versions of GMST that existed for each pause-interval tested, and with current versions of each of the GMST datasets. The tests are conducted following the common (but questionable) practice of breaking the linear fit at the start of the trend interval ('broken' trends), and also with trends that are continuous with the data bordering the trend interval. We also compare results when appropriate allowance is made for the selection bias problem. The results show that there is little or no statistical evidence for a lack of trend or slower trend in GMST using either the historical data or the current data. The perception that there was a 'pause' in GMST was bolstered by earlier biases in the data in combination with incomplete statistical testing.

In a recent issue of this journal, Loehle (2014) presents a “minimal model” for estimating climate sensitivity, identical to that previously published by Loehle and Scafetta (2011) . The novelty in the more recent paper lies in the straightforward calculation of an estimate of transient climate response based on the model and an estimate of equilibrium climate sensitivity derived therefrom, via a flawed methodology. We demonstrate that the Loehle and Scafetta model systematically underestimates the transient climate response, due to a number of unsupportable assumptions regarding the climate system. Once the flaws in Loehle and Scafetta's model are addressed, the estimates of transient climate response and equilibrium climate sensitivity derived from the model are entirely consistent with those obtained from general circulation models, and indeed exclude the possibility of low climate sensitivity, directly contradicting the principal conclusion drawn by Loehle. Further, we present an even more parsimonious model for estimating climate sensitivity. Our model is based on observed changes in radiative forcings, and is therefore constrained by physics, unlike the Loehle model, which is little more than a curve-fitting exercise.

In a recent paper (Chen et al., 2013), fractional changes in temperature were correlated with fractional changes in anthropogenic emissions of carbon dioxide in order to estimate the amount of warming attributable to CO2 emissions. No justification was given for using the emissions rate rather than cumulative changes in atmospheric CO2 and the assumptions are not physically-based. This leads to counter-physical predictions, such as cases where increased heating causes the Earth to cool. Furthermore, a 10-year shift in start date alters the calculated elasticity by a factor of 2. A standard energy balance model is physically-based and outperforms the Chen et al. (2013) model, and its fitted transient climate response is consistent with changes in atmospheric CO2 causing warming equivalent to approximately 100% of the temperature change observed since 1960, consistent with formal attribution analyses. It is cautioned that purely statistical correlations are not able to demonstrate cause, and that they are particularly poor at attribution when there is no physical basis for the selection of variables and functional forms used in the correlation analysis.

Human activities, principally the burning of fossil fuels, are changing the climate. Despite widespread scientific consensus on this fact, communicating the risks posed by climate change to the public remains challenging. We examine the role of contrarian narratives in climate communication, focusing on two terminological claims—(1) that scientists abandoned the term global warming in favor of climate change in response to a change in temperature evolution, and (2) that catastrophic anthropogenic global warming is the mainstream scientific position—and find them to be without merit. We discuss how scientists and communicators can neutralize these myths while informing the public. Finally, we summarize the existing literature on word choice in climate communications and suggest best practices based on target audiences.