Understanding the Global Temperature VII

I started trying to reconstruct a global temperature graph. I found that land based measurements like CRUTEM were reading too high and identified this as massive warming in Northern hemisphere land based measurements.

Sea surface measurements like HADSST gave longer term trends that were more consistent with satellite data and other metrics. However, they did not have the same year to year changes as the satellite data.

So, I proposed to take the fast changes from CRUTEM and add it to the longer term trend of HADSST as I hope the following graph shows:

Reconstrition20The top green is CRUTEM (land) – which leads the pack showing excessive warming. The lower green (toward the end) is CRUTEM less any longer term trends. The blue line is the sea temperature from HADSST with short term trends removed.

Purple shows UAH6 satellite and Red shows my reconstructed metric which simply adds long term trends from the sea measurements to short term trends from land.


This is clearly a good fit. “HASELER” is a bit low in the 1998 El Nino year and a bit too high in the 2016 El Nino year. But generally HASELER reconstruction follows UAH6 well.

Except … it shouldn’t!!

I’m happy that the sea temperatures representing 6/7 of the globe might represent the vast majority of global temperatures and so the sea long term trend will be close to that of the global temperature. But why on earth does the short term changes in global temperature reflect only the land-based measurements. It should only be 1/7 of the changes.

This suggests to me that most of the short term changes in global temperatures are affected by what happens over land and that the atmospheric transfer into the sea is relatively poor.

This suggests that over short periods the air flowing over the land, determines the temperature (or is determined in temperature by) the atmospheric temperature. But that what determines long term temperatures is the sea (or what is determined by long term temperatures).

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Understanding the Global Temperature VI

Yesterday I had a look at meteorological balloon data

RadioSonde1and found that if we plot the trend as shown, RadioSonde2below 10km (200mb) the atmosphere was warming and above it, it has been cooling and that this cooling reached a minimum at around 50mb (20km). At this point I rather cocked up on my explanation of what was happening in the atmosphere. So I’ll go back over it with some actual calculated changes rather than trying to work it out in my head.

We can think of the atmosphere as emitting radiation to space as shown below. We start at the top of the atmosphere where we naturally have 100% of the emitted radiation. As we go down through the atmospheric layers emitting radiation the percentage falls from 100% at the top downward depending on the proportion of greenhouse gases. And as we can see as we double or halve these percentages we in effect raise or lower the curve.


However, what matters for us here is not what happens to this curve, but the change in radiation from any layer. The amount any layer/height emits is inversely proportional to the gradient of the curve. This is shown below for selected curves from that above to show what happens.

Starting with a a percentage where almost all emission occur from the atmosphere (red). If we increase the gas concentration (2  → 4) the change in emissions with height is the red dotted curve. There’s no change at ground level, then as we rise we reach a region when the lower curve is emitting most so there is a drop in emission. Then we change to a region where the raised curve is emitting most and there is an increase in emissions. Finally when we rise up far enough, there’s too little greenhouse gas to cause any emissions.

The situation is similar with a curve where some radiation come from the ground except the lower part is cut off (and obviously there’d be a dramatic change at ground level).

If we now compare this curve with the balloon data we find:

RadioSonde2 ChangingRad

The left curve changes from warming in the lower atmosphere to cooling at 200mb or 10k. On the arbitrary scale of quantity of greenhouse gases, the curve marked “1”  changes from cooling to warming at 10km. However it peaks at 15km whereas the balloon data seems to peak at 50mb (20km). Also the right have “1” curve shows no net change of temperature at ground level whereas the curve on the left shows increased warming right to the ground and in the northern hemisphere (which is filled with land) the warming increases down to the ground. This is not compatible with a greenhouse gas. It seems more compatible with IR in a radiation window being blocked by a layer as it would by contrails.


However … what I cannot factor in is heat flows. The lower troposphere is continually overturning and heat moves throughout this region easily. The average depths of the troposphere are 20 km (50mb) in the tropics, 17 km (90mb) in the mid latitudes, and 7 km (400mb) in the polar regions in winter. The balloon data shows the equatorial change of sign occurs at 140mb (14km) the northern extra-equatorial at 240mb (10.5km) and souther extra-equatorial at 255mb (10.1km)

In other words, the temperature warming appears to be correlated with the troposphere and the cooling with the stratosphere.

As the sharp change occurs where the atmosphere changes characteristics and also where aeroplanes fly leaving con trails and also it is an important boundary layer between heat in the bottom of the atmosphere and top – so any change in atmospheric flows could change the heat, I’m now less certain as to what may be causing it.

The heat rabbit from the hat

This graphic shows the aeroplane routes. Now compare it with a map of long term warming trend from 1985:


Warming trend 1985-2014

Areas with large concentrations of aeroplane routes seem to be close to areas that have warmed most. But now if I add in trade wind vectors:


Warming trend 1985-2014 showing selected trade winds

I get very good correlation between the most dense areas of aeroplanes routes (N.America and Europe) and the areas of warming are downwind of the trade winds. Which seems like fairly conclusive proof that aeroplane contrails did it. Until I show the stratospheric winds which is what would push contrails along …

 showing selected trade winds

Warming trend 1985-2014 showing selected stratospheric winds

Now the N.American hot spot is too far north. This suggests that the main culprit is being driven along by lower atmospheric winds. Now we are looking for something that affects the lower atmosphere. Something showing dramatic changes since 1970 …

And there has been a massive change in the lower atmosphere … because since the 1970s we have had clean air regulations that massively reduced pollution. However … there is only so much pollution that can be removed from the atmosphere. And as we see in the graph above, pollution was reduced steadily when it was high, but lately since 2000 the change has been lower. And when did “the pause” start … ~1998. However, if we look at the meteorological balloon data, we find no obvious change in trend. However, whilst N.America and Europe have been reducing pollution, places like China have been increasing.

And of course one of the 50 excuses for the pause was:

Global warming slowed by China sulfur pollution

WASHINGTON – Scientists have come up with a possible explanation for why the rise in Earth’s temperature paused for a bit during the 2000s, one of the hottest decades on record. The answer seems counter intuitive. It’s all that sulfur pollution in the air from China’s massive coal-burning, according to a new study.

And if Pollution can halt warming since 2000, then the reduction in pollution since the clean air acts of the 1970s can cause it.


I now have several possible contenders for the oddities in global temperatures:

  1. CO2 – which is a relatively small effect
  2. Contrails – which have certainly grown since the 1970s as we need, and affect the atmosphere at 10km which is where we see the change from a warming to cooling trend – but there’s a discrepancy in that the hot spot that seems to be associated with the US is not down wind at the contrail height.
  3. Reduction in pollution, which has certainly massively decreased since the clean air acts of the 1970s – this change has been largest in N.America and Europe (where we get the big hotspots in the trend) and they are downwind at lower level wind directions.
  4. Natural variability – we must not forget, that the scale of natural variation is enough to explain all changes we see. Indeed, the changes in temperature are so slight that anything and everything we see could just be a random occurrence.

The important thing here is that because pollution and contrails are relatively short lived things, there effect tends to be strongest just at, or downwind of the source. And this is different from CO2 which is much longer lived. As such we ought to see characteristic trends associated with specific areas. If the cause of warming is pollution, we ought to see strong cooling downwind from Chinese industrial areas as pollution increased. And we also ought to see strong warming downwind of N.America and European polluters and they reduced pollution. Likewise, with contrails, we ought to be pick up patterns, but in slightly different areas particularly in transcontinental flight routes. So the pattern of warming should be different enough to identify the likely culprit.

CO2 warming

However even with CO2, we know where man-made emission are coming from as shown in the map below:co2_map_bigNaively I thought the areas with the highest CO2 would  naturally be the areas with high human emissions. But if we look to see which areas are relatively high or low in CO2 as shown below:

We see that the areas that “lead the pack” in terms of CO2 are central Africa. This suggests these are CO2 sources and those lagging are the northern tundra areas of Alaska and Siberia which are either least emitting or absorbing CO2. If CO2 were having a regional impact, this is the type of patter we would expect, which is very different from the regional hotspots we actually see. However, in defence of the CO2 hypothesis, it is well mixed and we probably shouldn’t expect to be able to discern any regional effects.


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The Science

After a recent comment I realised that it isn’t possible to include all the science in each article and that I’m going to have to provide some kind of prima for those who don’t yet understand important details of the science.

As such I’ve changed the menus around and have created links to the following:

  • GreenHouse Effect
    This is an important article because I’ve yet to see anyone who explains the greenhouse effect properly. What is worse, some of what you’ll find even from some academics is complete trash.
  • Lapse Rate
    Important only in that the lapse rate is key to the Greenhouse effect so it’s good to understand what it derives from
  • Introduction to 1/f climate noise
    An introduction to 1/f noise – the kind of noise seen in the climate signal
  • Natural habitats of 1/f noise errors.
    An illustration of the typical errors people get into when assessing 1/f type noise
  • Assessing recent temperature trends for abnormality
    The only way to assess something like climate where we have no idea of what is “normal” to assess what is abnormal, is to look at changes within the same signal. I show how the rate of change over various periods can be predicted, and how this can be used to assess recent temperature changes.

If there is anything missing please say so in the comments.

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Revised Temperature prediction

Following my series on Understanding the global temperature. I have realised that it is likely that a substantial part of recent warming – particularly northern hemisphere land-based temperatures have risen due to air plane contrails.

Thus for forecast I made a while back: My Global Temperature Forecast: cooling ~0.35C by 2030 years would need to be revised upward. Also having examined temperature records, I think the effect of the Atlantic oscillation is smaller than I suggested.

This is a “finger in the air” forecast because much of what I’m using is very poorly understood so use it at your own risk.

Direct CO2 warming is probably of the order of 0.05C/decade. The contrail warming is hard to quantify as it is so regional, but globally met balloons show a ground based trend of around 0.13/decade. The northern extra tropical regions is warming at 0.2C/decade faster than the southern area. If we assume this is due to contrail formation, this suggests very roughly around 0.1C/decade global warming due to increased air traffic and contrail formation.

Temperature rise from 1970-2000 as measured by HADCRUT was around 0.48C or 0.16C/decade. Meteorologically balloons indicate slightly lower warming globally of 0.14/decade since 1970.

We now have the following that suggest change:

  • Rising CO2 – causing perhaps 0.05C decade
  • Rising Contrails – which measured globally is of the order of 0.1C/decade
  • Possible negative phase of Atlantic Multidecadal Oscillation which at most is suggested at 0.1C cooling. But a lower figure is more likely (0.05C?)
  • Reduced solar activity. If contrails account for significant warming since 1970, then I estimate about 0.1C/decade cooling. (I’m using the suggested discrepancy from the graph below and suggesting half is caused by contrails). The forecast of this is difficult as who knows whether solar activity will remain low.


Based on this, my best estimate of global temperature change is from no change to perhaps 0.1C warming in the next decade. However, there is significant natural variation of around 0.8C so the forecast would need to be 0.1 ±0.8C in the next decade.

Based on what I know of climate, and the likelihood of negative feedbacks, I would suggest a best long term estimate of perhaps 0.8 warming by 2100.  Again there is significant natural variation of around 0.5C & I have no real idea of the scale of negative feedback so my best forecast would be something like 0.8±1C

This figure however relies on continued increase in contrails and no diminishing impact as the skies are filled with them. If however we find a way to reduce contrails, that figure will be substantially lower, but if the rate of filling the skies with contrails increases it could be higher.

In Perspective

To put this forecast in perspective here is a plot of daily temperatures in Boston. The day to day temperatures change considerably. Over the month the mean temperature also changes significantly. The total change due to global warming is entirely contained within the red line.


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Understanding the Global Temperature V – Met Balloon Data

Note: the comments on height and the greenhouse effect are not accurate. Please see next article for a better description

Summary so far

In previous articles, I have tried to work out to what extent I can produce a global temperature which is free from the “thumb on the scales” as Dr Bates referred to NOAA’s own attempts to get rid of the global temperature pause. There are also indications that NASA have been trying to get rid of the 1970s cooling.

I am reasonably confident that the satellite data is the best available global temperature we have. This is because it is the only sensor where we have a known quality standard and traceability of calibration back to recognised standards. In contrast, from my own experience, I know that ground sensors have huge problems, and there is a complete lack of quality control which would make even a chocolate chip manufacturer squirm.

So, far I have identified an apparent yearly increase in land surface temperature apparently starting in 1970. I have proposed a way to remove this and was at the stage of comparing my proposed solution with available temperature sets when I went to look at Meteorological balloons.

Meteorological Balloons

I downloaded the data from NOAA  and produced this.RadioSonde1
Something is very odd with this. All the layers above 300mb (9km) are cooling and the higher ones most and the lower layers are warming. Could this be the signature of global warming? According to the Noddy theory of global warming, CO2 traps IR, so this, Noddy researchers might conclude is the signature of greenhouse gases: the heat is trapped in the bottom of the atmosphere and so there’s no heat for the top. Continue reading

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Understanding Global Temperature IV

Following the last post  I had a go to see what the graph might look like. With a bit of added processing to CET to give it a similar dynamic to the other global temperature proxy datasets, I produced the following curves which are overlaid here:

And in one continuous sequence here:

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Understanding the Global Temperature III

In the last article I concluded that a reasonable proxy for global temperature could be produced using CET, then sea temperatures (HADSST3) then UAH6. However, that left me wondering why land based temperatures were so appalling. So, I decided to have a look at temperatures from 1980 onward which is when we see problems as the following shows:Reconstruction5It didn’t take me long to work out what was going on. The following graph (all 12month smoothing) is produced by overlaying onto UAH6 a copy of HADSST 3offset by 0.21 with a copy of land based measurements (CRUTEM4) with a -0.22 offset PLUS a “detrend” of 0.6. (Which is equivalent to about 0.17C/decade of introduced warming)

Reconstruction11I think it’s safe to say, that they are all close to each other. Continue reading

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Senator Inhofe retiring in 2020

Inhofe_snowballI was planning to write today about a superb piece by Coral Davenport of the New York Times which has run a few intelligent articles on climate and the environment lately:

Head Stacks Agency With Climate Change Skeptics

However, for me the most interesting part was close to the end:

Mr. Inhofe, 82, will complete his current Senate term in 2020. While he declined to speak of his retirement plans, Mr. Inhofe said of Mr. Pruitt, “I think he’d make a great senator.”

I will say very firmly that there are few politicians I admire as I think we are poorly served by most. However there are a few notable exceptions and Inhofe is one. Yes there are always back room guys who do the actual work like Mark Morano and others, but as I like to put it: “you always need a fairy to put on top of the tree”. And Inhofe was the guy who became the key politician, at a time of immense and systematic hostility, who was willing to speak up for common sense on climate.

Any politician can get behind a cause which is widely respected and liked. But few have the guts to stand up for what they know to be right at a time when every other politician is going with the crowd the other way. But Inhofe stood up to be counted at a key time and in doing so he was widely vilified and the target of much public hate. That takes guts for a politician.

Once Inhofe was one of the key politicians constantly in the climate news. But since Trump, I’ve noticed that Inhofe’s name has been missing and I was even wondering what had happened to him …. now perhaps we know? Has he has metaphorically handed the snowball onto a younger generation?

Thanks for all you’ve done Inhofe.

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Petition: Abolish House of Lords & replace with a people’s assembly

Following the behaviour of the Lords & many politicians in trying to thwart the will of the British people over Brexit, they have shown they cannot be trusted with our democracy. The House of Lords should be scrapped and replaced by an apolitical body such as a citizens assembly.

The exact nature of the citizen’s assembly is not as important as that the upper house should be largely free of the self-serving career politicians and bought peerages who have have recently shown so much contempt for the will of the people. Several options are possible including an assembly selected like a jury from volunteers or one appointed by a similar citizen’s panel where members are chosen for the character not their political colour.

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Understanding the Global Temperature II

Recap: in the last article, I showed that the satellite record, which is our most reliable indication of global temperatures, is most like the sea temperature record and least like the land based record. I had a go at trying to suggest a possible physical cause (other that data manipulation and/or rural heating), but as the aim is to create my own long term temperature series it does suggest a way forward.

Below is a plot of global sea temperatures HADSST3 and UAH6 with a 0.2C offset to UAH6

I think you’ll agree that is a remarkable fit. Which means that my best estimate of what a series like UAH6 would show in the past is HASSST3. So, now rather than relying on Hansen et al 1981 which is using known biased source I can create a long term series from HADSST:

Reconstruction9Not only is HADSST3 a good fit to CET, but having decided that HADSST (which is almost identical to UAH6) is our best proxy for global temperature it is great to find that CET appears to be a better fit to HADSST than Hansen et al 1981.  In other words it appears I am quite justified in ditching Hansen altogether. Continue reading

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