The BBC Horizon programme on ‘Global Weirding’
Horizon say: “Something weird seems to be happening to our weather – it appears to be getting more extreme.
The BBC reports:
Dame Julia Slingo, Met Office Chief Scientist, said the variable UK climate meant there was “no definitive answer” to what caused the storms. “But all the evidence suggests there is a link to climate change,” she added. “There is no evidence to counter the basic premise that a warmer world will lead to more intense daily and hourly rain events.”
“We have records going back to 1766 and we have nothing like this,” she said. “We have seen some exceptional weather. We can’t say it is unprecedented but it is exceptional.”
So what constitutes exceptional weather?
Paul Homewood has analysed the figures extensively and those suggest that for the UK, the weather is doing pretty much what it has always done. His blog is available at http://notalotofpeopleknowthat.wordpress.com/
As a manufacturing engineer I was introduced to the wonderful world of control charts so I have constructed these to see if our current winter UK rainfall was exceptional.
The ASQ (American Society for Quality) suggests these criteria for an out of control process:
- A single point outside the control limits.
- Two out of three successive points are on the same side of the centreline and farther than 2s
- Four out of five successive points are on the same side of the centreline and farther than 1s
- A run of eight in a row are on the same side of the centreline.
- Obvious consistent or persistent patterns that suggest something unusual about your data and your process.
When we look at the graphs below we see that in 2014 we have one point outside the Upper Control Limit, but looking at the previous years we see that the system was very much in control, the rainfall figures bouncing around the average, so is the Met Office basing its comments on a single data point? The figures also suggest that the period 1909 to 1930 was one of the most consistently wettest periods.
Roman Roads, A Simple Surveying Technique.
For many years I travelled the south of England in my work as a consulting engineer often on roads, that used as their base, the roman road system. At one time my base was in Chichester and I would often take the opportunity to walk on parts of the Stane Street. I, like many others, admired the skills of the Roman Engineers in laying out their roads and often wondered how they managed to layout such straight roads and know the directions from one town to another. My interest was recently re-kindled when I watched the TV programme with Adam Hart-Davis, “What the Romans Did For Us”, which suggested a technique using the groma’ assumed by many writers as the method used by the Roman surveyors. The drawback, as Adam demonstrated, was that it would have been extremely slow and tedious to use.
I thought again about how the Roman surveyors could have been able to get their bearings with such accuracy. Here I propose a method which would have been quick, easy, and well within their capabilities. I am not a historian so no doubt many who have professionally studied Roman roads may want to take task with my assumptions, however, all writers seem to agree that there is no record of how the Romans surveyors laid out their roads so there is no reason to suppose that they did not use this method. The proof would be to try this method in the field and see what problems were met.
We know the Romans could make accurate measurements of distance across country by witness of their mile posts on their roads. They also used an Hodometer to measure distances. This was a wheeled instrument that dropped pebbles into a container to count the revolutions of a large wheel. In the planning of the roads the Hodometer would almost certainly not have been used, as measuring distances along an undulating course would not have given an accurate determination of the straight line distance between two points. A surveyor’s method would be required. The Romans had knowledge of the Greek’s surveying instrument called the dioptra that could measure angles. This was a sophisticated instrument invented by Hero of Alexandria and similar to our modern theodolite. It is described by M J T Lewis in his book, Surveying Instruments of Greece and Rome. Also an excellent overview of Roman surveying methods can be found at:
Dr. Lewis, however, has kindly pointed out to me that there is no evidence whatever – whether in the Corpus Agrimensorum, which is a large collection of texts specifically on surveying, or anywhere else, that the dioptra was ever used in the western empire. To my mind the fact that we do not have any written record of how the Romans laid out their roads would not preclude the undocumented use of the dioptra in laying out their roads. On the assumption that they did not use the dioptra all they would need is the method of duplicating the angle between two sighting lines. For this they could use either rods to mark the sight lines or a simple plane table. They would also need some accurate means of measuring the distance between two points from which they would take their sight lines. For this they would use rods of a known length as described by various writers.
The Romans would have been able to locate due North or due South with some accuracy. My first thoughts were that they used Polaris, the pole star, however in my rush to get my ideas down on paper I forgot that Polaris would not have been suitable to determine true north as it was not in the position it is today due to the movement of the earth’s axis – the precession of the equinoxes] Dr. Lewis kindly corrected me. The Romans presumably knew the stellar methods of the Egyptians to determine true north and we know that sun dials were very popular in Roman times so they could easily locate due south. It would therefore have been easy for them to a north-south line by use of a ‘gnomon’, a simple pole placed to determine when the shadow of the sun is shortest, i.e. at midday when it is due south. They also used the ‘groma‘ to survey and determine accurate right angles.
Let’s plan the road from Chichester to London, NOVIOMAGVS to LONDINIVM known by us as Stane Street.
For the sake of this illustration I will assume just 3 sites between the two towns. From their general knowledge of the country side the Roman surveyors would have known from their army and scouting parties the general direction that the road would have had to follow and of any prominent features along the route. e.g. hill forts, burial mounds and features like Stonehenge.
Let’s start from Chichester. As he looked north towards the hills of the south downs, the surveyor would have known the approximate point on the hills that the soldiers would have taken as they descended down to Chichester. If there was a natural feature he would note it, or he would arrange with his helpers to start a fire at some convenient point on the hill on the days he wanted to survey. If the surveying was to be carried out on a calm day, then a smoky fire would have been useful, at night a brazier or beacon would be lit.
He lays out his north south line using two poles. At some point on that line he then sets up his plane table or uses another pole to sight to his marker/feature on the hill. He can now determine the angle between due north and his feature/fire.
Using his gromatici, [rod men], to measure the distance, the surveyor sets up at another point due west or east, a known distance from the first where he again lays out a north-south line and determines the angle to the feature/fire on the hill. Note he doesn’t need to know the actual measurement of the angles, he just has to be able to reproduce them. He now has a base line of known distance and two angles.
There will be a number of good sighting locations at the top of the hills between London and Chichester. For instance from the top of Bignor Hill.
He repeats this process at each of his features/fire sites. He can now reproduce the measurements using a scaled base line to produce similar triangles. Note the scaling can be carried out using a large surface. Typically we would think this would be done on paper but some writers suggest the surveyors would use a large floor with moveable objects to mark the observation points and the various obstacles. For greater accuracy the plot can be made in a large field. Alignment with due North would be required.
He will then get a result like this, when he can then produce a straight line to join the two towns and determine the angle from due north or south that he needs to plot his road from Chichester to London.
In the case of Stane Street, the road starts from the south end of London Bridge apparently directly aligned on Chichester’s East Gate, however the Roman surveyors diverted the road at various points to take into account the natural obstacles and the suitability of the ground to support a road, and the actual layout of the road is approximately:
A good account of the needs to vary the route of the road can be found in the book:
“An illustrated history of Roman roads in Britain by David E. Johnston”
copyright Adrian Kerton 2005
Stonehenge – The Car Park Post Holes
The debate about astronomical alignments at Stonehenge has continually raged between the archaeologists and the scientists, the archaeologists often relying on their opinion that the sighting lines through the trilithons and other stones are too short to provide accurate markers of the sun and moon alignments claimed by the scientists.
In his book The Astronomical Significance of Stonehenge, C. A. Newham investigates the three car park post holes and concludes:
“These post holes are unique for several important reasons, in my opinion these can be regarded as the most positive astronomical discovery yet made at Stonehenge.”
The sighting lines from the station stones and heelstone to the post holes:
“align on sun and moon settings with an extreme accuracy made possible by their considerable distance”
“the direction of the alignments is positive and cannot be regarded as reversible”
English Heritage ran radio carbon datings on the post holes and concluded:
“all of these determinations fall into the eighth or late ninth-millennium BC. They cover a period of about one millennium and so it cannot be established whether these features, containing upright pine posts, were exactly contemporary and ever all stood together, but they are certainly Mesolithic”
And then continues:
“and not related to the main Monument.”
Personally I side with Newham, but no doubt the archaeologists will never abandon their beliefs that ancient man was ignorant and incapable of advanced scientific thought, and in depth solar and lunar alignments, particularly in the eighth millennium BC. One archaeologist put forward the explanation that the posts must have been totem poles, anything it seems to deny the best fit facts as described by Newham. I questioned a TV archaeology personality who also rejected the hypothesis that Stonehenge should be now considered to date some 4000 years earlier than currently thought.
The station stones were part of the earliest features of Stonehenge so their alignments to the post holes suggests that they are also of the same era. Perhaps advanced archaeological/scientific techniques will one day settle the argument.
Climate Change and the Earth’s Magnetic Poles,
A Possible Connection
Author: Kerton, Adrian K.
Source: Energy & Environment, Volume 20, Numbers 1-2, January 2009 , pp. 75-83(9)
Publisher: Multi-Science Publishing Co Ltd
Many natural mechanisms have been proposed for climate change during the past millennia, however, none of these appears to have accounted for the change in global temperature seen over the second half of the last century. As such the rise in temperature has been attributed to man made mechanisms. Analysis of the movement of the Earth’s magnetic poles over the last 105 years demonstrates strong correlations between the position of the north magnetic, and geomagnetic poles, and both northern hemisphere and global temperatures. Although these correlations are surprising, a statistical analysis shows there is a less than one percent chance they are random, but it is not clear how movements of the poles affect climate. Links between changes in the Earth’s magnetic field and climate change, have been proposed previously although the exact mechanism is disputed. These include: The Earth’s magnetic field affects the energy transfer rates from the solar wind to the Earth’s atmosphere which in turn affects the North Atlantic Oscillation. Movement of the poles changes the geographic distribution of galactic and solar cosmic rays, moving them to particularly climate sensitive areas. Changes in distribution of ultraviolet rays resulting from the movement of the magnetic field, may result in increases in the death rates of carbon sinking oceanic plant life such as phytoplankton.
Keywords: MAGNETIC POLES; DRIFT; CLIMATE; COSMIC RAYS
Document Type: Research article
Although correlation does no prove cause, there is a significant body of evidence in paleomagnetic studies linking aspects of the Earth’s magnetic field with climate.
Here are 3 of the graphs from the paper which you can download as a pdf below. I would be grateful for any comments.
I am indebted to Professor Jan Veizer for his help and guidance in writing my first scientific paper.
Since the paper was published I am indebted to Dr. Simon Bray who ran the Spearman Pearson Product Moment test on my correlations.
Dr Simon Bray, Senior Teaching Fellow, School of Biological Sciences, Visiting Researcher
Centre for Environmental Sciences, School of Civil Engineering and the Environment
University of Southampton
1. Northern Hemisphere N. Pole Deviations 1. For correlation between Lat North and Anomaly, values are: R = 0.794. P = <0.001 (Highly significant). Data were normal – correlation was Pearson Product Moment method. Polynomial regression at 2nd order gave Rsq value of 0.7024 – see Figure 1
2. For correlation between Long West and Anomaly, values are:
R = 0.839. P = <0.001 (Highly significant). Data were normal – correlation was Pearson Product Moment method.
Polynomial regression at 2nd order gave Rsq value of 0.708 – see Figure 2
3. For correlation between Long West normalised and Anomaly, values are:
R = 0.839. P = <0.001 (Highly significant). Data were normal – correlation was Pearson Product Moment method.
Polynomial regression at 2nd order gave Rsq value of 0.708 – see Figure 3
Note same values for regression and correlation as unnormalised – see fig 2.
4. For correlation between Lat North normalised and Anomaly, values are:
R = 0.792. P = <0.001 (Highly significant). Data were normal – correlation was Pearson Product Moment method.
Polynomial regression at 2nd order gave Rsq value of 0.698 – see Figure 4
Note values for regression and correlation very similar to unnormalised (correlation mildly less, see Fig. 1)
5. Global Tem Geomagnetic N. Pole Deviation
For correlation between Long West and Anomaly, values are:
R = 0.741. P = <0.001 (Highly significant). Data were normal – correlation was Pearson Product Moment method.
Polynomial regression at 2nd order gave Rsq value of 0.8391 (very good!) – see Figure 5
6. For correlation between Lat North and Anomaly, values are:
R = 0.880. P = <0.001 (Highly significant). Data were normal – correlation was Pearson Product Moment method.
Polynomial regression at 2nd order gave Rsq value of 0.7848 – see Figure 6
7. For correlation between Long West Normalised and Temp, values are:
R = 0.739. P = <0.001 (Highly significant). Data were normal – correlation was Pearson Product Moment method.
Polynomial regression at 2nd order gave Rsq value of 0.838 – see Fig 7 (correlation and regression very slightly less than unnormalised – see Figure 5).
8. For correlation between Lat Normalised and Temp Anomaly, values are:
R = 0.882. P = <0.001 (Highly significant). Data were normal – correlation was Pearson Product Moment method.
Polynomial regression at 2nd order gave Rsq value of 0.7892 – see Figure 8 (slightly better than unnormalised – see Fig 6)
Out of curiosity I downloaded the station data from the Met Office Website for Oxford
This shows the average temperature that Oxford has enjoyed. You can see the slope of the increase will be very dependent on start and finish years. 0.0077 deg c per year doesn’t seem a lot!
Here is the difference between the above average temperatures for the year compared with the Met Office released CRU data for Oxford. I have asked the Met Office to check my calculations.
The CRU data available only covers the years 1900-1980
The major deviations are for the years 1978, 1979, 1980.
UK Wind Power Generation for 3rd quarter 2010
The ten years with the hottest months from the Met Office Station Data.
Order of maximum temperature
Oxford back to 1853
2006 1983 1995 1911 1921 1976 1868 1947 2003 1874
Stornaway back to 1873
1899 1947 1997 1880 1955 2006 1933 1955 1976 1901
Durham back to 1880
2006 1995 1887 1947 1983 1975 1989 1901 1940 1990
Sheffield back to 1883
2006 1975 1983 1995 1976 1947 1921 1934 1995 1887
Eskdalemuir back to 1911
2006 1947 1955 1983 1989 1995 1975 1976 1934 1940
From the Met Office 19 June 2013
The UK Met Office recently held an emergency meeting:
“Weather and climate experts from across the UK came together at the Met Office’s HQ in Exeter today for a workshop to discuss the recent run of unusual seasons in Europe.”
“Today’s included sessions which looked at the weather patterns and their potential causes in three recent seasons – the cold winter of 2010/11, the wet summer of 2012, and this year’s cold spring.”
From personal experience and a casual glance at the Met Office temperature figures it struck me that the variations seemed pretty much what we expect from our UK weather.
As a manufacturing engineer I was introduced to the wonderful world of control charts so I decided to construct these for the cold winter of 2010/11, the wet summer of 2012, and this year’s cold spring.
For those not familiar with a control chart an example is deciding if variations in a machine’s output is just normal or if the machine needs adjustment.
To decide if everything is OK the Mean and Standard Deviations of the data are computed and the upper and lower control limits are calculated and plotted on the chart of the data. The control limits are the mean plus and minus three times the standard deviation. These limits represent the edges of the normal distribution curve, so anything outside these limits is considered abnormal.
As you can see below the variations are for the most part well within the control limits, suggesting that he weather process is normal and we don’t have anything to worry about.
When looking for an out of control process here are some simple tests
[These are taken from ASQ.org, other organisations have similar rules ]
1. A single point outside the control limits.
2. Two out of three successive points are on the same side of the centerline and farther than 2 σ from it.
3. Four out of five successive points are on the same side of the centerline and farther than 1 σ from it.
4. A run of eight in a row are on the same side of the centerline.
5. Obvious consistent or persistent patterns that suggest something unusual about your data and your process.
If we apply these rules to the charts below what can we infer?
1. Yes, naughty Mother Nature is out of control at least once.
5. I would hazard a guess that from what we see the temperatures and rainfall can sometimes hit extremes but the pattern is normal and chaotic and that the recent experiences are just normal
Interestingly for rainfall it seems a high is followed by a low then a high then a low and this pattern repeats with only a few cases where a high is followed by another high though there can be considerable differences between the highs and lows.
So why did the Met Office call the meeting to discuss the unusual weather? For recent Spring temperatures we had a gradual rise and then one low instance, and again with the Winter temperatures the recent low only followed a gradual rise and the history suggests it is not unusual.
The simple statistics suggest we have nothing to worry about and the World Meteorological Organisation (WMO) requires the calculation of averages for consecutive periods of 30 years, so why did they panic with just a few years data?