Putting Climate Change Claims to the Test

This is a full transcript of a talk given by Dr John Christy to the GWPF on Wednesday 8th May.

When I grew up in the world of science, science was understood as a method of finding information. You would make a claim or a hypothesis, and then test that claim against independent data. If it failed, you rejected your claim and you went back and started over again. What I’ve found today is that if someone makes a claim about the climate, and someone like me falsifies that claim, rather than rejecting it, that person tends to just yell louder that their claim is right. They don’t look at what the contrary information might say.

OK, so what are we talking about? We’re talking about how the climate responds to the emission of additional greenhouse gases caused by our combustion of fossil fuels. In terms of scale, and this is important, we want to know what the impact is on the climate, of an extra half a unit of forcing amongst total forcings that sum to over 100 units. So we’re trying to figure out what that signal is of an extra 0.5 of a unit.

Here is the most complicated chart I have tonight, and I hope it makes sense:

The atmosphere is in the blue box, the surface is the green line and the sun is in yellow. It’s bringing in about 70 units of energy, 23 of which are absorbed in the atmosphere – if you were thinking about a salary that would be £23 coming into this bank account. About £47 comes into this bank account (down at the surface). By the way, that account has about £6 trillion in it right now. So we’re talking about small numbers compared to the vast reservoir of these energies.

This energy leaves the surface in a number of ways: through the evaporation of water; the flux from contact with the air; but radiation is the big one here. The atmosphere sends down about 100 units, the surface sends back about 105, so the net there is only about 5 units. What we are looking at here is: what does that 0.5 of a unit do, when you’ve got hundreds going back and forth, which vary by much more than half a unit over time. So that figure (evaporation) might be 24 one month, it might be 27 the next. That one (outgoing infrared radiation) could be 105 or it could be 102, and so now you see that 0.5 of a unit is almost within the noise level of what can be expected.

Another important thing to note is the energy that escapes. Notice that we have 70 units coming in, we have 70 units going out. Most of them leave from the atmosphere, only a small portion leave from the surface. The climate variable that you want to study, so you can understand where these joules of energy are being deposited and accumulated is this one right here (the deep atmosphere). You want to know what that deep atmosphere is doing because if you are out in space and you tune your eyeball to infrared frequency and look back at the earth, you’re seeing mostly the atmosphere. That’s the metric you want to use, and we’ll talk about that in a moment.

Let’s just look at the surface now and think of it as a tug of war.

On the left you see those that make it cooler, those are the units of energy that leave the surface, and at times they’ll be bigger than these accumulating, and so it will cool. They win. But then, a few months later, the guys on this side win, the red guys, and they’re pulling because they have more power, more energy absorbing, and they cause heating. This diagram is to scale, so you can see that downward infrared radiation to the surface is the biggest thing that heats up the surface, followed by solar radiation. Now, how big is this half a unit – that’s this little guy right here. We’re trying to figure out – does this little guy even make a difference in this huge tug of war of energy at the surface. So it’s a hard problem, and it needs very precise measurements.

The problem should be made simpler if you look at the troposphere – the deep atmosphere, where the atmospheric heat content is measured, and that’s where the atmospheric heat content leaves the planet. By monitoring changes in that big tropospheric temperature, we are essentially counting the joules of energy in the atmospheric system. This is a direct metric for calculating the greenhouse effect.

We want to know with the greenhouse effect, how many units are being collected, and accumulated in that system. Well, in 1994, 25 years ago, Dick McNider and I wanted to test the climate models which indicated that the warming rate should be 0.35oC per decade. That’s what James Hansen’s model said, that’s what other models said. We didn’t think that was a very good number, and we did not trust the surface temperature dataset especially at that time – most of the earth was not covered, and the way it’s measured is so inhomogeneous around the planet and in time. We had 15 years of satellite data – we thought perhaps we could do something with that, but the problem was that we had volcanoes and we had El Niño’s that had strong effects on temperature.

We wanted to answer the question – what was the slow increase [in global temperature] due to greenhouse gases? So we removed the El Niños and the volcanoes, and using this 15 year record we came up with the number of 0.09oC per decade, that was the warming rate of the planet if it did not have El Niños and volcanoes – and in that Nature paper, and that was back when Nature was able to publish reports about objective science. They would never publish something like this today, something which is just based on clear observations and so on. But there in that paper we say, that there is an upward trend of 0.09oC per decade, or about 1/4 of the magnitude of climate model results. That was published in Nature 25 years ago, when a different kind of climate, so to speak, was in the air.

In 2017, Dick McNider and I wanted to re-check our work from 1994, now with the time series 37.5 years long, that’s two and a half times longer than what was done in 1994. This is what we got – this is really the guts of this particular study.

The top line is the actual temperature of the global troposphere, and you can see how long our 1994 study was – it was just up to here (purple dotted line).

Now we had a much larger data set (up to 2017). So that’s the original time series. We were able to calculate and remove the El Niño effect – it explains a lot of the variance – the ups and downs of global temperature by that Pacific Ocean temperature due to El Niño’s – by the way, this SST effect has no trend to it if you look at it. The sea surface temperatures in the El Nino pacific region have no upward trend. Take that out and what you have left are these two dips in global temperature right exactly when El Chichon erupted and when Mt Pinatubo erupted. They sent stratosphere aerosols up which reflect sunlight, fewer units are coming in, so the earth cools. Those blue guys on the left side win. So, I fashioned a function, a gamma function, that creates the [tropospheric temperature] impact based on the stratospheric temperature change, which is a proxy for the amount of aerosols that the volcanoes put up. Pinatubo put up more aerosols than El Chichon, so it has a bigger impact. Taking that out we get pretty much just a straight line with a little noise in it, and that trend was 0.095 degrees C per decade. With much longer temperature data, and more El Niños and volcanoes and so on, our result was the same as it was 25 years ago.

I’ve challenged some of my colleagues, and maybe you could do that here in England, I want you to pull out a paper from 25 years ago and tell me what you predicted [at that time] for the climate system – were you right? Of course, there’ll be wrong, because they were based on model projections and on screaming about how bad the world was going to be. We’re very proud of the fact that the kind of science we did 25 years ago is still confirmed and affirmed by the way the global temperature is rising today. This is a pretty minor impact on global temperatures when you think about it. It’s pretty small.

We published our results in this journal [Asia-Pac. J. Atmos Sci.] Now we have a long period of a temperature change, that straight line, without the impact of natural and inter-annual fluctuations, and from the IPCC we know what the forcing was over that 37.5 years – how many extra greenhouse gas molecules there were and what forcing they would have done, as well as the aerosols, to calculate what I call the tropospheric transient climate response. In other words: how much the temperature actually changes versus how much extra greenhouse gas forcing is available. There’s a major assumption here, that there are no natural variations left, there are no long-term natural variations. I’m just going to say the climate had no long-term external forcing. It’s a big assumption, I understand it’s a huge assumption, but at least making that assumption we can step forward and calculate the next thing.

This is just a picture to show how you get the forcing numbers. From the IPCC, it says well how much forcing there was in 1979, how much forcing there was in 2011…So you can get the change in forcing that we’re looking for, the ∆f.

So here’s the deal. We have a change in temperature from the deep atmosphere over 37.5 years, we know how much forcing there was upon the atmosphere, so we can relate these two with this little ratio, and multiply it by the ratio of the 2x CO 2 forcing. So the transient climate response is to say, what will the temperature be like if you double CO 2 – if you increase at 1% per year, which is roughly what the whole greenhouse effect is, and which is achieved in about 70 years. Our result is that the transient climate response in the troposphere is 1.1oC. Not a very alarming number at all for a doubling of CO 2 . When we performed the same calculation using the climate models, the number was 2.31oC. Clearly, and significantly different. The models’ response to the forcing – their ∆t here, was over 2 times greater than what has happened in the real world.

So the evidence indicates the consensus climate sensitivity is incorrect, but is there another response metric you can use to test climate models regarding the response to that 0.5 units of extra energy forcing? Ross McKitrick, who I understand is no stranger to the Global Warming Policy Foundation, and I, set out to do this, and we had a paper published last year by the American Geophysical Union

First we decided to set ourselves some rules:

The response for this metric should be seen in all the models as a dominant characteristic. So when you look at climate models for [the response to] extra CO 2 , all of them should show that this metric changes, and it is the dominant change.

, all of them should show that this metric changes, and it is the dominant change. The response is not there when extra greenhouse gases are not included. When you run the control experiment you don’t see this response at all.

Thirdly, you measure the claim against the observed metric that was not used in the development of the model. We cannot use the surface temperature, because the surface temperature record was used in the development of the model. That’s just as if I gave all the answers out to my students on Monday, I gave them the final on Friday, and they all did spectacularly well. Well, because I gave them the answers ahead of time! You cannot use surface temperature as a metric to test your model because that was used to tune the model, and you are not doing a legitimate scientific test. We have to have a metric that was not used in the development of the model.

Observations should come from multiple independent sources.

Doesn’t this all just sound like simple science? The way we learned it long, long ago. And yet this is remarkably absent in the world of climate science that we see today.

That metric turned out to be the temperature of the atmosphere between 30,000 and 40,000 feet in the tropics, 20oN to 20oS. So think of a ring of air all the way around the tropics, and in every single model this thing popped out as the major response to greenhouse gas forcing that was not there without the extra greenhouse gas forcing – so this is the metric to go for.

Here is an example in the Canadian model. This is the North Pole on the right of thex-axis, South Pole on the left, tropics in the middle, and the y-axis is effectively the altitude. What we see here is a trend over the period from 1979 – 2017, 39 years. Right here you see this big red spot, in other words, in the models, they warm the surface temperature, but they really warm up the upper atmosphere because of the moist thermodynamics that exist in the models, which are very crude compared to what happens in the real world. That’s a visual image of this metric that we’re going to look at.

Now, I’ll also show a result from the satellite layer, which is this big layer in the dotted lines. Our satellites measure microwave emissions from oxygen, at around the 55 GHz band (54). That’s a deeper layer of temperature that we’ll measure. I’ll show both. But the key one here is 30-40,000 feet.

Climate models hypothesise that significant warming should already have occurred in that level, between 1979 to 2017. This is a hypothesis that we can easily put to the test, and as I said the warming hypothesised by the models is well above any natural fluctuations that appear in the controls which have no greenhouse forcing. None of the controls have any kind of dramatic change which occur in this metric.

This (graph) shows the average from 102 climate models here, the average trend is 0.44 degrees C per decade. Pretty rapid by the way, this is almost 40 years, so that’s 2 degrees – a huge amount of warming that these models have in that particular part of the atmosphere. They do vary a lot, one of them is quite low here, but some are very high as well.

This is the real world, and it’s down there at 1/3 of that amount. In other words, that key metric that is independently measured, and can be independently tied only to greenhouse gas forcing, nothing else causes that in the models except the extra greenhouse gases, is 3x too much in the average model. This is what the [time series] diagram looks like.

So these are the different models going like this, this is the average, and we like to deal with the average since that’s the consensus on which your regulations are being based. We see the two dips here: El Chichon and Pinatubo cooling, and you can see that their dips are much bigger than the real world, which tells you they’re too sensitive, the models are just too sensitive to anything that happens, that’s why they have these huge dips like this. You can easily see the 3x difference here, they’re just warming too fast.

There is one model that’s not too bad, it’s the Russian model. You don’t go to the Whitehouse today and say, “the Russian model works best”. You don’t say that at all! But the fact is they have a very low sensitivity to their climate model. When you look at the Russian model integrated out to 2100, you don’t see anything to get worried about. When you look at 120 years out from 1980, we already have 1/3 of the period done – if you’re looking out to 2100. These models are already falsified, you can’t trust them out to 2100, no way in the world would a legitimate scientist do that. If an engineer built an aeroplane and said it could fly 600 miles and the thing ran out of fuel at 200 and crashed, he might say: “I was only off by a factor of three”. No, we don’t do that in engineering and real science! A factor of three is huge in the energy balance system. Yet that’s what we see in the climate models.

This is the [time series of the] satellite layer, so it’s pretty much the same kind of picture, even though it’s a deeper layer we see the models warming way too rapidly. Some, up here, one of them is the US model, the GFDL model, is just off the charts. I don’t know what they’re doing with that model but it just cannot release heat to space from the atmosphere. Whereas the observational data; satellite observations, balloon observations, reanalysis observations, all show the same thing that these models are not showing.

Guess what has just come out? The CMIP-6 models on which policy will be based around for the next 10 years, and on which the IPCC (assessment report) will be based. It’s not getting any better. You can see here the observational metric from 2 different sources, on the left there – the grey bars. And here’s what the CMIP-6 models are doing. They actually have a higher sensitivity than the CMIP-5 models. In other words, they’re not getting better, they’re getting worse. Is that the way science is supposed to go, when you have hypotheses you can test and reject. Let’s see, I think we have a British model in here. Here is the UK ESM. It’s only about 5 times too warm! 0.1oC/decade is what happened during this period, and the UK’s model has 0.5. So if you’re policy is based on your model, you’d better buy stock in swimsuits or swimming pools, you know, or air conditioning or something. But that’s not happening at all right now in the real world. These guys need to go back to the drawing board and say “we’ve failed – something is really, really wrong”.

If you think about an air column in the atmosphere, this is where the energy is escaping from – the deep atmosphere. What we found is that in the climate models, when they warm up a degree, they only send out 1.4 W/m2. In the real world, when the Earth warms up a degree it sends out 2.6W/m2, so these models are trapping too much heat, and not letting enough escape during warmer periods. So you can imagine over time that every time there’s a warming event and the models don’t let that heat escape, it just stays in the atmosphere. It’s joules of energy you can’t destroy, they just stay there and accumulate and accumulate over time.

Now, people have known about this; I was on the National Academy report in 2000 where we said that the climate models were not matching real world data. “A more definitive reconciliation of modelled and observed temperature changes awaits… improvement of the models used to simulate the atmospheric response to these [natural and human-induced] forces.” Pretty simple statement – maybe we need models to be better. What I’ve shown you is that, unfortunately, (this is now the sixth generation of these models) this statement has not been heeded.

The IPCC AR5 knew that there was a problem and that this mismatch between models and observations was most obvious in the tropics, and they knew it but avoided drawing attention to it. In my review of the AR5 – by the way, since the AR3 – the TAR, as they called it – I’ve never been asked to be a lead-author again – that was the last time they actually had lead authors who were sceptics – Dick Lindzen and I were lead authors – but since then they have not had sceptics because the IPCC simply picks the authors that will write the story they want. So I pointed out this mismatch and said if this thing goes to court, it will not stand up to cross-examination. Your claims in this IPCC report cannot stand up to cross-examination. Your review process is not cross-examination, it’s mainly receiving comments that you can deny or throw away because the lead authors have final say.

Peer review is not a term to apply to the IPCC or its cousin the US National Climate Assessment. In these organisations the carefully selected lead authors will always have the final say and they determine what the materials will be included. So there’s no possibility what they write will be rejected, because there’s no-one behind them to reject them. They are the lead authors, they are the last ones and they can write a comment to my explanations that says ‘We disagree’, and that’s it. ‘We disagree’, and that’s it!

This diagram actually appeared in the AR5: and it shows a vertical temperature structure from the surface to the stratosphere, and between 20oN and 20oS. It was only because of my repeated insistence that the report could be open to legal challenge that they did put this chart in the Supplement. To avoid drawing attention to it, they buried it in the Supplementand it wouldn’t be published until long after the big press release.

I will enlarge this part of the diagram in the next slide, showing the temperature trend in the tropics. So this the troposphere; and this is the trend – it gets hot over here (to the right of the chart), cold the other way. The red – remember this is in the IPCC – the red bands as you go up in height are the trends from the models that were used in the AR5. The white bands show the actual observations. Do you see any crossover there? Maybe one tiny bit right at the bottom, but basically you can see there is almost no congruence, there is no agreement between the observations and the models. The IPCC knew it. They knew something else too. They also ran the models without any additional (anthropogenic) greenhouse forcing – and those results are shown by the blue bands. What do you see about the blue here? The blue bands closely match the observations. So if the models were run without extra greenhouse gases they reproduced the actual temperature of the atmosphere, and that was never ever mentioned anywhere in the text. You had to dig it out. And so I had to annotate it so you could see the IPCC was clearly aware their models had failed terribly but would not draw attention to it because then the whole scare scenario falls.

This is a more recent publication, this is in the BAMS Bulletin and shows the same thing. This is from the surface up to the stratosphere. These are the trends and the error bars on all 102 models and here are the observations. As you go up you see no crossover between the observations and the models. Again, this is in a peer reviewed document and yet we do not see the IPCC type folks responding. So the rate of temperature increase in the tropical atmosphere, the rate of accumulation joules of energy is significantly less than that depicted by the CMIP-5 climate models. Will the IPCC AR6 investigate this long-running mismatch between climate systems and models, and the climate system of the real world? I don’t make predictions – hardly at all – but here’s something I might think about.

Past responses have been:

1) The observations are wrong, the models are right, it’s the observations that are wrong.

2) The models had bad forcing; if they had the right forcing then they would get the observations.

But never 3) the models are failed hypotheses.

I predict 3 will not be the choice they choose, although the scientific methods that I grew up with and perhaps you grew up with, say that’s exactly the conclusion you are supposed to make when you do a test like this.

How many of you are familiar with this? I’ll go quickly through this extreme weather. Whether it’s tornado, drought, floods, fires, hurricanes, all getting worse, right? Everybody just knows that.

Well, as scientists we actually count tornadoes. I live in a state that has quite a few tornadoes as a matter of fact; we know how to count tornadoes. You go back to 1954, the United States which has the most tornadoes in the world, you see a downward trend. In fact 2018 was the lowest number of [major] tornadoes in our historical record.

What about hurricanes? This chart shows hurricane days, tropical storm days and major hurricane days: I like this metric – rather than just counting, because it tells you not only how many hurricanes you’ve had but also how long they existed. It’s a total integration of the energy that’s been processed. And you can see that in none of these do you have an upward trend in your current hurricanes. Lots of ups and downs but no trend.

This chart shows droughts and floods in the United States from 1895 – big variations in droughts and in floods but there is no trend in either. Stream flow records also show the same thing. We don’t have stream flow records that show an increase in floods.

What about temperature records – that’s where the media really jumps on it. A city over here has a record high temperature that day – it’s plastered through the media as a terrible occurrence and evidence of global warming. Well, I haven’t seen anyone do this chart. I was the first one to do it a few years ago in which I actually took 110 years of records. I took all the stations that had 110 years of records, 569 stations in the United States, and I calculated:

January 1st – when [in what year] did that record high temperature occur

January 2nd – when did that high occur

So I had 569 stations, 366 days per year and 124 years – work it all out – the average should be 813. But at any rate, all that aside, just look at the chart. Is that an upward trend in record high temperatures? 15 of the 16 years with the most temperature high records occurred before 1955, that’s a downward trend actually, in record high temperatures in our country.

This is a picture of global drought. I am one of the authors of the BAMS Summary of the Planet – every year we write one of these. This was the one of last year’s summary. You don’t see an increase in global drought at all.

Wildfires. This chart is of North American wildfires. In the United States, the TV which is saturated with wildfires in California this past year: people dying, people losing their homes, it all is a tragic, tragic story. But when you look at the 400 year history in the North American continent you see a dramatic decline. And it’s pretty simple. Think about it. Before Europeans came along there were no sophisticated fire suppression methods. You know, Native Americans didn’t have fire brigades and helicopters and so on. So when a fire started before 200 years ago, it burned until it burned out. It literally burned until the fall so these were huge, huge, fires. With improved fire suppression methods we see a dramatic decline in wildfires in our country.

In fact, I own a property in the foothills of California. This is a tinder dry area. In this phot I’m surveying and found that the owner of a neighbouring property had moved one of the stakes so he had a bigger piece of the property. Thank goodness for GPS devices! You can map the lot down to 5 decimal places. This guy moved it 40 feet. And on the best sort of property too. So I caught him. Anyway, I have not built anything on this property because I can’t figure out how to make it not burn. This kind of ecology, burns all the time. It is natural for it to burn. It is supposed to burn. That is how some of the seed-nuts open up with the high temperatures from the fire so the seeds can come out. So all these things are natural. It also keeps away some invasive species and things like that.

Now, what has happened in California is this. A real estate agent comes along: ‘Wouldn’t you like to buy a piece of property in California – you’re above the fog in the valley, you’re below the snow level’. And really, they’re selling you a piece of property which is nothing but matchsticks, all around. It is ready to go, just like that, just as we saw last fall in Paradise, CA.

Globally, guess what, people all around the world are putting fires out. This is the amount of fire acreage covered since 1900 around the world. And you see it here, it has declined. And if someone tells you ‘Wildfires! They’re terrible!’, as I have seen in Congress before Representatives and Senators – they will say ‘the fires are getting worse’. I will say: Congressmen – the evidence is here, the fires have gone way down in their current occurrence and frequency. ‘The fires are getting worse!’ – And I don’t know how to get through to their minds here, as to what evidence tells us about that simple statement. But the Congressman or woman will not change their mind – they just yell louder.

Snow cover. In the Northern hemisphere we were told snow is going away. But look at this. We see here a time series in which the highest snow coverage in the last 40-50 years has occurred just 6 years ago. This year was a pretty good year for snow cover around the world. Snow is not going away; it is still falling.

Arctic ice. Geologists think the most interesting time is to the right, so that means long ago. About 10,000 years ago there wasn’t much ice in the Arctic. It’s only in the last 1000 years that we’ve seen this coverage of ice that persists significantly through the summer time, and so if the Arctic ice melts back in the summer time now more than it has in the last 100 years because of warming. It’s nowhere near what it had been in the previous warm Holocene.

Probably the most important point for policymakers deals with human suffering, we see that the amount of damage caused by climate advance or weather advance, is actually declining. This is because we get smarter, people get smarter, we figure out how to protect ourselves from weather disasters. For example 17,000 people this past week, I think it was in Bangladesh, were evacuated because satellites were able to warn them that a hurricane was coming. So they were saved because of that kind of technology, whereas a 100 years ago they would not have been. And the amount of deaths too, is declining tremendously, with yearly totals in the tens of thousands compared to years in the early twentieth century in which millions of people were killed by weather disasters.

What about grain harvests? I don’t see a problem. If that’s global warming most people would say let’s have more of it. Because crop yields are improving and production is going up and up.

Ah. But John! Everybody! Everybody! Says humans are causing dangerous climate change! Yes, the United Nations, US Government, National Academy of Sciences, American Meteorological Society, New York Times, Washington Post, NPR, CNN, 97% of scientists: Leonardo di Caprio, Al Gore, Alexandria Cortes – she’s the new Congresswoman from New York – and the university professors – and you can put those in any order of credibility you want, and I don’t know which is better than the other. I mean, I’m from academia and I like to be out in the world with people like you because you work for a living – a lot of you do – and you’re accountable for what you do.

University professors, when you think about it, aren’t. They have tenure; they can say whatever they want. But this statement down at the bottom here says ‘Oops’ – their testable predictions have been falsified. It doesn’t matter what they say, if their

testable predictions have been falsified. Well. These are called arguments from authority and arguments from consensus, but they’re not arguments from science.

Many of these authorities are simply people that don’t check the numbers. Five years ago in 2014, someone asks in Congress, “Dr Christy, the National Academy of Sciences says dangerous global warming is upon us. How do you reply?” I say “Sir, they didn’t do what I did. I downloaded 102 climate model simulations, one at a time, over several weeks and nights and weekends. I unpacked 102 climate model formats to get them into a common format. I ran my code for 102 climate model simulations to generate the satellites radiances from the raw climate data and I was the one that compared them with the real data. They did not do that; I did. So I can say what I feel about this subject and what the evidence tells me. And this was the first time that this plot appeared; it was in the Wall St Journal in 2014, after Secretary of State John Kerry said if you don’t believe in climate change like I do, you believe in flat earth theory. And so we hit back with a headline that said: ‘It was Scientists that Proved that the Earth Wasn’t Flat with Real Observations’. So, here we are showing you that these climate models are false – that’s the flat earth, right there – this is what scientific observations show, and so that’s why I, when someone says, a huge authority, says ‘Blah’, I say ‘Blah blah’ back, because I did the work and they didn’t.

So as Richard Feynman says, “Science is a belief in the ignorance of experts”, and that’s why our President, President Trump, goes in strange directions at time because he’s probably seen in his experiences of life, and I see in here, you are all about my age, you have also seen how many times experts have been wrong. And so he just has a sense I think, that, well, these Government scientists, they’re probably wrong.

Michael Crichton says that in science consensus is irrelevant, what is relevant is reproducible results, consensus is inappropriate. So, as an aside, there’s a strange thing happening in climate science: the proliferation of unfalsifiable claims, in other words the unfalsifiable hypothesis. Remember I said that scientific method: you make a claim and the claim has to be testable and falsifiable and then you check and see if it’s the real thing.

Well here’s the claim. Whatever happens is consistent with global warming. Maybe it’s snow or no snow. More hurricanes? Less hurricanes? This method says wait for something to happen and then claim that human-caused warming is to blaem. That’s the unfalsifiable hypothesis and it has no information value and there is no way to test it, it has no testable parameter and so it is not science. The unfalsifiable hypothesis predicts anything is possible therefore nothing is testable.

Carbon & Energy

As you all know, and your group has done a yeoman’s job on this particular aspect, is that information about energy costs and who pays the most, proportionately of their income, is a sad story. As you can see here, the poorest people in the United States pay up to 40% of their income on energy costs. And that makes sense. When I go to the gas station, the petrol station, and this poor fellow comes in next to me, our gas tanks are the same size. He puts the same amount of gasoline in his car as I do in mine and we pay the same amount. But proportionately for my income it’s pretty small; for his it’s a big chunk. It pressures him, it costs a lot, and he pays that electric bill and he pays anything that touches energy, which is everything. That’s the issue there, that helping the poor means lowering energy costs. If you want to help the poor, if you lower energy costs immediately, you have immediately helped them buy food, medicine and so on. If you want to hurt the poor: raise their energy prices; they’ll feel it faster than anything else.

So, the Chinese, this is a quote, “lifted 400m people out of poverty by building a coal-fired power plant every week”.That was viewed as bad by the very wealthy environmental activist who said this, and I was there. But it’s viewed as good by the 400m people who no longer are in poverty and many more millions who strive to end poverty. So morality now is the question to consider: is it good or is it bad to enhance and extend people’s lives? Are the extra emissions from carbon dioxide good or bad, based upon the tremendous value they have to human life? Is it good or bad for the rest of the world to aspire to a higher standard of living, maybe one third of what we have? Is it OK to let them do that? Guess what? They’re going to do it anyway – no matter how much you and I scold them about it they’re going to do it.

So as you see, this wedge of carbon-based energy, these three right here, versus nuclear and hydro, and then this little bit of renewable right here – we see where the energy is coming from: it’s coming from carbon and it’s still coming from carbon. Our carbon dioxide emissions are going up as you see here, because the evidence from actual data – this isn’t my opinion it’s not your opinion – it’s just what’s happening – is that that drive to live a longer and better life is overcoming any willingness to succumb to the constraints of environmental virtue.

So, 25 years of being scolded about CO 2 emissions has not changed the fact that carbon is a terrific source of energy for today and the world is using more and more of it. The EIA, the Energy Information Administration of our government, predicts that that is going to continue.

Well, will CO 2 regulation save the planet? At one of the hearings I actually answered that question because they had a regulation that was supposed to reduce the CO 2 emissions by a small amount, I said I’ll just eliminate the United States completely, no people, no cars, no factories, no emissions from any activity. A country without anything except forest and birds and trees and so on. And that’s the impact on the global temperature using the IPCC models. In other words, if you see the actual variation of temperature that’s within the noise level of what the temperature is. You could not attribute a change in temperature of the globe to the fact the United States disappeared from the planet and changed the climate.

The average American, and, I suspect, the average Brit, I really do, is smarter than you think. They recognise it when an elitist is exaggerating a story, the end of result of which is to deny this average guy some aspect of life he or she wants and needs, while the elitist maintains a luxurious lifestyle. The average American is rightly sceptical of environmental claims given the track record of doomsayers since the first Earth Day in 1970.

I like this chart that you all made, whoever made it thank you very much (Josh the Cartoonist). And the reason I like it, is because I was there in college on the first Earth Day, in April 1970, and I remember a car there. For 25c you can pick up a sledge hammer, and beat the car three times. The idea was to mash the car into the ground. Now, these were not bright people at all, they were just emotional people, cars were bad to them at that time. Never realisingthatmobility device was one of the greatest devices humans had ever made to improve and enhance life. I’ve seen ambulances go up and down there a number of times. They help us, transportation, moving things in a free market economy when they are needed, is a terrific advance. So, I circled these predictions, and put at the bottom the answer to them. For example, this one says 100-200 million people will be starving to death within 10 years. Well, what’s actually happened in the data, it says: ‘Food has increased from 2300 to 2800 calories per person in that time, even though population has increased. So there’s more and more food, relative to the number of people. And all of these things are the same: ‘life expectancy will be 42 years by 1980’. Well, as it says here, life expectancy has increased by 30% in that time. So you can see all of these predictions, I remember those. The reason I put these claims here – is that I remember clearly those things being said, and what was going on on Earth Day. You just can’t trust people who are environmental doomsayers.

I have three conclusions for my talk:

Theoretical climate modelling is deficient for describing past variations. Climate models fail for past variations, where we already know the answer. They’ve failed hypothesis tests and that means they’re highly questionable for giving us accurate information about how the relatively tiny forcing, and that’s that little guy right there, will affect the climate of the future.

The weather we really care about isn’t changing, and Mother Nature has many ways on her own to cause her climate to experience considerable variations in cycles. If you think about how many degrees of freedom are in the climate system, what a chaotic nonlinear, dynamical system can do with all those degrees of freedom, you will always have record highs, record lows, tremendous storms and so on. That’s the way that system is.

And lastly, carbon is the world’s dominant source of energy today, because it is affordable and directly leads to poverty eradication as well as the lengthening and quality enhancement of human life. Because of these massive benefits, usage is rising around the world, despite calls for its limitation.

And with that I thank you very much for having me.