Home > Climate Change > >Climate models and why they don’t work

>Climate models and why they don’t work

>If the topic wasn’t climate change then prominent scientists such as James Hansen, Michael Mann and Gavin Schmidt et al would never have been heard of, as they are scientifically mediocre in the grand scheme of things.

Henk Tennekes, a proper scientist, enters the debate between Gavin Schmidt and Roger Pielke Sr.

Roger Pielke Sr. has graciously invited me to add my perspective to his discussion with Gavin Schmidt at RealClimate. If this were not such a serious matter, I would have been amused by Gavin’s lack of knowledge of the differences between weather models and climate models. As it stands, I am appalled. Back to graduate school, Gavin!

A weather model deals with the atmosphere. Slow processes in the oceans, the biosphere, and human activities can be ignored or crudely parameterized. This strategy has been very successful. The dominant fraternity in the meteorological modeling community has appropriated this advantage, and made itself the lead community for climate modeling. Backed by an observational system much more advanced than those in oceanography or other parts of the climate system, they have exploited their lead position for all they can. For them, it is a fortunate coincidence that the dominant synoptic systems in the atmosphere have scales on the order of many hundreds of kilometers, so that the shortcomings of the parameterizations and the observation network, including weather satellite coverage, do not prevent skillful predictions several days ahead.

A climate model, however, has to deal with the entire climate system, which does include the world’s oceans. The oceans constitute a crucial slow component of the climate system. Crucial, because this is where most of the accessible heat in the system is stored. Meteorologists tend to forget that just a few meters of water contain as much heat as the entire atmosphere. Also, the oceans are the main source of the water vapor that makes atmospheric dynamics on our planet both interesting and exceedingly complicated. For these and other reasons, an explicit representation of the oceans should be the core of any self-respecting climate model.

However, the observational systems for the oceans are primitive in comparison with their atmospheric counterparts. Satellites that can keep track of what happens below the surface of the ocean have limited spatial and temporalresolution. Also, the scale of synoptic motions in the ocean is much smaller than that of cyclones in the atmosphere, requiring a spatial resolution in numerical models and in the observation network beyond the capabilities of present observational systems and supercomputers. We cannot observe, for example, the vertical and horizontal structure of temperature, salinity and motion of eddies in the Gulf Stream in real time with sufficient detail, and cannot model them at the detail that is needed because of computer limitations. How, for goodness’ sake, can we then reliably compute their contribution to multi-decadal changes in the meridional transport of heat? Are the crude parameterizations used in practice up to the task of skillfully predicting the physical processes in the ocean several tens of years ahead? I submit they are not.

Since heat storage and heat transport in the oceans are crucial to the dynamics of the climate system, yet cannot be properly observed or modeled, one has to admit that claims about the predictive performance of climate models are built on quicksand. Climate modelers claiming predictive skill decades into the future operate in a fantasy world, where they have to fiddle with the numerous knobs of the parameterizations to produce results that have some semblance of veracity. Firm footing? Forget it!

Gavin Schmidt is not the only meteorologist with an inadequate grasp of the role of the oceans in the climate system. In my weblog of June 24, 2008, I addressed the limited perception that at least one other climate modeler appears to have. A few lines from that essay deserve repeating here. In response to a paper by Tim Palmer of ECMWF, I wrote: “Palmer et al. seem to forget that, though weather forecasting is focused on the rapid succession of atmospheric events, climate forecasting has to focus on the slow evolution of the circulation in the world ocean and slow changes in land use and natural vegetation. In the evolution of the Slow Manifold (to borrow a term coined by Ed Lorenz) the atmosphere acts primarily as stochastic high-frequency noise. If I were still young, I would attempt to build a conceptual climate model based on a deterministic representation of the world ocean and a stochastic representation of synoptic activity in the atmosphere.”

From my perspective it is not a little bit alarming that the current generation of climate models cannot simulate such fundamental phenomena as the Pacific Decadal Oscillation. I will not trust any climate model until and unless it can accurately represent the PDO and other slow features of the world ocean circulation. Even then, I would remain skeptical about the potential predictive skill of such a model many tens of years into the future.

As good a summary as you will see as to why climate models have a zero percent predictive track record.


His wikipedia entry states:

Hendrik (Henk) Tennekes (born December 13, 1936, Kampen) was the director of research at the Royal Dutch Meteorological Institute (Koninklijk Nederlands Meteorologisch Instituut, or KNMI), and was a professor of aeronautical engineering at Pennsylvania State University. Tennekes pioneered methods of multi-modal forecasting. He authored The Simple Science of Flight and A First Course in Turbulence. Tennekes was a strong proponent of scientific modeling, and he challenged the use of incomplete or unproven scientific models by those trying to explain complex phenomena such as global warming.

So he uses models to explain things but reckons climate models are not worth a cracker.


That’s because they’re all back-fitted, of course, which makes it a statistical impossibility for them to have any predictive power.

(Nothing Follows)


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Categories: Climate Change
  1. February 6, 2009 at 9:18 am

    >You are going to drive Fudgie – who does not understand (and cannot describe) the Scientific Method – absolutely batshit!

  2. February 6, 2009 at 11:03 am

    >He hasn’t described what his understanding of backfitting is, which I asked him a few days ago. It’ll be interesting to see how he describes the use of statistics at different stages of a model’s development.Perhaps he’s gone away to actually look it up and worked out he’s got the wrong end of the scientific stick.

  3. February 6, 2009 at 2:25 pm

    >”That’s because they’re all back-fitted, of course, which makes it a statistical impossibility for them to have any predictive power.”Pure bullshit. Climate models are based on physics, not statistics, but sadly you have no understanding at all of either.

  4. February 6, 2009 at 9:02 pm

    >Fudgie,You have just demonstrated that you have no idea how these models work.I’m a bit surprised, actually.Statistics are used to verify methodologies.Can you talk to your masters and get me back my 2008 Fudgie?The 2009 one is a bit dim.

  5. February 8, 2009 at 12:10 am

    >No, that’s what you’ve demonstrated – not just here but every time you’ve opened your mouth. You haven’t got the remotest idea about how climate models work.

  6. February 8, 2009 at 1:32 am

    >Fudgieeeee,You don’t actually understand how a model is created, do you?We’ll start with something simple that I hope you can answer.What role do statistics play in the development of any model (doesn’t have to be climate science)?

  7. February 8, 2009 at 9:47 am

    >I’m not the one who needs to explain anything. You said that there was “a statistical impossibility for them to have any predictive power”. To believe this, you have to believe that there is not a single piece of physics in the models. Do you believe that?

  8. February 8, 2009 at 10:36 am

    >Fudgie,I have to conclude that you don’t know the role statistics play in the development of any mathematical model.Thus, you are completely ignorant of the reason why climate models cannot possibly have any predictive power.

  9. February 8, 2009 at 4:26 pm

    >Answer the simple question. Is there physics in climate models, or is there not?

  10. February 8, 2009 at 9:01 pm

    >No one is denying there’s physics in climate models. That’s like asking whether there’s money in financial models.I don’t think you understand models at all.If so then you’d tell us what role stats play.The fact you cannot, or will not, is quite revealing.PS – have you spoken to your bosses yet? Can I have my 2008 Fudgie back instead of you?

  11. February 8, 2009 at 9:48 pm

    >”No one is denying there’s physics in climate models””statistical impossibility for them to have any predictive power”You realise these statements are mutually exclusive? Clearly out of physics and statistics you understand the meaning of at most one of them.

  12. February 9, 2009 at 2:34 am

    >Fudgie,You know nothing, nothing, about how models are developed otherwise you would describe the important role that statistics play in their development and ongoing tracking.And who do I talk to in order to get the 2008 Fudgie back? The 2009 one seems to have a different ISP.

  13. February 9, 2009 at 6:56 pm

    >Fucky,You know nothing, nothing, about the role that statistics play in climate models. If you did, you’d know that only a complete vegetable could think that it’s “a statistical impossibility for them to have any predictive power”.

  14. February 9, 2009 at 8:28 pm

    >Fudgie,I am not surprised that you know nothing about statistics and how important they are to the development of models.If you did then you wouldn’t be a Climate Fascist.

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