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Hacking: It’s Good for Science

Posted by softestpawn on November 21, 2009

Over the last few days the global warming communities – those ‘for’ and ‘against’ – have been deluged by the news that the computer systems at Hadley’s Climate Research Unit (part of the British Met Office*) have been hacked and the data posted on t’interwebs:

The alleged docs are here (along with on-line searchable access to the emails) but of course, this is the internet, and you can make up anything you like and post it. (Update: Downloading and expanding it, it appears to include 100mb of uncompressed code and data, mostly tree-ring/bristlecone proxy rather than weather station measurements. If this is made up, then someone’s been very busy; but there is also a danger that it is ‘mostly real’ with some key edits)

Assuming for the moment that these are real, and that Phil Jones does in fact admit it, then this is not good for the reputation of Science-The-Human-Endeavour. The tone and contents of the emails squash any claim that ‘you can trust us, we’re scientists, we’re objective and only interested in the facts’ (but then, we know that humans don’t do science)

It doesn’t even help, much, the scientific debate on global warming. As the above discussions show, the main responses are around dishonesty and legality (which are somewhat open to interpretation), rather than analysing the facts and the data. But then the scientific debate has always been very sparse across this general debate; everyone claims to have science on their side and will point to authority, to motivations, to allegiance, to politics, to vested interests, to the number of people working on it, even to assumed ideologies, in order to bolster that claim, but few will actually discuss the science. Well, the science is difficult OK?

But that will come. After the quote mining and short-term tribalist gloating is over, the Big Win for science is the simple straightforward forced releases of data that so far has been kept hidden, for possibly good but still also hidden commercial reasons (That is, CRU wouldn’t show any evidence for why it should be kept hidden, because they claimed to have lost that evidence).

Real Science – that is, the accumulation of a systematic body of knowledge, rather than the insular world of messy so-called-iterative academic research – requires rigour. It requires openness. It requires criticism, whether deserved or not, to tighten arguments and improve evidence quality, and expose gaps and risks. In other words, it requires independent review, or at the very least the threat of it.

Openness is forced internally in any organisation or project that practices ‘due diligence’. We have seen it introduced to medicine in only the last generation or so; many academic organisations** have been reluctant, slow and late to that particular party, for all kinds of ordinary people and practical reasons.

This hack – an externally forced openness – will not do much good in the short term, especially to those involved. But in the long term, we can hope to see researchers who inform public policy become openly professional – and scientific – throughout their work, because now they know that someone, internal or external, may come along one day soon and let unfriendly people examine it. All of it.

Update:Judith Curry (I think this climate researcher), talks about tribalism and the duty of public release here

* I’m not actually clear on the differences in responsibilities and allegiances of the Hadley center, The British Met Office, and East Anglia University’s Climate Research Unit. I don’t think they are either.

** And plenty of private organisations too. I’m just picking on researchers whose work is used to drive public policy (and I’ve made some changes to the text to make this clear)


Posted in Environmentalism, Global Warming, Science | Tagged: , | Leave a Comment »

The Equality Mistrust

Posted by softestpawn on October 5, 2009

Inequality within a society, we are sold, results in all sorts of Bad Things such as more and greater violence, poorer health, and more alcohol problems.

At first sight this would seem a bit odd. Marginal, subsistance societies where everyone is equally and awfully poor have infamously low life expectancy and high infant mortality rates. As a society’s wealth increases its health increases, and we can see this crudely with GapMinder; both over time and over space, richer societies show no obvious general trend to be any less ‘equal’ than poorer ones (in fact possibly maybe a bit the opposite), and do show an obvious trend to be healthier:


The Equality Trust

Still, the Equality Trust (“Because more equal societies work better for everyone”) are trying to make a case that ‘at some point’ – which just happens to be now in the UK and other western worlds – we can stop working on progress and instead focus on being fair. Because there are some indications that rich societies that are less ‘equal’ are also less healthy, more violent, etc:

Infant Mortality vs Equality

And if you click on that you can look at various other handy graphs.

Lots of skeptical alarm bells ring: there are no units on some of the graph axis, so what are the scales? There are few dates. Countries appear on some graphs and not others. And there’s the general background that “unfairness is bad, mkay?

In fact all that these graphs tell us is that some countries are quite consistent. The USA tops out as the least equal and most nasty, Singapore as the most equal and most nice, Japan as both equal and nice. It seems quite probable that there is something else at work here, such as differences in cultural approaches to wealth and health and social responsibility and so on.

Still, they Trust claim that “Compelling new evidence shows that large income inequalities within societies damage the social fabric and quality of life for everyone”. Presumably the well-established evidence that more income improves the quality of life is now old and optional.

Physical health vs inequality

So let’s have a look at a sample of their evidence. The paper on the first page in their evidence page, by Wilkinson and Pickett, Income inequality and population health: a review and explanation of the evidence has a title that tugs at those barely stilled skeptical alarm bells again: they are setting out to show something, not investigate. A reason to be skeptical, but not to disregard.

The abstract simply counts papers that they’ve found. There’s no indication of any methods to compensate for positive publication bias, or indeed any ordinary collection bias. They just went looking for papers, and found 155.

They then count papers and bin them according to ‘supporting’, ‘unsupporting’ and ‘partially supporting’. There’s no indication of scaling or weighting factors. So a paper that looks at one factor in a specific environment is either ‘supportive’ or ‘unsupportive’. A paper that considers more complex relationships is likely to find a bit of both, and so will be ‘partially supportive’. If you throw those inconvenient complicated relationships away, and look at just the simple positive findings vs the negative findings, then it should be completely unsurprising that 70% are positive, simply due to publication bias (though a ‘supportive’ positive finding is not necessarily the same as a positive result that biases publications).

It’s not at all right, on the basis of that review, to conclude that the literature shows even a link (let alone a causal link) between inequality and Bad Things. In the paper they go a bit deeper than that, but not by much. The studies included were from three previous reviews, electronic searches and informal contacts, thereby introducing various collection bias.

Self-enforced relationships

There’s an interesting circular argument on page 4: Wilkinson (in another paper) points out that communities across larger areas show more correlation between poor health and inequality. He argues that this is because people can see further across differences in that community, and so see more inequality, and we should measure across wide areas to capture this. By then showing that studies of communities across larger areas return such correlation, he thinks he bears out his argument that was formed as a possible explanation for this observation…

Smilarly at the bottom is an even more circuitous argument: Inequality relates to health as a measure of the social distances which are responsible for class differences in health (ie, the social distance here is measured in healthiness). Lo and behold, if you measure those social inequalities in that particular way, you will get differences in health. Lo further and behold more, the greater those social inequalities are measured to be, the greater the differences in health. Which is what you defined it as being in the first place.

On Page 7 they assume that income ‘inequality’ is the reason why Mr Average Black in the US has four times the income of Mr Costa Rican but a lifespan shorter by nine years, and ignore a host of other social factors.

Finally – at least as finally as I got to – was that “the relationship between income inequality and homicide shows beyond doubt that inequality has powerful psychosocial and behavioural effects” (my emphasis). This is not only very poor science (correlation does not show anything beyond doubt, certainly not cause), but is also wrong: this paper (“Income Inequality, Poverty, and Homicide across Nations “) says homicide depends on absolute wealth, not equality. Although this one (“Income inequality and homicide rates in Canada and the United States“) says otherwise.

Some speculation & Some other evidence

We should in fact expect to find “fairness” as some kind of indicator, or proxy, for health. When comparing countries with similar average income, a greater spread probably means the poor are poorer and the rich are richer. The poorer then will have more of the illnesses associated with poverty, while the richer benefit from much smaller improvements in health, and so countries with a greater spread in income will have worse overall health compared to others with the same overall wealth.

All we are seeing is the diminishing returns of increasing wealth on increasing health. It’s not the inequality that causes health and crime, it’s that less equality probably shows the presence of poorer people, who have worse health and often more crime.

A proper way to measure whether societies are ‘doing the right thing’ is to compare like with like. How are those who earn $1000/month “buying power” in the US comparing with those who earn $1000/month “buying power” in Nigeria, or Singapore, or the UK? As a society gets richer – and supposedly less equal – how do the people in the bottom quartile do as it does so?

If we take a look at gapminder, and compare the Gini ‘inequality index’ with life expectancy or infant mortality (do press Play to avoid being diverted by particular years), then you can see that there’s very little correlation in general between inequality and poor health:


Similarly compare the “Income share by the lowest 20%” with life expectancy and there’s little correlation.

Only very specific years show the correlations the Equality (Mis)Trust claim, and are quickly swamped by other effects as time goes on. In fact, we can pick the year 2000 and show that richer societies are more equal:

Income Vs Gini (2000)

What is more clear is the way that different parts of the world tend to sit in similar areas of the graphs. Cultural attitudes again perhaps.

What were they thinking?!

So why does this poor analysis turn up as ‘evidence’? Well the language seems a bit of a give away:

“Because more equal societies work better for everyone”

“Compelling new evidence shows that large income inequalities within societies damage the social fabric and quality of life for everyone”

“Great inequality is the scourge of modern societies”

This is the “It’s not fair” brigade dabbling in a bit of pretend science to bolster their dogma. Anyone turning up with that old mantra and a clutch of citations to prove it is going to have a lorryload of skepticism dumped on them.

Their case avoids comparisons with poor countries by assuming that ‘now we are rich and healthy’ we can take stock and think about doing things differently. But if we compare only the rich countries, the relationship is not as obvious or as large as they claim, which raises questions again about the scales of the axis used:


Even so, only most of us are whole, rich and healthy, and it’s not clear quite how rich we could be. In 50 years time, say, with free personal fusion power, no physical disabilities, no cancer, a healthy lifespan of 120 years and personal jetpacks (at last!) we might look back with pity at the relative poverty and disease-ridden state we are in now.

All the same we have some features that absolutely poor states don’t, including a relatively carefree life. We don’t start with the spectre of externally-caused starvation and death hanging over our shoulders, which tends to produce a work ethic dedicated to improving life, a sort of ‘eye on the horizon’ and a drive to work to get richer and safer.

Instead we can support whole communities of ‘idle’; that is, we can afford to pay people to do nothing, and it’s infamously depressing and frustrating to be part of those communities, and famously hard to get out of them.

It may be that we should look at the outliers in those graphs and examine potential causes; Scandanavians for example attempt to ensure full employment rather than compensate for unemployment via the dole, and that may be how they assure better equality and better health.

Wealth makes health

But in the meantime, the idea that greater inequality may sometimes be a proxy or indicator for the presence of lower absolute wealth in a society is trivial, and should not divert us from working to make everyone richer.

In particular, we must be wary of any argument that to reduce Bad Things or increase happiness, we could reduce the inequality by, say, limiting the income of the richer part of society, rather than by increasing the wealth of the poorer. As we can see above, health improves with wealth. The only happiness that such policy improves are of those who have no interest or ability to become rich, at the expense of all those who have, including the poor who are working to become rich.

The evidence remains, as can be seen above, that people living in an unfair rich society are much better off than those living in a fair poor one.

Posted in Environmentalism, Politics, Science | Tagged: , , | 2 Comments »

Cautiously Approaching the Precautionary Approach

Posted by softestpawn on August 25, 2009

Following a post about the appalling Precautionary Principle, some folks said I was a bit harsh and that I had constructed an extreme version of it that it was never meant to be.

I’ve not been given an alternative definition, but all the same let’s have a look at a softer ‘Precautionary Approach’. In this case we’ll consider it in its fuzziest nicest: that we should not do dangerous things, and that if something might (but plausibly might) be dangerous, then the people who want to do it should prove it safe before they start.

All well and good it seems. This is the mellow, relaxed and comfortable “better safe than sorry” or “look before you leap”. It means people have to prove stuff is safe before they start doing it. And what can be wrong with that?

Well it’s wrong, wrong, wrong and wrong as follows:

  • It considers only direct harm.
  • It includes the potential for possible harm, even with little or no supporting evidence
  • Proof lies with the advocates
  • It makes the decision for you

It considers only direct harm

Most activities include quite definite harm. These are traded against the benefits of doing, or indeed the harms of not doing: if I am being chased by a veloceraptor, I am not going to pause and look to see what’s on the other side of the log I’m about to leap. There is a much higher certainty of danger in not doing, than in doing.

When it comes to more complicated activities, like building a factory or a hospital, we have definite harm: the land occupied will destroy wildlife, it will require energy, roads. On the other hand we will have the things the factory makes, the lives saved by the hospital, the employment. There are costs and benefits too from the houses, shops, recreation activities, schools, hospitals and factories needed by the workforce.

And the same effects will appear harmful to some and beneficial to others. Sheep grazing keeps the heather down. If you replace sheep with some other local industry, then the heather can run riot; this is good for the heather, but not so good for the moorland. Creatures that like living in heather will thrive, at the expense of those that like moorland. Are you a fan of heather or moorland?

Caution is not free. The continued ban on GM crops affects the wealthy very little, who can afford the warm, cuddly feeling of ‘protecting the environment’ at the expense of a little more wealth. That same ban, even if justified, is cold, heartless and cruel to those living on the edge of starvation, who die very young, who are always hungry, diseased and frail.

It includes the potential for risk of harm

Most activities carry some risks that they might cause harm. With the precautionary approach, we’re not only interested in the ‘known risks’, but the ‘unknown risks”.

There is no indication of quite how much possible risk is important; any “plausible” cause is sufficient. So for example the initial studies that drew a “link” between the MMR vaccine and autism are sufficient to “take precautions”. There was no actual evidence of risk of harm (the single study that started the scare had no significant value in the existing evidence), but there was enough to indicate the potential of such a risk.

And that’s enough. Being generally precautious provides no help in evaluating the possible risk of harm, and so it all rather depends on the emotions and enthusiasms of those applying the approach. If you are scared or highly reluctant to use modern medicine, then the above tenuous link between MMR vaccine and autism is enough to “take precautions”, and keep your children safe from such injections. This exposes your children to the harm of not taking the vaccine, but that’s not part of the consideration.

So we end up making decisions based on lack of evidence; based on ‘fantasy’ where we can dig out any possible plausible danger and use it as if it was actual danger. You might as well make decisions based on the plausible possibility that aliens live in clouds.

Proof lies with the advocate

This is not necessarily part of being generally precautious, but it seems to come with the Precautionary Principle:  if you want something, you prove it’s completely safe.

Which has two problems:

(1) It’s rarely possible to prove that anything is completely safe. Lots of clever people have looked for links between the MMR vaccine and autism and found nothing, but maybe that’s just because they haven’t found the right thing yet. Maybe there are other dangers. And so anyone ‘being precautious’ can do do so for ever, happy in the knowledge that, because they’re using the important-sounding “Precautionary Principle”, they are doing the Right Thing.

(2) Expecting someone with a vested interest (who wants to build the factory, or vaccinate children against MMR) to be fair about the evidence they present is a bit naive. Or rather, it’s a way of maintaining the Precaution, no matter what evidence is presented. Because you can’t trust it, obviously, it’s from the evil capitalists who want to build the factory, or evil drugs companies who want to make money from vaccine injections.

It makes the decision for you. Or not

Evidence and analysis inform our decisions, but should not make them. Sometimes the decision is obvious based on that information but sometimes it is not.

The precautionary approach provides a way of shortcutting all that palavar, and tells you not to do something if it might be dangerous. Yet it contradicts itself: it will tell you opposite things depending on how you apply it to the same problem.

For example: “Do I get up tomorrow?” The precautious approach tells you that because there are many possible (and known) harms in doing so, you should not. Yet “Do I stay in bed all day?” also has many possible (and known) harms in doing so and the precautious approach tells you that you should not.

Instead you have to choose when to use it, and choose which way to phrase your same question in order for it to ‘work’, and that’s the giveaway that it’s not a useful scientific approach. It’s a way of providing a pseudo-scientific cover over an emotional approach.

So if we look at opponents of wind farms, nuclear power, road bypasses, new shops, and so on, we sometimes see people who find just possibilities of potential harm, and seem to think that this by itself is enough to call a halt.

The Reckless Approach

Taking the same approach in the opposite direction exposes the lack of evidence, reason and analysis behind the Precautionary Approach.

The Reckless Approach says that “if there is any potential benefit to the action, we should act”.

And if we apply this approach to any ideas, we can quickly see that we’ll end up doing lots of really rather dangerous things.

Risk Analysis

The way we really – and sometimes even scientifically – decide whether to do something is to weigh up the costs against the benefits, including the uncertainties which are usually given as risks (potential costs or harms) and potential benefits.

This might be brief and scrappy – as we run from the veloceraptor, we have to make snap judgements made on very little, but often very important, information. This is a long running issue in the military (the snap judgements, not the veloceraptors) where life and death decisions need to be made on little and uncertain information.

For the more complicated issues involved in environmental impacts, impact assessments are well established, if not entirely straightforward.

Which is perhaps the problem; carrying out a proper assessment is complicated, and involves making difficult decisions in weighing the various effects against others. How do you weigh, for example, the many benefits of faster, cheaper travel provided by a bypass with the deaths to cute furry animals? To the permanent loss of certain habitats?

But doing anything else is insufficient. To pick and choose amongst the effects of an action and wave only those around, as if they force only one possible decision, is not rational, scientific or even moral.

(See also Risky Business, Adam Curtis on the Precautionary Principle, SIRC on Beware The Precautionary Principle, Precautionary Principle, Evidence Based Belief, EU Commission’s Communication on Precautionary Principle)

Posted in Environmentalism, Metadebates, Politics | Tagged: , | 4 Comments »

CO2 vs Temperature

Posted by softestpawn on August 22, 2009

The idea that CO2 levels force temperature changes are key to the claims of global warmers. This post looks at how CO2 changes match temperature changes in the records.


There are lots of ways to find out how well two sets of values correlate, and a relatively simple way is to plot one against the other. If there’s a good positive correlation, we should get a graph something like this:


We can see that as X is higher, so is Y, and when X is lower, Y is lower. More than that, the larger that X is, so Y is larger.

Negative correlations simply swap direction, and might look like this:


The better the correlation, the closer the points are to a straight line.

This approach can help in noisy or chaotic systems, where a ‘by eye’ glance at data can get taken in by apparent but irrelevant patterns. It can also be useful when there are apparent overall similar trends over a long term.

Pre-Graphing Checks

According to the physics, CO2 slows the re-radiation of heat from the earth. So we expect – at the small changes in CO2 that we see from month to month or year to year – that the more CO2 that is added or removed, the more temperature will change. (The relationship is not linear on the larger scale, but we don’t need to worry about that).

We need to allow for time lags, at least between CO2 changing and the temperature of the instruments recording it changing. Mauna Lao is assumed to be ‘well mixed’ CO2, and the repeating patterns imply CO2 mixing on the order of a month is sufficient. CO2 effects tend to be on the whole troposphere, and there is likely to be some delay while the various temperature ‘pressures’ cause the ground to heat up. It’s hard to see, given daily variations, that this would take much longer than a day, but this assumption is definitely ‘iffy’.

Another potential lag is that of the semi-mythical ‘climate sensitivity’ effects. The more enthusiastic climatologists need these to multiply the ordinary not-very-dangerous temperature rises expected from CO2 change (less than 1C for doubled CO2 levels) in order to get to the scary dangerous temperature rises (3-6C). As these may be decoupled by much more than a month, we cannot assume that any correlation seen is accurate.

The system is very noisy, so we shouldn’t expect a good correlation anyway; there are many effects on temperature other than CO2.

We also need to be wary of seasonal effects. Each year the globe’s CO2 levels fluctuate (as you can see in Mauna Lao’s graph of CO2 levels, which has that ripple effect) and the temperatures similarly change over the year. So we might get a correlation that is a result of the earth’s orbit rather than the cause of one value on the other – the classic ‘correlation is not cause’. So we may have to check against annual values too, which may have their own systematic errors due to the rather arbitrary calendar year cutoff.

As an aside: many people have already plotted CO2 levels against temperature. This is not particularly useful; CO2 has risen nearly exponentially since the 1950s, so plotting CO2 levels is almost entirely equivalent to plotting time.

The Graph

But anyway, using Hadley CRU temperature records, Law Dome ice proxy CO2 records (1850-1978, low resolution thus the stripey effect) and Mauna Lao instrument CO2 records (1959-2008), this is a plot of the month to month (Mauna Lao) or year to year (Law Dome) change in average global temperature against the change in atmospheric CO2 for the same period.


And, rather interestingly, there’s almost no correlation at all. No matter how CO2 changes, the temperature changes in an almost completey independent manner.

With a month lag (ie, comparing the CO2 change with the temperature change of the following month), there’s still none. However if the ordinary CO2/temperature forcing has a lag longer than a week or so (ie, it reaches the same order as the granularity of the records), then this is probably the wrong approach.

Other articles

CO2 Science
Collapse of arguments for high climate sensitivity
CO2 Emissions vs atmospheric increase

Posted in Environmentalism, Global Warming | Tagged: , , | 2 Comments »

Oh no, not the Hockey Stick again

Posted by softestpawn on July 30, 2009

The “Hockey Stick controversy” centers around a graph published by a Dr Michael Mann. It showed how temperatures had remained fairly steady, until mankind started burning lots of coal and oil after which the globe heated alarmingly:


Because the world is mostly American, it’s an ice hockey stick rather than a real field hockey stick. The long steady decline is the hockey stick handle, the sudden rise the blade:

Ice Hockey Stick

The wiki article linked above outlines the main arguments about whether it’s valid, but there are a couple of other interesting things.

It became centre-piece to the IPCC 2001 report appearing in the summaries, and featuring (if I recall, I haven’t counted recently) eleven times throughout the complete reports.

That overt, specific and limited selection raised skeptic alarm bells. If there is overwhelming evidence for something, then you expect to see overwhelming evidence. Not a focus on one graph from one paper.

1998 as an end date

The first ‘interesting thing’ is that the graph stops in 1998, an unusually warm year, with an end temperature of around 0.7C above the 1961-90 baseline, which is indeed worrying.

Now that’s just a matter of timing rather than fraud (Mann et al’s paper was published in 1998). But by the time the 2001 IPCC report was released it was clear that 1998 had been unusual; 1999 and 2000 were only around 0.25C according to Hadley (0.35C according to GISS).

This rather makes a mockery of the complaints about ‘deniers’ using 1998 as a start point to show that the world is cooling. It’s not right to cherry pick such a year to show a trend now, and it wasn’t right for the IPCC to do so then.

It also indicates a bias in Evil Big Climate; observations that show unusual warming are accepted and published with warnings of runaway effects. Observations of unusual cooling – as in early 2008 – are bounded by warnings of temporary anomalies and ‘noise’

Consensus? What Consensus?

More interestingly it ran counter to the existing ‘consensus’ that there was a medieval warm period and a victorian ice age, supported by various accounts and proxy measurements dotted across the globe.

Which makes a mockery of the warmists cry that a ‘consensus’ should be accepted, even putting aside that a ‘consensus’ is not a measure of scientific fact.

The new Hockey Sticks

The arguments between McIntyre et al and Mann et al led to that particular Hockey Stick being abandoned, and the results of some new studies were collected into a new iconic graph:

As you can see these – and particularly the later ones, coloured red – are no longer Hockey Stick shaped; there is no long straight handle with a marked sudden change at industrialisation. Nevertheless these are called ‘hockey sticks’ by the faithful in memory of the original one.

All that is left is the blade, and even that is artificial. Despite including studies up to 2005 (click on the graph to see the references), the Big Black Line of recent temperature records stops at the steep slope we saw in the unusual year of 1998.

The Latest Hockey Stick

And still there’s some ‘interesting’ choices being made for graphs, these easily-understood, easily-published, easily-misleading summaries of evidence.

Recently Mann published a new one in September 2008:


We can see the medieval warm period and victorian ice ages are returning, more pronounced. The big red line at the end, forming the blade and shooting up past 0.8C by the year 2000, is based on Hadley’s CRUT land only dataset. The grey line hidden behind it is Hadley’s official global temperature estimate.

However CRUs global monthly and average (land) temperatures only break 0.8C in 1998; the average for the subsequent ten years between then and the study being published is 0.6C. Which would put the end of the red line on the graph, rather than have it shoot off into the infinite unknowns in 2000.

(The baselines look similar: CRU land only just passes its own 0C baseline in 1945 according to those records and similarly does so on Mann’s graph).

But the past proxies are not all land only; the black line is land+sea, Moberg 2005 combines ocean and lake data, and Mann and Jones 2003 is of mean surface temperature. So if we replace the red line with Hadley’s global temperature estimate, we get something like this instead:


which, while “unprecedentedly high”, is not quite so alarming.

(Not that we should read too much into the temperature records alone)

With thanks to Sophist et al at Bad Science. See also McIntyre’s more thorough castigation of the original

Posted in Environmentalism, Global Warming, Science | Tagged: , , , , | 1 Comment »