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The AR4 attribution statement

Filed under: — gavin @ 29 January 2012

Back in 2007, the IPCC AR4 SPM stated that:

“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.”

This is a clear statement that I think is very well supported and correctly reflects the opinion of most climate scientists on the subject (and was re-affirmed in two recent papers (Jones and Stott, 2011;, Huber and Knutti, 2011)). It isn’t an isolated conclusion from a single study, but comes from an assessment of the changing patterns of surface and tropospheric warming, stratospheric cooling, ocean heat content changes, land-ocean contrasts, etc. that collectively demonstrate that there are detectable changes occurring which we can attempt to attribute to one or more physical causes.

Yet, in a paper just out in BAMS (Curry and Webster, 2011) this statement is apparently evidence that IPCC is unable to deal with uncertainty. Furthermore, Judith Curry has reiterated on her blog that the term ‘most’ is imprecise and undefined. For instance:

Apart from the undefined meaning of “most” in AR4 (which was subsequently clarified by the IPCC), the range 50.1-95% is rather imprecise in the context of attribution.

However, Curry’s argument is far from convincing, nor is it well formed (why is there a cap at 95%?). Nor was it convincing when I discussed the issue with her in the comments at Collide-a-Scape last year where she made similar points. Since the C&W paper basically repeats that argument (as has also been noticed by Gabi Hegerl et al who have a comment on the paper (Hegerl et al.)), it is perhaps worth addressing these specific issues again.
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References

  1. G.S. Jones, and P.A. Stott, "Sensitivity of the attribution of near surface temperature warming to the choice of observational dataset", Geophysical Research Letters, vol. 38, 2011. DOI.
  2. M. Huber, and R. Knutti, "Anthropogenic and natural warming inferred from changes in Earth’s energy balance", Nature Geoscience, vol. 5, 2011, pp. 31-36. DOI.
  3. J.A. Curry, and P.J. Webster, "Climate Science and the Uncertainty Monster", Bulletin of the American Meteorological Society, vol. 92, 2011, pp. 1667-1682. DOI.
  4. G. Hegerl, P. Stott, S. Solomon, and F. Zwiers, "Comment on “Climate Science and the Uncertainty Monster” J. A. Curry and P. J. Webster", Bulletin of the American Meteorological Society, vol. 92, 2011, pp. 1683-1685. DOI.

Curve-fitting and natural cycles: The best part


It is not every day that I come across a scientific publication that so totally goes against my perception of what science is all about. Humlum et al., 2011 present a study in the journal Global and Planetary Change, claiming that most of the temperature changes that we have seen so far are due to natural cycles.

They claim to present a new technique to identify the character of natural climate variations, and from this, to produce a testable forecast of future climate. They project that

the observed late 20th century warming in Svalbard is not going to continue for the next 20–25 years. Instead the period of warming may be followed by variable, but generally not higher temperatures for at least the next 20–25 years.

However, their claims of novelty are overblown, and their projection is demonstrably unsound.

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References

  1. O. Humlum, J. Solheim, and K. Stordahl, "Identifying natural contributions to late Holocene climate change", Global and Planetary Change, vol. 79, 2011, pp. 145-156. DOI.

Global Temperature News

Filed under: — group @ 6 December 2011

There are two interesting pieces of news on the global temperature evolution.

First, today a paper by Grant Foster and Stefan Rahmstorf was published by Environmental Research Letters, providing a new analysis of the five available global (land+ocean) temperature time series. Foster and Rahmstorf tease out and remove the short-term variability due to ENSO, solar cycles and volcanic eruptions and find that after this adjustment all five time series match much more closely than before (see graph). That’s because the variability differs between the series, for example El Niño events show up about twice as strongly in the satellite data as compared to the surface temperatures. In all five adjusted series, 2009 and 2010 are the two warmest years on record. For details have a look over at Tamino’s Open Mind.
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References

  1. G. Foster, and S. Rahmstorf, "Global temperature evolution 1979–2010", Environmental Research Letters, vol. 6, 2011, pp. 044022-. DOI.

On record-breaking extremes

Filed under: — stefan @ 6 November 2011

It is a good tradition in science to gain insights and build intuition with the help of thought-experiments. Let’s perform a couple of thought-experiments that shed light on some basic properties of the statistics of record-breaking events, like unprecedented heat waves. I promise it won’t be complicated, but I can’t promise you won’t be surprised.
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The Climate Data Guide

Filed under: — Jim @ 30 October 2011

The National Center for Atmospheric Research (NCAR) has, in the last few months, developed an interesting and potentially very useful website The Climate Data Guide devoted to the ins and outs of obtaining and analyzing the various existing climatic data sets. The site describes itself as “…a focal point for expert-user guidance, commentary, and questions on the strengths and limitations of selected observational data sets and their applicability to model evaluations.”

There are already many climate data set websites in existence, and lists of links to same, including at this site. Some of them host the actual data, while others provide various statistical analysis or graphing/visualization tools, all of which are helpful. What makes this new site unique is: (1) expert users contribute pages describing and pointing to various existing data sources within certain topic areas, (2) explanations of various existing data formats, gridding approaches, etc, (3) an online discussion forum dealing with the appropriateness of particular data sets for addressing particular scientific questions, and (4) a news section as well as links to a very wide range of data repositories, among other things. Here for example, is the page summarizing the existing reanalysis data sets.

The site, sponsored by the NSF, appears to be a unique and valuable approach to advancing climate data analysis. We encourage everyone to check it out, register as members as appropriate, etc. This would also be a good place to discuss or point to other useful data and analysis oriented sites that are out there.


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