Watt about Chip and Paddy?

Watts Up With That (WUWT) has a new post called policy implications of climate models on the verge of failure. It discusses a poster presented by Paul C (Chip) Knappenberger and Patrick J. Michaels (Center for the Study of Science, Cato Institute, Washington DC) at the American Geophysical Union (AGU) Science Policy Conference that took place this week.According to the WUWT post, the poster including the following figure. This figure shows how the trend in the various global surface temperature anomaly datasets varies with time interval considered (they considered time intervals from 5 to 15 years). Now, I was a little surprised as I had thought that for time intervals greater than 10 years, the trend was around 0.1oC per decade, whereas this figure suggests it is much smaller. I then noticed that the y-axis was in units of oC per year. Okay, so they’ve changed the units. It has normally been presented as oC per decade, but there’s nothing wrong with changing units as long as it is clear (and, in this case, it didn’t take me long to work out).

Figure showing how the trend on the global surface temperature anomaly varies with time interval considered (credit : Paul Knappenberger and Patrick Michaels).

Figure showing how the trend on the global surface temperature anomaly varies with time interval considered (credit : Paul Knappenberger and Patrick Michaels).


The post then goes on to show the following figure (with some additions by me). This compares the observed trends (using a 15 year time interval) with the range predicted using climate models. So the implication is that the comparison is so poor that the models have failed. Well, what I’ve added are the errors in the 15-years GISSTEMP trends (solid vertical black lines). The errors are large, so in fact there is a very large overlap between the observed trends and the model trends. I’ve also added the trend and errors for a 20 year period (1993 – 2013), shown by the vertical dashed red line and the two vertical dashed black lines. The mean now lies almost exactly on the peak of the distribution of model trends and the range now overlaps almost exactly with the range of model errors. To be fair, I don’t quite now where the models come from and what time interval they consider, so am not sure if the 20-year comparison is strictly speaking correct.
Comparison between observed trends and model trends.  This figure includes errors on the 15-year trends (vertical solid black lines) and include a 20-year trend (vertical dashed red line) and errors on the 20-year trend (vertical dashed black lines).  (credit : Paul Knappenberg and Patrick Michaels,  Additions by me)

Comparison between observed trends and model trends. This figure includes errors on the 15-year trends (vertical solid black lines) and include a 20-year trend (vertical dashed red line) and errors on the 20-year trend (vertical dashed black lines). (credit : Paul Knappenberg and Patrick Michaels, Additions by me)


So, anyway it appears that Chip and Paddy have specifically chosen short time intervals (15 years or less) during which the mean of the observed trend is low but the error is large. They’ve ignored the error in their analysis and assumed that because the mean of the observed trend lies near the 2σ point on the distribution of model trends that it means that the models have failed. Given the large errors (uncertainties) in the observed trend, however, there is an extremely large overlap between the possible range of observed trends and the range of model trends and so such a conclusion seems somewhat premature. Also, as I pointed out in yesterday’s post, there is at least one climate model that has done a remarkably good job of predicting the evolution of the global surface temperature anomalies between 2001 and 2010.

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8 Responses to Watt about Chip and Paddy?

  1. The attacks on models by Watts et all comes across as a nonsensical grasping for straws followed by the usual mangled data. If anything, the fact that where models are shown to be in error, they’ve under-predicted certain trends in global warming, shows that we need a more rapid response to climate change. Watts position is that human caused climate change doesn’t exist so we should ignore it altogether. His mangling of models, in this case, appears to be a non-seq.

  2. Tom Curtis says:

    They have not just chosen a short trend period. They have explicitly chosen a period starting at the peak of the temperature spike from the 1997/98 El Nino. In other words, they have cherry picked outrageously.

    Where they interested in a serious analysis, they would have sampled twenty or so 15 year trends with randomly chosen start dates between 1975 and 1998 and compared the distribution of those trends with the model distribution. Such a method, however, would have been too informative to be published by the Cato Institute or WUWT.

  3. Indeed, you’re quite correct. Although the errors on the 15 year period are large (and hence we can’t say with certainty what the trend is) it is quite likely that the trend has been small because of the large El Nino in 97/98. That, however, doesn’t provide some evidence against global warming though.

  4. Something else I’ve started to realise is that this is an attempt to test the null hypothesis (no warming). What those who are doing this clearly don’t realise is that the null hypothesis for global warming is not that surface temperatures haven’t risen, it’s that the total energy in the climate system hasn’t risen. They seem to think they’re doing something really clever with regards to global warming, but all they’re really doing is showing that there are periods when the models don’t predict surface temperature trends all that well. So what? They still can’t technically reject the models in favour of the null because they’re only failing at the 10% level, and there are many other indicators of global warming and the energy associated with surface temperature rise is a small fraction of the excess energy.

  5. Even with surface temperatures as the only variable, their version of the null is dramatically wrong. When their ‘test’ is a graph they fiddled with in order to create optical illusions with the data, it’s pretty tough for me to treat them seriously.

    .8 C average warming since 1880 (atmosphere). That’s what scientists (NASA, NOAA, etc) find. Then, CATO, which is an org funded by the Koch brothers, fiddles around with some graph in order to make it appear that climate scientists are wrong. I’m sticking with NASA.

    My null hypothesis is not that Earth hasn’t warmed, but that CATO has produced no science.

  6. BBD says:

    Wotts says:

    They seem to think they’re doing something really clever with regards to global warming, but all they’re really doing is showing that there are periods when the models don’t predict surface temperature trends all that well.

    Actually, I suspect that they know perfectly well that what they are doing is more or less worthless as science, but it works for confusing politicians and the public, so its purpose is achieved.

    Their aim is political, not scientific.

  7. So you confirm my Watts null science hypothesis 😉

    Classic misinformation and agitation. I believe you’re correct — it’s entirely political. And it shows how much political influence fossil fuel special interests still retain. A fuel switch is not only important for mitigating the powerful and dangerous force of a changing climate, it’s also important because it reduces the negative and politically damaging power oil, gas, and coal companies have exerted.

    Sadly, agitators like Watts do not exist in a vacuum. Their rhetoric is specifically targeted to defend a special interest. Links between Watts and CATO (Fox News) are further validation for this null science hypothesis.

    What would be interesting news (and challenging but rewarding research) would be tracking Watts ties and associations with right wing and fossil fuel connected organizations.

  8. BBD says:

    We know Watts was paid by Heartland. We know HI is a corporate-funded generator climate disinformation. That’ll do for me.

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