Thinking Problems - Transmission

This is a follow-up to Thinking Problems – Lab Leak.  One could have thought that, by now, the issues of COVID would have faded into the background, but no.  Misinformation about the COVID vaccine is still circulating.

In discussions with JP, there was a common claim that “they” had said that the vaccine would prevent transmission.  For example, in August 2021, JP was housebound because he was worried about a local outbreak.  I asked about his vaccine status and his reply indicated that there would have been little consolation in having a second jab if he could still spread it.  A month later he was claiming that the “initial focus was on preventing spread”.

The problem is that the issue is very complicated.  I know that I am going to overly simplify things here, but I do so with the intent of getting past an apparent blockage on the part of some of the more conspiracy minded among us.

For a virus-based disease, there is sequence of events somewhat like this:

When thought of like this, it is clear that having a vaccine cannot help with certain stages.  You are either exposed or you are not.  With infection, that’s more a question of whether you ingested the virus or not.  Here things are a bit blurry because there is you and there are your cells.  There is also the virus and there are virions.  It’s possible that a virion (one particle of the virus) got into you, but did not enter a cell (thus infecting it) before being excreted or destroyed.  Did you (the human) get infected by the virus?  You certainly got closer than if you were merely exposed to the virus (ie sitting in a room in which virions were floating around in the air that you breathed, but you didn’t happen to breathe in one).

What about if one or a few of your cells did get infected, but your immune system immediately identified the threat and destroyed the infected cells before they could set up their virus replication process?  You didn’t contract the disease, your body as a whole didn’t get infected, but you were partially infected.

What about if you did get widespread infection of cells by the virus, your immune system swung into gear mounting an effective response, but you never got any symptoms – meaning that, strictly speaking, you never developed the associated disease?  This is non-symptomatic infection, which in hindsight appears to have happened with considerable frequency.  Usually, being non-symptomatic means you are not contagious.  But not always (as the Typhoid Mary case demonstrates).

I am going to just highlight a grey area between infection by the virus and development (or contraction) of the disease.  For the purposes of this argument, I am counting disease as including the non-symptomatic who produce enough virions to be contagious.

If viruses didn’t cause disease, we probably wouldn’t care about them.  It is worth noting though that not all the symptoms of an infection are due to the pathogen (virus or bacteria) per se – some of them are the immune system fighting against the infection (fevers for example).

The job of a vaccine is to prepare the immune system for fighting a specific pathogen (or suite of pathogens).  The better prepared the immune system is, the less likely it is that the disease will take hold.  This can range from preventing symptoms entirely, making the symptoms less severe and reducing the time that it takes for the immune system to eliminate the disease.

Viruses are particularly nasty because they take over the cells of hosts and redeploy them to replicate virions.  It’s rarely a friendly take-over, with the replication machinery set to keep working until the cell bursts, releasing thousands of virions which go on to infect new cells.  Quickly, the body is riddled with virions which then get into various liquids in the body, including those in the lungs, meaning that when an infected person breathes out, there are virions lurking in droplets that we inevitably spread about us.

This is transmission in the schema above.  The virus effectively uses us to spread itself around us in a fog of about 1.5-2 metres (as is most visibly noticeable on a cold day).  But note that transmission does not mean reception (exposure or infection).

If you have a viral disease, the only way to prevent transmission is to prevent droplets getting out and to another person.  The right sort of mask, when worn properly, can do that.  Or keeping away from others (social distancing).  Or not going out in public (isolating).  The vaccine will not help you, if you already have the disease.  Your having been vaccinated will also not help you if it is not you who has the disease, it won't stop stop someone else transmitting.

What the vaccine will do is increase the likelihood, if you get virions into your body, that your immune system will prevent an infection progressing to disease, reduce the seriousness of the disease if you can't prevent it (and possibly reduce the number of virions you produce that can then be transmitted to someone else) and shorten the period in which you have the disease (and are contagious).

In that sense, the vaccine can certainly minimise spread of the disease.

But it will never prevent contagious people from transmitting the virus, nor will it necessarily prevent you developing some form of the disease if you are infected (although it's much more likely to be mild, or even asymptomatic, rather than severe).

That’s not to say that there aren’t sterilising vaccines or other treatments –that are hugely effective and prevent you from producing virions if treated.  It’s simply that the covid vaccines were never advertised as those.  The effort was all about preventing severe disease, which is why they are described as COVID-19 vaccines not SARS-CoV-2 vaccines.

Thinking Problems - Lab Leak

This is Fu (it's his name in PowerPoint).  He's our nominal Patient O (also sometimes styled as 0, or Zero) for Covid-19, caused by the virus SARS-CoV2.  Behind him is a potential other person in the chain, we can call him Fu2, he's a hypothetical intermediate human carrier of the virus who didn't come down with Covid-19 - who may or may not exist.  As they collectively are the portal of the virus into humanity, we can just refer to the Fu/Fu2 nexus as Fu, just keeping in mind that there may have been that human-human mechanism right at the start.

We don't know how Fu got infected with SARS-CoV2, but there are some theories, indicated by the lines.

It could be entirely natural, noting that there are some variants of that, some of which have the virus being shared between different animal vectors as it evolved (some of which might have been human).  That's what the additional dotted box means.  Fu interacted with an animal in the wild, at a market or somewhere else that had the virus and got Covid-19.

SARS-CoV2 could have been genetically engineered in a lab and then Fu could have been deliberately infected with it.  This would imply that SARS-CoV2 had been developed as a biological weapon.

Alternatively, there could have been infection from a petri dish, test tube or surface in a lab where the virus was being genetically engineered, as a biological weapon, in a gain of function effort to develop better methods for treating coronaviruses more widely (vaccines, retrovirals, and the sort) or just out of scientific curiosity (i.e. pure research).

Finally, there could have been a crossover from an animal infected with SARS-CoV2 that was being treated, dissected, studied or whatever in a lab.  This may have been with the intent to develop a biological weapon, or do some gain of function for benign reasons, but in this case there had not (yet) been genetic engineering carried out.

Note that the purple arrows are pointing at the boxes, not any of the other arrows.  The amount of evidence for each event is nominal, the size of the bubble could also relate to the quality of evidence, rather than a mere quantity.  Note that it's evidence, not proof.  Some evidence might support multiple possibilities.

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I think I have captured all the possibilities being thought of seriously.  Even if there is some bizarre vector, like aliens or the New World Order doing the genetic engineering and deliberately injecting Fu, this still falls into the category "Genetic Engineering".  Same with a god doing it, it's just that the technology would be different (supernatural genetic engineering).  If there is something that I have missed, I am more than happy to go through it and try to weave it in.

Note that even with genetic engineering, there was still a natural origin of the base virus that was being fiddled with.  So, there is naturally going to be a lot of evidence for natural origins.  I'm not really thinking about evidence that supports all cases, just delta evidence.  Those cases are (arrow type):

• purely natural – Natural Origins→Fu (large red)
• simple leak from a lab – Natural Origins→Leak from a Lab→Natural Origins→Fu (small orange)
• deliberate infection – Natural Origins→Genetic Engineering→Fu (tiny grey)
• complex direct leak from a lab – Natural Origins→Genetic Engineering→Leak from a Lab→Fu (large green)
• complex indirect leak from a lab – Natural Origins→Genetic Engineering→Leak from a Lab→Natural Origins→Fu (small blue) – so we can think of zoonosis as “natural”, in a sense, even if the virus were to be tinkered with at some point.

There is one other that I identified after I put the image together, namely Natural Origins→Leak from a Lab→Natural Origins→Fu.  The notion here is that the virus was transferred from where it normally is (in a bat, in a cave, somewhere in southern China) to a lab and gets into another animal (pangolin, civet cat or one of those adorable raccoon dogs), and then that other animal becomes the vector for transmitting SARS-COV2 into humans.

There is also the possibility of a pre-SARS-COV2 virus being carried from a lab to the animal (via an intermediate human infection), with mutation(s) then happening in an animal or range of animals – resulting in a variant that became known as the Wuhan strain of SARS-COV2.

I’m not specifying a lab, although there are two candidates that seem more reasonable than any others given the location of the first outbreak – Wuhan Institute of Virology and the Wuhan Centre for Disease Control (about a quarter of a kilometre from the Huanan Seafood Market [also variously known as the Huanan Wholesale Market and Huanan Wholesale Seafood Market]).  It’s somewhat less likely that any leak occurred at another of the many labs in large cities in China and then got carried to Wuhan to break out there.  About as likely as Chinese authorities deliberately releasing a deadly virus on the doorstep of their major virology institute.

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The problem, as I see it, is that the light blue ellipse encompasses what some people refer to as a "lab leak", also indicated by the larger green arrow – implying genetic engineering in a lab with an accidental release, possibly of a biological weapon but, at the very least, some questionable gain of function research.  Then they take any evidence that there might have been a leak from a lab as evidence for genetic engineering, which it isn't.

I suspect that there's a similar problem on the other side in that initial discussions of a "lab leak" included the assumption that it encompassed both a leak from a lab and genetic engineering, so they weren't counting direct transmission from an animal to a human inside a lab (or even just a SARS-CoV2 sample from an animal, onto a surface or into a test tube and thence to a human) as a "lab leak".  So they were saying that a "lab leak" was considered extremely unlikely where, in reality, a leak from a lab is entirely possible and they should have said more clearly that genetic engineering is extremely unlikely (for various reasons) but not entirely impossible.

It isn't helped by the fact that dog-whistles are used on both sides, and the one term sometimes means quite different things.

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If something seems unclear, please let me know.

The Death of Nuance

 On 20 Jul 2023, Alex Gutentag, Leighton Woodhouse and Michael Shellengberger published a piece titled Covid Origins Scientist Denounces Reporting On His Messages As A “Conspiracy Theory” (archived) which contains links to two documents, one containing Slack comments and the other containing emails between Kristian Andersen, Andrew Rambaut, Edward C. Holmes, and Robert F. Garry – the authors of “The proximal origin of SARS-CoV-2” (archived pre-print | published).

 

The existence of this was hinted at by JP (of climate denial fame, see earlier posts that started in earnest at Ice Extent Challenge).  He didn’t, of course, just say “interesting piece at this website”.  Oh no, it was a single SMS, “And now we have covid-gate.  Grist for the mill.”  I actually thought it was a joke.  Unfortunately no.  About two hours later I dug a little and found the article mentioned above.

 

And, naturally, he wasn’t going to actually read the slack messages and emails.  He’s too busy, but he was nevertheless convinced that the paper (The proximal origin of SARS-CoV-2 – let’s call it “Proximal Origins” as Shellenberger etc do) should never have been published.  He wasn’t even going to read the paper (although he later said he had skimmed it and knew the main conclusions, which on cajoling he summarised as “Lab leak is bunkum. Only explanation is zoonotic source”).

 

Ok.  So, I am not going to go into detail of why it’s probably better to look at original documents than rely on videos that come up in your YouTube feed.  This post is about the death of nuance.

 

JP is all about nuance.  There’s no grand conspiracy, it’s all social contagion, social pressure.  You just need to listen to the heterodoxes for your serving of truth, but you need to be discerning because sometimes even the most brilliant people might say something that isn’t 100% true.  So, you know, nuance.

 

My view on nuance is a little different.  Things are complicated.  Some things we simply can’t know.  Sometimes we know that we can’t actually know something for sure, but we can take a balance of probability approach.  The story which by necessity involves large groups of people acting together to deliberately and effectively hide the truth from us is probably not the real story – even if you can convince yourself that they are doing this organically rather than deliberately.

 

JP is also into narratives, whereas I prefer to deal in facts, despite knowing that sometimes those facts are not available.

 

And that is a problem.  I worry that this sort of big reveal by Shellenberger and friends, like the University of East Anglia email saga (also known as Climate-gate) will have a chilling effect on research, and the discovery/confirmation of facts.

 

Science works best if there is an open exchange of ideas, including bad ideas and partially developed ideas and preliminary ideas.  Get the ideas out there, discuss them, test them and ditch those that don’t stand up to scrutiny.  Sometimes, possibly rarely though, what initially seem to be bad ideas turn out to be really good ideas, the sorts of ideas that revolutionise science.

 

In this instance, there were a few credible ideas about where Covid came from – directly from bats, from bats via another animal, from culturing of a natural virus in a lab (and then accidental release) and from genetic engineering of a virus in a lab (and then accidental release).  Plus some much less credible ideas – deliberate insertion of HIV into the virus (release mechanism unclear), deliberate engineering and release of the virus to target white (and black) people, and so on.

 

In the early weeks of Covid, the authors of Proximal Origins discussed the possibility of a lab leak.  They actually favoured a lab leak as the origin.  But as evidence mounted, they changed their minds and began to favour natural origin, without declaring the lab leak impossible.  Proximal Origins was pre-published almost a month before the declaration of a pandemic.  Even the formal publishing was less than a week after that declaration (and had been in the works for a while before that).

 

The authors did not know for sure, at that time, that Covid would become a pandemic, nor that it would be as serious a pandemic as it came to be.  The signs were there and I recall, perhaps erroneously now, that I thought it was going to be a pandemic well before the official announcement – at the very least I had set up a spreadsheet and was already tracking the numbers as early as 10 February 2020 and I had never done that before.  But nevertheless, it was very early days when the Proximal Origins authors started putting together the paper.  This was a very good time to be considering all options, discussing furiously what seemed to be a good idea to you and what ideas from others seemed to have massive holes in them.

 

However, if scientists know or fear that anything they say, in semi-private Slack chats, or emails, might be picked apart by hostile bloggers and commentators … they may well stay silent.

 

This won’t necessarily sound a death knell to all scientific collaboration, since it’s still possible to talk in person or over the phone, but as I said, it could have a chilling effect.  It’s often the case, for me at least, that it helps to get my thoughts down on paper, or in pixels, rather than trying to engage in a discussion which can often be hijacked by some other interest of the day (much as the intro to this post was, who the hell is JP after all? what do you care?)  I think many of us would lose a lot if we were badgered into not writing anything down for fear of some moron using it against us in the future.

 

A move away from being able to share ideas openly over email or other recorded mechanisms will only hurt us – all of us.

 

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And is there anything worrisome in the Slack messages and emails?  No, it’s just some guys talking about their work and one joke about the French.

Atomic Tea

There is at least one complaint made by my climate denialism curious friend, JP, that is valid.  Some elements of the media are guilty of catastrophising.

 

I can understand why they do it, to a certain extent – they are selling papers, or magazines, or advertising airtime, or clicks, or eyeballs, or bums on seats etc etc.  The complete and accurate truth is, in at least one sense, not primary.  If the complete and accurate truth got them the outcome there are after, then they would be all for it, but still only as a means to an end, not as the end itself.  Even non-commercial media has to report viewer numbers, or levels of engagement, making them more and more like the commercial outlets with their click-baity headlines and sensational content.

 

The most recent example that I have read, at time of writing, is a piece by the Australian ABC, talking about how bad 2020 was.  I think we call all agree that 2020 was pretty bad but this article was focussed on something that has not been foremost in our concerns for a while – the climate.  The climate is still there, even if it’s largely outside and many of us have been locked inside more than usual.  And it’s still on a bit of a slide.

 

The article in question did highlight something of considerable concern, namely that the “world's oceans absorbed 20 sextillion joules of heat due to climate change in 2020 and warmed to record levels” (referencing a paper that has “temperature” in the title, but not so much in the text).  For context, it’s worth considering what NOAA have to report.  They talk about this in terms of a “heat content anomaly” measured against the average for the period 1955-2006 in the top 700m of (ocean) water:

Note that a sextillion (or zetta) is 10²¹, so don’t let the fact that this is sitting just under 20x10²² confuse you.  Things are a little more clear in another chart (lower on the same page).

It does seem like 20 zettajoules in a year is a bit of a spike, but there are ups and downs, so we really should be thinking about the trend, which is a bit over 160/27 = ~6 zettajoules per year.  Still not great.

 

The most egregious statement, in my view, is that 20 zettajoules is equivalent to the release of 10 Hiroshima grade atomic bombs each second.  That’s more than 300 million bombs, or slightly over two bombs for every square kilometre of land surface on the planet which, even if it happened only once in a year, would be enough to make that a worse year than 2020.

 

(For those keeping score, the Hiroshima bomb, “Little Boy”, is calculated to have released between 50 and 75 terajoules.  If we say it was 63 terajoules [15 kilotons], then you would indeed need very close to 10 bombs per second for a year to reach 20 zettajoules.)

 

It’s very scary to think of so many atomic bombs going off and one could well imagine that this was intention of the writer.  It’s also probably pretty scary to imagine that amount of energy being added to the oceans, since it’s the heat in oceans that cause the sort of storms that can do so much damage to coastal regions and it’s simple to imagine that more energy equals either more storms or stronger storms (or perhaps both).  Whether there is such a simple link? … perhaps, perhaps not.  Oil extraction companies have upgraded their drilling platforms, so perhaps they think there might be.

 

I wondered, however, how much energy we expend each year on hot drinks?  To make it easier, I am going to limit it to tea and assume that for tea, one boils fresh water from room temperature (293K) to boiling (373K) without markedly affecting the density of said water.  I am also going to assume one drinks from a standard cup at 0.24 litres.  So, a litre of fresh water weighs one kilogram and the heat capacity of water is 4.2kJ per kg per K.  Conveniently, this is very close to 1kJ per cup of water per K and since the temperature difference is 80K, we expend 80kJ on boiling water for each cup of tea (assuming no wastage).

 

The question then is how many cups of tea do we, as humans, drink?  World Tea News (yes, there is such a thing) has the answer, conveniently in terms of cups per second – 25,000 cups.  That means that we expend about 2 million kilojoules per second on tea.  This is somewhat short of a sextillion, but we are thinking in terms of Hiroshima grade atomic bombs, each at 63 terajoules.   A terajoule is 10¹² joules, so one bomb is equivalent to 31437 seconds of tea preparation, which is one bomb every 8.7 hours, or very close to 1,000 bombs a year.

 

I am reasonably certain that the average English person would be willing to accept 1,000 bombs a year in order to have a good cup of tea.  What, on the other hand, would be patently ridiculous is to express the energy used to prepare tea in terms of atomic bombs.  I have a nagging feeling that the same applies to the amount of energy absorbed by the oceans.

 

Perhaps the author of the article (and the original paper) could have assisted by expressing the temperature change that would be caused by the 20 zettajoules being absorbed by the oceans.  If we make some assumptions, we can get a rough idea.  The ocean surface is about 360 million square kilometres.  The paper was referring to a depth of water of 2,000 metres, but not all the ocean is that deep, and beyond a certain depth (the epipelagic zone) there really isn’t much variation in the temperature, so we could make a rough calculation using an average of 600 metres depth, which is in the middle of the mesopelagic zone, so we have an ocean volume of 2.17x10¹⁷ m³ and given that there are 1000 litres in a cubic metre and it takes 3850J to raise a litre of seawater by 1K, that’s about 0.024K a year or 0.24 degrees per decade.  Note that this is very rough calculation, but it’s in the same order as what NOAA are reporting (at climate.gov) where they say that temperatures have been rising at 0.18 degrees per decade since 1981.  If we use 800m, which is towards the bottom of the mesopelagic zone, the result is very close to 0.18K per decade.  I doubt that that figure is right though, since that’s the average since 1981, and today’s figure is likely to be higher (although maybe not as much as a full third higher).

 

If anyone knows what the actual average temperature increase of the ocean was, please let me know.  Looking at the heat content chart (1955 through to 2020) overlaid on the temperature chart (1880 through to 2016), it looks like it’s probably gone up:

The Very Model of Climate Change Concern

A friend of mine, JP, started all of this when writing:

If you were to ask me 2 years ago what my key understandings were about climate change, I would have said the following:

Sea ice is rapidly shrinking (summer arctic sea ice to be gone by 2015)

Sea levels are rising and accelerating

Polar bear populations are under stress (have increased in the last 20 years)

The levels of glacial retreat around the world are unprecedented (similar retreats have been seen in the last century)

97% of scientists agree that global warming is real and an urgent problem

Any scientist who is skeptical about the claims made about climate change is a "denier" and is funded by oil/resource companies

We are seeing an increase in extreme weather events (they are actually getting less common)

Climate models are accurate in their predictions 

Every one of those things is either totally false, or a largely exaggerated claim.

This is the eighth in a series based on my response, which itself was split over a few emails.  The first was Ice Extent Challenge (in which I provided a little more context about JP) and was followed by Sea Levels Rising, Polar Bears and Climate Change, Glacial Retreat, A Worry of Climate Change Scientists, Denying Denialism and Weathering a Storm of Climate Denial.  Some of the issues may also be touched on in a series of articles on the nature of climate denialism.  Please also note the caveat.

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JP’s Claim: The statement “Climate models are accurate in their predictions” is either totally false or largely exaggerated

Note that JP is most familiar with statistical modelling.  JP has modelled demand on a supply chain and it’s amazingly accurate.  Based on statistical data from previous years, and possibly a whole suite of data that I am not aware of, JP can get very close to current demand.  It’s brilliant stuff.  However, it should also be noted that climate models are not, repeat NOT, and – just to make this perfectly clear – climate models are NOT statistical models.  They are models of physical processes.

I’ve long been of the opinion that models are never entirely accurate, no matter what sort of model they are, and that the only completely accurate model of the universe is … the universe.  This applies also to systems that are smaller than the universe, even though processing power necessary to do the modelling decreases significantly as you approach more human-sized scales.

You don’t need to take my word for it, you can just consider the three body problem.  Start with two bodies in otherwise empty space that are acting on each other gravitationally, say a star and a planet.  They will orbit the centre of their combined mass with a speed and separation that is inversely proportional to their relative mass (the heavier body will have a smaller separation from the centre of the combined mass than the lighter one, they will share the orbital period and thus the lighter one will have a higher speed having a greater distance to cover – with something as massive as a star compared to a planet, ).

Then consider three bodies, specifically two stars and a planet – like Tatooine:

Note that the planet orbits the pair of stars, since it’s the light one of the three-some.  This is not solvable analytically, it can only be solved numerically, meaning that you have to plug the figures in an run the problem (like at the link).  Now in the second program window, if you fiddle with the code to make one of the stars more than twice as heavy as the other, something strange happens (at a factor of 2.2):

At higher values, the binary stars lose the planet entirely (pretty much immediately at a factor of 3).

Now imagine trying to predict where the planet in the image above will be after 50 years.  It’s easy enough to run the simple program and find out, but you have some issues that are going to affect your results.  How accurate is your value of G?  How accurate are your masses?  How accurate were your initial conditions (speed and direction)?

Your inaccuracy in any of these figures are going to affect your results and that’s when you are assuming a spherical cow.  The bodies in question are not perfect point masses, they are two balls of gas and … a planet, which might be a third, smaller ball of gas or a conglomeration of rocks – and we are assuming only one single rock in the system.

The upshot of this is that we can predict with great accuracy where the planets in our solar system will be in the short term, but have no idea where they will be in 100 million years – and it’s not that we just haven’t worked it out yet but rather that, at that longer scale, the solar system is chaotic.

Now consider a model involving 10⁴⁴ gas molecules (the atmosphere), interacting with 10 million cubic kilometres of water (admittedly only the top layer of it, so more than 350 million square kilometres times the average significant depth, whatever that is) and just under 150 million square kilometres of land surface which is covered variously by deserts, forests, ice, mountains, lakes, grasslands and, relatively recently, cities and towns.  Then factor in the vagaries of the sun, which has its own cycles which do affect us (for example with solar minima, grand or otherwise) and all the different products that end up in the atmosphere (CO2, methane, aerosols, water, etc).

Climate models don’t even bother trying to be accurate.  Instead, they do what is call parametrisation, breaking the planet up into gridboxes – the size of which vary depending on the precise application (and the computing power available).  The smallest gridboxes are usually in the range of about 5km, with clouds sometimes being modelled at 1km – and this is way too coarse for most clouds.

Even at the finest parametrisation used today, there will still be inaccuracies inherent in the model.  These are expected and discussed with an eye to minimising them (see “Are Climate Change models getting better?” which starts on page 824 at the linked document).  In part because the models are never perfect, the IPCC and climate scientists in general talk about trends and projections rather than predictions.  The trend observable in all the models across the standard scenarios (RCPs 2.6, 4.5, 6.0 and 8.5) is that the more you increase the amount of CO2 in the system, the more the temperature rises.

Again, you don’t need to take my word for this.  The outputs of the models are freely available (admittedly they take some time to figure out).

I compared the results against the temperature measurements available from NASA and NOAA which, without a model overlay, looks something like this:

Once I converted to absolute (rather than anomaly) values and corrected for an oddity in starting temperatures, the HADGEM2-ES model results look like this:

Be very careful about just accepting this though.  I don’t understand the starting temperature oddity, but basically not all models had the same temperatures at the beginning of the run, or the same date for the beginning of the run.  I fixed for that and used this model as an example because, without that correction, the results were offset by about 0.2 degree (noting that I used an RCP8.5 run).  The corrections I made did not change the trend, they just shifted the entire yellow line up a bit.  Additionally, I don’t know precisely what was fed into the model.  They seem to have included some volcanoes (which pump aerosols into the atmosphere and push down the temperature for a short period) and anthropogenic aerosol production seems to be accounted for, but this is just guesswork on my part.

With those caveats in mind, this is what the results look like from a raft of models (note that HADGEM is not in this one, so the yellow line represents output from a different model):

There’s a range of about a degree between the models, and about four of them are consistently higher than the measurement (although, prior to my adjustment, they were all below so perhaps I’ve messed it up somehow – and that messing up could be contributing to the spread as well) … but note that the overall trend is precisely the same.  Over the period 1880-2020, there is a rise in temperature of about a degree – which is consistent with the measurements.

Therefore, noting that the models are not expected to be wholly accurate, indicating temperature rise in pretty much precisely what we have experienced, and that they provide projections rather than predictions, JP is simply wrong when claiming the climate change models predictions projections are inaccurate.  They are a lot more accurate than one might have predicted.

Weathering a Storm of Climate Denial

A friend of mine, JP, started all of this when writing:

If you were to ask me 2 years ago what my key understandings were about climate change, I would have said the following:

Sea ice is rapidly shrinking (summer arctic sea ice to be gone by 2015)

Sea levels are rising and accelerating

Polar bear populations are under stress (have increased in the last 20 years)

The levels of glacial retreat around the world are unprecedented (similar retreats have been seen in the last century)

97% of scientists agree that global warming is real and an urgent problem

Any scientist who is skeptical about the claims made about climate change is a "denier" and is funded by oil/resource companies

We are seeing an increase in extreme weather events (they are actually getting less common)

Climate models are accurate in their predictions 

Every one of those things is either totally false, or a largely exaggerated claim.

This is the seventh in a series based on my response, which itself was split over a few emails.  The first was Ice Extent Challenge (in which I provided a little more context about JP) and was followed by Sea Levels Rising, Polar Bears and Climate Change, Glacial Retreat, A Worry of Climate Change Scientists and Denying Denialism.  Some of the issues may also be touched on in a series of articles on the nature of climate denialism.  Please also note the caveat.

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JP’s Claim: The statement “We are seeing an increase in extreme weather events” is either totally false or largely exaggerated and “they are actually getting less common”

There are two factors here which need to be extracted – the frequency of extreme weather events and the severity of extreme weather events.  JP’s parenthetical codicil seems to indicate that it’s a question of frequency while, from my reading, it’s more about severity.

Then there is the question of timing.  Is it merely about historical records, about which you think there would be little controversy?  Or is it about the projections produced by climate modelling?

If it’s related to climate modelling, then we must consider both the accuracy of the models and the accuracy of the data.  It’s quite possible that models, especially earlier models, have been inaccurate in their projection of extreme weather events – underlying assumptions may have been wrong, our understanding of the physics may have been immature, parameterisation may have been too coarse and the data input to the models is unlikely to have been absolutely correct (for instance there will be rounding of datapoints).

In IPCC report AR5 Part A, there is reference to Severe Storms:

Severe storms such as tropical and extratropical cyclones (ETCs) can generate storm surges over coastal seas. The severity of these depends on the storm track, regional bathymetry, nearshore hydrodynamics, and the contribution from waves. Globally there is low confidence regarding changes in tropical cyclone activity over the 20th century owing to changes in observational capabilities, although it is virtually certain that there has been an increase in the frequency and intensity of the strongest tropical cyclones in the North Atlantic since the 1970s (WGI AR5 Section 2.6). In the future, it is likely that the frequency of tropical cyclones globally will either decrease or remain unchanged, but there will be a likely increase in global mean tropical cyclone precipitation rates and maximum wind speed (WGI AR5 Section 14.6).

Note that this IPCC report is a key reference document with respect to climate change.  It basically collates evidence from 9200 peer-reviewed studies and concludes that climate change is happening, that climate change is due to human activity and that the effects of climate change (both current and future) are worth worrying about.  Per Wikipedia, the principal findings were:

General

·        Warming of the atmosphere and ocean system is unequivocal. Many of the associated impacts such as sea level change (among other metrics) have occurred since 1950 at rates unprecedented in the historical record.

·        There is a clear human influence on the climate

·        It is extremely likely that human influence has been the dominant cause of observed warming since 1950, with the level of confidence having increased since the fourth report.

·        IPCC pointed out that the longer we wait to reduce our emissions, the more expensive it will become.

Historical climate metrics

·        It is likely (with medium confidence) that 1983–2013 was the warmest 30-year period for 1,400 years.

·        It is virtually certain the upper ocean warmed from 1971 to 2010. This ocean warming accounts, with high confidence, for 90% of the energy accumulation between 1971 and 2010.

·       It can be said with high confidence that the Greenland and Antarctic ice sheets have been losing mass in the last two decades and that Arctic sea ice and Northern Hemisphere spring snow cover have continued to decrease in extent.

·        There is high confidence that the sea level rise since the middle of the 19th century has been larger than the mean sea level rise of the prior two millennia.

·        Concentration of greenhouse gases in the atmosphere has increased to levels unprecedented on earth in 800,000 years.

·        Total radiative forcing of the earth system, relative to 1750, is positive and the most significant driver is the increase in CO
2's atmospheric concentration.

Models

AR5 relies on the Coupled Model Intercomparison Project Phase 5 (CMIP5), an international effort among the climate modeling community to coordinate climate change experiments. Most of the CMIP5 and Earth System Model (ESM) simulations for AR5 WRI were performed with prescribed CO2 concentrations reaching 421 ppm (RCP2.6), 538 ppm (RCP4.5), 670 ppm (RCP6.0), and 936 ppm (RCP 8.5) by the year 2100. (IPCC AR5 WGI, page 22).

·        Climate models have improved since the prior report.

·        Model results, along with observations, provide confidence in the magnitude of global warming in response to past and future forcing.

Projections

·        Further warming will continue if emissions of greenhouse gases continue.

·        The global surface temperature increase by the end of the 21st century is likely to exceed 1.5 °C relative to the 1850 to 1900 period for most scenarios, and is likely to exceed 2.0 °C for many scenarios

·        The global water cycle will change, with increases in disparity between wet and dry regions, as well as wet and dry seasons, with some regional exceptions.

·        The oceans will continue to warm, with heat extending to the deep ocean, affecting circulation patterns.

·        Decreases are very likely in Arctic sea ice cover, Northern Hemisphere spring snow cover, and global glacier volume

·        Global mean sea level will continue to rise at a rate very likely to exceed the rate of the past four decades

·        Changes in climate will cause an increase in the rate of CO2 production. Increased uptake by the oceans will increase the acidification of the oceans.

·        Future surface temperatures will be largely determined by cumulative CO2, which means climate change will continue even if CO2 emissions are stopped.

The summary also detailed the range of forecasts for warming, and climate impacts with different emission scenarios. Compared to the previous report, the lower bounds for the sensitivity of the climate system to emissions were slightly lowered, though the projections for global mean temperature rise (compared to pre-industrial levels) by 2100 exceeded 1.5 °C in all scenarios.

The IPCC report is by no means a climate denial document, but even so, it states that the number of tropical cyclones (including hurricanes and typhoons, which are basically the same thing in a different geographical location) will either decrease or stay the same and it’s only the severity that might increase, with increased global mean windspeed and precipitation rates.  The only quantitative statement I could find on cyclones was this (page 247): “In the tropics, the intensity of cyclones is projected to increase 2 to 11% by 2100, which may increase soil erosion and landslides (Knutson et al., 2010).”  Given the timescale involved, it would be unsurprising if there was little or no indication of an increase in cyclone severity in the recent past.

It should be noted that cyclones have a maximum potential intensity and thus a maximum windspeed (about 100 m/s or 360 km/hr), but so far the top speed measured was 345 km/hr in 2015.  (Prior to that, the record was 305 km/hr in 1980.)

Therefore, even if the ocean is warming and that provides more energy to spin up cyclones, then there’s still going to be an upper limit.   It would be reasonable think though that a warmer ocean would power a storm for a longer period and a greater proportion of storms would reach Cat 5.

There is a problem associated with assessing the number and severity of storms, related to the news cycle.  The whole world will hear about a storm that affects the US for days, but rarely will we hear anything about any storm that wipes out small, remote islands without a large tourist trade.  The Union of Concerned Scientists did however report an increase in hurricane activity in the North Atlantic:

Note that there is a downwards trend for hurricanes that reach the US.  The total number of hurricanes appears to be about even (on average) or perhaps increasing, but only by a little.  The data there says nothing about strength though, or duration of the storms.  The same organisation reports that there does not seem to be an increase in hurricane activity across the world, with about 90 per year, mostly in the Pacific.  NOAA report basically no change in the number of storms and their models predict fewer storms, but these storms would produce more precipitation, they would be more intense and more of them would be Cat 4 or 5.  This is also a bit hard to track, I don’t know if they bother recording a storm if it doesn’t reach land, but I am going to go out on a limb and say that they pretty much all do (reach land that is because a cyclone just keeps getting stronger while over a warm sea and will only lose power if it ends up over land or cooler water).

Looking at the records for the Atlantic, there were 2 Cat 5 in the 1950s,  (6 in the 1930s, but there don’t seem to be records for the 40s), 4 in the 60s, 3 in the 70s, 3 in the 80s, 2 in the 90s, 8 in the 00s, and 6 in the 10s.  They seem to be getting stronger, with 5 out of 6 being at 280km/hr or less in the 30s and 4 out of 5 being 280km/hr or more in the 10s, the most recent being 295km/hr (beaten only by Allen in 1980).  There’s an oddity in that in the past, there is a correlation between pressure and top windspeed, generally the lower the pressure, the faster the wind – but in the 2010s, all of the storms had higher pressures despite the wind being fast (recent slower storms were all quite short lived as a Cat 5, half an hour, three hours and six hours – these were basically ambitious Cat 4 hurricanes that didn’t really have the legs to become a proper Cat 5).

I don’t know whether there is enough data there to make any conclusions.  But if we look at Cat 4 hurricanes (in the Atlantic), we see:

Which does seem to have a distinct trend to it.  If we did something similar with Cat 5s, it would look like this:

Which again appears to have something like a trend to it.

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Going back to JP, it was claimed that the statement “We are seeing an increase in extreme weather events” is either totally false or largely exaggerated and “they are actually getting less common”.

This just does not seem to be true.  There appears to be about the same number of severe storms, cyclone or hurricanes, but there is a distinct increase in the number of both Cat 4 and Cat 5 cyclones.  NOAA reports “that, after adjusting for such an estimated number of missing storms, there remains just a small nominally positive upward trend in tropical storm occurrence from 1878-2006. Statistical tests indicate that this trend is not significantly distinguishable from zero.”   They conclude: “In short, the historical Atlantic hurricane frequency record does not provide compelling evidence for a substantial greenhouse warming-induced long-term increase.”  That would indicate that the increase in Cat 4 and Cat 5 storms is at the expense of less intense storms, or rather those storms that do happen are more likely to be intense.

This, in any rational interpretation, means that we are seeing an increase in number of extreme weather events and, on average, weather events are becoming more extreme – although it is conceded that the number of weather events themselves are not necessarily increasing in number.

Therefore, with regard to weather events, the evidence does not support JP’s claim.