Wednesday, 30 April 2008

Why doesn't it get hotter every year?

One of the most common questions encountered in discussions on climate change especially by those who don't accept the science is, "Why doesn't it get hotter every year?" or other variants, such as, "Why hasn't it warmed since 1998?" (pick your favorite year). The real question underlying all this is: "If there is a warming trend of so many degrees per century, why can't we see that exact trend if we compare any two years, or any sequence of e.g. ten years?"

The answer is pretty simple. The climate change trend is a long-term effect. If it warms by 3°C per century, that means an average of 0.03°C per year. That amount is well within the limits of accuracy of measurement techniques. What's more, without a significant global warming effect, much higher variation than this occurs. The critical difference is that ordinarily, that sort of variation is short term and the highs and lows pretty much cancel out. It's only if there's a major change in the atmosphere (greenhouse gases causing warming, volcanic output causing cooling) or solar input to the system (change in the earth's orbit, change in solar activity) that you get a break out of this sort of random fluctuation -- and only a really big external change causes a real climate shift (like into or out of an ice age).

One can of course (and should, if doing serious scientific studies) apply sophisticated data analysis techniques to the problem, but what I aim to do here is to provide a feel for how to understand the difference between short-term and long-term effects with simple approaches you can apply yourself if you know how to drive a spreadsheet. All you need is the ability to plot points, and to get a trend line. The other critical thing is to ask the spreadsheet (or graphing or stats package) to give you the r2 value for the trend line, which is a measure of how much you can read into it.

I took a look at the first 50 years of the HadCRUT3 dataset, from 1850 to 1899, before significant CO2 emissions could have caused a greenhouse effect, and plotted the annual averages (HadCRUT3 uses anomalies relative to a base period of 1961-1990) to see if I could discern a trend. Over this time, data from Oak Ridge National Labs showed that annual emissions of CO2 increased from 54 to 507 (measured as million tonnes of carbon); the latest figure is less than 10% of current levels. The effect of this increase in emissions was that atmospheric CO2 increased less than 4%, not enough to have any measurable effect on temperature. So let's take this period as indicative of "natural variability". Solar activity over that period was on the way down, probably not enough to have a significant effect on climate.

What can we see from this picture? Aside from that there are many short-term bumps, the trend isn't too clear. The fitted trend line shows a small upwards drift (an annual trend of 0.0008°C, or 0.08° per century), but the crucial thing is to note the r2 value, which shows that the trend isn't very strong. Statisticians interpret r2 as an indication of how much of the variance in the data can be explained by the trend line; in this case, a bit over 1%, so the trend is not significant; you would expect an r2 value in this ballpark for random numbers.

What has the trend been over the last 50 years (1958-2007)? Let's plot the graph as well and see how it looks. Note that in all graphs, I keep the vertical scale the same (-0.6 to 0.6) so the graphs are comparable. It is important to get this right: I've seen many attempts at comparing values using inconsistent scales. I do however adjust the horizontal scale when dealing with shorter sequences of years: be careful not to compare these with the longer sequences.

How does the recent data compare with the picture of 1850-1899? The trend is now much clearer. The r2 value is 0.7347, meaning that the trend line is a very good fit to the data. The annual trend is an increase of 0.0129°. I haven't taken into account here that the trend may be accelerating, which is missed by a simple linear regression over the entire period, so do not get too excited that the trend is on the low side of IPCC projections.

It is a simple matter to add an annual trend of an increase of 0.0121 to each temperature record from 1850 to 1899, to see what the resulting picture looks like relative to today's. Why is this interesting? Because if I do this, I know there is a trend of 1.21° per century over and above natural variability -- and this figure will make the trend match that of the last 50 years. This allows us to explore the argument that artificial warming is behaving like a slow, long-term adjustment to natural variability which would otherwise be pretty much random. We will also be able to see whether it's possible to discern this trend at all scales, answering the question posed at the start. So let's see how the adjusted nineteenth century data looks.

Remarkably (or perhaps not) the adjusted nineteenth century picture has statistical properties very similar to the modern picture. The rate of increase is the same because I made that so. The r2 value is 0.7613, showing a similar degree of fit to the data to the modern (unaltered) data.

Is that cheating? Yes and no. I forced the old data to look like the new data. But the point is that the old data looked pretty close to random. That's the nature of weather. You got hot days, you get cold days. You get a heat wave, you get snow in summer. Looked at short-term, the weather is hard to predict; look at it over a span of years, and it doesn't look much different to random, if you filter out seasons (as you do with an annual average). So adding a linear trend onto the 1850-1899 data is not too different to the predicted effect of adding global warming onto natural variability.

So what of talk we have lately of how global warming has flatlined, or temperatures have dropped over the last 10 years? Let's look for a comparable case we can find in the adjusted nineteenth century data. If we look at a period of ten years of the adjusted data when the graph looks relatively flat, 1880-1889, the trend is 0.008° per year, with r2 = 0.1227: somewhat better than random, but not a convincing fit to the data.

Remember, this data has been explicitly constructed so that there was a hundred-year warming trend of 1.21° and we are testing the argument that if such a trend exists, you should be able to find it in any sequence of years.

Now move the trend period back two years to 1878-1887 and what do you get? A trend of a decrease of 0.0166° per year, or a decrease of 1.66° per century, the opposite to the trend I artificially added to this data and of bigger magnitude! What's more, r2 is now at a significantly more convincing level of 0.2947 than the 1880-1899 (adjusted) trend.

Remember, this is data that was explicitly constructed to add a trend of increasing temperature on top of data which was statistically random.

If you take any period of ten years, you can see similar effects: most go up in varying degrees, some are flat, a few go down.

So what can we conclude from all this?

If we have a data series with a natural variability significantly above a new source of artificial change, even if that change is consistently applied over a long time, we cannot expect to discern that change accurately by looking at a short time sequence. That change will, however, be clear if you keep looking for long enough. In other words, anyone demanding that temperatures increase every year -- or even over a period of ten years -- is not testing the theory of anthropogenic global warming, but their own understanding of data analysis.

Finally, let's apply one more data analysis technique, familiar to economists, at least when they do market analysis, even if some forget it when they consider climate change: the moving average. The way this works is you plot the average of the past n years at each data point as a way of smoothing out short-term fluctuations. NASA's GISS temperature graphs generally show a 5-year average. Here, I'll use a 10-year average to smooth out the bumps even more.

The black line with squares on the data points is the temperature data; the red line without markers on the data points is the 10-year average.

Can you see a downhill trend over the last 10 years now? Not convinced? Look at the data points since 1998 (the big spike near the end). How far back can you go before all the temperature measures are lower than any since 1998? Click on the picture if you want a larger version. To make it easier, I've put in a dotted line marking the lowest temperature since 1998. You'll see that it's higher than any temperature before 1995.

Additional Reading

For those who find my stats treatment a bit too lowbrow, plus some other interesting points:


Repeat the experiment on the modified nineteenth century data with 20-year sequences. You will see that although the trend is more consistently up and closer to the 50-year trend, you can still find at least one patch where the trend appears to be down -- though with a low r2.

Monday, 28 April 2008

The Mysterious Vanishing Ice Age

On 23 April 2008, The Australian published an article, "Sorry to ruin the fun, but an ice age cometh" by Phil Chapman, geophysicist and astronautical engineer, who was also the first Australian to be sent into space by NASA.

Possibly he's still out there, because he tells us:
All four agencies that track Earth’s temperature (the Hadley Climate Research Unit in Britain, the NASA Goddard Institute for Space Studies in New York, the Christy group at the University of Alabama, and Remote Sensing Systems Inc in California) report that it cooled by about 0.7C in 2007. This is the fastest temperature change in the instrumental record and it puts us back where we were in 1930. If the temperature does not soon recover, we will have to conclude that global warming is over.

I haven't tracked down all four of the data sets he mentions but two should be sufficient since he claims they are all consistent.

Let's look at Hadley: HadCRUT3 is their most commonly quoted data set. What does it show (each year is represented in two rows: the first has the year, 12 monthly values and ends with an annual value, the second gives percent coverage for each monthly measure)? The global average for 2006 was 0.422° (measured as an "anomaly" versus the average over the years 1961-90). The number for 2007 was ... wait for it ... 0.402° -- a drop of 0.02°. Only a factor of 3.5 out.

What of NASA's GISS data? Their data is slightly different. Their anomalies are relative to the average over 1951 to 1980, and their data gathering and analysis also results in slightly different numbers. But this is good: if the rival data sets are consistent, it adds confidence to the credibility of the data. The numbers we want are in the column "AnnMean J-D". For 2006: 0.54° and for 2006: 0.57° for a difference of 0.03° -- in this case an increase rather than a decrease.

Whether we look at either of these figures separately or look at them together, the overall conclusion is the same: 2007 was much the same on average as 2006. If you look at NASA's graph of temperatures, you will see that these variations are well within the error bars (green vertical lines).

So where does the 0.7°C drop come from? I have to guess since he doesn't supply his working. The GISS data has a drop of about this order between the monthly average for January 2007 (0.86°) and the monthly average for January 2008 (0.12°). HadCRUT3 shows a similar but smaller effect between the Decembers of the two years (a drop from 0.536° to 0.201°). However, short term swings are common. One on this scale is unusual, but it is not uncommon for a comparable month to differ by a lot more from its predecessor than yearlong averages.

A fair number of people posted comments on the original article pointing the error out. So what did The Australian do? They made the version with comments inconspicuous (no longer linked from the main opinion pages) but kept a version without comments in a more conspicuous location.

Then, to drive the point home, the inimitable (fortunately) Christopher Pearson, the same one who incorrectly quoted the Pope as being in the anti-global warming camp, followed up with an article on 26 April 2008 "A cool idea to warm to" repeating the error. Pearson quotes Keynes: "when the facts change, I change my mind."

How about a couple more quotes for you, Chris?

Senator Daniel Patrick Moynihan:
You are entitled to your opinion. But you are not entitled to your own facts.
Or how about Richard Feynman:
Reality must take precedence over public relations, for nature cannot be fooled.

How long will we have to wait for another mea culpa? Three weeks like last time? Or is it OK to be loose with the facts unless you offend the Catholic Church?

Follow-up: The Australian on 29 April 2008 published another article, "Warming trend has not been reversed" by David Karoly, professor in the University of Melbourne School of Earth Sciences, correcting the many errors in the original article. Not bad: only 6 days after the original. The Pope will feel slighted.

More data: Karoly refers to the World Data Centre for Solar Terrestrial Physics at the National Geophysical Data Centre in Boulder, Colorado as the main source on sunspot numbers; if you want to check his 2008 data, here it is.

Tuesday, 22 April 2008

Zimbabwe and China: A Toxic Legacy

A shipload of armaments for Zimbabwe was turned away from South Africa on Friday 18 April 2008, thanks to activist unions, an inquiring press and a strong human rights activist community.

The timing of this shipment leads to the obvious question: is this the reason for the delays in counting the votes in the now not so recent election? Was the government waiting for fresh stocks of ammunition before embarking on all-out war on its own people? 3-million AK47 bullets would go a long way in a country of 12-million.

This is not an isolated incident.

China is accused of complicity in genocide in other parts of Africa. For example, the Rwanda government imported sufficient machetes from China to give one to every third male member of the population. Then there's Darfur -- despite worldwide publicity of horrific crimes of violence, China remains the Sudan's biggest armaments supplier.

Throughout all this -- and protests about Tibet and human rights violations generally in China itself -- the continuing mantra has been "no interference in internal affairs". If you check out the Chinese human rights policy in detail, you will see it's very carefully fudged to allow interference where activities "endanger world peace and security", which means
colonialism, racism, foreign aggression and occupation, as well as apartheid, racial discrimination, genocide, slave trade and serious violation of human rights by international terrorist organizations.

How, I wonder, is supplying weapons in Darfur, Rwanda and now Zimbabwe justified in this light? "Genocide" is listed in the categories where interference is allowed. Some might argue that annexing Tibet and destroying its culture is "colonialism".

The saddest thing of all though about this whole debacle is the way South Africa has repositioned itself as fudging human rights in its policy to Zimbabwe. The armaments shipment was not stopped by an intervention of the government. On the contrary, there is evidence that the South African government was facilitating it, offering a government-owned logistics operation when others refused to handle the shipment. It was the ruling African National Congress which, in opposition, did the most to change the inviolability of "non-interference in internal affairs" by making human rights a limiting factor on what governments could do.

If the Chinese government can see no evil, it's sad but not surprising. If the South African government can neither see nor hear any evil, it's pathetic. You have to wonder what the whole anti-apartheid movement was actually about. It certainly has not resulted in the ANC perpetuating the legacy in international affairs that it fought for. Thanks to a vigilant press, an activist civil society and a strong union movement, South African has been saved from total disgrace. But it's hard to see how Thabo Mbeki (a leading promoter of the ANC in exile) can't leave office as a total failure. First there was the debacle of failing to deal with the HIV pandemic based on the remote possibility that the mainstream science was wrong, then there was backing incompetent ministers at all costs, now this -- the defense of a failed policy on Zimbabwe at all costs.

And China? I hope there will be a day not too far in the future when China will be a more open society, and its people will look back on its role in Africa with shame and embarrassment. But I am not holding my breath; the Belgians, for example, have battled to accept their role in the destruction of the Congo, including complicity in the murder of independence prime minister, Patrice Lumumba. And of course, for Chinese readers, there's the reluctance of the Japanese to admit their crimes in World War II.

Crimes against humanity are not crimes only against individuals, but crimes against us all: they violate the very concept of what it is to be human. Until this idea is widely accepted, we will have made no advance over the barbarity that was unleashed in Europe in 1914, when old-fashioned limits to the projection of power were overwhelmed by mechanized warfare. Until we develop limits not only on what we can do, but on what we should do, crimes will continue to be committed.

Follow Up

South Africa's main union federation, COSATU (Congress of South African Trade Unions), is playing an increasing role in regional pressure on Zimbabwe. A good source on news on that country is ZimOnline, e.g., here's a story about COSATU's role.

The arms shipment has subsequently been reported as delivered, allegedly with connivance of the South African government.

An update of this article has been published at Online Opinion on 24 June 2008. Sadly, very little had to be altered other than noting the withdrawal of the MDC from the presidential run-off, and integrating the paragraph preceding this one into the text.

Tuesday, 15 April 2008

Rob Robertson: A Tribute

I did not know Rob Robertson and his wife Gert well. My wife Fiona Semple introduced me to them, and they immediately felt like old friends. In a few visits, I had a sense of a big life, lived to the full, yet without selfishness.

On our last visit in December 2006, he proudly showed off mementoes of his bungee jump. He had done this at the highest jump site in the world. He had negotiated to do it for free for the publicity value of being the first 80-year-old to do so and was very disappointed that another octogenarian (a word that didn't fit his demeanour) had beaten him to it. Nonetheless, the operators let him have his jump free of charge.

That Fiona had over 50 emails from various people within days of hearing of his death – he was knocked down by a speeding car while crossing the road on the way home from a run – indicates that his life had a lot more depth to it than I experienced personally. I would like anyone who knew him to post a comment here; I feel unqualified to comment on his long life and quiet achievement, including his early attempts at breaking down the walls of apartheid.

Thursday, 10 April 2008

Climate Science Predictive Power

I must say up front that I would be ecstatic if the anti-anthropogenic global warming position was shown to be correct, because the probability of action to stop CO2 emissions in time to avert some of the predicted consequences is close to zero. Unfortunately, the universe does not subvert itself to my will, so I have to work with the next best thing: understanding reality as well as possible, and working to manage my life and that of others to fit reality.

In my last article, "Who's putting the 'political' in climate science, now?", the most serious allegation by commenters was that, "To put it simply, models have got better at being tweaked to match historical climate but no-one has the faintest idea of how good they are at predicting future climate." In other words, the models have no predictive power.

To investigate this claim, I went back to one of the earliest global climate model papers [Hansen et al. 1988].

If this allegation is true, this paper should be wide of the mark; after all, if refinements to the science have gone nowhere, a paper from 20 years ago should be nowhere close to predicting future climate. On the other hand, if the allegation is false, while we can expect some errors, some predictions made by the paper should be reasonably close to reality -- certainly close enough that we could have used them for broad policy decisions, if not for detailed planning.

Let's start by looking at temperature trends as predicted in the paper. The paper uses three scenarios, A, B and C. A assumes exponential growth in CO2 outputs, scenario B a slowdown to linear increase, and C a slowdown to no increase. The authors indicate that they considered B the most likely, and focused their analysis on that case (though the others were covered too, to provide a range of scenarios).

Let's start by looking at the 1988 paper's temperature trend prediction.

As with current work, temperatures are reported as an "anomaly" versus the average from 1951-1980.

In 1990, the scenario B predicted temperature anomaly was about 0.4 degrees; in 2000, the scenario B prediction was 0.55°C (approximately: I had to eyeball the graph since no data tables are provided). If we look at the 5-year mean in current data, what do we see? In 1990, the anomaly was 0.27; in 2000 it was 0.45.

Here's the most recent temperature trend from NASA. You should look at the 5-year mean, the red line, as representing the trend (smoothing out short-term variation). The green bars represent uncertainty bars (95% confidence limits), allowing for gaps in measurement.

How far out is the 1988 paper? The number for 1990 was 48% over the measured number. In 2000, the prediction was 22% out. It is also worthy of note that these differences are within the range of uncertainty in the measurement.

How big a deal is this? Certainly, it would have been a huge surprise if a model with as many omissions as were reported (e.g. a very crude model of the ocean) in the paper was spot on. But remember, the allegation is that the models used have no predictive power, and can only be retrofitted to the past. What we have found instead is that while the model over-predicts compared with reality, it does so within the range of uncertainty in the subsequent measurement.

Let's look at the distribution of temperature change as predicted then, and as subsequently observed. First, let's look at a map from the paper, then a similar map generated from NASA's current data.

The temperature scale on the older map goes -3 to 5, but with similar significance to the colour scale (no warming is white, warming is yellow through orange to red).

The newer map is from NASA's GISS site, with the parameters in the next picture, covering the same period as the illustrated 1988 model run.

Exercise for the reader: rerun my example at GISS for 2000-2007. It looks a lot closer to the 1988 paper's "2010s" picture, except the Antarctic hasn't warmed to the predicted extent. I'm not including this though, because we should really have a whole decade to compare with the paper.

What can we see from these two maps? Clearly, there are differences. The distribution of warming is not the same. In particular, the original study had more of the warming away from the tropics, and had more warming in the Antarctic. However, in general terms, the 1988 paper cannot be said to have no predictive power. The range of warming temperatures is approximately right, the real distribution of warming does show some bias towards the north and there are few areas which actually cooled over the 1990s, as opposed to none in the model.

Are these predictions of any use? Clearly, if you were using them to predict where to invest in agriculture over the long term, you would have made some serious mistakes. If on the other hand you were using the model predictions to decide whether anthropogenic climate change was a real effect, the predictive power is more than sufficient.

For those who say it's all natural effects, just the sun, etc.: please provide me with a 1988 paper that came as close as this one to predicting the future climate. Too hard? How about any "it's all the sun" paper that has done better than fit to the past. (Or whatever else you think is the sole driver of climate; I really do want to be convinced.)

So what's the bottom line?

It's not too surprising that this early model, with less data and computing power than is available today, should have some inaccuracies. However, the allegation that models have never been able to predict anything but are only capable of being fitted to the past is clearly false. One commenter on my previous article insisted that it's up to the climate change modellers to convince everyone, not the doubters. I don't think so. This study plus others subsequent to it have been making the case for twenty years. I suggest the denial crew get a job with Robert Mugabe's election procrastination team.


RealClimate has a useful article on comparing models with predictions, in case anyone thinks I'm the only one doing this. I've also spotted their own analysis of Hansen's 1988 paper versus reality since I wrote this (I deliberately didn't seek it out before so I could keep my opinion independent). There's also been a recent study (April 2008) showing that climate models on the whole are doing pretty well. My main motivation for doing this myself was to check for myself, rather than rely on climate scientists who may, according the the denial mantra, have a vested interest in making the models look good.

As a courtesy to other readers, please provide references (not just a web site or an organisation please: something that can be found) if you have information to add. I do not feel obligated to respond to unsubstantiated claims to the same extent.


[Hansen et al. 1988] Hansen, J., I. Fung, A. Lacis, D. Rind, Lebedeff, R. Ruedy, G. Russell, and P. Stone, 1988: Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model. J. Geophys. Res., 93, 9341-9364, doi:10.1029/88JD00231

Wednesday, 9 April 2008

Who's putting the "political" in climate science, now?

On 9 April, The Australian published an article titled "Good science isn’t about consensus" on its front page.

The New York Times's masthead motto is "All the news that's fit to print." The Australian's might as well be "All the news that fits our prejudice."

Don Aitkin is of course entitled to his opinion (though as the late Senator Moynihan reminded us, he is not entitled to his own facts). The paper could have run his piece as an op ed on the inner pages (though for what purpose, I don't know). But by running it with the prominence they have, you have to wonder at their motivation. Don Aitkin is a political scientist, no doubt eminent in his field. But no one can pretend he is an authority on climate science. What's more, his article contains nothing of any novelty. So what purpose can there be in not only publishing the article, but in giving it the prominence of a page 1 placement? All I can think of is that The Australian wishes to continue to stoke controversy -- whether to generate circulation (which doesn't work with me, I stopped buying the paper) or to pursue its own agenda on climate science.

However, since they have done this, and in addition, posted a lengthier paper (an address he gave to the Planning Institute of Australia), his views demand rebuttal. Here it is, based on the lengthier paper.

  • Arguing about "consensus" is silly. There was a consensus before Einstein's time that Newton had the Laws of Physics stitched up. Einstein found a more general theory. "Consensus" in science is not a deep concept -- just a way of expressing the fact that most scientists do not see the point in arguing over something that has been shown to be valid, and no one has successfully invalidated. There was a similar "consensus" about the link between tobacco and cancer, which the relevant industry attacked vigorously, using similar language to the anti-AGW movement. That consensus remains to be overturned, despite the fact that we still have a lot to learn about the mechanisms of cancer.
  • He claims that he is "presently agnostic about the central Anthropogenic Global Warming...proposition" but this is not borne out by his article, which dwells on arguments against AGW. To quote Monty Python, that's not debate, it's contradiction.
  • The "panicky media mood" he talks about is no reason to trash the science, rather to be skeptical about the quality of science journalism in popular media. There was a similarly panicky media mood about global cooling in the 1970s (he quotes Newsweek further on) but if you actually search the scientific literature, there was very little basis in science for this. I don't think you will find a "panicky mood" if you read Science or Nature. A paper has been published showing that 7 papers in the 1970s predicted cooling, compared with 42 predicting warming. The cooling papers attracted only 12% of the citations counted. In other words, even in the 1970s, the evidence available at the time -- Newsweek and other popular media notwithstanding -- was that warming was more supportable than cooling.
  • Einstein and Feynman on refutation and uncertainty in science: the anti-AGW movement can be accused of a higher degree of certainty with considerably less evidence on their side. Read Bob Carter's polemics. Is there a hint in any of his writing the he could be wrong? On the contrary, there is a bellicose certainty in his writing which I have not found in the scientific literature -- which I find odd from a scientist of his experience (here's a classic example).
  • "...human beings barely understand 'climate'". Well of course this is a vast field but enormous strides have been made over the last 20 years. I have been following this issue over that period, and the scope and accuracy of the models have improved vastly. To speak of the field in terms that were true 20 years ago is misinformed, I'm afraid. Models developed over that time have for example accurately predicted the effect on climate of a major volcanic eruption.
  • Urban heat island effect -- I suggest he reads the literature on how this effect has been isolated out. For example, warming in the Arctic cannot be explained by this effect. Studies have been done eliminating urban sites to see if they skew the trend, and statistical techniques like jackknifing have been applied to determine whether a fraction of the stations is skewing the trend. There is an excellent discussion of this issue at the RealClimate site.
  • Reduction in measuring stations -- the reason for this is the introduction of satellite-based measurement. Satellites can measure bigger areas more accurately (though they do need careful calibration, the source of some of errors which have since been put right).
  • Uncertainty brushed aside -- this is simply untrue. Measurements and model outcomes are given with a range of values to allow for the uncertainties in measurement and modeling. Uncertainties in IPCC reports are expressed numerically (90% probability etc.).
  • "IPCC, for example, discredits satellite-based measurements, perhaps because they are lower). But let all that pass too." If he didn't mean the reader to take this into account, why mention it? This is a rhetorical trick befitting a shaky legal case not a serious academic argument. As I pointed out earlier, satellite measurements are subject to a period of calibration, as is true for any new instrument.
  • Wine-making in England: this is skimpy evidence at best for unusual warmth. Wine is grown in England on an even bigger scale now, and has been for years. It's also grown in much cooler climates (Germany, Canada: have you heard of Eiswein?). The literature on the medieval warm period is subject to much greater uncertainties than the modern climate record, and that the world as a whole was warmer (as opposed to a few regions) has not been established. It is a bit rich to complain of the IPCC brushing aside uncertainties, then accepting the "medieval warm period" as fact, without any doubts as to the accuracy of measurement.
  • "... we don't know what the 'normal' production of CO2 is". The natural carbon cycle is very well understood. Try looking for papers by Berner for example.
  • He correctly points out that the greenhouse effect of CO2 is logarithmic, then goes on to look for a "dramatically linear relationship". Why would you expect to find a linear relationship if the effect is logarithmic?
  • The claim that the warming of the troposphere doesn't match models arises from improper handling of uncertainties (where have we heard that before?).
  • IPCC and sea levels: the IPCC's 2007 numbers are lower than their earlier numbers because they took out the area of greatest uncertainty, ice loss. This is not reassuring. The behaviour of the Antarctic is deviating from models significantly, including much more rapid ice discharge than predicted. If you want to criticise the IPCC for inadequate handling of uncertainty, this is the place.
  • "... slight cooling in the sea" -- again, a problem with calibrating new instrumentation. See the note at the head of the press release that started it all. Prof Aitkin may be a novice at climate science so one could forgive him the lapse of failing to check for follow-up studies. This error has been known for almost a year. But Bob Carter was advising him. Surely he can't be that incompetent. Or is he dishonest?
  • Antarctica: the West Antarctic Ice Sheet is cause for concern. It is grounded below sea level (up to 2km in parts) and if it destabilized, it could come apart quickly, adding around 5m to sea levels. The problem is that we don't have good models to predict its behaviour. There is evidence of very rapid ice loss in the distant past, but no evidence of the mechanism.
  • Climate models versus weather prediction. I've seen this argument often and it doesn't improve with age, unlike a good wine (British or not). Climate is a long-term effect, averaged over many years. Weather is an instantaneous measure (what you see now). I can predict with reasonably accuracy, based on decades of medical data, that flu cases will increase over winter. I cannot, however, predict whether any individual will get ill at all, let alone when. Should we stop advising the infirm to take flu shots, because we don't know which of them will succumb? One of the great advances in the twentieth century is the science of large numbers. We can do epidemiological studies, accurate censuses, and the like -- even though there are many errors in the data.
  • Validity of models -- there are many climate models, not just one. They broadly show the same trend with small differences. If modeling the climate many different ways arrives at a similar outcome, it increases your confidence in the models. If a discrepancy is found, either the discrepant model is invalid, or the others are, and work goes into fixing the problem. This has been happening over a couple of decades. If you think this is not a very good approach, what would you advocate we do instead? Carry on as normal, and see if nothing happens? Is that a responsible position if the best science we can do, whether imperfect or not, says we are heading for trouble?
  • He claims that the IPCC has extraordinary influence and that its work is political. I argue the opposite. If they had significant influence, we would have a much stronger worldwide agreement than Kyoto by now. On the contrary, the anti-AGW position is largely political (show me the scientific papers: I've found a few, but they are not convincing); I refer you again to the style of Bob Carter. If you think the language of the IPCC Summaries (for policymakers, note, not for scientists -- responsible policymakers will in any case run the detail past their own scientists) is not very scientific, look again at the Carter article I referred you to earlier (not an isolated example).
  • "... tendency of scholars to 'protect' their theory" -- I suggest he takes a step back and looks at the anti-AGW position in the same light. Lindzen for example persists with his "iris" theory even though he has no hard evidence to back it (and there's a very fundamental reason that it is unlikely to be right -- ask nicely and I'll explain).
  • "... quasi-religious view" -- again, look at the anti-AGW position. Many of its proponents aren't scientists, or are retired scientists. Their orthodoxy is being challenged, and they are putting up a bitter fight. Similar opinions were expressed about tobacco and cancer, and the ozone hole. What is a scientist who finds that an industrial practice is harmful to do? Shut up and live with the consequences, or speak out and be accused of "religion" or "politics"? Take a step back from the anti-AGW position, and ask yourself what you would do faced with that situation.
  • Influence of "Greens and environmentalists" -- now he is moving into the political. Is he saying that NASA's labs, the UK Antarctic Survey, et al. are mainly populated by Greens and environmentalists? This is where the science is coming from. I've been in science for over 20 years, and my experience is that scientists are significantly more conservative on average than his end of academia. That there is a Green vote no doubt influences governments to take some kind of action, but you can be sure that as long as that vote is under 10%, that action will be tokenism at best.
  • "... if there is no true causal link between CO2 and rising temperatures" -- there is. The physics is well established. The only cause for uncertainty is the feedbacks (e.g., extra heating caused by reduced albedo).
  • "I ask for a public inquiry" -- what purpose would this serve? The detail of the science is beyond the non-scientist, and any scientist can look up the relevant literature. The IPCC is an enquiry of a sort, but he rejects it; would the anti-AGW camp accept any finding they didn't like? His supposition is that the IPCC was set up with the AGW hypothesis set as truth. However, thousands of scientists working on the problem had every opportunity to refute it. Some have pointed out problems, most of which have been addressed, as he would have found had he followed up his limited literature review with a search for citations. There is in fact considerable reward in demonstrating flaws in the science because so few people are doing it -- hence the entry into the field of previous unknowns like Lomborg (would any conventional funding agency have funded him? Only one journal publication, and not in a relevant area ... or now that Aitkin's no longer involved in funding decisions, does he no longer accept track record as a criterion for funding research?) Why are so few people doing it? Is it because the "consensus" is substantially right? Because of a conspiracy?
  • "... ensure that the funding directed to climate science research be allocated in a disinterested way" -- does he have any evidence that it's not? Again, I point to Lomborg. No track record, no relevant scientific background, yet he was able to attract significant funding. If you want to look for political interference in funding, look no further than his case.
  • "... started to think through how to find alternatives to oil" -- James Hansen at NASA, often accused of being alarmist, has also pointed this out.
  • "likely to be attacked and demonised" -- I have seen this claim often but I have yet to see a real instance. Lomborg for instance was attacked largely on the poor quality of his science, which he took personally. The Australian has plenty of articles "attacking and demonising" the IPCC position (how would you classify his?) He may find, however, that some people are annoyed by the fact that he is raking over old arguments that are easy to refute. I was annoyed enough to write this lengthy rebuttal when I have better things to do with my time.

The only part of Aitkin's paper which makes any sense is where he points out that there are other good reasons to aim for a cleaner, greener planet. Well good. Why, then, muddy the waters by pontificating at length on matters on which he is not qualified and which he clearly does not underestand?

As a courtesy to other readers, please provide references (not just a web site or an organisation please: something that can be found) if you have information to add. I do not feel obligated to respond to unsubstantiated claims to the same extent.


Predictive Power of Models

One of the comments on this article claims, "To put it simply, models have got better at being tweaked to match historical climate but no-one has the faintest idea of how good they are at predicting future climate." In other words, the models have no predictive power. I took this as a challenge, and compared one of the earliest papers with reality.


Also since the Antarctic has been the subject of some discussion, I though this picture may be of interest: The picture (sourced from NASA) shows the warming trend around the Antarctic, 1982-2004. As you can see warming around the edges is very significant, but much of the interior is cooling. The overall picture is consistent with the view that the region is warming, but the special properties of the continent with its extremely massive, high ice cap are causing it to deviate from the trend.


I was accused of talking nonsense when I spoke of "consensus". Another area where this term is used in in evolution. As with climate change, effects are long-term and can't be observed directly. If most evidence points to a particular view and there is scant evidence to the contrary, it is reasonable in science to talk about "consensus" emerging. It is simply not true that a scientific theory can only exist if you can directly demonstrate its validity experimentally. Evolution and geology operate on multi-million-year timescales; cosmology on even longer timescales. We can no more recreate the steps leading from simple organic molecules to multicellular beings (at least in some cases) possessing intelligence than we can recreate the steps from the instant of creation of the universe to countless millions of stars as we know them. Nor can we experience climate change directly and change its course by a simple experiment. None of this means that we cannot have valid scientific theories in these areas -- only that testing them is hard, and those who refuse to be persuaded have an easy time developing arguments that seem compelling to the non-scientist.

Satellite data

One of the comments said:
Satellite-based measurements are more accurate - I agree - and the calibration issues have been resolved. Both the University of Alabama (Huntsville) and RSS are now producing very similar temperature data and .. I suppose to your dismay ... it's showing little sign of warming.

It took me a while to get to this and ... why should I be dismayed? If the problem is going away we can all breathe easy. As it turns out, recent corrections show that errors in Christy and Spencer's work significantly underestimated the warming trend.

Sea Level Rise

Here's something I found recently on sea level rise and the potential for a rapid meltdown of ice caps, based on paleoclimate studies:

Jonathan T. Overpeck, Bette L. Otto-Bliesner, Gifford H. Miller, Daniel R. Muhs, Richard B. Alley, and Jeffrey T. Kiehl. Paleoclimatic Evidence for Future Ice-Sheet Instability and Rapid Sea-Level Rise, Science, vol. 311 no. 5768 24 March 2006, p, 1747-1750.