Archive for the ‘Simple Science’ Category

Ignorance: Eggs & Weather Forecasts

November 26, 2018

Every so I often I learn something so simple and shocking that I find myself asking:

How can I possibly not have known that already?“.

Eggs

Eggs

Eggs

While listening to Farming Today the other morning, learned that:

Large eggs come from old hens

In order to produce large eggs – the most popular size with consumers – farmers need to allow hens to reach three years old.

So during the first and second years of their lives they will first lay small eggs, then medium eggs, and finally large eggs.

On Farming Today a farmer was explaining that egg production naturally resulted a range of egg sizes, and it was a challenge to find a market for small eggs. Then came the second bomb’shell’.

The yolk is roughly same size in all eggs

What varies between small and large eggs is mainly the amount of egg white (albumen).

How could I have reached the age of 58 and not  known that? Or not have even been curious about it?

Since learning this I have become a fan of small eggs: more yolk, less calories, more taste!

But my deep ignorance extends beyond everyday life and into the professional realm. And even my status as ‘an expert’ cannot help me.

Weather Forecasts & Weather Stations

Professionally I have become interested in weather stations and their role in both Numerical Weather Prediction (NWP, or just weather forecasting) and in Climate Studies.

And as I went about my work I had imagined that data from weather stations were used as inputs to NWP algorithms that forecast the weather.

But in September I attended CIMO TECO-2018 (Technical Conference on Meteorological and Environmental Instruments and Methods of Observation) in Amsterdam.

And there I learned in passing from an actual expert, that I had completely misunderstood their role.

Weather station data is not considered in the best weather forecasts.

And, on a moment’s reflection, it was completely obvious why.

Weather forecasting work like this:

  • First one gathers as much data as possible about the state of the atmosphere ‘now’. The key inputs to this are atmospheric ‘soundings’:
    • Balloon-borne ‘sondes’ fly upwards through the atmosphere sending back data on temperature, humidity and wind (speed and direction) versus height.
    • Satellites using infrared and microwave sensors probe downwards to work out the temperature and humidity at all points in the atmosphere in a swathe below the satellite’s orbit.
  • The NWP algorithms accept this vast amount of data about the state of the atmosphere, and then use basic physics to predict how the state of the entire atmosphere will evolve over the coming hours and days

And then, after working out the state of the entire atmosphere, the expected weather at ground level is extracted.

Visualisation of the amount of moisture distributed across different heights in the atmosphere based on a single pass of a 'microwave sounding' satellite. Image credit: NASA/JPL-Caltech

Visualisation of the amount of moisture distributed across different heights in the atmosphere based on a single pass of a ‘microwave sounding’ satellite. The data gathered at ground level is just a tiny fraction of the data input to NWP models. Image credit: NASA/JPL-Caltech

Ground-based weather stations are still important:

  • They are used to check the outputs of the NWP algorithms.
  • But they are not used as inputs to the NWP algorithms.

So why did I not realise this ‘obvious’ fact earlier? I think it was because amongst the meteorologists and climate scientists with whom I spoke, it was so obvious as to not require any explanation.

Life goes on

So I have reached the age of 58 without knowing about hen’s eggs and the role of weather stations in weather forecasting?

I don’t know how it happened. But it did. And I suspect that many people have similar areas of ignorance, even regarding aspects of life with which we are totally familiar – such as eggs – or where one is nominally an expert.

And so life goes on. Anyway…

This pleasing Met Office video shows the importance of understanding the three-dimensional state of the atmosphere…

And here is a video of some hens

 

Mug Cooling: Salty fingers

November 23, 2018

You wait years for an article about heat transfer at beverage-air interfaces and then four come along at once!

When I began writing these articles (1, 2, 3) I was just curious about the effect of insulation and lids.

But as I wrote more I had two further insights.

  • Firstly the complexity of the processes at the interface was mind-boggling!
  • Secondly, I realised that cooling beverages are just one example of the general problem of energy and material transfer at interfaces.

This is one of the most important processes that occurs on Earth. For example, it is how the top layer of the oceans – where most of the energy arriving on Earth from the Sun is absorbed – exchanges energy with the deeper ocean and the atmosphere.

But in the oceans there is another factor: salinity.

Salinity 

Sea water typically contains 35 grams of salt per litre of water, and is about 2.4% denser than pure water.

So pure water – such as rain water falling onto the ocean surface – will tend to float above the brine.

This effect is exacerbated if the pure water is warm. For example, water at 60 °C is approximately 1.5% less dense than water at around 20 °C.

Video 

In the video at the top of the article I added warm pure water (with added red food colouring) to a glass of cold pure water (on the left) and a glass of cold salty water (on the right).

[For the purposes of this article I hope you will allow that glasses are a type of mug]

The degree to which the pure and salty water spontaneously separated surprised me.

But more fascinating was the mechanism of eventual mixing – a variant on ‘salt fingering‘.

Salt Fingers Picture

The formation of ‘salty fingers’ of liquid is ubiquitous in the oceans and arises from density changes caused by salt diffusion and heat transfer.

As the time-lapse section of the movie shows – eventually the structure is lost and we just see ‘mixed fluid’ – but the initial stages, filmed in real time, are eerily beautiful.

Now I can’t quite explain what is happening in this movie – so I am not going to try.

But the web has articles, home-made videos and fancy computer simulations.

 

Mug Cooling: The Lid Effect

November 12, 2018
IMG_7906

Droplets collect near the rim of a mug filled with hot water.

During my mug cooling experiment last week, I was surprised to find that taking the lid off a vacuum insulated mug increased its initial cooling rate by a factor 7.5.

Removing the lid allowed air from the room to flow across the surface of the water, cooling it in two ways.

  • Firstly, the air would warm up when it contacted the hot water, and then carry heat away in a convective flow.
  • Secondly, some hot water would evaporate into the moving air and carry away so – called ‘latent heat’.

I wondered which of these two effects was more important?

I decided to work out the answer by calculating how much evaporation would be required to explain ALL the cooling. I could then check my calculation against the measured mass of water that was lost to evaporation.

Where to start?

I started with the cooling curve from the previous blog.

Slide5

Graph#1: Temperature (°C) versus time (minutes) for water cooling in an insulated mug with and without a lid. Without a lid, the water cools more than 7 times faster.

Because I knew the mass of water (g) and its heat capacity (joule per gram per °C), I could calculate the rate of heat loss in watts required to cool the water at the observed rate.

In Graph#2 below I have plotted this versus the difference in temperature between the water and the room temperature, which was around 20 °C.

Slide6

Graph#2: The rate of heat flow (in watts) calculated from the cooling curve versus the temperature difference (°C) from the ambient environment. The raw estimates are very noisy so the dotted lines are ‘best fit lines’ which approximately capture the trend of the data.

I was struck by two things: 

  • Firstly, without the lid, the rate of heat loss was initially 40 watts – which seemed very high.
  • Secondly:
    • When the lid was on, the rate of heat loss was almost a perfect straight line This is broadly what one expects in a wide range of heat flow problems – the rate of heat flow is proportional to the temperature difference. But…
    • When the lid was off, the heat flow varied non-linearly with temperature difference.

To find out the effect of the lid, I subtracted the two curves from each other to get the difference in heat flow versus the temperature of the water above ambient (Graph#3).

[Technical Note: Because the data in Graph#2 is very noisy and irregularly spaced, I used Excel™ to work out a ‘trend line’ that describes the underlying ‘trend’ of the data. I then subtracted the two trend lines from each other.]

Slide7

Graph#3: The dotted line shows the difference in power (watts) between the two curves in the previous graph. This should be a fair estimate for the heat loss across the liquid surface.

This curve now told me the extra rate of cooling caused by removing the lid.

If this was ALL due to evaporative cooling, then I could work out the expected loss of mass by dividing by the latent heat of vaporisation of water (approximately 2260 joules per gram) (Graph#4).

Slide8c

Graph#4. The calculated rate of evaporation (in milligrams per second) that would be required to explain the increased cooling rate caused by removing the lid.

Graph#4 told me the rate at which water would need to evaporate to explain ALL the cooling caused by removing the lid.

Combining that result with the data in Graph#1, I worked out the cumulative amount of water that would need to evaporate to explain ALL the observed extra cooling (Graph#5)

Slide9

Graph#5: The red dashed line shows the cumulative mass loss (g) required to explain all the extra cooling caused by removing the lid. The green dashed lines show the amount of water that actually evaporated in each of the two ‘lid off’ experiments. The green data shows additional measurements of mass loss versus time from a third experiment.

In Lid-Off Experiments#1 and #2, I had weighed the water before and after the cooling experiment and so I knew that in each experiment with the lid off I had lost respectively 25 g and 31 g of water –  just under 10% of the water.

But Graph #5 really needed some data on the rate of mass loss, so I did an additional experiment where I didn’t measure the temperature, but instead just weighed the mug every few minutes. This is the data plotted on Graph#5 as discrete points.

Conclusions#1

In Graph#5, it’s clear that the measured rate of evaporation can’t explain all the increased cooling rate loss, but it can explain ‘about a third of it‘.

So evaporation is responsible for about a third of the extra cooling, with two thirds being driven by heat transfer to the flowing air above the cup.

It is also interesting that even though the cooling curves in Graph#1 are very similar, the amount of evaporation in Graph#5 is quite variable.

The video below is backlit to show the ‘steam’ rising above the mug, and it is clear that the particular patterns of air flow are very variable.

The actual amount of evaporation depends on the rate of air flow across the water surface, and that is driven both by

  1. natural convection – driven by the hot low-density air rising, but also by…
  2. forced convection – draughts flowing above the cup.

I don’t know, but I suspect it is this variability in air flow that caused the variability in the amount of evaporation.

Conclusions#2

I have wasted spent a several hours on these calculations. And I don’t really know why.

Partly, I was just curious about the answer.

Partly, I wanted to share my view that it is simply amazing how much subtle physics is taking place around us all the time.

And partly, I am still trying to catch my breath after deciding to go ‘part-time’ from next year. Writing blog articles such as this is part of just keeping on keeping on until something about the future becomes clearer.

P.S. Expensive Mugs

Finally, on the off-chance that (a) anybody is still reading and (b) they actually care passionately about the temperature of their beverages, and (c) they are prepared to spend £80 on a mug, then the Ember temperature-controlled Ceramic mug may be just thing for you. Enjoy 🙂

 

Mug Cooling: Initial Results

November 7, 2018

One of life’s greatest pleasures is a nice cup of tea or coffee.

  • But what temperature makes the drink ‘nice’?
  • And how long after making the beverage should we wait to drink it?
  • And what type of mug is optimal?

To answer these questions I devised a research proposal involving temperature measurements made inside mugs during the cooling process.

I am pleased to tell you that my proposal was fully-funded in its initial stage by the HBRC*, having scored highly on its societal impact.

Experimental Method

The basic experiment consisted of pouring approximately 300 ml of water (pre-stabilised at 90 °C) into a mug sitting on a weighing scale. The weighing allowed low uncertainty assessment of the amount of water added.

The temperature of the water was measured every 10 seconds using four thermocouples held in place by a wooden splint. The readings were generally very similar and so in the graphs below I have just plotted the average of the four readings.

Experiments were conducted for a fancy vacuum-insulated mug (with and without its lid) and a conventional thick-walled ceramic mug. The results for the vacuum-insulated mug without its lid were so surprising that I repeated them.

This slideshow requires JavaScript.

Results

The average temperature of the water in the mugs is shown in the two graphs below.

The first graph shows all the data – more than 8 hours for the vacuum insulated mug – , and the second graph shows the initial behaviour.

Also shown are horizontal lines at various temperatures that I determined (in a separate series of experiments) to be the optimal drinking range.

Slide1

The average temperature of the water in the mugs versus time.

Slide2

The first 120 minutes of the cooling curves. The water was poured in at 4 minutes.

Discussion

The most striking feature of the cooling curves is the massive difference between the results for the vacuum insulated mug with, and without, its lid.

As I mentioned at the start, the result was so striking that I repeated the measurements (marked as #1 and #2) on the graphs.

The table below shows how many minutes it took for the water to cool to the three states highlighted on the graphs above:

  • Too hot to drink, but just sippable
  • Mmmm. A nice hot cuppa.
  • I’ll finish this quickly otherwise it’ll be too cold.

Minutes to reach status

  Vacuum-Insulated Mug

Ceramic Mug

 No Lid

 With Lid

Just Sippable

2

10

66

Upper Drinkable Limit 12 24

151

Lower Drinkable Limit

28

53

296

Conclusion

The insulating prowess of the vacuum insulated mug (with lid) is outstanding.

But the purpose of a mug is not simply to prevent cooling. It is to enable drinking! 

So to me this data raises a profound question about the raison d’être for vacuum insulated mugs.

  • Who  makes a cup of coffee and then thinks “Mmm, that’ll be just right to drink in two and a half hours time!”

Admittedly,  the coffee will then stay in the drinkable range for an impressive two hours. But still.

In contrast, the ceramic mug cools the hot liquid initially and allows it to reach the optimal drinking temperature after just a few minutes.

Further work

The review committee rated this research very highly and suggested two further research proposals.

  • The first concerned the explanation for the very large effect of removing the lid from the vacuum insulated mug. That research has already been carried out and will be the result of a further report in this journal.
  • The second concerned the effect of milk addition which could significantly affect the time to reach the optimal drinking temperature. That research proposal is currently being considered by HBRC.

==============================

*HBRC = Hot Beverage Research Council

Hydraulic jumps in the kitchen

September 1, 2018

It has been a difficult summer for me.

Putting on the Royal Society Summer Science Exhibition was utterly exhausting, and even two months on, I have not been able to catch up on all the extra days and hours I worked. And I fell behind on every other project on which I am working.

So every day as I enter work I have to catch my breath, staunch my sense of panic, and force myself to stay calm as I begin another day of struggling through tiredness to avoid failure on all the projects on which I am way behind.

But earlier this week my colleague caught me staring at the water flowing down the sink in the kitchenette where we prepare tea.

img_7694

I was staring at a phenomenon I have been fascinated by since childhood – the way water falling from the tap onto the bottom of the kitchen sink forms a smooth flat circle for a few centimetres around where the water lands – and then forms a ‘wavy wall’ around this circle.

My colleague said to me: “It’s great isn’t it. It’s called a hydraulic jump“. Learning that this phenomenon had a name lifted my spirits enormously and made me more curious about what was going on.

So today (Saturday) I have wantonly avoided catching up with my weekly tide of failure, stupidly neglected to pack for my week long conference in Belfast starting tomorrow, and spent the afternoon playing at the kitchen sink. I have experienced transitory happiness.

Hydraulic jump

Naming a phenomenon is stage#1 of the process of understanding it. Knowing this name allowed me to read a number of  – frankly confusing – articles on the web.

But after reading and playing for a while I think I am now beginning to understand what makes the circle form. There are two parts to my understanding:

The first insight arises from comparing:

  • the flow speed of the water with,
  • the speed at which waves travel on the surface of the water.

Inside the circle, the flow is faster than the speed at which waves can travel in the water.  So surface disturbances are swept outwards – the waves are not fast enough to travel ‘upstream’, back towards the centre.

As one moves further away from the centre, the flow speed falls and at the edge of the circle, the flow speed is just equal to the speed of water waves. So water waves travelling back towards the centre of the circle appear stationary – this what makes the circle appear to be ‘fixed’ even though it is a dynamically created structure.

Outside the circle, the flow slows sufficiently that water waves can travel upstream (towards the middle) but they can never travel into ‘the circle’. (There is actually a scientific paper in which this circle is used as an analogy to the ‘Event Horizon’ in a putative ‘White hole’!)

Hydraulic Jump Illustration

The second insight, arises from considering turbulence.

Once waves can travel in both directions in the water, turbulence builds up which slows the speed of the flowing water dramatically.

So in the steady state, the depth of the water builds up suddenly and the ratio of the depth of water inside the circle to the depth outside the circle is simply the ratio of the speeds of water flow just outside and just inside the circle.

So if the speed of flow is 10 times slower outside the circle, then the water will be be 10 times deeper outside the circle.

In the picture above and the video below, you can see the very strikingly different nature of the liquid surfaces. Shallow and perfectly smooth within the circle, and deeper and turbulent outside the circle.

Experiments

I began playing by finding a better surface than the bottom of a sink. I used an upside down baking tray and adjusted it to be as level as I could manage.

img_7695

Not knowing what to do, I began by measuring the diameter of the circle formed for different flow rates:

  • I measured the diameter roughly with a ruler
  • I measured the flow rate by timing how long it took to fill a measuring jug which I weighed before and after filling.

This produced a pleasing graph, but no real insight. An increased flow rate meant made the circle larger because it took more time (and distance) for the flowing water to slow down to the speed of water waves.

Graph

Looking at the algebra, I realised I really needed to know the speed of the water and depth of the water. But how could I measure these things?

I tried estimating the speed of the water by injecting food colouring into the flow and making a movie using the slow-motion mode of my iPhone camera.

Knowing the circle was about 8.8 cm in diameter, this allowed me to estimate the speed of flow as roughly 1.5 ± 0.5 metres per second in the centre zone. However I couldn’t think how to estimate the thickness (height) of the flowing layer.

By sticking a needle in I could see that it was much less than 1 mm and appeared to be less than a tenth of the thickness of the water outside the circle. But I couldn’t make any meaningful measurements.

Then I realised that I could I estimate the speed of the water in a different way. If I placed a needle in the moving water, it produced an angular ‘shock wave’.

This is similar to way an aeroplane travelling faster than the speed of sound in air produces a ‘sonic boom’.

  • For an aeroplane, the angle of the shock wave with respect to the direction of motion is related to the ratio of the speed of the plane to the speed of the sound.
  • For our flowing water, the angle of the shock wave with respect to the direction of motion is related to the ratio of the speed of the water to the speed of the water waves.

Unfortunately the angle changes very rapidly as the ratio of flow speed to wave speed approaches unity and I found this phenomenon difficult to capture photographically.

Graph 2

But as the photographs below show, I could convince myself qualitatively that the angle was opening out as I placed the obstacle nearer the edge of the circle.

Hydraulic Jump Pictures

Observations of the shock wave formed when an obstruction is placed in the water flow. The top row of photographs shows the effect of moving the obstruction from near the centre to near the edge of the circle. The bottom row of photographs are the same as the top row but I have added dotted lines to show how the shock angle opens up nearer the edge of the circle.

Summary

  • My work remains undone.
  • I still have to pack in order to leave for the conference at 8:30 a.m. on Sunday morning: less than 8 hours away as I finish this. (Perhaps I will have a chance to complete some tasks at the airport or on Sunday evening?)
  • I have understood a little something about one more little thing in this beautiful world, and that has lifted my spirits. For now at least.

img_7689

 

 

 

 

 

 

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.

Talking about the SI

June 24, 2018

In just a few days, we will be setting up our stand about the International System of Units, the SI, at the Royal Society Summer Science Exhibition (RSSSE).

In May 2019 the world plans to redefine four of the base units of the SI. The re-definition represents a profound change in our concept of measurement.

And it involves quantities with which most people are familiar, such as ‘a kilogram’, or ‘a degree Celsius’.

So we have thought long and hard about how to communicate this at RSSSE.

Where to start?

The geographical theory of knowledge  suggests that ‘explanations of concepts’ are like ‘directions from one place to another’.

And thus, when people visit our stand, we are obliged to start giving ‘directions’ from where they actually ‘are’.

Although we want to talk about the re-definition of the SI, we have to acknowledge that most people don’t actually know much about the SI.

So if we want to ‘start from where people are’, we first need to explain what the SI is now, and why it matters. And that is what we have done.

It’s about Measurement.

In the ‘orientation’ for colleagues who will be helping at the RSSSE, we have stressed three starting points to help orient visitors to the stand.

  • At the heart of science and engineering, there is measurement.
  • Measurement is the comparison of an unknown thing against a standard.
  • In the International System of Units there are seven standard things against which all physical quantities are compared.

We then have seven hands-on demonstrations – one for each of the seven standard quantities (called ‘base units’)- which will hopefully serve as starting points for conversations.

Keep it simple!

In developing the ‘hands-on demonstrations we worked with the magical people at Science Projects to build apparatus that was robust and simple.

They have years of experience developing hands-on kit for museums and interactive science centres.

As we honed our initial ideas, Science Projects staff constantly challenged us to ‘keep it simple’. And in (almost) every case, their instincts were sound.

A demonstration which is engaging and which can be immediately grasped is a dramatically better starting point for a conversation than one which is beautifully sophisticated, but only elicits the Ah-yes,-I-see-now-moment after 5 minutes.

NPL Stands for the RSSSE exhibition

Stands for the RSSSE exhibition

NPL tweaks!

We developed the demonstrations and tried them out on NPL’s Open Day in May. The stands all survived and people seemed happy with the demonstrations.

But because we are NPL, and because at RSSSE we also need to interact with Fellows of the Royal Society, we had to add some truly complex and amazing features that are right at the forefront of science.

  • The ‘time team’ decided to develop an app that would allow people to compare the time on their own phones with the time from NPL’s Caesium atomic clock.
  • The ‘length team’ decided they wanted to develop a laser interferometer that would measure the height of SI-bots in terms of the wavelength of light.
  • The ‘mass team’ wanted to put an actual working Kibble balance on the stand at the Royal Society.

As I write this on Sunday 24th June, – none of these demonstrations are ready! But my colleagues are working hard and I am cautiously confident they will succeed.

If you get a chance to visit, the RSSSE is FREE and runs from Monday 2nd July 2018 until Sunday 9th July 2018.

 

 

 

Summer Science

May 26, 2018

Video Capture 2

For some months now I have been preparing for the Royal Society Summer Science Exhibition.

We have been working with the fabulous team at Science Projects on developing seven demonstration experiments – one for each of the seven SI base units.

Being so distracted, the deadline for submitting a video almost passed me by. In fact my colleague Andrew Hanson and I remembered with just one day to go!

So after a necessarily short planning phase, Andrew and I shot the video below on Andrew’s iPhone.

The background noise on some of the sections was problematic and Andrew had to do a great deal of filtering to get anything close to intelligible.

But given that everything was shot in’one take’, we were pretty happy with it, even if it came out a bit long (5’20”)

The end of the film was forced on us because my colleagues from the ‘length team’ were both absent when the end of the film was shot at about 7:30 p.m.!

After feedback from the team at the Royal Society we were asked to shorten the video and we took that opportunity to re-shoot the start and end of the movie with a proper microphone.

And here is the final shortened version (2’34”) which should be on the Royal Society site next week.

I hope you enjoy it.

Thanks 

Thanks to everyone who helped: Andrew Hanson, Brian Madzima, Rachel Godun, Stuart Davidson, Robin Underwood, Teresa Goodman, Lucy Culleton, Masaya Kataoka and Jonathan Fletcher

 

The James Webb Space Telescope

May 10, 2018

Last week I was on holiday in Southern California. Lucky me.

Lucky me indeed. During my visit I had – by extreme good fortune – the opportunity to meet with Jon Arenberg – former engineering director of the James Webb Space Telescope (JWST).

And by even more extreme good fortune I had the opportunity to speak with him while overlooking the JWST itself – held upright in a clean room at the Northrop Grumman campus in Redondo Beach, California.

[Sadly, photography was not allowed, so I will have to paint you a picture in words and use some stock images.]

The JWST

In case you don’t know, the JWST will be the successor to the Hubble Space Telescope (HST), and has been designed to exceed the operational performance of the HST in two key areas.

  • Firstly, it is designed to gather more light than the HST. This will allow the JWST to see very faint objects.
  • Secondly, it is designed to work better with infrared light than the HST. This will allow the JWST to see objects whose light has been extremely red-shifted from the visible.

A full-size model of the JWST is shown below and it is clear that the design is extraordinary, and at first sight, rather odd-looking. But the structure – and much else besides – is driven by these two requirements.

JWST and people

Requirement#1: Gather more light.

To gather more light, the main light-gathering mirror in the JWST is 6.5 metres across rather than just 2.5 metres in the HST. That means it gathers around 7 times more light than the HST and so can see fainter objects and produce sharper images.

1280px-JWST-HST-primary-mirrors.svg

Image courtesy of Wikipedia

But in order to launch a mirror this size from Earth on a rocket, it is necessary to use a  mirror which can be folded for launch. This is why the mirror is made in hexagonal segments.

To cope with the alignment requirements of a folding mirror, the mirror segments have actuators to enable fine-tuning of the shape of the mirror.

To reduce the weight of such a large mirror it had to be made of beryllium – a highly toxic metal which is difficult to machine. It is however 30% less dense than aluminium and also has a much lower coefficient of thermal expansion.

The ‘deployment’ or ‘unfolding’ sequence of the JWST is shown below.

Requirement#2: Improved imaging of infrared light.

The wavelength of visible light varies from roughly 0.000 4 mm for light which elicits the sensation we call violet, to 0.000 7 mm for light which elicits the sensation we call red.

Light with a wavelength longer than 0.000 7 mm does not elicit any visible sensation in humans and is called ‘infrared’ light.

Imaging so-called ‘near’ infrared light (with wavelengths from 0.000 7 mm to 0.005 mm) is relatively easy.

Hubble can ‘see’ at wavelengths as long as 0.002 5 mm. To achieve this, the detector in HST was cooled. But to work at longer wavelengths the entire telescope needs to be cold.

This is because every object emits infrared light and the amount of infrared light it emits is related to its temperature. So a warm telescope ‘glows’ and offers no chance to image dim infrared light from the edge of the universe!

The JWST is designed to ‘see’ at wavelengths as long as 0.029 mm – 10 times longer wavelengths than the HST – and that means that typically the telescope needs to be on the order of 10 times colder.

To cool the entire telescope requires a breathtaking – but logical – design. There were two parts to the solution.

  • The first part involved the design of the satellite itself.
  • The second part involved the positioning the satellite.

Cooling the telescope part#1: design

The telescope and detectors were separated from the rest of the satellite that contains elements such as the thrusters, cryo-coolers, data transmission equipment and solar cells. These parts need to be warm to operate correctly.

The telescope is separated from the ‘operational’ part of the satellite with a sun-shield roughly the size of tennis court. When shielded from the Sun, the telescope is exposed to the chilly universe, and cooled gas from the cryo-coolers cools some of the detectors to just a few degrees above absolute zero.

Cooling the telescope part#2: location

The HST is only 300 miles or so from Earth, and orbits every 97 minutes. It travels in-to and out-of full sunshine on each orbit. This type of orbit is not compatible with keeping a gigantic telescope cold.

So the second part of the cooling strategy is to position the JWST approximately 1 million miles from Earth at a location known as the second Lagrange point L2.

At L2 the gravitational attraction of the Sun is approximately 30 times greater than the gravitational attraction of the Earth and Moon.

At L2 the satellite orbits the Sun in a period of one year – and so stays in the same position relative to the Earth.

  • The advantage of orbiting at L2 is that the satellite can maintain the same orientation with respect to the Sun for long periods. And so the sun-shade can shield the telescope very effectively, allowing it to stay cool.
  • The disadvantage of orbiting at L2 is that it is beyond the orbit of the moon and no manned space-craft has ever travelled so far from Earth. So once launched, there is absolutely no possibility of a rescue mission.

The most expensive object on Earth?

I love the concept of the JWST. At an estimated cost of $8 billion, if this is not the most expensive single object on Earth, then I would be interested to know what is.

But it has not been created to make money or as an act of aggression.

Instead, it has been created to answer the simple question

I wonder what we would see if we looked into deep space at infrared wavelengths.”. 

Ultimately, we just don’t know until we look.

In a year or two, engineers will place the JWST on top of an Ariane rocket and fire it into space. And the most expensive object on Earth will then – hopefully – become the most expensive object in space.

Personally I find the mere existence of such an enterprise a bastion of hope in a world full of worry.

Thanks

Many thanks to Jon Arenberg  and Stephanie Sandor-Leahy for the opportunity to see this apogee of science and engineering.

Resources

Breathtaking photographs are available in galleries linked to from this page

 

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


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