Sunday, 4 January 2015

How climatology treats sceptics

2014 was an exiting year for me, a lot happened. It could have gone wrong, my science project and thus employment ended. This would have been the ideal moment to easily get rid of me, no questions asked. But my follow-up project proposal (Daily HUME) to develop a new homogenization method for global temperature datasets was approved by the German Science Foundation.

It was an interesting year. The work I presented at conferences was very skeptical of our abilities to removed non-climatic changes from climate records (homogenization). Mitigation skeptics sometimes claim that my job, the job of all climate scientists, is to defend the orthodoxy. They might think that my skeptical work would at least hurt my career, if not make me an outright outcast, like they are.

Knowing science, I did not fear this. What counts is the quality of your arguments, not whether a trend goes up or down, whether a confidence interval becomes larger or smaller. As long as your arguments are strong, the more skeptical, the better, the more interesting the work is. What would hurt my reputation would be if my arguments were just as flimsy as those of the mitigation skeptics.

With a bunch colleagues we are working on a review paper on non-climatic changes in daily data. Daily data is used to study climatic changes in extreme weather: heat waves, cold spells, heavy rain, etc. Much too simplified we found that the limited evidence suggests that non-climatic changes affect the extremes more than the mean, that removing them is very hard, while most large daily data collections are not homogenized or only for changes in the mean. In other words, we found that the scientific literature supports the hunch of the climate skeptics of the IPCC:
"This [inhomogeneous data] affects, in particular, the understanding of extremes, because changes in extremes are often more sensitive to inhomogeneous climate monitoring practices than changes in the mean." Trenberth et al. (2007)
Not a nice message, but a large number of wonderful colleagues is happy to work with me on this review paper. Thank you for your trust.

Last May at the homogenization seminar in Budapest, I presented this work, while my colleague presented our joint work on homogenization when the size of the breaks is small. Or, formulated more technically: homogenization when the variance of the break signal is small relative to the variance of the difference time series (the difference between two nearby stations). The positions of the detected breaks are in this case not much better than random breaks. This problem was found by Ralf, a great analytical thinker and skeptic. Thank you for working with me.

Because my project ended and I did not know whether I would get the next one and especially not whether I would get it in time, I have asked two groups in Budapest whether they could support me during this bridge period. Both promised they would try. The next week the University of Bern offered me a job. Thank you Stefan and Renate, I had a wonderful time in Bern and learned a lot.

Thus my skeptical job is on track again and more good things happened. For the next good news I first have to explain some acronyms. The World Meteorological Organisation ([[WMO]]) coordinates the work of the (national) meteorological services around the world, for example by defining standards for measurements and data transfer. The WMO has a Commission for Climatology (CCl). For the coming 4-year term this commission has a new Task Team on Homogenization (TT-HOM). It cannot be much more than 2 years ago that I asked a colleague what this abbreviation he had used "CCl" stood for. Last spring they asked whether I wanted to be member of the TT-HOM. This autumn they made me chair. Thank you CCl and especially Thomas and Manola. I hope to be worthy of your trust.

Furthermore, I was asked to be co-convener of the session on Climate monitoring; data rescue, management, quality and homogenization at the Annual Meeting of the European Meteorological Society. That is quite an honor for a homogenization skeptic that is just an upstart.

More good things happened. While in Bern, Renate and I started working on a database with parallel measurements. In a parallel measurement an old measurement set-up stands next to a new one to directly compare the difference between them and to thus determine the non-climatic change this difference in set-ups produced. Because I am skeptical of our abilities to correct non-climatic changes in daily data, I hope that in this way we can study how important they are. A real skeptic does not just gloat when finding a problem, but tries to solve them as well. The good news is that the group of people working on this database is now a expert team of the International Surface Temperature Initiative (ISTI). Thank you ISTI steering committee and especially Peter.

In all this time, I had only one negative experience. After presenting our review article on daily data a colleague asked me whether I was a climate "skeptic". That was clearly intended as a threat, but knowing all those other colleagues behind me I could just laugh it off. In retrospect, my choice of words was also somewhat unfortunate. As an example, I had said that climatic changes in 20-year return levels (an extreme that happens on average every 20 years) probably cannot be studied using homogenized data given that the typical period between two non-climatic changes is 20 years. Unfortunately, this colleague afterwards presented a poster on climatic changes in the 20-year return period. Had I known that, I would have chosen another example. No hard feelings.

That is how climatology treats skeptics. I cannot complain. On the contrary, a lot of people supported me.

If you can complain, if you feel like a persecuted heretic (and not only claim that as part of your political fight), you may want to reconsider whether your arguments are really that strong. You are always welcome back.


A large part of the homogenization community at a project meeting in Bucharest 2010. They make a homogenization skeptic feel at home. Love you guys.

[UPDATE.
Eric Steig strongly criticized the IPPC, his experience (archive):

I was highly critical of IPCC AR4 Chapter 6, so much so that the [mitigation skeptical] Heartland Institute repeatedly quotes me as evidence that the IPCC is flawed. Indeed, I have been unable to find any other review as critical as mine. I know "because they told me" that my reviews annoyed many of my colleagues, including some of my RC colleagues, but I have felt no pressure or backlash whatsover from it. Indeed, one of the Chapter 6 lead authors said “Eric, your criticism was really harsh, but helpful "thank you!"

So who are these brilliant young scientists whose careers have been destroyed by the supposed tyranny of the IPCC? Examples?


James Annan later writes:
Well, I don't think I got quite such a rapturous response as Eric did, with my attempts to improve the AR4 drafts, but I certainly didn't get trampled and discredited either [which Judith Curry evidently wrongly claims the IPCC does] - merely made to feel mildly unwelcome, which I find tends to happen when I criticise people outside the IPCC too. But they did change the report in various ways. While I'm not an unalloyed fan of the IPCC process, my experience is not what she [Judith Curry] describes it as. So make that two anecdotes.

Maybe people could start considering whether there is a difference between qualified critique and uninformed nonsense. Valuing quality is part of the scientific culture.
]

Related posts


On consensus and dissent in science - consensus signals credibility


Why doesn't Big Oil fund alternative climate research?

Are debatable scientific questions debatable?

Falsifiable and falsification in science

Peer review helps fringe ideas gain credibility


Reference

Trenberth, K.E., et al., 2007: Observations: Surface and Atmospheric Climate Change. In: Climate Change 2007: The Physical Science Basis. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

4 comments:

  1. Congratulations - multiple times. You have had a busy year and it looks as if it will become even more busy.

    Can you explain what you mean by parallel data? (I think I can guess but I could be wrong.)

    ReplyDelete
  2. Thanks. The really busy year is the next one, after initiating so much, now the work needs to be done.

    Nowadays more and more observations are performed with Automatic Weather Stations (AWS), typically small cylinders with multiple white cones on the outside and an electronic resistance thermometers inside. Previously Stevenson screens (Cotton region shelters; a 2 meter high free standing garden screen with a box on top with white Louvres walls) with a liquid in Glass Thermometer were standard.

    To see how this affects the temperature measurement, we make parallel measurements where both instruments stand next to each other and measure the same weather. A famous example for this is that the AWS in the US (called MMTS) measure a temperature that is about 0.2°C colder than the previously used Stevenson screens.

    One reason for differences is that radiation can heat or cool the sensor and how much gets onto the sensor depends on the exact design. The influence of radiation can be reduced nowadays with mechanical ventilation, there are also differences in how much solar radiation gets onto the instrument and if the sensor is small radiation has less influence.

    If the problem is warming due to solar radiation (typical) this problem will be stronger on a hot day than on an average day (hot days are typically sunny). Thus you would expect that this problem has more influence on non-climatic changes in heat waves than on the average temperature.

    More information can be found here: background and pratical stuff.

    ReplyDelete
  3. Excellent, thanks Victor. There's no-one from Australia yet? I saw you referenced Blair Trewin in your slide presentation. (I'm not trying to dob him in.)

    ReplyDelete
  4. Congratulations, Victor!
    It's good to know that the scientific community treats people according to the strength of their arguments and their methods and not just on their conclusions.

    ReplyDelete

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