Showing posts with label sea surface temperature. Show all posts
Showing posts with label sea surface temperature. Show all posts

Sunday, 21 August 2016

Naïve empiricism and what theory suggests about errors in observed global warming

In its time it was huge progress that Francis Bacon stressed the importance of observations. Even if he did not do that much science himself, his advocacy for the Baconian (scientific) method, gave him a place as one of the fathers of modern science together with Nicolaus Copernicus and Isaac Newton.

However, you can also become too fundamentalist about empiricism. Modern science is characterized by an intricate interplay of observations and theory. An observation is never free of theory. You may not be aware of it, but you make theoretical assumptions about what you see in any observation. Theory also guides what to observe, what kind of experiments to make.

[UPDATE. I finally found the Darwin quote I had wanted to use below. It is:
About thirty years ago there was much talk that geologists ought only to observe and not theorise; and I well remember some one saying that at this rate a man might as well go into a gravel-pit and count the pebbles and describe the colours. How odd it is that anyone should not see that all observation must be for or against some view if it is to be of any service! ]
Charles Darwin often claimed to adhere to Bacon's ideals, but he had another side. University of California professor of biology and philosophy Francisco Ayala writes in Darwin and the scientific method:
“Let theory guide your observations.” Indeed, Darwin had no use for the empiricist claim that a scientist should not have a preconception or hypothesis that would guide his work. Otherwise, as he wrote, one “might as well go into a gravel pit and count the pebbles and describe the colors. How odd it is that anyone should not see that observation must be for or against some view if it is to be of any service”
But his ambivalence is seen in Darwin's advice to a young scientist:
Let theory guide your observations, but till your reputation is well established be sparing in publishing theory. It makes persons doubt your observations.
The same ambivalence is seen in Einstein. Mitigation skeptics like this quote:
No amount of experimentation can ever prove me right; a single experiment can prove me wrong.
They quote this when the observations show less changes than the model. If the observations show more changes than the model/theory the observations, they quickly forget Einstein and the observations are suddenly wrong.

In practice Einstein was more realistic. Prof in molecular physics [[John Rigden]] wrote in his book about Einstein's wonder year 1905: "Einstein saw beyond common sense and, while he respected experimental data, he was not its slave."

That is perfectly reasonable. When theory and observations do not match, the theory can be wrong, the observations can be wrong and the comparison can be wrong. What is called observations is nearly always something that was computed from observations and also that computation can be imperfect. Only when we understand the reason, can we say what it was.

The main blog of the mitigation skeptical movement, WUWT, on the other hand is famous for calling trying to understand the reasons for discrepancies: "excuses".

Global mean temperature

That was a long introduction to get to the graph I wanted to show, where theory suggests the global mean temperature estimates in some periods may have problems.

The graph was computed by Andrew Poppick and colleagues[, now published in Advances in Statistical Climatology, Meteorology and Oceanography] and it looks as if the manuscript is not published yet. They model the temperature for the instrumental period based on the known human forcings — mainly increases in greenhouse gasses and aerosols (small airborne particles from combustion) — and natural forcings — volcanoes and solar variations. The blue line is the model, the grey line the temperature estimate from NASA GISS (GISTEMP).



The fit is astonishing. There are two periods, however, where the fit could be better: world war II and the first 40 to 50 years. So either the theory (this statistical model) is incomplete or the observations have problems.

It is expected that the observations in the WWII are more uncertain. Especially the sea surface temperature changes are hard to estimate because the type of ships and thus the type of observations changed radically in this period. The HadSST estimate of the measurement methods is shown below. During WWII American war ships dominated and they mainly used Engine Room Intake observations, whereas before and after the war merchant ship would often measure the temperature of a bucket of sea water.



The figure above are the observational methods estimated by the UK Hadley Centre for HadSST. Poppick's manuscript uses GISTEMP. Its sea surface temperature comes from ERSST v4. (The land data of GISTEMP comes from the stations gathered by NOAA (GHCNv3) and additional Antarctic stations).

ERSST estimates the observational methods of ships by comparing the sea surface temperature to the night marine air temperature (NMAT). This relationship is only stable over larger areas and multiple years. They can thus not follow the fast changes in the WWII observational methods well.

Also for HadSST it is not clear whether these corrections are accurate and they are large: in the order of 0.3°C. What makes this assessment more difficult is that in the beginning of WWII there was a strong and long [[El Nino event]]. Thus a bit of a peak is expected, but it is not clear whether the size is right.

I would not mind if a reviewer would request to add a statistical model that includes El Nino as predictor in Poppick's paper. That would reduce the noise further (part of the remaining noise is likely explained by El Nino) and that would make it easier to assess how well the temperature fits in the WWII.


The Southern Oscilation Index (SOI) of the Australian Bureaux of Meteorology (BOM). Zoomed in to show the period around WWII. Values below -7 indicate El Nino events and above +7 La Nina events.

It would be an important question to resolve. The peak in the WWII is a large part of the hiatus (a real one) we see in the period 1940 to 1980. If you think the peak in the 1940s away, this hiatus is a lot smaller. The lack of warming in this period is typically explained with increases in aerosols. It ended when air pollution regulations slowed the growth of aerosols; especially in the industrialised air quality improved a lot. I guess that if this peak is smaller, that would indicate that the influence of aerosols is smaller than we currently think.

While the observations hardly showed any warming the first 40 to 50 years, the statistical model suggests that there should have been some warming. The global climate models also suggest some warming. And also several other climate variables suggest warming: the warming in winter, the time lakes and rives freeze and break up, the retreat of glaciers, temperature reconstructions from proxies, and possibly sea level rise. See for example this graph of the dates rivers and lakes froze up and broke up.



I wrote about these changes in my previous post on "early global warming". Poppick's statistical model adds another piece of evidence and suggests that we should have a look whether we understand the measurement problems in the early data well enough.

By comparing the observations with the statistical model we can see periods in which the fit is bad. Whether the long-term observed trend is right cannot be seen this way because the statistical model would still fit well, just with a different coefficient for the long-term forcings. This relationship is likely biased in a similar way as the simple statistical models used to estimate the equilibrium climate sensitivity from observations. This model, and thus theory, does provide a beautiful sanity check on the quality of the observations and suggests periods which we may need to study better.


Related reading

Falsifiable and falsification in science

Early global warming

On the naive empirical view of Australian politician Malcolm Roberts on science: What Climate Change Skeptics Aren’t Getting About Science

Piers Sellers in The New Yorker: Space, Climate Change, and the Real Meaning of Theory

Cowtan, Kevin Douglas, Robert Rohde and Zeke Hausfather, 2017: Evaluating biases in Sea Surface Temperature records using coastal weather stations. Quarterly journal of the royal meteorological society. doi: 10.1002/qj.3235

Thompson, David W.J. , John J. Kennedy, John M. Wallace & Phil D. Jones, 2008:
A large discontinuity in the mid-twentieth century in observed global-mean surface temperature. Nature, 453, pages 646–649, doi: 10.1038/nature06982.

References

Andrew Poppick, Elisabeth J. Moyer, and Michael L. Stein, 2016: Estimating trends in the global mean temperature record. Unpublished manuscript. Now published in Advances in Statistical Climatology, Meteorology and Oceanography

* Portrait of Francis Bacon at the top is taken from Wikipedia and is in the public domain.

Thursday, 12 February 2015

Just the facts, homogenization adjustments reduce global warming

Climatologists make adjustments to climate data to remove non-climatic changes (homogenization). This fact is used to accuse them of fiddling with temperature data to create or exaggerate global warming. This is often done by showing for a small piece of the data and suggesting it is typical. Often mentioned is the USA, where the raw data only show half the warming of the adjusted data. However, the USA is big, but still only 2% of the Earth's surface.

In recent weeks we had a similar case in The Telegraph about Paraguay. Last year we had similar misleading stories about two stations in Australia and the stations in New Zealand.

Global temperature collections contain thousands of stations. CRUTEM contains 4,842 quality stations and Berkeley Earth collected 39,000 unique stations. No wonder some are strongly adjusted up, just as some happen to be strongly adjusted down. In fact it would be easy to present a station where the raw data shows a cooling trend of several degrees being adjusted to a warming trend. However, then the reader might start to think if the raw data is really better.

The information on small regions or a few stations is normally not put into perspective: the average trend over all stations is only adjusted upwards slightly.

It is normally not explained why these adjustments are made nor how these adjustments are made.

Zeke Hausfather, an independent researcher that is working with Berkeley Earth, made a beautiful series of plots to show the size of the adjustments.

The first plot is for the land surface temperature from climate stations. The data is from the Global Historical Climate Dataset (GHCNv3) of NOAA (USA). Their method to remove non-climatic effects (homogenization) is well validated and recommended by the homogenization community.

They adjust the trend upwards. In the raw data the trend is 0.6°C per century since 1880 while after removal of non-climatic effects it becomes 0.8°C per century. See the graph below. But it is far from changing a cooling trend into strong warming. (A small part of the GHCNv3 raw data was already homogenized before they received it, but this will not change the story much.)



Not many people know, however, that the sea surface temperature trend is adjusted downward. These downward adjustments happen to be about the same size, but go into the other direction. See below the sea surface temperature of the Hadley Centre (HadSST3) of the UK MetOffice.



Being land creatures people do not always realise how big the ocean is, but 71% of the Earth is ocean. Thus if you combine these two temperature signals taking the area of the land and the ocean into account you get the result below. The net effect of the adjustments is a reduction of global warming.



It is pure coincidence that this happens, the reasons for the adjustments are fully different.

The land surface temperature trend has to be adjusted up because old temperatures were often too high due to insufficient protection against warming by the sun, possibly because the siting of the stations improved and there are likely more reasons.

The old sea surface temperature are adjusted downward because old measurements were made by taking a bucket of water out of the ocean and the water cooled by evaporation during the measurement. Furthermore, modern measurements are made at the water inlet of the engine and the hull of the ship warms the water a little before it is measured.

But while it is a pure coincidence and while other datasets may show somewhat different numbers (the BEST adjustments are smaller), the downward adjustment does clearly show that climatologists do not have an agenda to exaggerate global warming. That would still be true if the adjustments had happened to go upward.



Related reading

If you need a peer reviewed reference, the influence of the adjustments on the global mean temperature is also shown in Karl et al. (2015).

Phil Plait at Bad Astronomy comment on the Telegraph piece: No, Adjusting Temperature Measurements Is Not a Scandal

Kevin Cowtan made two videos on the claim of the Telegraph on Paraguay and the Arctic. The second video shows how to check such claims yourself.

John Timmer at Ars Technica is also fed up with being served the same story about some upward adjusted stations every year: Temperature data is not “the biggest scientific scandal ever” Do we have to go through this every year?

The astronomer behind And Then There's Physics writes why the removal of non-climatic effects makes sense. In the comments he talks about adjustments made to astronomical data. Probably every numerical observational discipline of science performs data processing to improve the accuracy of their analysis.

Steven Mosher, a climate "sceptic" who has studied the temperature record in detail and is no longer sceptical about that reminds of all the adjustments demanded by the "sceptics".

Nick Stokes, an Australian scientist, has a beautiful post that explains the small adjustments to the land surface temperature in more detail.

My two most recent posts were about some reasons for temperature trend biases: Temperature bias from the village heat island and Changes in screen design leading to temperature trend biases

You may also be interested in the posts on how homogenization methods work (Statistical homogenisation for dummies) and how they are validated (New article: Benchmarking homogenisation algorithms for monthly data)

Tuesday, 10 February 2015

Climatologists have manipulated data to REDUCE global warming

Climatologists are continually accused of fiddling with the data to make global warming stronger for political purposes by political activists.

A typical scam is to show a few stations that have been adjusted upwards and act as if that is typical. For example, recently The Telegraph article, "The fiddling with temperature data is the biggest science scandal ever", wrote about someone comparing
temperature graphs for three weather stations in Paraguay against the temperatures that had originally been recorded. In each instance, the actual trend of 60 years of data had been dramatically reversed, so that a cooling trend was changed to one that showed a marked warming.
Three, I repeat: 3 stations. For comparison, global temperature collections contain thousands of stations. CRUTEM contains 4,842 quality stations and Berkeley Earth collected 39,000 unique stations. No wonder some are strongly adjusted up, just as some happen to be strongly adjusted down. In fact it would be easy to present a station where the raw data shows a decreasing trend of several degrees being adjusted upwards, but then the reader might start to think if the raw data is really better.

What these people do not tell their readers is that the average trend over all station is only adjusted upwards slightly. That would put things too much in perspective. What these people do not tell their readers is why these adjustments are made. That might make some think that it may make sense. What these people normally do not tell their readers is how these adjustments are made. That would not sound sufficiently arbitrary and conspirational.

Last year we had similar scams about two stations in Australia and the stations in New Zealand.

In an internet poll, 88% of the readers of the abysmal Telegraph piece agree with the question: "Has global warming been exaggerated by scientists?"

I hope that after reading this post, these 88% will agree that they have been conned by The Telegraph. That scientists have actually made global warming smaller.

Zeke Hausfather, an independent researcher that is working with Berkeley Earth, made a beautiful series of plots to show the size of the adjustments.

The first plot is for the land surface temperature from climate stations. The data is from the Global Historical Climate Dataset (GHCNv3) of NOAA (USA). Their method to remove non-climatic effects (homogenization) is well validated and recommended by the homogenization community.

They adjust the trend upwards. In the raw data the trend is 0.6°C per century since 1880 while after removal of non-climatic effects it becomes 0.8°C per century. See below. But it is far from changing a cooling trend into strong warming.

(In case you believe many national weather services are also in the conspiracy: a small part of the GHCNv3 raw data was already homogenized before they received it.)



Not many people know, however, that the sea surface temperature trend is adjusted downward. That does not fit the narrative of WUWT & Co. It sounds like even many scientists did not know that. These downward adjustments happen to be about the same size, but go into the other direction. See below the sea surface temperature of the Hadley Centre (HadSST3) of the UK MetOffice.



Being land creatures people do not always realise how big the ocean is. Thus if you combine these two temperature signals taking the area of the land and the ocean into account you get the result below. The net effect of the adjustments is a reduction of global warming.



It is pure coincidence that this happens, the reasons for the adjustments are fully different.

The land surface temperature trend has to be adjusted up because old temperatures were often too high due to insufficient protection against warming by the sun and possibly because the siting of the stations improved. There are likely more reasons.

The sea surface temperature are adjusted downward because old measurements were made by taking a bucket of water out of the ocean and the water cooled by evaporation during the temperature measurement. Furthermore, modern measurements are made at the water inlet of the engine and the hull of the ship warms the water a little before it is measured.

But while it is a pure coincidence and while other datasets may show somewhat different numbers (the BEST adjustments are smaller), the downward adjustment does clearly show that climatologists do not have an agenda to exaggerate global warming. Like all reasonable people already knew. That would still be true if the adjustments had happened to go upward.

[UPDATE:

Small networks

The smaller the networks, the larger the size of the non-climatic changes typically is.

A recent paper about the US mountain network (SNOWTEL) explained that their mountain stations showed more warming than the lower lying USHCN stations. This could be a snow-albedo feedback (that the warming reduces the white snow and reveals the dark surface leading to more warming. However they found it was a non-climatic change in the temperature due to in the installation of new equipment. The new instruments recorded about 1.5°C higher minimum temperatures; an extraordinary large change (the maximum temperature was hardly affected). Accurate data is not just important for trends, but also for physics (snow-albedo feedback).

That is another case of climatologists reducing warming and a feedback.

But what did a well-know blog of the mitigation sceptics, WUWT, write? They headlined: "Another bias in temperature measurements discovered" and opened: "From the “temperature bias only goes one way department”".

The second comment is by "cg": "Lying in Weather Reporting is common place and shamelessly just like the Global Financiers want it. Pure Evil."
Brute: "You sound insane."
KaiserDerden: "no more insane than you do claiming CO2 controls the weather/climate… actually less so in fact ...
Brute: "I have never said a single word regarding how “CO2 controls the weather/climate”. It is curious how much paranoia one finds around here... just about as much as one finds among the warmist cults...."
Sun Spot: "@Brute, you sound sanctimonious"
Ofay Cat: "CG ... you have it right ... those others are uninformed or misinformed. Which means Liberal."
cg: "Thanks"
]

Let's end on a depressive note. Rob Honeycutt says:
Take note. Proving the conspiracy wrong is sure to be taken as proof you’re part of the conspiracy.

It would be interesting to track, but I somehow doubt the number of “skeptic” posts with accusations of fraud is going to change. And I think this is merely because the source of the “skepticism” isn’t rooted in true scientific skepticism. It’s formed on an ideological basis. So, asking them to accept the data as correct is the same, from their standpoint, as asking them to change their ideology.
End of rant. Sorry for the tone. One sometimes gets the impression that WUWT & Co. select the most stupid memes possible to produce the largest antagonistic effect possible. It would be too easy to talk about the real caveats, the ones also mentioned by the enemy in the IPCC reports. For example, that assessing the impacts of climate change is enormously difficult because it involves ecosystems and humans. For example, that estimating trends in extreme weather is very challenging and very much current research; also partially due to non-climatic changes in the daily data.

[UPDATE. This version got a bit snarkier than usual, which maybe warranted in talking to hardcore mitigation sceptics. To link to in discussions with people who might be open for debate, I have written a second matter-of-fact version: Just the facts, homogenization adjustments reduce global warming. In case of doubt, when you do not know people well, that is probably also the best version.]



Related reading

If you need a peer reviewed reference, the influence of the adjustments on the global mean temperature is also shown in Karl et al. (2015).

Phil Plait at Bad Astronomy comment on the Telegraph piece: No, Adjusting Temperature Measurements Is Not a Scandal

John Timmer at Ars Technica is also fed up with being served the same story about some upward adjusted stations every year: Temperature data is not “the biggest scientific scandal ever” Do we have to go through this every year?

The astronomer behind And Then There's Physics writes why the removal of non-climatic effects makes sense. In the comments he talks about adjustments made to astronomical data. Probably every numerical observational discipline of science performs data processing to improve the accuracy of their analysis.

Steven Mosher, a climate "sceptic" who has studied the temperature record in detail and is no longer sceptical about that reminds of all the adjustments demanded by the "sceptics".

Nick Stokes, an Australian scientist, has a beautiful post that explains the small adjustments to the land surface temperature in more detail.

My two most recent posts were about some reasons for temperature trend biases: Temperature bias from the village heat island and Changes in screen design leading to temperature trend biases

You may also be interested in the posts on how homogenization methods work (Statistical homogenisation for dummies) and how they are validated (New article: Benchmarking homogenisation algorithms for monthly data)