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Anti-scientists

Filed under: — rasmus @ 9 February 2016

Ross McKitrick was so upset about a paper ‘Learning from mistakes in climate research(Benestad et al., 2015) that he has written a letter of complaint and asked for immediate retraction of the pages discussing his work.

This is an unusual step in science, as most disagreements and debate involve a comment or a response to the original article. The exchange of views, then, provides perspectives from different angles and may enhance the understanding of the problem. This is part of a learning process.

Responding to McKitrick’s letter, however, is a new opportunity to explain some basic statistics, and it’s excellent to have some real and clear-cut examples for this purpose.

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References

  1. R.E. Benestad, D. Nuccitelli, S. Lewandowsky, K. Hayhoe, H.O. Hygen, R. van Dorland, and J. Cook, "Learning from mistakes in climate research", Theoretical and Applied Climatology, vol. 126, pp. 699-703, 2015. http://dx.doi.org/10.1007/s00704-015-1597-5

Climate Sensitivity Week

Some of you will be aware that there is a workshop on Climate Sensitivity this week at Schloss Ringberg in southern Germany. The topics to be covered include how sensitivity is defined (and whether it is even meaningful (Spoiler, yes it is)), what it means, how it can be constrained, what the different flavours signify etc. There is an impressive list of attendees with a very diverse range of views on just about everything, and so I am looking forward to very stimulating discussions.

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Rossby waves and surface weather extremes

Filed under: — stefan @ 10 July 2014

A new study by Screen and Simmonds demonstrates the statistical connection between high-amplitude planetary waves in the atmosphere and extreme weather events on the ground.

Guest post by Dim Coumou

There has been an ongoing debate, both in and outside the scientific community, whether rapid climate change in the Arctic might affect circulation patterns in the mid-latitudes, and thereby possibly the frequency or intensity of extreme weather events. The Arctic has been warming much faster than the rest of the globe (about twice the rate), associated with a rapid decline in sea-ice extent. If parts of the world warm faster than others then of course gradients in the horizontal temperature distribution will change – in this case the equator-to-pole gradient – which then could affect large scale wind patterns.

Several dynamical mechanisms for this have been proposed recently. Francis and Vavrus (GRL 2012) argued that a reduction of the north-south temperature gradient would cause weaker zonal winds (winds blowing west to east) and therefore a slower eastward propagation of Rossby waves. A change in Rossby wave propagation has not yet been detected (Barnes 2013) but this does not mean that it will not change in the future. Slowly-traveling waves (or quasi-stationary waves) would lead to more persistent and therefore more extreme weather. Petoukhov et al (2013) actually showed that several recent high-impact extremes, both heat waves and flooding events, were associated with high-amplitude quasi-stationary waves. More »

References

  1. J.A. Francis, and S.J. Vavrus, "Evidence linking Arctic amplification to extreme weather in mid-latitudes", Geophysical Research Letters, vol. 39, pp. n/a-n/a, 2012. http://dx.doi.org/10.1029/2012GL051000
  2. E.A. Barnes, "Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes", Geophysical Research Letters, vol. 40, pp. 4734-4739, 2013. http://dx.doi.org/10.1002/grl.50880
  3. V. Petoukhov, S. Rahmstorf, S. Petri, and H.J. Schellnhuber, "Quasiresonant amplification of planetary waves and recent Northern Hemisphere weather extremes", Proceedings of the National Academy of Sciences, vol. 110, pp. 5336-5341, 2013. http://dx.doi.org/10.1073/pnas.1222000110

The most common fallacy in discussing extreme weather events + Update

Filed under: — stefan @ 25 March 2014

Does global warming make extreme weather events worse? Here is the #1 flawed reasoning you will have seen about this question: it is the classic confusion between absence of evidence and evidence for absence of an effect of global warming on extreme weather events. Sounds complicated? It isn’t. I’ll first explain it in simple terms and then give some real-life examples.

The two most fundamental properties of extreme events are that they are rare (by definition) and highly random. These two aspects (together with limitations in the data we have) make it very hard to demonstrate any significant changes. And they make it very easy to find all sorts of statistics that do not show an effect of global warming – even if it exists and is quite large.

Would you have been fooled by this?

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The global temperature jigsaw

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.

AR5_temp_obs

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 »

Statistics and Climate

Filed under: — rasmus @ 18 November 2013

Do different climate models give different results? And if so, why? The answer to these questions will increase our understanding of the climate models, and potentially the physical phenomena and processes present in the climate system.

We now have many different climate models, many different methods, and get a range of different results. They provide what we call ‘multi-model‘ and ‘multi-method‘ ensembles. But how do we make sense out of all this information?

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Should regional climate models take the blame?

Kerr (2013) recently provided a critical review of regional climate models (“RCMs”). I think his views have caused a stir in the regional climate model community. So what’s the buzz all about?

RCMs provide important input to many climate services, for which there is a great deal of vested interest on all levels. On the international stage, high-level talks lead to the establishment of a Global Framework for Climate Services (GFCS) during the World Climate Conference 3 (WCC3) in Geneva 2009.

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References

  1. R.A. Kerr, "Forecasting Regional Climate Change Flunks Its First Test", Science, vol. 339, pp. 638-638, 2013. http://dx.doi.org/10.1126/science.339.6120.638

Don’t estimate acceleration by fitting a quadratic…

Filed under: — stefan @ 20 November 2012

… if your data do not look like a quadratic!

This is a post about global sea-level rise, but I put that message up front so that you’ve got it even if you don’t read any further.

The reputable climate-statistics blogger Tamino, who is a professional statistician in real life and has published a couple of posts on this topic, puts it bluntly:

Fitting a quadratic to test for change in the rate of sea-level rise is a fool’s errand.

I’d like to explain why, with the help of a simple example. Imagine your rate of sea-level rise changes over 100 years in the following way:
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Stronger regional differences due to large-scale atmospheric flow.

A new paper by Deser et al. (2012) (free access) is likely to have repercussions on discussions of local climate change adaptation. I think it caught some people by surprise, even if the results perhaps should not be so surprising. The range of possible local and regional climate outcomes may turn out to be larger than expected for regions such as North America and Europe.

Deser et al. imply that information about the future regional climate is more blurred than previously anticipated because of large-scale atmospheric flow responsible for variations in regional climates. They found that regional temperatures and precipitation for the next 50 years may be less predictable due to the chaotic nature of the large-scale atmospheric flow. This has implications for climate change downscaling and climate change adaptation, and suggests a need to anticipate a wider range of situations in climate risk analyses.

Although it has long been recognised that large-scale circulation regimes affect seasonal, inter-annual climate, and decadal variations, the expectations have been that anthropogenic climate changes will dominate on time scales longer than 50 years. For instance, an influential analysis by Hawking & Sutton (2009) (link to figures) has suggested that internal climate variability account for only about 20% of the variance over the British isles on a 50-year time scale.
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References

  1. C. Deser, R. Knutti, S. Solomon, and A.S. Phillips, "Communication of the role of natural variability in future North American climate", Nature Climate Change, vol. 2, pp. 775-779, 2012. http://dx.doi.org/10.1038/nclimate1562
  2. E. Hawkins, and R. Sutton, "The Potential to Narrow Uncertainty in Regional Climate Predictions", Bulletin of the American Meteorological Society, vol. 90, pp. 1095-1108, 2009. http://dx.doi.org/10.1175/2009BAMS2607.1

Trying to shoot the messenger

Filed under: — gavin @ 7 November 2012

Does this sound familiar? A quantitative prediction is inconvenient for some heavily invested folks. Legitimate questions about methodology morph quickly into accusations that the researchers have put their thumb on the scale and that they are simply making their awkward predictions to feather their own nest. Others loudly proclaim that the methodology could never work and imply that anyone who knows anything knows that -it’s simply common sense! Audit sites spring up to re-process the raw data and produce predictions more to the liking of their audience. People who have actually championed the methods being used, and so really should know better, indulge in some obvious wish-casting (i.e. forecasting what you would like to be true, despite the absence of any evidence to support it).

Contrarian attacks on climate science, right?
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