by Michael E. Mann and Gavin Schmidt
This time last year we gave an overview of what different methods of assessing climate sensitivity were giving in the most recent analyses. We discussed the three general methods that can be used:
The first is to focus on a time in the past when the climate was different and in quasi-equilibrium, and estimate the relationship between the relevant forcings and temperature response (paleo-constraints). The second is to find a metric in the present day climate that we think is coupled to the sensitivity and for which we have some empirical data (climatological constraints). Finally, there are constraints based on changes in forcing and response over the recent past (transient constraints).
All three constraints need to be reconciled to get a robust idea what the sensitivity really is.
A new paper using the second ‘climatological’ approach by Steve Sherwood and colleagues was just published in Nature and like Fasullo and Trenberth (2012) (discussed here) suggests that models with an equilibrium climate sensitivity (ECS) of less than 3ºC do much worse at fitting the observations than other models.
S.C. Sherwood, S. Bony, and J. Dufresne, "Spread in model climate sensitivity traced to atmospheric convective mixing", Nature, vol. 505, pp. 37-42, 2014. http://dx.doi.org/10.1038/nature12829
J.T. Fasullo, and K.E. Trenberth, "A Less Cloudy Future: The Role of Subtropical Subsidence in Climate Sensitivity", Science, vol. 338, pp. 792-794, 2012. http://dx.doi.org/10.1126/science.1227465
Since 1998 the global temperature has risen more slowly than before. Given the many explanations for colder temperatures discussed in the media and scientific literature (La Niña, heat uptake of the oceans, arctic data gap, etc.) one could jokingly ask why no new ice age is here yet. This fails to recognize, however, that the various ingredients are small and not simply additive. Here is a small overview and attempt to explain how the different pieces of the puzzle fit together.
Figure 1 The global near-surface temperatures (annual values at the top, decadal means at the bottom) in the three standard data sets HadCRUT4 (black), NOAA (orange) and NASA GISS (light blue). Graph: IPCC 2013. More »
No doubt, our climate system is complex and messy. Still, we can sometimes make some inferences about it based on well-known physical principles. Indeed, the beauty of physics is that a complex systems can be reduced into simple terms that can be quantified, and the essential aspects understood.
A recent paper by Sloan and Wolfendale (2013) provides an example where they derive a simple conceptual model of how the greenhouse effect works from first principles. They show the story behind the expression saying that a doubling in CO2 should increase the forcing by a factor of 1+log|2|/log|CO2|. I have a fondness for such simple conceptual models (e.g. I’ve made my own attempt posted at arXiv) because they provide a general picture of the essence – of course their precision is limited by their simplicity.
T. Sloan, and A.W. Wolfendale, "Cosmic rays, solar activity and the climate", Environ. Res. Lett., vol. 8, pp. 045022, 2013. http://dx.doi.org/10.1088/1748-9326/8/4/045022
Some will be luckier than others when it comes to climate change. The effects of a climate change on me will depend on where I live. In some regions, changes may not be as noticeable as in others. So what are the impacts in my region?
Last year I discussed the basis of the AR4 attribution statement:
Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.
In the new AR5 SPM (pdf), there is an analogous statement:
It is extremely likely that more than half of the observed increase in global average surface temperature from 1951 to 2010 was caused by the anthropogenic increase in greenhouse gas concentrations and other anthropogenic forcings together. The best estimate of the human-induced contribution to warming is similar to the observed warming over this period.
This includes differences in the likelihood statement, drivers and a new statement on the most likely amount of anthropogenic warming.
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