Archive for the ‘Climate Change’ Category

Learning about weather

March 17, 2019

I have just completed a FREE! ‘Learn About Weather‘ course, and slightly to my surprise I think I have learned some things about the weather!

Learning

Being an autodidact in the fields of Weather and Climate, I have been taught by an idiot. So ‘attending’ online courses is a genuine pleasure.

All I have to do is to listen – and re-listen – and then answer the questionsSomeone else has selected the topics they feel are most important and determined the order of presentation.

Taking a course on-line allows me to expose my ignorance to no-one but myself and the course-bot. And in this low-stress environment it is possible to remember the sheer pleasure of just learning stuff.

Previously I have used the FutureLearn platform, for courses on Global WarmingSoil, and Programming in Python. These courses have been relatively non-technical and excellent introductions to subjects of which I have little knowledge. I have also used the Coursera platform for a much more thorough course on Global Warming.

So what did I learn? Well several things about about why Global Circulation Cells are the size they are, the names of the clouds, and how tornadoes start to spin. But perhaps the best bit was finally getting my head around ‘weather fronts’.

Fronts: Warm and Cold

I had never understood the terms ‘warm front’ and ‘cold front’ on weather forecasts. I had looked at the charts with the isobars and thought that somehow the presence or absence of ‘a front’ could be deduced by the shapes of the lines. I was wrong. Allow me to try to explain my new insight.

Air Mixing

Air in the atmosphere doesn’t mix like air in a room. Air in a room generally mixes quite thoroughly and quite quickly. If someone sprays perfume in one corner of the room, the perfume spreads through the air quickly.

But on a global scale, air doesn’t mix quickly. Air moves around as ‘big blobs’ and mixing takes place only where the blobs meet. These areas of mixing between air in different blobs are called ‘fronts’

Slide1

In the ‘mixing region’ between the two blobs, the warm – generally wet – air meets the cold air and the water vapour condenses to make clouds and rain. So fronts are rain-forming regions.

Type of front

However it is unusual for two blobs of air to sit still. In general one ‘blob’ of air is ‘advancing’ and the other is ‘retreating’.

This insight was achieved just after the First World War and so the interfaces between the blobs were referred to as ‘fronts’ after the name for the interface between fighting armies. 

  • If the warm air is advancing, then the front is called a warm front, and
  • if the cold air is advancing, then the front is called a cold front.

Surprisingly cold fronts and warm fronts are quite different in character.

Warm Fronts 

When a blob of warm air advances, because it tends to be less dense than the cold air, it rises above the cold air.

Thus the mixing region extends ahead of the location on the ground where the temperature of the air will change.

The course told me the slope of the mixing region was shallow, as low as 1 in 150. So as the warm air advances, there is a region of low, rain-forming cloud that can extend for hundreds of kilometres ahead of it.

Slide2

So on the ground, what we experience is hours of steady rain, and then the rain stops as the temperature rises.

Cold Fronts 

When a blob of cold air advances, because it tends to be more dense than the warm air, it slides below it. But sliding under an air mass is harder than gliding above it – I think this is because of friction with the ground.

As a result there is a steep mixing region which extends a little bit ahead, and a short distance behind the location on the ground where the temperature of the air changes.

Slide3

So as the cold air advances, there is a region of intense rain just before and for a short time after.

So on the ground what we experience are stronger, but much shorter, rain events at just about the same time as the temperature falls. There generally follows some clearer air – at least for a short while.

Data

I had assumed that because of the messy nature of reality compared to theory, real weather data would look nothing like what the simple models above might lead me to expect. I was wrong!

As I was learning about warm and cold fronts last weekend (10 March 2019) by chance I looked at my weather station data and there – in a single day – was evidence for what I was learning – a warm front passing over at about 6:00 a.m. and then a cold front passing over at about 7:00 p.m.

  • You can look at the data from March 10th and zoom in using this link to Weather Underground.

This is the general overview of the air temperature, humidity, wind speed, rainfall and air pressure data. The left-hand side represents midnight on Saturday/Sunday and the right-hand side represents midnight on Sunday/Monday.

Slide4

The warm front approaches overnight and reaches Teddington at around 6:00 a.m.:

  • Notice the steady rainfall from midnight onwards, and then as the rain eases off, the temperature rises by about 3 °C within half an hour.

The cold front reaches Teddington at around 7:00 p.m.:

  • There is no rain in advance of the front, but just as the rain falls – the temperature falls by an astonishing 5 °C!

Slide5

Of course there is a lot of other stuff going on. I don’t understand how these frontal changes relate to the pressure changes and the sudden rise and fall of the winds as the fronts pass.

But I do feel I have managed to link what I learned on the course to something I have seen in the real world. And that is always a good feeling.

P.S. Here’s what the Met Office have to say about fronts…

Global Oxygen Depletion

February 4, 2019

While browsing over at the two degrees institute, I came across this figure for atmospheric oxygen concentrations measured at a station at the South Pole.

Graph 1

The graph shows the change in:

  • the ratio of oxygen to nitrogen molecules in samples of air taken at a particular date

to

  • the ratio of oxygen to nitrogen molecules in samples of air taken in the 1980’s.

The sentence above is complicated, but it can be interpreted without too many caveats as simply the change in oxygen concentration in air measured at the South Pole.

We see an annual variation – the Earth ‘breathing’- but more worryingly we see that:

  • The amount of oxygen in the atmosphere is declining.

It’s a small effect, and will only reach a 0.1% decline – 1000 parts per million – in 2035 or so. So it won’t affect our ability to breathe. Phewww. But it is nonetheless interesting.

Averaging the data from the South pole over the years since 2010, the oxygen concentration appears to be declining at roughly 25 parts per million per year.

Why?

The reason for the decline in oxygen concentration is that we are burning carbon to make carbon dioxide…

C + O2 = CO2

…and as we burn carbon, we consume oxygen.

I wondered if I could use the measured rate of decline in oxygen concentration to estimate the rate of emission of carbon dioxide.

How much carbon is that?

First I needed to know how much oxygen there was in the atmosphere. I considered a number of ways to calculate that, but it being Sunday, I just looked it up in Wikipedia. There I learned that the atmosphere has a mass of about 5.15×1018 kg.

I also learned the molar fractional concentration of the key gases:

  • nitrogen (molecular weight 28): 78.08%
  • oxygen (molecular weight 32): 20.95%
  • argon (molecular weight 40):0.93%

From this I estimated that the mass of 1 mole of the atmosphere was 0.02896 kg/mol. And so the mass of the atmosphere corresponded to…

5.15×1018 /0.02896 = 1.78×1020

…moles of atmosphere. This would correspond to roughly…

1.78×1020 × 0.02095 =3.73×1019

…moles of oxygen molecules. This is the number that appears to be declining by 25 parts per million per year i.e.

3.73×1019× 0.000 025= 9.32×1014

…moles of oxygen molecules are being consumed per year. From the chemical equation, this must correspond to exactly the same number of moles of carbon: 9.32×1014. Since 1 mole of carbon weighs 12 g, this corresponds to…

  • 1.12×1016 g of C,
  • 1.12×1013 kg of C
  • 1.12×1010 tonnes of C
  • 11.2 gigatonnes (Gt) of C

Looking up the sources of sources, I obtained the following estimate for global carbon emissions which indicates that currently emissions are running at about 10 Gt of carbon per year

Carbon Emissions

Analysis

So Wikipedia tells me that humanity emits roughly 10 Gt of carbon per year, but based on measurements at the South pole, we infer that 11.2 Gt of carbon per year is being emitted and consuming the concomitant amount of oxygen. Mmmmm.

First of all, we notice that these figures actually agree within roughly 10%. Which is pleasing.

  • But what is the origin the disagreement?
  • Could it be that the data from the South Pole is not representative?

I downloaded data from the Scripps Institute for a number of sites and the graph below shows recent data from Barrow in Alaska alongside the South Pole data. These locations are roughly half a world – about 20,000 km – apart.

Graph 2

Fascinatingly, the ‘breathing’ parts of the data are out of phase! Presumably this arises from the phasing of summer and winter in the northern and southern hemispheres.

But significantly the slopes of the trend lines differ by only 1%.  So global variability doesn’t seem to able to explain the 10% difference between the rate of carbon burning predicted from the decline of atmospheric oxygen (11.2 Gt C per year) , and the number I got off Wikipedia (10 Gt C per year).

Wikipedia’s number was obtained from the Carbon Dioxide Information and Analysis Centre (CDIAC) which bases their estimate on statistics from countries around the world based on stated oil, gas and coal consumption.

My guess is that there is considerable uncertainty – on the order of a few percent –  on both the CDIAC estimate, and also on the Scripps Institute estimates. So agreement at the level of about 10% is actually – in the context of a blog article – acceptable.

Conclusions

My conclusion is that – as they say so clearly over at the two degrees project – we are in deep trouble. Oxygen depletion is actually just an interesting diversion.

The most troubling graph they present shows

  • the change in CO2 concentration over the last 800,000  years, shown against the left-hand axis,

alongside

  • the estimated change in Earth’s temperature over the last 800,000  years, shown  along the right-hand axis.

The correlation between the two quantities is staggering, and the conclusion is terrifying. chart

We’re cooked…

 

Christmas Bubbles

December 23, 2018
Champagne Time Lapse

A time-lapse photograph of a glass of fizzy wine.

Recently I encountered the fantastic:

Effervescence in champagne and sparkling wines:
From grape harvest to bubble rise

This is a 115-page review article by Gérard Liger-Belair about bubbles in Champagne, my most favourite type of carbon dioxide emission.

Until January 30th 2019 it is freely downloadable using this link

Since the bubbles in champagne arguably add £10 to the price of a bottle of wine, I guess it is worth understanding exactly how that value is added.

I found GLB’s paper fascinating with a delightful attention to detail. From amongst the arcane studies in the paper, here are three things I learned.

Thing 1: Amount of Gas

Champagne (and Prosecco and Cava) have about 9 grams of carbon dioxide in each 750 ml bottle [1].

Since the molar mass of carbon dioxide is 44 g, each bottle contains approximately 9/44 ~ 0.2 moles of carbon dioxide.

If released as gas at atmospheric pressure and 10 °C, it would have a volume of approximately 4.75 litres – more than six times the volume of the bottle!

This large volume of gas is said to be “dissolved” in the wine. The molecules can only leave when, by chance, they encounter the free surface of the wine.

Because the free-surface area of wine in a wine glass is usually larger than the combined surface area of bubbles, about 80% of the de-gassing happens through the liquid surface [2].

Thing 2: Bubble Size and Speed 

But fizzy wine is call “fizzy” because of the bubbles that seem to ceaselessly form on the inner surface of the glass.

Sadly, in a perfectly clean glass, such as one which has repeatedly been through a dishwasher, very few bubbles will form [3].

But if there are tiny cracks in the glass, or small specks of dust from, for example, a drying cloth, then these can trap tiny air bubbles and provide free-surfaces at which carbon dioxide can leave the liquid.

At first a bubble is just tens of nanometres in size, but it grows at a rate which depends upon the rate at which carbon dioxide enters the bubble.

As the bubble grows, its surface area increases allowing the rate at which carbon dioxide enters the bubble to increase.

Eventually the buoyancy of the bubble causes it to detach from its so-called ‘nucleation site’ (birthplace) and rise through the liquid.  This typically happens when bubbles are between 0.01 and 0.1 mm in diameter.

To such tiny bubbles, the wine is highly viscous, and at first the bubbles rise slowly. But as more carbon dioxide enters the bubble, the bubble grows [4] and its speed of rise increases. The rising speed is close to the so-called ‘Stokes’ terminal velocity. [5]

So when you look at a stream of bubbles you will see that at the bottom, the bubbles are small and close together and relatively slow-moving. As they rise through the glass, they grow, and their speed increases.

If you can bear to leave your glass undrunk for long enough, you should be able to see the rate of bubble formation slow as the carbon dioxide concentration falls.

This will be visible as an increase in the spacing of bubbles near the nucleation site of a rising ‘bubble train’.

Thing 3: Number of bubbles

Idle speculation often accompanies the consumption of fizzy wine.

And one common topic of speculation is the number of bubbles which can be formed in a gas of champagne [6]. We can now add to that speculation.

If a bubble has a typically diameter of approximately 1 mm as it reaches the surface, then each bubble will have a volume of approximately 0.5 cubic millimetres, or 0.000 5 millilitres.

So the 4.75 litres of carbon dioxide in a bottle could potentially form 4750/0.0005 = 9.5 million bubbles per bottle!

If a bottle is used for seven standard servings then there are potentially 1.3 million bubbles per glass.

In fact the number is generally smaller than this because as the concentration of carbon dioxide in the liquid falls, the rate of bubble formation falls also. And below approximately 4 grams of carbon dioxide per litre of wine, bubbles cease to form [7].

Thing 4: BONUS THING! Cork Speed

When the bottle is sealed there is a high pressure of carbon dioxide in the space above the wine. The pressure depends strongly on temperature [8], rising from approximately 5 atmospheres (500 kPa) if the bottle is opened at 10 °C to approximately 10 atmospheres (1 MPa) if the bottle is opened at 25 °C.

GLB uses high-speed photography to measure the velocity of exiting cork, and gets results which vary from around 10 metres second for a bottle at 4 °C to 14 metres per second for a bottle at 18 °C. [9]

I made my own measurements using my iPhone (see below) and the cork seems to move roughly 5 ± 2 cm in the 1/240th of a second between frames. So my estimate of the speed is about 12 ± 5 metres second, roughly in line GLB’s estimates

Why this matters

When we look at absolutely any phenomenon, there is a perspective from which that phenomenon – no matter how mundane or familiar – can appear profound and fascinating.

This paper has opened my eyes, and I will never look at a glass of Champagne again in quite the same way.

Wishing you happy experimentation over the Christmas break.

Santé!

References

[1] Page 8 Paragraph 2

[2] Page 85 Section 6.3

[3] Page 42 Section 5.2

[4] Page 78 Figure 59

[5] Page 77 Figure 58

[6] Page 84 Section 6.3 & Figure 66

[7] Page 64

[8] Page 10 Figure 3

[9] Page 24 Figure 16

Hot dry summers

August 10, 2018

Apparently its been hot all around the northern hemisphere this summer.

And that got me thinking about the long hot summer of 1976 when I was 16.

I have the general impression that summers now are warmer than they used to be. But I am aware that such impressions can be misleading.

Being the age I am (58), I fear my own mis-remembering of times past.

So was 1976 really exceptional? And will this year (2018) also prove to be really exceptional?

I decided to download some data and take a look.

Heathrow Data.

I popped over to the Met Office’s Climate pages and downloaded the historical data from the nearby Heathrow weather station.

I had downloaded this data before when looking at long-term climate trends, but this time I was looking for individual hot months rather than annual or decadal trends.

When I plotted the monthly average of the daily maximum temperature, I was surprised that 1976 didn’t stand out at all as an exceptional year.

Heathrow Monthly Climate Data July Maxima Analysis

The monthly average of the daily temperature maxima are plotted as black dots connected by grey lines. I have highlighted the data from July each year using red squares. Notice that since 1976 there have been many comparable July months.

In the graph above I have highlighted July average maximum temperatures. I tried similar analyses for June and August and the results were similar. 1976 stood out as a hot year, but not exceptionally so.

Ask an Expert

Puzzled, I turned to an expert. I sent an e-mail to John Kennedy at the UK’s Met Office  and to my astonishment he responded within a few hours.

His suggestion was to try plotting seasonal data.

His insight was based on the fact that it is not so unusual to have a single warm month. But it is unusual to have three warm months in a row.

So I re-plotted the data and this time I highlighted the average of daily maximum temperatures for June, July and August.

Heathrow Monthly Climate Data June July August Maxima Analysis

The monthly average of the daily temperature maxima are plotted as black dots connected by grey lines as in the previous figure. Here I have highlighted the seasonal average data (from June July and August) using red squares. Notice that 1976 now stands out as an exceptionally warm summer.

Delightfully, 1976 pops out as being an exceptional summer – in line with my adolescent recollection.

More than just being hot

But John suggested more. He suggested looking at the seasonal average of the minimum daily temperature.

Recall that in hot weather it is often the overnight warmth which is particularly oppressive.

In this graph (below) 1976 does not stand out as exceptional, but it is noticeable that warming trend is easily visible to the naked eye. On average summer, summer nights are about 2 °C warmer now than they were at the start of my lifetime.

Heathrow Monthly Climate Data JJA Minimum Analysis

The monthly average of the daily temperature minima are plotted as black dots connected by grey lines. Here I have highlighted the seasonal average data (from June July and August) using red squares. Notice that 1976 does not stand out exceptionally.

John also suggested that I look at other available data such as the averages of

  • daily hours of sunshine
  • daily rainfall

Once again seasonal averages of these quantities show 1976 to have been an exceptional year. Below I have plotted the Rainfall totals on two graphs, one showing the overall rainfall, and the other detail of the low rainfall summers.

Heathrow Monthly Monthly Rainfall

The monthly average of the daily rainfall total are plotted as black dots connected by grey lines. Here I have highlighted the seasonal average data (from June July and August) using red squares. Notice that 1976 was a dry summer. The data below 50 mm of rainfall are re-plotted in the next graph.

Heathrow Monthly Monthly Rainfall detail

Detail from the previous figure showing the low rainfall data. The monthly average of the daily rainfall total are plotted as black dots connected by grey lines. Here I have highlighted the seasonal average data (from June July and August) using red squares. Notice that 1976 was a dry summer.

de Podesta ‘Hot Summer’ Index

Following on from John’s suggestion, I devised the ‘de Podesta Long Hot Summer Index‘. I defined this to be:

  • the sum of the seasonal averages of the minimum and maximum temperatures (for June July and August),
  • divided by the seasonal average of rainfall (for June July and August).

Plotting this I was surprised to see 1976 pop out of the data as a truly exceptional hot dry summer – my memory had not deceived me.

But I also noticed 1995 ‘popped out’ too and I had no recollection of that being an exceptional summer. However this data (and Wikipedia) confirms that it was.

Now I just have to wait until the end of August to see if this year was exceptional too – it most surely felt exceptional, but we need to look at the data to see if our perceptions are genuinely grounded in reality.

Heathrow Hot Dry Summer Index

The de Podesta Hot Dry Summer (HDS) index as described in the text.  Construct an ‘index’ in this way really flags up the exceptional nature of 1976, and also 1995.

John Kennedy’s blog

In typical self-deprecating manner, John calls himself a ‘diagram monkey’ and blogs under that pseudonym. 

His is one of just two blogs to which I subscribe and I recommend it to you highly.

The view from 10 kilometres

June 3, 2018

At the start of May I travelled by air to and from California.

The flight takes an extraordinary route, crossing the southern tip of Greenland, the vast shield of northern Canada, the American mid-west and the south-western deserts.

But despite the extreme terrain covered by the plane, for me the journey was easy. It was nothing more than an exercise in advanced sitting, and I am good at sitting.

And looking out the window, I saw two extraordinary things.

London to LA

Greenland

I had chosen a window seat on the right-hand side of the plane on the off-chance that visibility would be good as we flew over Greenland. I also brought my camera with a pointy lens.

The camera’s field of view on the ground was roughly 1 km at best, and I could see detailed features of the spring-melt of the sea-ice around Greenland.

Greeland Ice

At times I could see the surface texture of what I guess was a glacier as it reached the sea in an ice-cliff.

Greeland Ice 5

The scale of the ice was overwhelming. It didn’t look like a ‘snowy polar cap’ on the globe. It looked like a vast and utterly alien ice world.

I found it interesting to compare this ‘bird’s-eye’ view with the data gathered by satellites that have charted the decades long decline in the extent of the sea ice.

California-Nevada

As we flew over the Nevada-California border I was delighted  to catch a  glimpse of the immense Ivanpah solar power plant (Link & Wikipedia article).

One of three solar collectors at the Ivanpah solar power plant.

One of three solar collectors at the Ivanpah solar power plant.

The three solar collectors of the Ivanpah solar plant together with a vast solar photo-voltaic array

The three solar collectors of the Ivanpah solar plant together with a vast solar photo-voltaic array. It is clear that solar generation is not limited by available land!

Next to Ivanpah was a vast conventional solar photo-voltaic plant.

As I had been when I flew over Greenland, I was struck by the vastness of the landscape and the boldness of these engineering ventures in that inhospitable climate.

The link

Momentarily I allowed my self to hope – forgive me: I was on holiday.

I allowed myself to hope that solar engineering might really provide a way to de-carbonise electricity production.

From 10 km above the ground  it was breathtakingly clear that a lack of suitable land for solar power plants was not a limitation on production. Surely not even 1% of the available land was being used.

And as we flew over the Hoover Dam – with water sadly still at historically low levels – I allowed myself to imagine a world powered by renewable energy.

And as result, eventually there would be a slowdown in the rate of loss of arctic sea ice.

Hoover Dam  from 10 km

Hoover Dam from 10 km

It struck me that the first step required to make this happen was to imagine that it could even be possible.

From 10 kilometres up, briefly it all seemed clear

 

 

Air Temperature

April 1, 2018

Recently, two disparate strands of my work produced publications within a week of each other.

Curiously they both concerned one of the commonest measurements made on Earth today – the measurement of air temperature.

  • One of the papers was the result of a humbling discovery I made last year concerning a common source of error in air temperature measurements. (Link to open access paper)
  • On the other  paper I was just one amongst 17 authors calling for the establishment of global reference network to monitor the climate. My guess is that most people imagine such a network already exists – but it doesn’t! (Link to open access paper)

I am writing this article because I was struck by the contrasting styles of these papers: one describing an arcane experimental detail; and the other proposing a global inter-governmental initiative.

And yet the aim of both papers was identical: to improve measurement so that we can more clearly see what is happening in the world.

Paper 1

In the middle of 2018 I was experimenting with a new device for measuring air temperature by measuring the speed of sound in air.

It’s an ingenious device, but it obviously needed to be checked. We had previously carried out tests inside environmental chambers, but the temperature stability and uniformity inside the chambers was not as good as we had hoped for.

So we decided to test the device in one of NPL’s dimensional laboratories. In these laboratories, there is a gentle, uniform flow of air from ceiling to floor, and the temperature is stable to within a hundredth of a degree Celsius (0.01 °C) indefinitely.

However, when I tried to measure the temperature of the air using conventional temperature sensors I got widely differing answers – varying by a quarter of a degree depending on where I placed the thermometer. I felt utterly depressed and humiliated.

Eventually I realised what the problem was. This involved stopping. Thinking carefully. And talking with colleagues. It was a classic case of eliminating the impossible leaving only the improbable.

After believing I understood the effect, I devised a simple experiment to test my understanding – a photograph of the apparatus is shown below.

tubes-in-a-lab-photo.png

The apparatus consisted of a set of stainless steel tubes held in a clamp stand. It was almost certainly the cheapest experiment I have ever conducted.

I placed the tubes in the laboratory, exposed to the downward air flow, and  left them for several hours to equilibrate with air.

Prior to this experience, I would have bet serious amounts of money on the ‘fact’ that all these tubes would be at the same temperature. My insight had led me to question this assumption.

And my insight was correct. Every one of the tubes was at a different temperature and none of them were at the temperature of the air! The temperature of the tubes depended on:

  • the brightness of the lights in the room – which was understandable but a larger effect than I expected, and
  • the diameter of the tubes – which was the truly surprising result.

Results 1

I was shocked. But although the reason for this is not obvious, it is also not complicated to understand.

When air flows air around a cylindrical (or spherical) sensor only a very small amount of air actually makes contact with the sensor.

Air reaching the sensor first is stopped (it ‘stagnates’ to use the jargon). At this point heat exchange is very effective. But this same air is then forced to flow around the sensor in a ‘boundary layer’ which effectively insulates the sensor from the rest of the air.

Air flow

For small sensors, the sensor acquires a temperature close to that of the air. But the air is surprisingly ineffective at changing the temperature of larger sensors.

The effect matters in two quite distinct realms.

Metrology

In metrology – the science of measurement – it transpires that knowledge of the temperature of the air is important for the most accurate length measurements.

This is because we measure the dimensions of objects in terms of the wavelength of light, and this wavelength is slightly affected by the temperature of the air through which the light passes.

In a dimensional laboratory such as the one illustrated below, the thermometer will indicate a temperature which is:

  • different from the temperature of artefacts placed in the room, and
  • different from the temperature of the air.

Laboratory

Unless the effect is accounted for – which it generally isn’t – then length measurements will be slightly incorrect.

Climatology

The effect is also important in climatology. If a sensor is changed in a meteorological station people check that the sensor is calibrated, but they rarely record its diameter.

If a calibrated sensor is replaced by another calibrated sensor with a different diameter, then there will be a systematic effect on the temperatures recorded by the station. Such effects won’t matter for weather forecasting, but they will matter for people using the stations for a climate record.

And that brings me to Paper 2

Paper 2

Hadcrut4 Global Temperature

When we see graphs of ‘global temperatures’ over time, many people assume that the data is derived from satellites or some ‘high-tech’ network of sensors. Not so.

The ‘surface’ temperature of the Earth is generally estimated in two quite distinct parts – sea surface temperature and land surface temperature. But both these terms are slight misnomers.

Considering just the land measurements, the actual temperature measured is the air temperature above the land surface. In the jargon, the measurement is called LSAT – the Land Surface Air Temperature.

LSAT is the temperature which human beings experience and satellites can’t measure it.

LSAT data is extracted from temperature measurements made in thousands of meteorological stations around the world. We have data records from some stations extending back for 150 years.

However, it is well known that data is less than ideal: it is biased and unrepresentative in many ways.

The effect described in Paper 1 is just one of many such biases which have been extensively studied. And scientists have devised many ways to check that the overall trend they have extracted – what we now call global warming – is real.

Nonetheless. It is slightly shocking that a global network of stations designed specifically with the aim of climate monitoring does not exist.

And that is what we were calling for in Paper 2. Such a climate network would consist of less than 200 stations world-wide and cost less than a modest satellite launch. But it would add confidence to the measurements extracted from meteorological stations.

Perhaps the most important reason for creating such a network is that we don’t know how meteorological technology will evolve over the coming century.

Over the last century, the technology has remained reasonably stable. But it is quite possible that the nature of data acquisition for meteorological applications will change  in ways we cannot anticipate.

It seems prudent to me that we establish a global climate reference network as soon as possible.

References

Paper 1

Air temperature sensors: dependence of radiative errors on sensor diameter in precision metrology and meteorology
Michael de Podesta, Stephanie Bell and Robin Underwood

Published 28 February 2018
Metrologia, Volume 55, Number 2 https://doi.org/10.1088/1681-7575/aaaa52

Paper 2

Towards a global land surface climate fiducial reference measurements network
P. W. Thorne, H. J. Diamond, B. Goodison , S. Harrigan , Z. Hausfather , N. B. Ingleby , P. D. Jones ,J. H. Lawrimore , D. H. Lister , A. Merlone , T. Oakley , M. Palecki , T. C. Peterson , M. de Podesta , C. Tassone ,  V. Venema, K. M. Willett

Published: 1 March 2018
Int. J. Climatol 2018;1–15. https://doi.org/10.1002/joc.5458

Santa Rosa Fire: Update

October 18, 2017

The fires surrounding Santa Rosa are slowly coming under control. And – thankfully – rains are due tomorrow (Thursday 19th October).

From the San Francisco Chronicle’s interactive graphic page, I compiled the animated gif above to show how closely the fires approached Santa Rosa from two directions.

Each frame shows one day’s fire extent starting with day 0 – the day before the fires – to  day 11: the 18th October 2017.

What is particularly striking is the rapidity of the spread of the so-called ‘Tubbs Fire’ on Day 2.

It completely outpaced any attempt to contain it, and it devastated the north-eastern suburb of Fountaingrove.

I confess I immediately thought that this extraordinary fire, following an extended drought, had the fingerprints of ‘Climate Change’ written all over it.

And I was sure that Suzanne would feel that way too. But this is not quite the open-and-shut case that I thought.

It turns out that there was a great ‘Hanley’ fire in 1964 that has an uncanny geographical overlap with the the 2017 fires. Several newspapers have featured recollections of the blaze (here and here) and Suzanne sent me the graphic below.

The ‘hatched’ regions correspond to the extent of the 1964 fires, and the coloured dots correspond to the 2017 fires. The overlap is… suspicious. And it rather changes ‘the story’ of the fires.

Santa Rosa Fires 1964-2017

The narrative now appears to be less “OMG! Climate change induced fire-meggedon“, and more “Were the proper planning procedures followed?“. i.e. rather less dramatic, but just as important if it happened to be your house that was burned.

It appears that the fire burned in the same place as it did previously, but in the intervening 53 years, thousands of homes were built.

One irony that Suzanne reports is that a couple of years ago, there was a move to build a fire station in Fountaingrove, but there were objections because it might lower property values in the area.

The fire station was eventually built, but – like everything else there – it has been devastated.

I suspect that when they re-build having a fire station nearby will not be seen with quite the negativity that it once was.

UPDATE: The Washington Post have also run with this story under the headline Santa Rosa ignored nature’s warning . Perhaps after reading my blog?

 

The Santa Rosa Fire

October 16, 2017

Santa Rosa FiresIt’s been a few year’s since we visited my friend Suzanne in Santa Rosa. But I remember the street on which she lives.

In the early mornings, I would go jogging around the neighboured which was sleepy and suburban.

But this memory contrast strongly with the news that the largest of the recent Northern California wildfires (The Tubbs Fire) stopped just about 100 metres short of Suzanne’s home.

The map at the head of the page (stolen from the excellent San Francisco Chronicle) shows how the fire swept across the suburbs from the north east, and by nothing more than good chance, stopped just short of her home.

It’s not just people who have lost homes. Businesses have been burned out too.

But Keysight (formerly Agilent, formerly Hewlett Packard) who have their HQ in Santa Rosa seem to have lost only a few out-buildings.

Aside from the unimaginable personal and financial losses, this must be devastating for the entire community.

I don’t want to say anything about this now because it’s too shocking and the fires are not yet out. But until this moment, I would never have believed this possible.

 

Not everything is getting worse!

April 19, 2017

Carbon Intensity April 2017

Friends, I find it hard to believe, but I think I have found something happening in the world which is not bad. Who knew such things still happened?

The news comes from the fantastic web site MyGridGB which charts the development of electricity generation in the UK.

On the site I read that:

  • At lunchtime on Sunday 9th April 2017,  8 GW of solar power was generated.
  • On Friday all coal power stations in the UK were off.
  • On Saturday, strong winds and solar combined with low demand to briefly provide 73% of power.

All three of these facts fill me with hope. Just think:

  • 8 gigawatts of solar power. In the UK! IN APRIL!!!
  • And no coal generation at all!
  • And renewable energy providing 73% of our power!

Even a few years ago each of these facts would have been unthinkable!

And even more wonderfully: nobody noticed!

Of course, these were just transients, but they show we have the potential to generate electricity which has a significantly low carbon intensity.

Carbon Intensity is a measure of the amount of carbon dioxide emitted into the atmosphere for each unit (kWh) of electricity generated.

Wikipedia tells me that electricity generated from:

  • Coal has a carbon intensity of about 1.0 kg of CO2 per kWh
  • Gas has a carbon intensity of about 0.47 kg of CO2 per kWh
  • Biomass has a carbon intensity of about 0.23 kg of CO2 per kWh
  • Solar PV has a carbon intensity of about 0.05 kg of CO2 per kW
  • Nuclear has a carbon intensity of about 0.02 kg of CO2 per kWh
  • Wind has a carbon intensity of about 0.01 kg of CO2 per kWh

The graph at the head of the page shows that in April 2017 the generating mix in the UK has a carbon intensity of about 0.25 kg of CO2 per kWh.

MyGridGB’s mastermind is Andrew Crossland. On the site he has published a manifesto outlining a plan which would actually reduce our carbon intensity to less than 0.1 kg of CO2 per kWh.

What I like about the manifesto is that it is eminently doable.

And who knows? Perhaps we might actually do it?

Ahhhh. Thank you Andrew.

Even thinking that a good thing might still be possible makes me feel better.

 

Climate Reflections

March 28, 2017

I am currently in Exeter attending the 22nd meeting of the WMO GCOS/WCRP AOPC. Let me translate:

In short, I am here to talk about monitoring the global climate with some of the best climate scientists from around the world.

The topics being discussed are diverse, and I am here to talk about one small part of the work. However, I feel honoured to take coffee with these people and to be able to legitimately call them ‘colleagues’.

My contribution is to speak on Thursday about creating a reference network of climate monitoring stations.

Historically, we have used records from normal weather stations to monitor the changing climate. But these stations have known biases that have to be detected and corrected.

It would have been really helpful if 100 years ago, scientists had thought to create a reference network where every time a new thermometer screen was installed, they recorded the fact. But they didn’t.

So the idea is to create that reference network now so that in 100 year’s time when climate scientists look back they will say:

“Thank heaven for AOPC-22: that’s when our job got easier! They created a Climate Reference Network that has allowed us to detect anomalies in the climate signal inferred from analysing regular weather stations.

But that’s not what I wanted to talk about.

The mood of the meeting

This meeting is busy. People are mindful of the ability of a roomful of scientists to chat endlessly about details. And to counter this there is a powerful focus on getting things done.

However President Trump casts a shadow over the meeting.

Trump collage

Headlines from news sites today.: BBC, Guardian and Ars Technica

And the news today is that he has signed executive orders that effectively scrap energy policies based on avoiding the worst effects of climate change.

Most people at the meeting find this depressing. And it would be an understatement to say that colleagues from the US are ‘concerned’.

Trump’s policies are ultimately based on a simple belief which is summed up in the graph below from the Gapminder foundation.

2013 data for the countries of the world showing GDP per person versus carbon dioxide emissions per person. Each bubble represents a country and the size of each bubble is proportional to its  population.

2013 data for the countries of the world showing GDP per person versus carbon dioxide emissions per person. Each bubble represents a country and the size of each bubble is proportional to its population.

The graph shows that countries that emit a lot of carbon per person are richer.

However the graph shows correlation not causation. Emitting carbon dioxide of itself does not make anyone richer.

Burning carbon produces energy, and it is access to energy that makes countries rich, and unequivocally improves the quality of people’s lives.

But emitting ~30 billion tonnes of carbon dioxide per year also has another effect which is not documented on the ‘bubble graph’. As the people at this meeting have helped make clear, it has warmed the surface of the planet and will continue to do so for centuries to come. But we no longer need to emit carbon to produce energy.

Currently renewable energy sources are (generally) more expensive than fossil fuels. But there is no reason why that will always be the case.

Indeed, if Trump’s aim is to make America independent of foreign energy sources, the best thing he could do would be to increase exploitation of renewable energy which would reduce its cost.

Personally, I think that it is already too late for coal and that Trump’s efforts to open coal mines and burn more coal will fail, just like efforts to create ‘clean coal’ have utterly failed.

 


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