Ignore the Executive Summary on Climate Change

Just released I told you so data for the Climate Change Camp comes in the form of the Global Humanitarian Forum's "Human Impact Report" (old joke - Are you a vegetarian? No I'm a humanitarian.).

This is being picked up as proof that climate change leads to death, disease, financial loss and premature baldness... okay maybe not that last one, expect that later; anyway as such it means we (meaning um the UN, the Government, Superman?) can start to legally sue polluters for all their evil evil nastiness.

It's not hard to deduce from the Executive Summary that starts off with the statement that

Science is now unequivocal as to the reality of climate change. Human activities, including in particular emissions of greenhouse gases like carbon dioxide are recognized as its principle cause.

And there I was thinking it was all the methane from those cows. Also good in that as "Science is unequivocal" anyone who thinks otherwise is by definition not using 'Science'.

The findings of report indicate that every year climate change leaves over 300,000 people dead, 325 million people seriously affected, and economic losses of US$125 billion. 4 billion people are vulnerable, and 500 million people are at extreme risk.

Guess we'd better do something then. But wait how did the report come to that conclusion, perhaps looking at that boring Notes on report methodology (pdf, 64 KB) that's so important it doesn't show up on the left hand menu or get translated to HTML format. Gee why would that be, you'd think they were trying to persuade people not to look at it.

Okay the first page essentially says they're looking at floods, tornadoes, determining which are attributable to climate change and using numbers of affected and dead as indicators. First page up and I've already got some questions 1) how are you determining which weather patterns are attributable to climate change and 2) You're using people as the indicator, thus a class 5 hurricane that blows over a deserted island doesn't appear but a class 1 that traps a bunch of school-kids does? Hmmm.

Second Page and the scary -

Basic reasoning behind methodology
The frequency and intensity of weather-related disasters is often associated with climate change in public debate and common perceptions.

Yes and I've been told cutting my hair will make it grow back thicker, doesn't mean that's correct.

In its Fourth Assessment Report, the IPCC found that weather patterns have become more extreme, with more frequent and more intense rainfall events,
more intense heat waves and prolonged droughts. However, there is not yet any widely accepted global estimate of the share of weather-related disasters that are attributable to climate change.

Ah subtlety thy name is GHF. Notice the implicit link there - weather is getting extreme, but we have yet to estimate how much is attributable to climate change, implying that there is a link. Remember kiddies shares can go down as well as up, in this case it might well be zero.

First of all, natural variability and socio-economic factors have an impact
on the frequency and scale of natural disasters. This means that the increase in weather-related disasters over the past decades cannot be entirely attributed to climate change... A comparison of the trend in weather-related disasters to the trend geophysical disasters can provide an indication of the share of weather-related disasters attributable to climate change.

Remember these points for later. Moving on to page 3 Basically this is where the data comes from and we're looking at a meagre 25 year time frame from 1980 to 2005

because there is robust data for this period and it is the period when it is assumed that climate change has started to have an impact

Again remember that for later. Why do I say meagre? Because in terms of world geography and climate it's a less than a blink of an eye. Next up is our first graph plotting Floods, Windstorms, and Earthquakes now these figures are relative which means if there were 100 earthquake disasters in 1980 and 150 in 1990 then the figure for 1990 would be 1.5 (okay not quite as they're also factoring in scale, but the principle's the same); why not use the figures directly? Well it just makes things easier and don't worry it doesn't affect the data. However the eagle-eyed among you will spot that the Windstorms data doesn't start at 1.0, as both Floods and Earthquakes do and would thus suggest 1980 is the relative point that's odd. Where's the start point for Windstorms? The dotted lines are trendlines and I'll deal with those in just a bit.

Onto page 4 and an explanation:

The share of weather-related disasters attributable to climate change in 2005 is calculated by comparing the number of weather-related disasters (floods and windstorms) with what the number would be if growth rate had been similar to earthquakes.

This confirms that point I wanted you to remember about comparing weather disasters to geophysical ones.

There now follows a quick discussion on trendlines for the non-statistically minded.

Trendlines are useful tools as they even out the peaks and troughs of data to show the underlying trend. So imagine I run a company making flibbets I can plot my profit data which may have seasonal variations, and I can use a trendline to show that despite the ups and downs profit is steadily increasing. This is good news for me.

Trendlines are also good at comparing data sets. So imagine I obtained the profit/loss data for a rival company that also makes flibbets I plot their trendline and see it to is rising, but not at an angle as sharply as mine. Again good news for me my profit growth is larger than my competitor's.

Finally trendlines can be used to show the effects of change. So why is my profit trend higher? Well in 1990 I introduced a new type of flibbet, must be that? Nope! What I can do is look at the trend line for both companies prior to 1990 then the entire trendline again. It may be that my profit rate was always higher than my competitor's and hasn't altered, which means my expensive new flibbet process hasn't altered anything (or may have staved off loss, who can tell?). However if the trendlines are different than all other things being equal I can assign the difference to the introduction of my new flibbet.

Okay everyone got that? Now the data here is comparing the Flood and Windstorms trends to Earthquake trends and stating that the difference is due to climate change. If you've followed the explanation on trends you may well have spotted the two problems already, the first main one being - is there a relationship between Earthquakes and Floods or Windstorms? What use would my flibbet data be if I compared it to tree growth data?

The second point harks back to that point I wanted you to remember about climate change starting in 1980ish (i.e. the equivalent of when I introduced my new flibbets). In exactly the same way I can only state that the data change is being caused by the introduced factor if I can show that there was a different change prior to its introduction. Do we get that data, does it even state that anywhere in the document? No it doesn't.

Finally back to the very first point I asked you to remember in that there are socio-economic factors to take into consideration. Imagine a tsunami hits a country and kills the peasant fishers along the coast - disaster but only few lives lost; so small disaster. Now imagine that the government uses the fact that the peasants have been swept out to turf them off the land and build a hotel and tourist resort along the same stretch of coast. Another identical tsunami hits but this time with a much larger loss of life - bigger disaster and shows up in our relative scale as a larger point. Is this attributable to climate change - nope. Just as if in 1980 everyone lived scattered in rural communities and in 1990 all moved to the city.

To an extent I can see why they'd use the Earthquake data to even these things out, but still no connection is shown between the data sets to justify this.

So we have a report stating links between climate and pollution without evidence being presented, just hearsay; and comparing data between two sets that doesn't span over a wide enough set of years and is not proven to be relatable in any way either.

And that's where I'll end because everything after that point about calculating disease, famine, or financial cost uses that data for it's 'these events are caused by climate change' and as presented the data appears suspect, so everything based upon it is also suspect.