Wednesday, 25 February 2015

In the news?

The Australian has a story today about the head of the UN's Intergovernmental Panel On Climate Change (IPCC) who's resigned following sexual harassment charges.

Not surprisingly, I can find no mention of this event on the ABC. The Age reprinted a brief article from the Washington Post.

Climate chief quits over suit

Environment Editor
RAJANDRA Pachauri has stood down as chairman of the Intergovernmental Panel on Climate Change and been admitted to hospital as details of his ­alleged sexual harassment of a junior employee were tended to a Delhi court.
Dr Pachauri is embroiled in allegations of sexual harassment from a 29-year-old research analyst at the The Energy and Resources Institute he heads.
A Delhi court says Dr Pachauri cannot be arrested until ­tomorrow, but the woman at the centre of the allegations has started recording her statement in camera.
According to Indian media, the lawyer for the alleged victim said the instances of sexual harassment “were so many that she will resume recording her statement tomorrow also”.
Lawyers for Dr Pachauri describe the complaint as “false, baseless and motivated”.
The IPCC last night said it had appointed vice-chairman ­Ismail El Gizouli to act in Dr Pachauri’s place.

What is Climate Science? continued

In my last post, I started to look at what comprises the modern phenomena of “climate science”. The definition I used had three main points:

1.      It’s a science:
2.      It’s about average conditions, not weather; and
3.      It’s about average conditions over time.

Average Conditions

Climate science is concerned with “average conditions”. We all know what average means.  “He’s of average height.” “I had an average day.” etc.

The “average” or “mean” is a term from the branch of mathematics called statistics.

So climate science is about using statistics to analyse various climactic conditions. Which conditions?

Some of the obvious ones are:

·         Temperature;
·         Wind speed and direction; and
·         Rain, snow, hail and other precipitation.

Some other, less obvious ones include:

·         Clouds of various types, shapes and configuration;
·         Storms; and
·         Total solar irradiance, the amount of the sun’s energy at various wavelengths, that hits the Earth.

The biggie, of course is temperature. We’re not told to be worried about polar bears getting wind burn, or getting fur-rot from too much rain. Temperature’s the problem, supposedly.

One of the things left out of the definition above is that all of these conditions can vary at different places on the planet’s surface. Obviously the temperature’s different at different places and, of course, at different times.  There’ll be more about that in the next section.

While climate science deals with averages, it also deals with other statistical measures like minimums and maximums, as in “It was the hottest/ coldest/ wettest/ driest/ cloudiest/ clearest Tuesday afternoon in February since last month”.  Maximums and minimums can also be treated with appropriate statistical tools.

Statements about averages, minimums, maximums and other statistical quantities can help us understand “the big picture”.  They can also confuse and, in the worst cases, deceive.

The most important idea in statistics is this:

Everything we measure has an error.  The temperature in my office wasn’t 29 degrees Celsius a moment ago. It was somewhere between a little less than 29 degrees and a little more than 29 degrees. Thermometers, and in fact all the stings we use to measure, have errors in their mechanisms that mean there’s always a bit of error or uncertainty in the measurement.

There are some statistical tools that allow us to estimate how much error is present in a measurement or set of measurements.

Over time

The third qualifier in the definition of “climate science” is that the average conditions are studied “over some time period”.

Sticking to the temperature example we might ask “What’s the temperature, where I’m standing, now?”, meaning over a very short period of time, say, a second.

Another, quite different question would be “What’s the average temperature of my office over the last year?”

I could actually answer this with some confidence if I got an electronic thermometer, connected it to my computer and got a reading of temperature every second for a whole year.  That’s 365 x 24 x 60 X 60 = 31,536,000 seconds and, of course, the same large number of measurements.

To find the average I’d just add up the 31,536,000 measurements and divide by 31,536,000. (Of course, I’d get the computer to do the adding and dividing.)

I would certainly get a number.  No doubt about that.  How accurate would it be?  That’s a topic for another post.

I could simplify this whole thing enormously by just measuring the temperature once or twice per day. Maybe I could measure it at midnight one day and noon the next or maybe whenever I got up or went to bed. I wonder if that would affect the uncertainty or accuracy of my measurement.


In summary, then, “climate science” is the study of the average values of conditions like temperature across varying periods of time.

In order to hypothesise an effect, like “Humans are causing global warming by burning fossil fuels.” We obviously need to make a before and after comparison.

Breaking the question down, we can ask:

“What was the average temperature of the Earth before wicked humans started burning fossil fuels?”

“What is the average temperature of the Earth now?”

“What’s it likely to be in one month?

“What’s it likely to be in one year?”

“What’s it likely to be in ten years?”

“What’s it likely to be in one hundred years?”

“What’s it likely to be in one thousand years?”

You get the idea.

Take note of the difficulties with all this:

·         Thermometers have built-in errors that cannot be gotten rid of;

·         We’re asked to measure the average temperature of the planet, but we only have thermometers in a relatively few places, mostly in North America.  What do we do about all the places in between?

·         How do we determine what the average temperature of the Earth was one hundred years ago? There were thermometers back there, but how accurate were they?

·         How about one thousand years ago, before the invention of the thermometer?

It appears to me that “climate science” has set itself an impossible task.

Sunday, 22 February 2015

What is Climate Science?

We're constantly bombarded with claims that the Earth is in terrible danger from the trauma of human-induced (anthropogenic) global warming.  We' told "the science is settled." and this is based on the opinions of "climate scientists".

So what is “climate science” and who are “climate scientists”?

Many universities now offer programs in “climate science”. The University of Iowa in the US is one.  Their definition of climate science is fairly typical and is shown below:

“Climate science is distinguished from the more general discipline of atmospheric science or meteorology by its emphasis on climate as opposed to weather. Climate science is the study of average conditions over some time period, whereas meteorology is the study of actual events.”

The definition goes on to quote Mark Train who famously said “Climate is what we expect, weather is what we get”.


This definition and those like it, distinguish between “climate” and “weather”.

Weather is what we experience every minute of every day as in “I got caught in the hail storm. What s****y weather.”

Climate science, we’re told is the study of weather conditions over some period of time.

Let’s look at the words one at a time.


Science is supposed to follow the scientific method that we all learned about at school. It goes something like this:

1.      Conduct a bunch of experiments and make a bunch of observations about some aspect of nature.  For example I might observe all of the dogs in two particular houses in Cooloongatta Drive, Tyers and note that all three of them are Cocker Spaniels;
2.      Based on these observations, form a hypothesis (educated guess). I might hypothesise “All dogs in Cooloongatta Drive are Cocker Spaniels.”;
3.      If the observations are repeated many times and are always consistent with the hypothesis, then it might be elevated to the status of a theory; but
4.      If at any time an observation if found to be inconsistent with the hypothesis or theory, then all bets are off and the idea must be adjusted or discarded. As soon as I see a Labrador on Cooloongatta Drive, I have to throw away my, admittedly stupid, hypothesis.

Albert Einstein’s reaction to the 1931 book One Hundred Authors Against Einstein was: “If I were wrong, then one would have been enough!” Once a theory is falsified, then all bets are off and it’s back to square one.

A few other rules of the game:

·         Scientists have to report ALL observations, not just ones that confirm their theory. Failure to do this is called “cherry picking”, a euphemism for “cheating”.
·         Scientists have to LOOK for observations that might falsify their theory. If they don’t do it themselves, other scientists need to do it for them; and
·         The experiments leading up to a hypothesis or theory need to be available to other scientists for analysis and need to be repeatable.

Noted physicist Richard Feynman says all of this far better than I can an so here’s a link to a video: 


“It doesn't matter how beautiful your theory is, it doesn't matter how smart you are. If it doesn't agree with experiment, it's wrong.”

You can read more quotes from Richard at Quotes from Richard Feynman

In later posts I will look at things like the world temperature record and the details of the hypothesis of human induced global warming in term of the scientific method.

In the next post I’ll talk about the other two parts of the definition:

1.      Average conditions; and
2.      Average conditions over time.