Yet again, my websites and emails have been subject to another attack starting sometime before 10am and ending around 2pm. This time I’ve decided to report the incident to the police.
If anyone else is subject to such attacks, please report them to the police.
This will ensure such attacks are treated appropriately.
| Field summary for Q06 | |||
|---|---|---|---|
| How many years have you worked in science | |||
| Answer | Count | Percentage | |
| 1 year (1) | 81 | 3.26% | |
| 2 – 3 years (2) | 284 | 11.41% | |
| 4 – 7 years (3) | 315 | 12.66% | |
| 8 – 15 years (4) | 337 | 13.55% | |
| 16+ years (5) | 1452 | 58.36% | |
| No answer | 19 | 0.76% | |
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Just back from the Scottish parliament which I attending with Lord Monckton where we attended something called SPREEE. Here we heard three of their advisers starting with WWF.
I repeat: starting with WWF! What on earth are they doing advising the Scottish parliament? Not on how to bread pandas or haggis, but on energy policy! And what were these advisers saying? They were insisting that climate would warm 6C (as a result of Monckton’s questions) and not one of them cared at all about the effects on the hard pressed consumer as not one mentioned the cost to people in Scotland or the harm being done until I got the last question in.
And to cap it all, it was snowing – so I got in the mention about “children won’t know what snow is”.
I couldn’t believe it when the answer came back “it’s cheaper than it would have been if we hadn’t done anything”. Putting up fuel bills by the renewable stealth tax in a country with massive fuel poverty is “cheaper”.
And then I happened to be on the same train as someone else who had gone to the Scottish parliament. They worked for a charity called Energy Action Scotland who deal with fuel poverty.
Apparently 900,000 Scots are in fuel poverty. That’s an utter disgrace. In a country with oil and coal, 900,000 cannot afford to adequately heat their homes.
And what is the Scottish parliament doing on this wintry day? Taling about the real problems facing Scots or the delusional beliefs of the greenblob? They were pandering to the greenblob without a care for the thing that directly impact Scots and kills many of them.
| Field summary for Q05 | |||
|---|---|---|---|
| Have you worked in science for more than one year? | |||
| Answer | Count | Percentage | |
| Yes (Y) | 1050 | 25.41% | |
| No (N) | 3081 | 74.55% | |
| No answer | 2 | 0.05% | |
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I just love watching these high cost committee produced greenblobbiest videos from the pause deniers to see just how soon they start telling lies. And I did not have to wait long. After the 10s “I did media studies” type intro, the video failed … in 2 seconds flat … on the sixth word:
“Let’s not beet around the rapidly melting ice …”
All their money gone to waste – they can’t be pleased with the latest news:
I was reading Bob Tisdale’s blog Absolutely Amazing! A Climate Scientist Writes a Blog Post about… in which he discusses a post on unRealClimate, in which unRealClimate discuss Anthony Watts blog’s widget. (right)
And I was looking forward to seeing how they would replace the widget. Obviously it would turn from blue to red, their graph would highlight 1970-2000 and “hide the pause” afterwards, etc.
Time and again I hear nonsense from people saying climate signals are, or are not, “significant”, by this they suppose they mean “cannot be normal”. But they ignore the fact that in order to say whether or not something it abnormal, we must know what is normal. And they do not know what is normal but assume a model of “normality” which is totally wrong for the claimate. So I decided to write this explanation of 1/f climate noise to help explain the difference.
It’s often easier to see something that for someone to explain it. So it might help to have a look at the demo of 1/f noise I have at uburns.com (I’ve jokingly portrayed this as a “forecast” but it just generates noise similar to climate noise. Further info is on the about page. I’ve got some results showing how variance increases: Statistics of 1/f noise – implications for climate forecast. And I’ve even collected together a few examples of how 1/f noise causes errors in interpreting data even by sceptics: Natural habitats of 1/f noise errors.
Also for a wider perspective of how we need to know the underlying variation in order to know what is meaningful see: Lies, damned lies, and statistical significance of climate trends
Fig 1 so called “normal distribution”
The so called “normal distribution” shown right is arguably one of the worst concepts in the whole of mathematics and science. I suspect is the single biggest cause of the failure of climate academics to comprehend why they can’t predict the climate.
Continue reading
| Field summary for Q04 | |||
|---|---|---|---|
| Please tick any of the following areas where you have received formal post-school education or training | |||
| Answer | Count | Percentage | |
| Climatology (a05) | 282 | 5.04% | |
| Geology or other earth science (a01) | 893 | 15.97% | |
| Environmental studies (a02) | 663 | 11.86% | |
| Computer programming (a03) | 2251 | 40.27% | |
| Biology or other life science. (a06) | 737 | 13.18% | |
| Economics (a07) | 1057 | 18.91% | |
| Philosophy (a08) | 427 | 7.64% | |
| Physics /Chemistry (a09) | 1827 | 32.68% | |
| Mathematics (a10) | 1864 | 33.35% | |
| Engineering (1) | 2053 | 36.73% | |
| Architecture/Planning (2) | 239 | 4.28% | |
| Medical sciences (3) | 397 | 7.10% | |
| Arts/History/Languages (4) | 574 | 10.27% | |
| Business/Law/Accounting (5) | 1209 | 21.63% | |
| Education (6) | 407 | 7.28% | |
| Social Studies (7) | 221 | 3.95% | |
| Other | 572 | 10.23% | |
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I’ve been collecting a few interesting curves from the 1/f generator at uBurns.com and here is a selection showing the kinds of features that are typical of 1/f noise and which we regularly see being mistaken for “something”.
Note
First all references to “forecasts” is just my attempt at humour. It is 1/f noise, but such noise makes it impossible to forecast and it’s ridiculous to attempt to do so.
The plots are:
Habitat of error: IPCC report and almost every alarmist website.
A very common characteristic of 1/f noise is that there will appear long-term trends. These are just the coincidental juxtaposition of smaller trends which happen all to go the same direction, but they clearly confuse some academics who cannot understand that such trends are perfectly natural.
Across at uBurns.com, a slow trickle of people have been looking at the page giving me a total of 221 page views. So, I thought there was enough data to do some preliminary stats.
First to recap: the climatic temperature data has a 1/f frequency response showing that natural variation can be modelled by 1/f noise. So assuming all the variation is natural we should be able to model climate with 1/f noise. But little has been written on the statistics of 1/f so it is difficult to know how it will behave. So, I have created a simple 1/f noise generator at uBurns.com and am using this to get data.
To do this, I’ve split the 1000 or so data points of each trial into 16 “buckets” and recorded the average value and slope of each bucket for each trial.
The predictions I made were as follows:
As predicted the variance (sum of squares) of the 1/f noise (shown above in blue) increases with each successive “bucket” so that the increase is proportionate to the square root of the number of points (or in this case buckets). It’s not a perfect fit, but it looks like it’s heading that way. Continue reading
