Who’s to Blame for our Changing Climate?

The term 'smoking gun' is often brought up in reference to climate change, a quick google search reveals that this phrase has been thrown around in climate circles at least for the last 20 years or so. Often, the 'smoking gun' is a reference to some single, unrefutable piece of evidence that might finally silence climate change deniers, such as the rising levels of CO₂ (e.g. by Julia Slingo, Chief Scientist of the Met Office). However, for most people carbon dioxide levels in the atmosphere are not particularly tangible while, for example, the floods afflicting the south-west of England last winter or the record summer seen in Austria and Slovenia are much more visible and closer to our everyday experiences. Attributing events like these to climate change is not always simple though; after extreme weather events there may be debate regarding whether the event (or the scale thereof) can be attributed to the effects of climate change; perhaps these might just be part of natural climate variability? Such discussions rarely result in any kind of satisfactory answer for the media and, I suspect, the general public. The reason for this is not, as commonly claimed, that a single event cannot possibly be attributed to any root cause (although this is largely true) but rather that natural climate variability and climate change are not separate. Any trend in overall climate variables (e.g. temperature) will underlie the natural variability and it is this that makes global warming so dangerous. It has been repeatedly said (largely as a joke) that an extra degree or two might make the weather in [insert country/state/county here] more bearable. However, this simplification of the global warming trend discounts the variation which has existed and would exist without any warming (or cooling) trend.

An increasing temperature moves climate variability with it.

In this image (taken from climatecommunication.org) you can see how temperatures vary around a central, average temperature^*. A shift in average temperature (which is what climate change/global warming implies) shifts the entire distribution to the right, i.e. towards hotter temperatures. That means that weather events that might exist in this portion of the plot...

  ... which were once the extreme end of the distribution, now become far more common. So attributing a weather event to climate change means that we are saying it falls in the red part of this inset plot, rather than the orange. We are not able to definitively do that. What we can do is measure the number of times that extreme events occur and see how that compares with our plot of variability. A new record temperature is bound to occur at some point, when a record temperature is reported as being a 1-in-1000 year event, that means we only expect a temperature that high to occur once every thousand years. If a temperature that high were to happen tomorrow, it is possible (likely even) that it was just random chance that it occurred when it did. However, if it happened again the month after, that looks a little suspicious. If we were to reach that temperature again in two years, then again in another 10, then we begin to cast real doubt on our definition of 1-in-1000 year event. Either our statistics and/or model were wrong in the first place, or the system has changed.

The evaluation of how often certain weather events should occur is a type of risk analysis. By analysing the number of times that events occur, we can say how likely they are to happen in the future. Given enough data, we can even say what the contributing factors to those events are. For example, the NHS and other medical institutions can evaluate the risk of developing lung cancer. Given data about the lifestyles of the people who do develop it, it is possible to draw correlations between factors such as smoking and the incidence of the disease. After further investigation it is possible to more firmly establish these links and therefore we can say that there are different risks of lung cancer for smokers vs non-smokers and what these risks are. The important thing to remember here is that these are probabilistic risks, we have all had a great aunt or other relative who smoked 80-a-day and lived to a ripe old age. At the same time, there are many unfortunate people who live exemplary, healthy lives, who will contract lung cancer nonetheless. These people represent the natural variability of this system, while the people who smoke have shifted the distribution of probability towards contracting lung cancer.

Having described this kind of analysis in perhaps too much detail, I can get to the point of this post - the study by Sophie Lewis and David Karoly, researchers at the University of Melbourne in the overwhelmingly appellated 'School of Earth Sciences and Australian Research Council Centre of Excellence for Climate System Science'. They have performed an analysis like that I've described for the extreme summer of 2013 in Australia. I'll link to the paper itself here, published in the journal Geophysical Review Letters, although I'm not sure about paywalls, etc. - apologies if it's not readily available to you.

Lewis and Karoly performed an extensive analysis using suites of models to determine exactly how likely the extreme heat seen in the summer of 2013 in Australia would be in the natural (no human contribution) course of events and then again with human contributions included. They extended this further to include the RCP8.5 emission scenario (covered in a previous blog here) running forward to 2020.

The Australian 'Angry Summer' of 2013 saw record-breaking temperatures on a daily, as well as seasonal basis with the all-time record holders for hottest day and hottest month occurring. By running large numbers ('ensembles') of climate models, some of which included human contributions to emissions and some which didn't, Lewis and Karoly were able to evaluate the probability that these contributions would result in such an extreme summer. In addition to their paper, the authors have published two blogs which sum up their findings very well here and here. Here they publish their plots which illustrate their findings that human contributions have increased the likelihood that the 'Angry Summer' would occur by a factor of five. The plots below show how models incorporating natural as well as anthropogenic contributions reveal dramatically increasing probabilities of raised temperatures when evaluated from 2006 onwards.

Probability distribution of average temperaturevariations across Australia in summer from observations (dashed line) and climate model simulations (solid line) for 1910-2005. The vertical lines mark the temperature departures for 1998 summer (the second hottest) and 2013 (the hottest) summer across Australia/ Lewis & Karoly

As above, but showing the shift in the probability distribution for 2006-2020 from climate model simulations including increasing greenhouse gases and other human influences on climate. Lewis & Karoly

It is worth digging into these results a bit, they are explained thoroughly by the authors in the paper and summarised well in their blog postings so I'm not going to repeat what they say. What is worth showing here is the spread of their model results. I think the plot below shows something that is often missing from statistical reports, climate or otherwise.

Australian annual temperature changes (relative to 1911-1940 average) for observations (dashed black) and model simulations with natural influences only (green) and with both human and natural influences (red). The grey plumes indicate the range of values simulated across nine global climate models used. Average Australian temperature anomalies are indicated for 2013 and the previous hottest year on record in 2005. David Karoly & Sophie Lewis

What this plot shows is not only the results from the various models (green showing climate variability arising from natural contributions only, red including human emission contributions) but also what the spread in those models looks like (in grey). This is very important as it is easy to see from the variation in observed temperatures that, for any given year, the red line and green line aren't really separated by more than we might expect from natural variations anyway. The grey spread of model results shows us that the green line, representing the 'natural' state, is now right on the edge of the feasible range predicted by our models. This means that we are now entering a period in which it is impossible (statistically) to account for current weather trends without incorporating the influence of human emissions. Australian Prime Minister Tony Abbott is fond of quoting the poet Dorothea Mackellar in her description of Australia as 'a land of droughts and flooding rains' in dismissing possible climate change. However, it has become completely untenable to ignore the changing climate in that country. Climate change deniers, who once might have charitably been called skeptics have descended into the realm of conspiracy theory. I won't link to any sites because I'd rather not give them any traffic but it is all too simple to search online (or simply look in the comments of legitimate blog posts) for climate change in Australia and find sites, no longer able to refute scientific findings, which now simply accuse scientists of falsifying data, proactively as well as retroactively.

One of the more legitimate plausible explanations for high temperatures in Australia is the El Niño Southern Oscillation (ENSO), which has been regularly linked to higher than average temperatures in the Pacific. It is true that the second hottest summer in Australia to date (1998) may well owe some of its heat to ENSO. However, 2013 was essentially an 'ENSO - neutral' year and so the record temperatures were almost certainly unaffected by it.

One last thing to mention about Australia's extreme climate (changing or not) is the absolutely phenomenal amount of rainfall experienced there in the last few years. In the two years preceding the 'Angry Summer' Australia was subject to exceptionally heavy rainfall, this time perhaps linked to an El Niño/La Niña event. While attributing this heavy rainfall to human influences is more muddled than with the record temperatures, I reiterate my earlier point that we can no longer take 'natural variability' in isolation from anthropogenic global warming. My main reason for bringing the rainfall is that I was struck by the fact that so much water fell on Australia in those two years that sea levels ceased to rise. Andrew Freedman blogs here in detail about this topic, the main gist being that the 3.2 mm/year sea level rise that has been observed for decades plateaued for an 18 month period correlating with the rains falling in Australia. The explanation posited in this study is that the particular geography of Australia prevented much of this water returning to the oceans on short timescales - therefore taking water from the oceans without returning it.

^*This is a bit simplified, this temperature distribution shows an essentially Gaussian distribution. There are good reasons why real temperature distributions might not be Gaussian but that's another story for another time... The general principle here will still stand.

Solar Panels and Tofu

Just a quick post today, it would be nice to pretend that I can contribute to this blog often and regularly but that's not always possible. Heard this neat story on Inside Science and so wanted to throw it up on the blog as it doesn't seem to have been very widely reported anywhere else.

Solar panels have, in theory at least, the potential to have a massive impact on our renewable energy consumption. While solar panel efficiencies have been climbing fairly steadily over the last few decades concerns have been raised regarding the toxic materials used in the manufacture of the solar cells. There are actually several areas in which the environmental impact of the life-cycle of solar panels may be less than ideal, as outlined here. However, the toxicity of some of the components (or materials used in the manufacture thereof..) seems to have been cause for widest concern, especially when it relates to the disposal of old solar panels.

There was good news on Wednesday for those of us who worry about such things when Jon Major of Liverpool University published a paper in Nature (link here, not sure about paywall access, etc). The paper claims that the toxic cadmium chloride used to 'activate' the solar cell (increasing the energy efficiency from less than 2% to more than 10%) can be simply and easily replaced with magnesium chloride, a compound typically used bath salts and in the manufacture of tofu.

Jon Major himself is quoted here as saying “The problem is cadmium telluride [sic]* itself is a highly toxic compound," Major said. "It’s been linked to genetic defect, and if it gets into the water supply, it can poison fish for generations.” The toxicology report for cadmium, which includes reports on cadmium chloride, makes for some fairly scary reading, detailing interstitial pneumonitis, diffuse alveolitis, fibrosis, increased lung weight, reduction in body weight, focal interstitial thickening, oedema, pulmonary haemorrhage and emphysema in rats exposed to cadmium chloride.

Not only is a reduction in the overall toxicity of the solar cell production process good news for the environment but, by using a naturally-occurring substance which will allow for a significant reduction in the costs of handling and disposal of materials, the overall cost of production will be brought down.

While there are still other environmental problems relating to the use of solar panels, including other toxic/hazardous materials, it is cheering to see that progress is being made. It is good to remember that many renewable energy sources are still in relatively early days as far as development is concerned. Ongoing research is constantly improving the methods and materials used in solar, wind and water power (not to mention fusion reactors).

A small aside I wanted to mention, having heard it reported recently (seems like a lot of my posts recently have been inspired by Radio 4, I'm clearly of a certain demographic these days!) is the rather strange legal situation home-owners might find themselves in in the UK. It is now fairly common for people to effectively lease their roof to a solar panel company in return for free electricity and installation of the solar panels, which remain the property of the company that market them. These sounds like a pretty good deal to begin with. However, there are rather harsh ramifications when it comes to re-mortgaging or selling the home, given that the solar panel company is now effectively a tenant on your roof! Certainly not a reason to not get some solar panels installed but good to be aware of.

*not sure if this is a typo/misquote or perhaps Jon Major simply mis-spoke, cadmium telluride is actually rather stable and not very soluble. Provided that it is disposed of correctly, it's pretty safe and, given the context I believe he meant cadmium chloride not telluride.

D-Day and the Met Office

If I were being glib (and I often am) then I might have titled this post 'How the Weather Won the War'. However, I find it hard to be glib about war, particularly World War II. Perhaps it's memories of my grandfather, who fought a role in the war that went far beyond the stories he told me as a child. More likely it is simply the staggering loss of life that I am now better able to comprehend. Certainly, I am sobered by the realisation that the work I now do may once have contributed to one of the most important battles ever fought.

If ever there was an example of high-pressure meteorology then it must have been the weather forecasts made by the chief meteorological officer for Operation Overlord, Group Captain James Stagg on and around June 4th 1944. Though, to see a picture of the guy, he looks like he could probably handle it. That steely glare was presumably captured at some other time than the 4th of June though when he wrote in his diary 'I am now getting rather stunned - it is all a nightmare'.

Stagg was responsible for advising Eisenhower when D-Day (variously referred to as the largest seaborne, the largest amphibious and the largest just plain old invasion of human history) would go ahead. The requirements placed upon Stagg were that the day be close to a full moon and that low tide be at or around dawn. So far, so good, a reasonable almanac and/or calendar would be able to supply that information. However, it was also necessary that winds be light, that conditions be no worse than slightly cloudy (30% coverage below 8,000 feet) and that visibility be more than three miles. These conditions are considerably harder to predict and forecasting them, particularly 70 years ago, is an error-prone business.

Sian Lloyd has written a great piece at the Huffington Post which lays out the order of events which came from James Stagg's predictions, including his advice that the operation not go ahead on the 5th, as planned. Instead, on the night of the 4th, Stagg told Eisenhower that there should be a break in the otherwise unsettled weather on the morning of the 6th. This break in the weather was not predicted by the Germans and so German intelligence had decided that a landing would be unlikely on that day.

It is likely that James Stagg would have known that the Germans failed to predict the break in the weather as he had access to observations coming from the Germans themselves. Weather reports originating from German U-boats were encoded by the Enigma machine and, thanks to the deciphering done by Bletchley Park these reports were now readable by Allied forces. An intriguing sidenote, given the meteorological theme here, is the vital role that weather reports played in the Allied capture and decoding of the Enigma code. It was Harry Hinsley, working at Bletchley Park, who reportedly realised that German weather trawlers must be able to decode Enigma messages and so must have code books aboard. This realisation led directly to the attack of one of these trawlers and the capture of a code book.

The fact that Group Captain Stagg had access to German weather reports may well have led directly to the success of the Normandy landings. However, it was weather coming from the west that was most crucial to the D-Day landing decision and so it certainly helped that an observation network was in place providing data from reconnaissance aircraft as well as ships at sea. While ships were supposedly restricted by a radio silence order, it has been speculated that weather reports were sent in via messenger pigeon. All of these observations contributed to the hand-drawn charts used at the time for forecasting. The chart from the day itself is available (upon request) at the Met Office library and is a remarkable piece of scientific history. Seeing the chart, which admittedly looks like almost any other synoptic chart, makes one feel the weight that history placed on that single sheet of paper. Not only that but the responsibility that those scientists that drew the chart bore for being absolutely correct in their determinations. Quite frankly, I think I would prefer the astronomical observations I'm more familiar with, I am unable to think of a single situation in which anyone's life has been placed at risk due to my mis-calibration of GBT data!

Weather charts from both the Allied and Axis forces for June 6th, 1944 are shown below. Note how the Allied chart contains observations covering Germany while the German chart contains none of Britain. The entire outcome of World War II may well have come down to the simple superiority of our knowledge about the weather.

Allied weather chart for 6th of June, 1944

Axis weather chart for 6th of June, 1944

There is a webpage hosted by the Met Office itself with some embedded videos which go into detail regarding the interpretation of the weather charts and what the contributing factors were at the time. If you are interested in some of the finer details of the meterology involved here then I advise you to go here.

I think it is worth pointing out the role that women meteorologists played in these predictions. Although there were no women forecasters until 1947 Wren meteorologists were stationed with the other navy staff at Portsmouth collectively responsible for drawing the D-Day planning charts and other work. It was often roles such as these chart-drawers and the 'Harvard Computers' that were 'allowed' to be filled by women and lay the groundwork for a future which includes female Lego scientists(!) While I have mainly focussed on James Stagg in my post, it should be remembered that there were other contributors to the forecasts that decided that the Normandy invasion should go ahead. They too, must have surely felt the gripping tension James Stagg did when he wrote 'Fair interval confirmed, invasion put on "Final and Irrevocable Decision". Whatever the outcome the decision is taken.'

The next possible window for the planned invasion was to be two weeks later, at the next suitable tides. Stagg later wrote to Eisenhower that, had the landing been delayed until that day, the troops would have met the worst weather in the region for 20 years. Eisenhower wrote back - 'Thanks, and thank the Gods of war we went when we did'.

Why the world cup will/won't be predicted by computer modelling.

You may have recently heard about attempts to predict the results of the upcoming World Cup in a scientific way. Although it's not mentioned explicitly the calculations by Stephen Hawking and Goldman-Sachs (GS) are the results of statistical modelling. Fortunately for me, this ties in well to a blog post I already wanted to write about just this subject.

The online betting company Paddy Power has employed Stephen Hawking for a month in order to calculate the probability that England will win the world cup. A more general aim of evaluating the overall outcome of the world cup has been undertaken by GS. I heard Peter Oppenheimer of GS interviewed last Thursday morning by John Humphrys and the interview in general was a really good example of the problems with the public perception of probability and statistics. The interview should be available for the next few days at least here and the bit I'm referring to was slightly before 7 am if you're trying to pinpoint it.

The interview consisted largely of Peter Oppenheimer explaining the details of their model, which include the past goal-scoring history of each team (as might be expected). Some more subtle analysis included the under- or over-performance of those teams at previous world cup tournaments as well as home vs away games. Hawking's analysis allowed for more intricate inputs, such as the height above sea level for the match. However, Hawking was approaching the problem from a different perspective, analysing the prospects of a single team, while GS were modelling the entire competition and the relative placings of every team.

  What I found particularly blog-worthy about the Radio 4 interview was the attitude of John Humphrys. Humphrys, along with his radio 4 compatriot Melvin Bragg are exceptionally intelligent men and yet they are often dismissive of vital aspects of the scientific method. I am dragging Bragg into this because I have heard several episodes of In Our Time which have a scientific theme in which he happily confesses his ignorance of maths and science to his guests. This disregard would be very poorly received if it related to a knowledge of British history, for example. However, numerical and scientific theorems do not appear to warrant the same level of esteem.

  I digress, in the interview Humphrys was incredulous of Oppenheimer's World Cup predictions. Notably he said something like 'I don't even follow football, yet I can probably tell you the four teams that will end up in the semi-finals' (apologies if this is horribly paraphrased, I am unable to listen to the interview again at the moment). Implying perhaps that the work by GS was worthless as it only told us something that could be guessed at by a layman anyway. There are two important points here. Firstly, I think that this misses the point entirely. The phrase that springs to mind is 'when you do something right, people won't be sure you've done anything at all' (if anyone can trace this quote back further than the Futurama link I've pasted please let me know!).  Humphrys statement actually shows us that there is really an intuitive element to probability which isn't always evident, especially when it comes to some of the more esoteric results of probability theory, such as the still-argued-over Monty Hall problem. If a layman can predict the four teams to reach the semi-finals of the World Cup 2014, why scoff at attempts to do the same thing in a numerical, analytical manner? Why does John think he can predict the semi-finalists? Because he is aware that Brazil, Germany, Argentina and Spain are probably the best teams in the world, even if he gained this awareness through osmosis, something very easy to do, at least in the UK. Why are these teams the best (or perceived to be so)? Because they win a lot, meaning that they have good, measurable goal scores and differences - exactly the kind of variable that is input into the GS model. Even I, as a complete football luddite, know that Brazil are extremely likely to beat the U.S. at 'soccer' (no offence U.S.). This is because I have been brought up with images of Pelé as the messiah of football while there's only a grudging willingness to acknowledge the participation of the U.S. in the same sport because, you know, at least they give it a go.

  The second point I want to make is that I think Humphrys misunderstands the language of probability that Oppenheimer is using. I think that this represents a fundamental lack of public understanding of probability. Scientists understand that very few hypothesis can ever truly be ruled out completely and so may appear vague or uncertain about their findings. This allows scientific theories to be cast as 'doubtful' when they are, in fact, remarkably certain.

  We (or at least John Humphrys) seem to have some inbuilt desire for our models to be 'deterministic', meaning that there will be an exact, predictable outcome. The alternative being presented by GS is for a 'probabilistic' result. The difference between these two interpretations is rather philosophical and so somewhat loosely defined, this is probably (heh) why it's not easily digested by the public at large. A glib explanation of this difference comes from the Terry Pratchett book 'The Colour of Magic' in which a character flips several coins. The deterministic philosophy would lead us to expect that half of the flips land on heads while half land on tails, in the book what happens is that four of the coins land on the coins' edge while another turns into a caterpillar. While it's unlikely that a probabilistic analysis of coin flipping could predict these outcomes, it may be able to account for a very slightly weighted coin, or perhaps a coin flipper who consistently puts the coin a particular way up before flipping. Either of these elements (and more) could contribute to the outcome of a coin flip being other than 50:50. This might actually be important to you if you really care about the outcome of 1,000 coin flips. Worse, you might care about the outcome of the World Cup, particularly where England are involved. That might mean you care about El Niño and its intensity this year, not because there's some spooky coincidence between that intensity and how well England perform but because a strong El Niño might make it hot and dry in Brazil during the competition, probably not a good thing for footballers who are used to playing in the cold and wet.

Our ability to model things like El Niño or, heaven forfend, the entire Earth climate, depend on things that have far more effect on outcomes than a slightly weighted coin or a sneaky flipper. They depend on things like knowing the sea temperature in the middle of the pacific and how exactly that temperature varies with the depth of the ocean. Even our best measurements of such quantities are subject to errors as banal as being mistyped by a sleepy meteorologist or as sophisticated as rounding error in a big-endian vs little-endian machine. These errors have the potential to grow and lead to larger and larger effects. When climate modelling reveals emergent properties that have large effects, such as hurricanes, it becomes vitally important that those properties are not being unduly amplified by errors in your inputs. For an excellent overview of how climate modelling works in just this context see Gavin Schmidt's TED talk, 'The Emergent Patterns of Climate Change'. Of course, when running models as complex as climate modelling, essentially trying to recreate the entire Earth system with computer simulations we have to bear in mind that 'garbage in = garbage out' and that if our measurements are not at least correct on average then our model is likely to be meaningless (though possibly still informative). Knowing that it is perfectly possible that errors do creep in though, enables us to be probabilistic about our analysis. For example, we want to be absolutely sure that, when we are looking at our climate model we are not looking at that tiny fraction of coin flips that land on the edge (or turn into a caterpillar). We can do this by running our climate models again and again and then analysing the results of all of the different simulations in a statistical way. It is for this reason that scientists cite a percentage likelihood that an event will occur. Rather than hedging their bets, they are simply telling you how many times a certain event will occur, given certain conditions. This may be seen as dodging the question but it is actually an attempt to be utterly transparent and honest about results.

The statistician George E.P. Box wrote that 'essentially, all models are wrong, but some are useful'. This summarises beautifully our inability to fully recreate complex systems in simulations, we can only extrapolate and interpret.

Something in the Air

A lot happens at the Met Office that goes largely unreported upon. For example, planting transmitters on seals to measure sea temperature might not be the first thing to cross your mind if you were asked what the Met Office actually does. As I listened to a talk this week about tracking the spread of atmospheric particles I realised that this was something else that would fall under this umbrella. Time for a blog post!

The talk was by the Atmospheric Dispersion and Quality (ADAQ) group who are responsible for some very interesting aspects of the MO services like supporting the emergency services in the event of civil contingencies like chemical fires, radioactive accidents, volcanic ash and animal and plant health. This is achieved through the use of NAME - the Nuclear Accident ModEl, one of the more outrageous examples of acronym abuse I've come across.

NAME was developed by the MO following the Chernobyl disaster in 1986 when weather conditions conspired to spread the released radioactive particles across Europe, including the Welsh hills. How exactly this happened can be seen in the model image below.

Since then, NAME has been through multiple iterations, capable of predicting the transport, dispersion and chemistry of atmospheric particles. If you're interested in the gritty (haha) details then I can tell you that it does this through the modelling of core atmospheric processes such as turbulence, deep convection, deposition & sedimentation^* and chemistry. If you want to know exactly how it does that then here would be a good place to start.

^*material removed from atmosphere by transport to, and uptake by the ground. Gravitational settling, rain 'washout' (material is brought down to ground by rain), rain absorption (precipitation forms around particles directly).

The latest generation of NAME is NAME III and this has been used extensively in recent times to track the effects of the Fukushima Daiichi nuclear disaster, the second event ever to reach the highest rating of 7 on the International Nuclear and Radiological Event Scale. Research into the health effects of the Fukushima disaster is ongoing, incorporating the results of NAME's model analysis.

NAME is supported by many tools which work over different scales, interesting in various ways. In order of increasing scale over which they function:

• PACRAM (Procedures And Communications in the event of a release of Radioactive Material) gives little information generally but the main priority is to be fast so as to advise emergency services, etc. on possible hazardous directions or areas to avoid in the event of a UK nuclear power plant event.

• RIMNET (not sure if this is a really convoluted acronym or just a name...) a Met Office-managed project in partnership with DECC and DEFRA. A country-wide network of gamma radiation detectors (isn't this a plot device from the Avengers?!) which allow the UK to monitor background radiation levels. All measurement and reference data is stored in the UK National Nuclear Database.
• Regional Specialized Meteorological Centers and the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) give the international radiological response. The CTBTO (actually a preparatory commission as the treaty is not yet law) are tasked with establishing and developing a worldwide network which monitors the planet for nuclear explosions. This network is reportedly 85 percent complete at the time of writing.

One of the more useful aspects of atmospheric modelling is that it can be run backwards to establish the source of an atmospheric feature. For example, if a non-reported nuclear event were to occur, this can be traced back to its source through inputting current observations into the NAME model.

This feature has proved particularly useful in disease control such as in the outbreak of  Legionnaires Disease in Edinburgh in 2012. Not only can the model predict the spread of airborne bacteria and so inform the public and authorities if certain areas are at particularly high risk but, once an infection has been found, the model can be run backwards to see where the bacteria might have originated from in the first place. Useful again in the case of animal and plant health. The Met Office has been researching the spread of Foot and Mouth Disease since the 1960s, again through the dispersion in the atmosphere of airborne particles originating from infected pigs.

There is more use to this than might be immediately obvious, vaccines are often limited in amount, especially in the case of a sudden outbreak. By identifying the likely spread of diseases, the vaccines can be distributed in a targeted way.

There are yet more applications of this technology and, to be honest, I wasn't particularly familiar with them before the talk. I'd heard of 'Ash dieback', apparently spread on the small scale (up to 10s of miles) by windborne spores but what has apparently been called the 'polio of wheat', UG99, is also the subject of Met Office research.

The front line of the climate change battle, as viewed from a safe distance…

Since starting to work for the Met Office I have been able to have a front row seat when some interesting new science is announced. Recently the Intergovernmental Panel on Climate Change (IPCC) released their fifth assessment report. This was reported pretty widely in the Guardian, the BBC and various other places and so I'm probably not bringing much to the table in talking about it now. However, the announcement and its content relates well to some of the wider themes I'm trying to explore in this blog and, as I'm experiencing some of the science first-hand I thought that I could write something worthwhile about it.

In case you want to go and read the original report, it is here. This is actually only one of four reports coming from each of three working groups and a synthesis report. The report I'm referring to is the WGI report which focusses on the physical science behind climate change and this is arguably the most important as it is this science which the other working groups build on. WGII concentrates on 'Impacts, Adaptation and Vulnerability' while WGIII takes on the problem of climate change mitigation.

The fact that the report exists at all (the IPCC AR5 WGI report to give it its full name) is amazing to me. The entire report is summarised in a trifling 14,000 word Summary for Policy Makers, in which every single sentence has been agreed upon by all 101 countries in attendance. Having spent literally months in meetings of five people simply trying to decide whether or not to buy a treadmill for the work gym I would be stunned if you told me that 101 countries had managed to agree on what time to have lunch.

One of the messages climate scientists are told to convey to the public is that there is an extremely strong consensus amongst scientists regarding the science behind climate change. I think that, if anyone truly still believes that human-driven climate change is a contentious subject, they should reflect on the fact that 101 countries could all agree on a report that unequivocally states that this is the case.

Not only does the report's existence refute the idea that intergovernmental bodies are unable to make any progress, it is also a remarkable testament to the power of peer review. In my last post I gave an example of peer review that shows how it can be a time-consuming, unsatisfactory process for all involved. That was for a paper involving only five authors and three referees. The WGI report involved 259 authors covering 14 main chapters utilising 1,089 reviewers who gave 54,677 comments.

The summary of the report, the Summary for Policy Makers, contains only robust science, agreed upon by all the attendees as well as the relevant scientists. I have it on good authority that there was less political motivation involved than might be expected. Certain oil-producing countries did apparently make every effort to stress the uncertainties inherent in the science of the report. However, while this is presumably politically/economically motivated, it can only lead to more robust findings. These findings have been boiled down to a single page (well, two sides) of the headlines which are kept here but, in case that still seems like a bit much, the climate scientist Professor Thomas Stocker has boiled these down to three main messages

• The evidence for climate change is unequivocal
• The role of human influence in climate change is clear
• The limiting of climate change will require substantial carbon reductions

If you're the kind of person who likes plots and can interpret them easily then this one should give you a fairly hefty amount of information.

  What this shows is how much warming we might expect (y-axis) as a function of how much CO₂ eventually ends up in the atmosphere (x-axis). This is presented for multiple potential scenarios referred to as 'RCP's. 'RCP' stands for Representative Concentration Pathway and relates the emission of greenhouse gases to the 'radiative forcing' that would result from that emission. There's a pretty good summary with all the detail you could probably ask for here but I'm going to leave 'radiative forcing' very loosely defined here as the difference between the heat energy received by the Earth (from the Sun) and the amount of energy radiated back into space. In a system in equilibrium this would be zero, with no overall warming or cooling resulting. We know that this value is not zero for the Earth at the present time and that is why it is warming. What the different trajectories followed by the different RCPs can tell us is what the eventual extent of the warming will be. The RCPs can also allow us to plan our emissions so as to take this into account. For example, the Copenhagen Accord (2009) stated that a temperature rise of 2°C or above would lead to 'dangerous climate change'. Of our four presented RCPs, the only one which would allow us to stay below a rise of 2°C (by the year 2100) is the RCP2.6. It is pretty much accepted that this is not going to happen. To follow RCP2.6 all man-made carbon emissions would have to cease today, a scenario I think we can all agree is unlikely (I apologise if this is hyperbole or a gross oversimplification, I am attempting to keep things non-technical and reasonably concise). Further, if you're sharp-eyed you may notice that the RCP2.6 pathway on the inlaid plot in the above figure goes into negative numbers meaning that, not only would carbon emissions have to decrease substantially, we would have to actually start removing carbon from the atmosphere via carbon capture or geoengineering. Scenarios which are now reportedly accepted by those within the UK government.

At the other extreme is RCP8.5 pathway, generally known as the 'business as usual' pathway. This is the scenario under which we continue to burn fossil fuels with absolutely no mitigation whatsoever. As you can see from the plot, this would lead to the Earth exceeding the 2°C milestone in something like 25 years. Whether we even have the resources to continue burning fossil fuels at our current rate for that long is a separate question but, as oil and gas become more scarce, they become more expensive leading to the techniques used to acquire them becoming more cost-effective, fracking being a case in point.

While it is somewhat unsettling to accept that climate change is now unavoidable, even at dangerous levels, I have found that scientists in the field are, if not upbeat, then at least somewhat positive. This positivity appears to be more of a recent development and it appears to be due to the fact that governments are actually listening these days. The fact that the IPCC AR5 reports even exist are a testament to that. At the Met Office I have been pointed towards five key components of our communications regarding climate change

1. Climate change is happening
2. This is largely due to us
3. Overall it will be bad
4. Scientists overwhelmingly agree on above
5. There are many things we can do about above and we're free to argue about what

It is this final point that I think is responsible for the trend towards positive attitudes in the climate science community. The government department responsible for energy is now also responsible for our actions on climate change and it is their mission to take action on this front. Their stated vision is for the UK to have made a safe and secure transition to a low carbon economy. Take that with as many pinches of salt as you wish but I believe that there is at least an attempt to take the issue seriously. I think that it also helps that the projected scenarios regarding climate change are veering away from the drastic and towards the affordable. While accepting some warming and slowly weaning ourselves away from fossil fuels is not the ideal solution for many people, it is far more palatable to government ministers who have to soothe the worries of economists and energy companies.

The framing of climate change mitigation as 'affordable' and, more importantly, possible, may not place enough emphasis on the dangers of global warming and exaggerate our ability to deal with them. However, it does allow those in power to do something, which is always preferable to nothing.

Publishing in Science and Peer Review

As I stated in my last post, I wanted to write something about how my last astronomical paper went through the publication process. As promised, here is the second part of that post.

Part II

A question often asked by a scientist's friends and family is 'what do you actually do?' A pretty fair question really, especially as many of us only get to be career scientists through the support of the government and thus the tax payer. The truth is that, most often, scientists are writing papers. A (largely) complete description of an experiment, the results and some analysis/summary based on those results. Scientists are always writing at least one paper because this is what we are really judged on, really, to a degree that would probably astonish you.

Getting these papers published means submitting them to peer review, something pretty much any scientist can tell you is a fairly painful process. We have all at some time created a work of art, a piece of writing, a meal or anything at all that is then subjected to some level of criticism. For some people this is a more personal and profound experience than for others. It is easy to imagine that a painter or playwright may feel quite affected by a series of poor reviews of their work. It may be somewhat harder to imagine that scientists often go through a similar experience.

The process of peer review has grown from the earliest ideas that any judgement may be best done by a collection of your peers. In the 18th century this idea began to be applied to the publication of scientific results. As early as 1731 scientific results were being distributed amongst individuals deemed by the editor to be worthy to evaluate them. The idea being not so much that peer review could police fraudulent results or the like but simply that a filter was in place to help guide the editors towards relevant and interesting results. It is almost certainly a coincidence but only one year earlier a tightening of control over judicial peer review was also put into place.

The utopian model of peer review is one in which the journal you want your paper published in is run by a 'benevolent dictator' of an editor. This editor would be all-knowing, all-wise, fair, ethical and, above all has the time and energy to read and evaluate my paper along with the thousands of others submitted every year. This actually wasn't far from the case when Albert Einstein himself published his 'Annus Mirablis' papers in 1905. Each of Einstein's 'Miracle Year' papers was read and reviewed by Max Planck himself, the associate editor of Annalen der Physik at the time. Max Planck was the genius physicist on whose work Einstein had based his first paper and who would later win the Nobel Prize himself.

These days papers are doled out by the editors (or sub-editors) to referees whom they deem to be experts in the field. I have received papers myself to review, although that is another story for another time, and I don't intend to criticise this process. After all, Churchill's quote on democracy is particularly apt here in that peer review may arguably be a horrible process but it does have the advantage of being better than any others that have been tried.

Once an article has been placed with a referee, that referee evaluates it and submits a report, along with one of three recommendations.

1. Firstly, that the journal should accept the article 'as is'; this does actually happen, although extremely rarely.
2. Secondly, that the article should be accepted, though some revisions should be made first. This is the most common result in my experience, particularly when this recommendation is subdivided further into decisions ranging from 'major revisions with subsequent review' to 'minor revisions with no subsequent review'.
3. Finally, an article may be outright rejected if it is considered to contribute nothing of any publishable value and/or be so poorly written that a complete rewrite is necessary.

I should point out that this entire process is anonymous, at least from the side of the author. The person reviewing my work knows who I am (I flatter myself, I mean that they know my name at least) while they remain anonymous to me.

As I alluded to in my last post, my most recent paper took a great deal of time to publish. The reasons for that are many, some of which are my own fault, some are just happenstance and some are the fault of the journal (in my opinion). I submitted the paper just before Christmas 2012 with high hopes that this paper would draw a little attention, enough perhaps that I might be able to score a job interview or two off the back of it. I had certainly invested enough time and effort into it and, at over 40 pages at the time it was hefty enough to be recognised as a solid body of work.

The paper came back with a substantial referee report. We took this report seriously and worked through the suggested revisions, resubmitting the paper in early April. At this point I was still hopeful that the paper would get out quickly and be useful in my ongoing job-hunting. A further referee's report came back, again fairly substantial, although this time the report asked only for some moderate revisions. The editor told us at this point that the referee was happy with the paper assuming that we took care of the second set of revisions and that they didn't want to review it a third time. We received assurance from the editor that, so long as we were conscientious about our revisions, the paper would be accepted and published with our next submission.

So, thinking we were on the home straight, I took care of the changes and resubmitted the paper. At this point the editor, without consulting us, forwarded the manuscript to another referee altogether. This was unexpected, especially considering that the editor had specifically told us this wouldn't happen. We were a bit taken aback by this turn of events but not particularly worried, given that we had already been through two revisions of the paper.

This is where the random and capricious nature of the peer review process struck. The second (anonymous) referee rejected our paper outright with a fairly cursory explanation as to why. Given that the paper now represented over two years of work on my part I was understandably upset. Challenging this resulted in a rather hostile statement that the paper did not present results worthy of publication. This seemed a rather odd thing to say after the paper had already been under review for eight months and had been essentially accepted, even praised by the first referee. We were able to win an agreement to send the paper to a third, deciding referee. This referee was sympathetic to both previous reports and suggested re-writes of their own to make the paper somewhat more concise. At this point the paper had been 'in the works' for nearly eight months and I was in the middle of a move (both in career and location) and my wife's pregnancy. All of the impetus of the paper had been taken away and so it took a good deal of time to make yet another set of revisions and resubmit the paper. This was done 13 months after its first submission, when it was finally accepted.

I hope that this kind of experience is rare but I do believe that the journals and editors need to look carefully at their processes. In a field in which publication is so vital to the careers of the submitting authors it seems irresponsible to take less than the utmost care and diligence in publishing their works. In the scientific realm scientists are supposed to be above reproach when presenting their results. Falsifying data is one of the most heinous academic crimes possible and, along with plagarism, about the only things one can do to have their PhD revoked. I think that editors should be held to similar standards and that misleading authors and/or delaying the publication of results (intentionally or not) are arguably just as serious.

I'm not sure of the point of blogging this story, maybe it's just to complain about the peer review process. Perhaps I just want to get a dig in at the editors that held up my paper when my attention should have been elsewhere. In the end I'm just trying to give an impression of some of the pain that a scientist goes through when trying to get their work published. It is not an easy process and, akin to writing or other artistic processes is rife with criticisms and other obstacles. It seems that the public's perception of science is that it has a clear answer, things are right or they are wrong. If this were the case then publishing scientific results would be a much easier process, a paper would be right or wrong and could be published or rejected. As it is, it often comes down to a friendly or hostile editor combined with a friendly or hostile referee (or a majority of such!) to decide whether or not you will be published and how quickly. When your career can depend on these decisions it might be just as well to let the criticisms go and, like any endeavour, have faith in your work. You will know the effort that you have poured into it and you will know what that is worth, even if others don't always recognise it.