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A Bit More Sensitive…

Filed under: — mike @ 2 January 2014

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 3ÂşC do much worse at fitting the observations than other models.

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References

  1. 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
  2. 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

Arctic and American Methane in Context

Filed under: — david @ 24 November 2013

Lots of interesting methane papers this week. In Nature Geoscience, Shakhova et al (2013) have published a substantial new study of the methane cycle on the Siberian continental margin of the Arctic Ocean. This paper will get a lot of attention, because it follows by a few months a paper from last summer, Whiteman et al (2013), which claimed a strong (and expensive) potential impact from Arctic methane on near-term climate evolution. That economic modeling study was based on an Arctic methane release scenario proposed in an earlier paper by Shakhova (2010). In PNAS, Miller et al (2013) find that the United States may be emitting 50-70% more methane than we thought. So where does this leave us?

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References

  1. N. Shakhova, I. Semiletov, I. Leifer, V. Sergienko, A. Salyuk, D. Kosmach, D. Chernykh, C. Stubbs, D. Nicolsky, V. Tumskoy, and Ă. Gustafsson, "Ebullition and storm-induced methane release from the East Siberian Arctic Shelf", Nature Geosci, vol. 7, pp. 64-70, 2013. http://dx.doi.org/10.1038/NGEO2007
  2. G. Whiteman, C. Hope, and P. Wadhams, "Climate science: Vast costs of Arctic change", Nature, vol. 499, pp. 401-403, 2013. http://dx.doi.org/10.1038/499401a
  3. N.E. Shakhova, V.A. Alekseev, and I.P. Semiletov, "Predicted methane emission on the East Siberian shelf", Dokl. Earth Sc., vol. 430, pp. 190-193, 2010. http://dx.doi.org/10.1134/S1028334X10020091
  4. S.M. Miller, S.C. Wofsy, A.M. Michalak, E.A. Kort, A.E. Andrews, S.C. Biraud, E.J. Dlugokencky, J. Eluszkiewicz, M.L. Fischer, G. Janssens-Maenhout, B.R. Miller, J.B. Miller, S.A. Montzka, T. Nehrkorn, and C. Sweeney, "Anthropogenic emissions of methane in the United States", Proceedings of the National Academy of Sciences, vol. 110, pp. 20018-20022, 2013. http://dx.doi.org/10.1073/pnas.1314392110

Simple physics and climate

Filed under: — rasmus @ 12 November 2013

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.

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References

  1. 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

The evolution of radiative forcing bar-charts

Filed under: — gavin @ 7 October 2013

As part of the IPCC WG1 SPM(pdf) released last Friday, there was a subtle, but important, change in one of the key figures – the radiative forcing bar-chart (Fig. SPM.4). The concept for this figure has been a mainstay of summaries of climate change science for decades, and the evolution over time is a good example of how thinking and understanding has progressed over the years while the big picture has not shifted much.


The Radiative-Forcing bar chart: AR5 version

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The new IPCC climate report

The time has come: the new IPCC report is here! After several years of work by over 800 scientists from around the world, and after days of extensive discussion at the IPCC plenary meeting in Stockholm, the Summary for Policymakers was formally adopted at 5 o’clock this morning. Congratulations to all the colleagues who were there and worked night shifts. The full text of the report will be available online beginning of next week. Realclimate summarizes the key findings and shows the most interesting graphs.

Update 29 Sept: Full (un-copyedited) report available here.

Global warming

It is now considered even more certain (> 95%) that human influence has been the dominant cause of the observed warming since the mid-20th century. Natural internal variability and natural external forcings (eg the sun) have contributed virtually nothing to the warming since 1950 – the share of these factors was narrowed down by IPCC to ± 0.1 degrees. The measured temperature evolution is shown in the following graph.

Figure 1 The measured global temperature curve from several data sets. Top: annual values. ​​Bottom: averaged values ​​over a decade.
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