For anyone even vaguely involved in the world of blogs and climate change, logical fallacies are a familiar thing. The straw man, the appeal to authority, ad hominem attacks, the biased sample/cherrypicking, and many more are all used by both sides of the argument, to a greater or lesser degree.

On the side of climate scientists/environmentalists (Yes, I know that some won’t agree with my lumping those two groups together - it’s a crass generalisation, and it makes my case looks stronger (I am an environmental activist studying science), however it is true in the majority of cases) one of the arguments that comes up quite often is this:

Denier: “why should I trust the science - it’s biased/has vested interests/goes against my religion/philosophy.”

Greenie/scientist: “Why should you trust science? Look around you. You enjoy watching television, don’t you? And you’re using a computer right now, and I bet you drive a car. Science brought you those things.”

No. It didn’t.

Science is not technology, and technology is not science. The two are separate, although closely linked.

Science relies on certain technologies, such as microscopes, rulers and protractors, test tubes, and for more complex calculations, computers, etc. It does NOT rely on technologies like television, or the internal combustion engine, although these can make it easier.

Likewise, technology relies on science, but it also relies on the values of the individuals and societies building it, the resources that are available, and of course, the technology required to build it.

How about this:

Denier: “why should I trust the science - it’s biased/has vested interests/goes against my religion/philosophy.”

Greenie/scientist: “Why should you trust science? Think about this: The atom bombs dropped on Nagasaki and Hiroshima, engineered viruses, toxic toys, and television advertising. Science brought you those things.”

The point is that Technology isn’t brought to you by science. technology is brought to you by humans. True, the scientific understanding is a limiting factor on the technology available, but this does not mean that the technology will become available as the science advances.

Science, in it’s purest form, is just the pursuit of knowledge. More knowledge is, as far as I can work out, never a bad thing. Technology can go either way, and depends on the values of those designing it. Conflating the two is potentially a very dangerous thing to do, and even in cases where it’s safe,  to do so is still a logical fallacy.

There’s a long list of logical fallacies here: http://www.nizkor.org/features/fallacies/, but I don’t think this one features there. Perhaps it’s some kind of cause/effect fallacy. Perhaps it should be called the “Science for the Good/Bad life”.

I’d like to declare here and now that I’m sceptical about the “reality” of the round earth. There are many dissenting voices, sceptics of the current “consensus”, and significant evidence to show that the earth is not round. Not to mention that it’s bleedingly obvious - just look out the window: No curvature there, eh?

But despite this, dissenting voices in the debate are silenced. Proponents of the round earth hypothesis pursue their beliefs with a zeal unmatched even by the world’s most fundamentalist religions. While it’s true that many scientists believe that the earth is round, there are also significant dissenting voices, but were one to mention this in general conversation, or on talk back radio, one would immediately be shouted down, cut off, ostracised. In short, censored.

This is not how science should operate. Science is not decided by majority opinion, but by healthy debate. And while one side is being censored, there can be no real debate.

I’m not saying definitively that the earth flat or round - I’m still undecided, just that the debate needs to be opened up, so the true process of science can run its course, with maximum access to evidence and competing theories from both sides. Until all the information is on the table, I’ll be most skeptical of the majority-imposed “consensus”.


Sound familiar? The above arguments are frequently used by the denial-o-sphere (denial-o-plane?). While obviously climate change science is not so developed, or certain (or simple) as planetary physics, that does not mean that the above arguments have any weight in a climate context. (more…)

I’ve been starting to learn Octave, a maths programming language. Octave is similar to other packages that are often used to create nice graphs that you often see around the place, especially when it relates to climate change. This is a bit of a slap-dash tutorial on how to get some graphs happening with Octave. It probably assumes advanced high-school level maths.

If you wanna learn, I suggest you get QtOctave, which is damn nice, and in the Ubuntu repositories, and probably in most other distributions of linux (you can run Octave on windows - but if you really want to be this geeky, and are still on windows, you need to re-asses your values). QtOctave has a nice help-search function that lest you find most of what you need to know about functions, and installing it installs all the pre-requisites too, although depending on your distro, you might need some of the extra packages from octave-forge.

At the very bottom is an attachment with most of this code in it. I think most of this stuff will also work in Matlab, but you gotta pay for that…

Then read all of this excellent tutorial. That’s where I learned nearly everything for this tutorial, apart from the names of a few functions.

Crank out a graph!

Now you’re ready to go. Get yourself a copy of some temperature data to play with. I used NASA’s GISTEMP data. You can use any data you want, but I’ve attached a file that will do everything I’m talking about here, and includes octave-formatted GISTEMP data.

Ok, so assuming you’ve got your data in a matrix, you can then extract the relevant bits (Some of the variable names are different here to in the attachment, to save space):

% get the years from the first column
yr = GISTEMPdata(:,1);

(You did read that octave tutorial, right?)

% get the monthly averages
Temps =
GISTEMPdata(:,1);
% Average them, to get the yearly means (2 refers to the second dimension, ie. average rows, not columns)
AnnualTemps = mean (Temps, 2);

You can now hack out a simple graph:

plot(yr, AnnualTemps)

gistempplain

If you read tutorial, you’ll know how to adjust the axes, and add legends and titles, and all that jazz. I’m going to ignore that.

You’ll notice that the data range from -60 to 80. That’s because it’s a graph of temperature differences (anomalies) - which means that what matters isn’t the starting point, but rather, the relationships between the data. In this case, the -60 means -0.6DegC, and 80 means +0.8DegC (this is explained in the header of the GISTEMP file I linked to up top).

To change it to real values, to give it some human scale, we have to make the 1951-1980 average = 14DecC.

% Divide by 100, add 14, and subtract the average from the anomaly means
% 1951-1879 = 72, 1980 = 101
RealTemp = AnnualTemps / 100 + 14 - mean( mean( GISTEMPData(72:101,2:13) ) );

gistempsimple

Cool, huh? Okay, let’s get a Trend line going.

Getting Trendy

So, basically, a trend line is a best-fit line. You can do this automatically with a couple of functions in Octave, but since we’re going for just a straight trend line at the moment, we can just use a fairly simple one: a first degree polynomial fit. (a first degree polynomial is a straight line at any angle, from any starting point).

Polynomials are those equations you did in high school maths, that looked like:

y = x2+3x+1.5

That one would give you a basic parabola, shifted down and to the left a bit (I think, I haven’t actually graphed it). High-degree polynomials (where x is raised to the power of 2 or more) aren’t particularly useful for finding trend lines - they can look pretty, but don’t really help much. But more on that later. Simple first order polynomials (straight lines) are a good way of getting an idea of an overall trend.

To get the equation for the line, we need to get all the values for the basic form of a first degree polynomial:

y = mx+b

to get m and b from the data, we can use the polyfit() function, with 1, for 1st degree:

EQ = polyfit ( yr , TempReal , 1 ) ;

which provides us with an array, like:

0.0061271   2.1103472

The first value is m, the second is b.  Now we apply y=mx+b:

TrendLine = EQ(1) .* yr + EQ(2)

Now you can graph the trenline, with the original data:

plot(yr, AnnualTemps, yr, TrendLine)

gistemptrend

Looks ok to me. (I also note that even with the so-called “cooling since 1998/2000/2002/cherrypick”, 2008’s average temperature is almost 0.2DegC higher than the linear trend for the last 129 years..)

How Not To do Climate Stats

This is where the higher-degree polynomial equations come in. A high-degree polynomial can easily be made to fit a curve, but that doesn’t particularly mean anything, unless a high-degree polynomial cause can be hypothesised, that matches the trend. I don’t know of any that can.

All this was recently news, because the Australia published a piece of stupid masquerading as climate science.

Anyway, I want to show you how to do that same kind of stupid (albeit with 129 year data, not 30). You can try it with the last 30 if you like. Or with the last two. I don’t care, just don’t be surprised by the results, because they don’t mean anything.

So, we want a sixth-degree polynomial, that best fits the data we have. In other words, we want something like this:

y = rx6 + qx5 + px4 + ox3 + nx2 + mx + b

And we need to find r, q, p, o, n, m, and b. Again, we do it with polyfit(), this time with 6:

EQ = polyfit ( yr , TempReal , 6 ) ;
and we get something like:

1.3740e-16 -7.9135e-13 1.5165e-09 -9.6503e-07 -1.9859e-09 -2.5545e-12 -2.6291e-15

You might point out that these numbers are so small that they are ridiculous. To that, I’d reply: Good point.

Anyway, on with the stupidity, let’s whack those numbers into the above equation:

TempPoly6=EQ(1).*(yr.^6) + EQ(2).*(yr.^5) + EQ(3).*(yr.^4) + EQ(4).*(yr.^3) + EQ(5).*(yr.^2) + EQ(6).*(yr.^1) + EQ(7);

I hope that makes sense, it took me a while to get it.

Now we can graph it, along with the real data, and the linear trend line:

plot(yr, AnnualTemps, yr, TrendLine, yr, TempPoly6 );

gistemppoly6

Nice, huh? Now, any sane person would see without any stats education would see that an think: yep, that’s a pretty good match. Looks like a good fit to me.

But you already know it’s stupid, so you should be looking at it with even more critical eyes than usual. One of the best ways to be critical in a situation like this is to step back, and take a wide view. So let’s see how those trend lines look if we add another century on each end: 1700 to 2100.

to do this in Octave, you need to stretch the “years” component first, then just put it back into the same equations:

yr = [1700:2100]‘

The ‘ is important, it makes the vector matrix vertical. Now you can just hit the up-key to access the same lines as before:

TrendLine = EQ(1) .* yr + EQ(2)

TempPoly6=EQ(1).*(yr.^6) + EQ(2).*(yr.^5) + EQ(3).*(yr.^4) + EQ(4).*(yr.^3) + EQ(5).*(yr.^2) + EQ(6).*(yr.^1) + EQ(7);

Then just run the last plot command again, (yr has changed length though, so go back to the GISSTEMPdata for the years for the original data:

plot(GISTEMPdata(:,1), AnnualTemps, yr, TrendLine, yr, TempPoly6 );

gistemppoly6long

That’s right. By 2100, temperatures won’t be 2DegC warmer, nor 4… Nope, it’s gonna be 21 degrees centigrade - 7 degrees warmer. And the “medieval warm period”? Didn’t exist. Was actually an ice age.

Disclaimer

I’m not a statistician, though I do hope to be doing stats at Uni this year. I’m reasonably sure this is all correct, though I haven’t used this kind of maths since high-school, more than half a decade ago. I learned what I now know in Octave in the last 2-3 days, so there might be better ways of doing this, I don’t know. I’d appreciate any corrections, if they’re needed, and feedback is always welcome.

I’d also appreciate any help on running a LOESS filter on the data. I don’t understand the maths except in the vaguest terms (moving polynomial average, or something?), but it seems like it applies a very useful smoothing, although it doesn’t provide any kind of future prediction the way a linear trend does (ie. in a very limited way).

ATTACHMENT:

gisstempdata.m - THIS IS A PLAIN TEXT FILE, NOT AN ODT. rename it to gisstempdata.m to use it in octave/matlab.

Until now, the technology hasn’t been available to obtain fine-scaled, precise measurements of CO2 in the atmosphere. But the launch next year of two carbon-detecting satellites, NASA’s Orbiting Carbon Observatory and the Japanese Greenhouse Gases Observing Satellite, should soon help to fill in this knowledge gap, which is critical to establishing a reliable carbon accounting system. - Amanda Leigh Mascarelli

There’s more info on the NASA project at http://oco.jpl.nasa.gov/, and on the Japanese project at http://www.jaxa.jp/projects/sat/gosat/index_e.html

It amazes me that this isn’t getting more attention already. It’s going to mean a massive increase in our ability to account for carbon and other greenhouse gas emissions and uptakes. Seems to me that these projects should be WAY more exciting than the Large Hadron Collider, for example, since they will so directly effect the science around one of the most important and controversial issues of this… century? millenium?

It also strikes me that images extrapolated from the data could be strikingly beautiful - in a similar way to the “earth by night” photos. Obviously carbon concentrations won’t be so strictly confined as light sources, and the images will obviously be false colour (since CO2 is invisible). But other effects, like those of coriolis winds and ocean and forest carbon sinks would be great to see in action, especially with changes over the seasons.

Reference:

Leigh, A. et al. (2008, December 18). What we’ve learned in 2008. Nature Reports Climate Change. Retrieved January 12, 2009, from http://www.nature.com/climate/2009/0901/full/climate.2008.142.html.

There was such an uproar in response to this hilariously crap PR campaign, that America’s Power has killed it. It’s not on facebook, and it’s not even on their own website any more. Fucking classic. That PR agency won’t be popular next year. America’s Power’s has made some weak excuse for killing the little bastards. “Behind the plug” - so that’s what it was? looks like it’s been pulled good and proper.

Anyway, there’s one fragment of it left on the ‘net, if you still want to check it out: Google Cache of the Facebook page. The comments don’t have quite the vehemency of the other one that were there when I checked last time.

That’s right, Rudd’s targets of 5% by 2020, from 2000 levels mean almost nothing.

According to the UN(1), Australia’s 1990 emissions totalled 416.2Mt. In 2000 it was 495.2Mt - an increase of ~19%.

A 5% cut from 2000 levels is approximately a 13% increase from 1990 levels. Even a 15% cut from 2000 levels is a 1% increase on 1990 levels.

We need to be dramatically cutting our emissions, not increasing them.

The targets the government has announced fall within Garnaut’s 550ppm range, even though the IPCC and other scientific reports are saying that even a 450ppm target will fall short of saving the Great Barrier Reef, Kakadu, and result in eventual melting of a large percentage of the world’s ice caps and glaciers.

Rudd and Co, in the lead up to the election, promised swift action on climate change. So far, apart from some loose symbolic gestures, Labor hasn’t done anything that the Liberal Party wouldn’t have been forced to do anyway. Weak.

Some Rising Tide crew slammed Rudd during his speech, shouting “NO!” as soon as he announced the target, and then continuing to interrupt him until they were dragged out. Some Brisbaners stages an office occupation of Rudd’s Brisbane office during the speech too.

At least there was some decent media - nearly everyone slamming the government, even the Oz, in an online opinion piece. SBS had decent coverage of the protests. Congratulations on NBN (NineMSNs version wasn’t quite as good) TV News in Newcastle too, for some really good pieces on the announcement. TV news reporting is rarely as balanced as that.

(1) http://unfccc.int/resource/docs/2008/sbi/eng/12.pdf (p. 16)

CSS template-based layouts, or something like them, have been a long time coming. John Resig has blogged about them recently, echoing the attitudes of a few people, it seems. I generally agree: this looks great, and will be a vast improvement for HTML+CSS web development: finally HTML document structure will be largely separate from visual layout. This is something that CSS grids/tables completely fail to do - divs still have to be in row>column order: a semantic change from HTML tables, and nothing more, and they still aren’t supported by ie yet anyway (EDIT: Xanthir points out below that I was confused: CSS3-grid is actually a completely separate proposal to tables, and it’s basically the same as what I suggest here, albeit without the ability to name the grid).

But…

Yep, of course there are a few things I’m concerned about (and as there should be - if there weren’t I’d know I hadn’t been looking hard enough). First, there are a few minor points (Disclaimer: I may have missed or misunderstood parts of the spec. Feel free to correct me): (more…)

When I’m reading about climate change in public forums like the internet, or newspapers, I expect to see denial argments all over. Usually, they’re the same old shit, that’s been roundly debunked by numerous people. So it’s a pleasant suprise to find new arguments - it gives you something to think about.

This one really was suprising though: Richard Lindzen is well known for being a good debater, and well-read. He’s one of the last deniers that mainstream seems to accept. So it’s a suprise that I haven’t seen this particular arguement before: usually these things get picked up like smallpox. This article’s actually a bit old (2004), so I’d expect it to be well spread around the internet by now, but it isn’t.

In the 2004 article/interview by Marc Morano for CNSNews.com, Lindzen says: “Although there is [Arctic] melting going [on] now, there has been a lot of melting that went on in the [19]30s and then there was freezing.”

Ok, so the basic appeal of the argument - it’s happened before, so who cares if it’s happening now? - has appeared in many denial rants before, but this one is very specific, and it isn’t documented in any of the other major lists of old denier arguments.

The second part of the suprise is that it’s so damn easy to debunk. You don’t need to be a scientist for this one. You just need to go to the NOAA Arctic website (see the updated graph). Ok, so there was melting from 1934-40, but there was roughly the same amount of ice INCREASE in the year before that trend started. If any sane person looked at that graph, they’d immediately see that the sea ice extent trend is pretty much static up to about the 50s or 60s, and then the trend swings down dramatically, dropping from a relatively constant ~13.5m sqkm, down to about 11.5-12m sqkm over the last decade.

Anyway, the article is generally crap, nothing that hasn’t been talked about thousands of times since. I just thought that this specific bit should be pointed out. I’m not going to go seeking it, but I’d be interested to know what Lindzen thinks about that graph, and whether NOAA is part of the whole conspiracy or not. I’d also be interested to hear why he thinks that fossil fuel companies, with all their billions of dollars of annual profit, haven’t been funneling some that money into climate science to see if they can get a different result - obviously if it could be done, the rewards (of not having to deal with environmental regulation) would be significant…

I don’t usually like spruiking for the corporate media, but channel 7 is doing something good with their Sunrise solar panel petition. I don’t make any comment on the rest of what channel 7 does - I usually avoid it like the plague.

But they’re right, a means test on the solar rebate scheme is bloody stupid. There are lots of people out there who want solar panels, but for the rebate, you have to have the money upfront. Not many people on a median wage (~$25,000/annum) have thousands of dollars just lying around. If they have a mortgage, neither do people on an average wage (~$57,000/annum). So means testing the rebate has already meant a massive drop in household solar installations(1).

But a means test could be a good thing. If the government wants to do something that has a real impact, and is actually equitable for people of all socio-economic classes, it should means test. But don’t means test down, means test up. For the rich, leave it as it is, or perhaps leave it at $8000 for households on $100k/annum or what ever other arbitrary measure you want, and reduce it in small increments as wages go up. For everyone else, offer an increasing rebate as wages go down, and a low-interest (0%, inflation adjusted) loan>here was a loan something like this in the budget this year (not sure how “low interest”), but only for solar hot-water, and only for a couple of hundred thousand homes(2). Expand this to include all homes and photovoltaics, and by all means means-test the loan.

A good idea might be to cap the loan at a calculated value - say enough to buy a system that could power a small family house - and then offer normal, or slightly lower than normal interest rates for any money needed over that cap. That would allow even mcmansions to go solar, but without encouraging excess energy consumption.

Obviously this solution wouldn’t be perfect, but it would sure be better than what’s currently on offer. The main thing at this stage is to wean ourselves off fossil fuels at quickly as possible. And that means spending big now - it won’t seem like much of a cost later, especially when it pays itself off in a few years anyway.

  1. Rethink solar rebate, industry urges Govt. (2008, May 17).ABC News. Retrieved June 30, 2008, from http://www.abc.net.au/news/stories/2008/05/17/2247721.htm.
  2. Simon, D. (2008, May 14). “Green” budget passed and pasted in Australia. Retrieved June 30, 2008, from http://de.indymedia.org/2008/05/217318.shtml.

After months of wondering why Americans are always complaining about petrol prices, I finally figured out why.

This might seem obvious to some, but the solution everyone seems to come up with seems pretty stupid to me. To start with, let’s compare fuel prices in a few countries (unleaded fuel, at the bowser):

  • US fuel price: around $4/gallon (1)
  • Australia: about $1.65/L
  • UK: about £1.18/L (2)
  • France: about €1.40/L (3)

Just to compare, let’s change that to US$/Litre (1 US gallon  = 3.7 litres, Exchange rates from http://www.xe.com/ucc/):

  • US: $1.08/L
  • Aus: $1.57/L
  • UK: $2.32/L
  • Fr: $2.19/L

Of course, these calculations could be off a fair bit, but with a difference like that, the error couldn’t be very sginificant.

From that, you can see why I was confused: Americans have some of the cheapest fuel in the industrialised world. It certainly isn’t anything to scream about. In fact, with peak oil almost certainly hitting around now (The actual centre of the peak being somewhere between a couple of years ago, to perhaps a few years ahead), it more like something to just get used to. It certainly isn’t going to get cheaper for any significant period of time.

But then I realised that there was another factor: Wages. If americans are earning less than us here in Aus, then the fuel is obviously costing them relatively more. So let’s see average weekly wages for the four countries:

  • US: $600.80 (4)
  • Aus: $1008.10 (5)
  • UK: About £460 (from average yearly estimate wage of $24000)
  • Fr: ???

And compared to fuel costs:

country fuel cost
(100L)
weekly wage 100L as % of
weekly wage
USA $108 $600.80 18%
Australia $165 $1008.10 16%
United Kingdom £118 £460 25%

Which is obviously the reason why americans currently care more about fuel than australians. This is obviously going to be compounded by wage inequality - the average wage is a pretty stupid measure of income, because the richest few people make the average wage higher than the vast majority will ever earn. Looking at a median wage is a far better way to do it, and if that was done, and considering that america seems to have worst income inequality than most industrialised nations, that percentage, compared to australia would be much higher than it is above, both absolutely, and relative to the other countries.

But what about the UK? Why aren’t they going nuts about fuel prices? Even if their income inequality is far less that the US, they probably still have a higher fuel price compared to wages. The answer is obvious: they spend less money on fuel because they buy less fuel. There are two reasons for this: the UK is a more compact country than the US - people don’t need to drive as far when they do drive. But more importantly, both for its impact, and for its potential for change, is public transport. Most of the US, by all accounts, has a terrible, or even non-existant public transport service. New York has the metro, and San Francisco has it’s trams, but most other cities are designed almost exclusively for cars - in some it’s hard to even walk any where. When you’re forced to drive a car to get to work, school, or anywhere else, you’re going to feel the fuel crunch pretty hard.

Americans do have a fuel problem, but calling for lower prices isn’t going to help in the long run. Peak oil means that fuel prices are on a roughly exponentially increasing path - even if we knock 20 cents off now, it’ll only be a matter of months, a couple of years at the most, before it’s back where it was again. If you want a solution to fuel prices, then call for a decent minimum wage (the american minimum wage is far less than the australian minimum wage, and was even when the australian dollar was at US$0.55 a few years ago. Now it’s well under half). If you want to do something permanent about making transport cheaper, then call for real public transport systems, especially electricity driven public trasnport, like trains, trams, and street cars. That’s going to be just about your only livable way out of this mess.

Sources:

  1. http://tonto.eia.doe.gov/oog/info/gdu/gasdiesel.asp
  2. http://www.petrolprices.com/
  3. http://www.prix-carburants.gouv.fr
  4. http://www.bls.gov/news.release/empsit.nr0.htm
  5. http://www.smh.com.au/articles/2005/08/18/1123958181797.html

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