Moritz Büsing
Some time ago I stumbled upon a curiosity in temperature measurement publications of the last 30 years:
When you turn the temperature anomaly curves into absolute temperature curves then the past has been getting colder.
The decade 1880 to 1890 is in recent publications 0.3°C (0.5°F) colder than it was in publications from 15 years ago, and 0.5C (0.9°F) colder than it was in publications 30 years ago. The weather station database for land surface temperatures of this time period has not changed much in the last 30 years, but the analysis methods have changed.
Therefore, I went down the rabbit hole and tried to understand how one analyzes the data from thousands of weather stations at many different locations with changing technologies over time. Here I found a systematic error in one of the most important analysis processes: homogenization
Homogenization consists of removing stepwise breaks and trends in the data series that result from non-climate related sources. For example, relocating a weather station from the top of a mountain to the valley can cause a permanent offset in temperature measurements. Also using a new type of thermometer or a new type of housing of the thermometer can permanently change the measured temperatures. These changes lead to stepwise breaks in the data series. Other changes, such as urbanization, lead to non-climate related trend changes in the data series that are also permanent. These permanent errors are corrected by increasing or decreasing all the past data at a stepwise break such that the temperature curve becomes continuous (This process is not trivial, and I will not elaborate on it here).
Here I discovered the error:
Not all non-climate related changes are permanent.
Especially the ageing effects of the paint or plastic of a weather station housings are removed, when the housing is repainted or replaced. But after the aging effects have been removed, the new paint or plastic starts to age again. A study by a team at the Istituto Nazionale die Ricerca Metrologica in Turin, Italy Comparative analysis of the influence of solar radiation screen ageing on temperature measurements by means of weather stations confirms that this ageing effect is real.
This alone would not be a big issue. The ageing effect only reaches 0.1-0.2°C (0.18-0.36°F) difference which would be negligible, and indeed undetectable by the homogenization algorithms. The homogenization algorithms can neither detect such a small warming trend from aging nor the tiny downward stepwise break from renewal. However, when other sources for larger stepwise breaks (change in location, new instrumentation) coincide with repainting, replacing or at least cleaning of the housing, then a systematic error occurs where these small steps are added up each time.
While the aging effect is too small to detect in individual weather stations due to the noisy data, it is still large enough to detect in the changes of temperature trends in a statistical analysis of thousands of weather stations. So, I analyzed the homogenized data sets from the National Centers of Environmental Information (NCEI) in comparison with the non-homogenized data sets. Here I was indeed able to identify and quantify the ageing effects.
On average, a stepwise break is corrected once in every 19 years of weather station data. Therefore, there are on average roughly 7 “corrections” of the weather station data of the last 140 years. Even a small aging effect of 0.1°C would then lead to roughly 0.7°C of erroneously recorded global warming!
This is only a rough estimate, so I looked at the global land surface temperature calculation GISTEMP from the Goddard Institute for Space Studies (GISS). They did a really good job in making their methods transparent and offered all their tools for download online, so everybody can reproduce their results. I corrected the aging effect in the homogenized data set and ran this corrected data set with the tool from the GISTEMP team. The result is a reduction of the temperature change between the decades 1880-1890 and 2010-2020 from 1.43°C to 0.83°C CI(95%) [0.46°C; 1.19°C].
This result also shows a better fit with satellite data provided by the University of Alabama in Huntsville (UAH):
I collected all the sources and wrote a paper about my findings: Correction of Systematic Error in Global Temperature Analysis Related to Aging Effects. I tried to publish this paper in four different peer reviewed journals, but it was always rejected with canned answers (“…our readers would not be interested…”) even before it was reviewed by a peer.
My methods were very careful and I made several conservative assumptions. In the paper I also quantify a less conservative analysis, which leads to only 0.41°C global warming within 140 years.
One more interesting finding is, that the corrected temperature curve is a worse fit with the CO2 concentrations. The R² values (statistical number identifying how much one data set predicts another data set) of the resulting temperature curves and the base 2 logarithm of CO2 (temperature change per doubling of CO2) are the following:
– GISTEMP: up to 92%
– Corrected conservative mean: up to 73%
– Estimate of the corrected mean without conservatisms: up to 36%
This means, that a smaller fraction of global warming is caused by CO2. So, for the conservative case up to 73% of 0.83°C global warming, i.e. at most 0.61°C, are caused by CO2. For the less conservative case only up to 36% of 0.41°C global warming, i.e. at most 0.15°C, are caused by CO2.
These temperature data curves are the basic input data for many other studies and are the calibration targets of many climate models. This will revolutionize climate science, if my findings are confirmed.
The precise number is not that important to me. What is important is that this analysis indicates there is yet another reason to question how much temperatures have increased since 1850 and how much is attributable to CO2.
The list of uncertainties continues to grow. Coverage of land pre 1900 was 12% in the SH. Millions of square miles of ocean pre 1900 had no regular SST direct measurements. Questions are continuing to be raised about even recent temperature measurements.
Millions of square miles of wetlands have been destroyed and massive deforestation has occurred in the last 200 years probably affecting temperatures. Questions about the effects of UHI are still being debated.
We are coming out of the LIA and the tidal gauge data don’t look much different from when we just started out of the LIA.
Instead of increasing our knowledge of how much temperatures are increasing and the role of CO2, we are backtracking and the doubts just keep mounting.
we are coming out of a ‘LIA but
IT HASNT WARMED??????
IT WAS COLDER IN THE PAST, BUT ITS NOT WARMER NOW!!!
WE DONT KNOW EXACTLY HOW MUCH WARMER, THEREFORE IT WASNT COLDER BEFORE
Now you are just spamming
Mosher is just trying to be his cutie self. He knows what I was talking about. He is upset he bet on the wrong horse years ago and the facade is collapsing before his very eyes.
Nobody knows or will ever know the exact proportion of warming from CO2. They will go on for generations with a big question mark. The honest scientists will admit that. The rest will be blowing smoke.
Mosh, like Nick, will say and do whatever is necessary to protect their paychecks.
I’m going out on a limb and guessing that you actually think you are being funny,
Since your statement doesn’t look even slightly like any argument that’s actually been made, the only thing you manage to look like is stupid.
Prof. Lindzen: “Misrepresentation, exaggeration, cherry picking, or outright lying pretty much covers all the so-called evidence marshalled in support of the theory of imminent catastrophic global warming caused by fossil fuels and CO2″.
Climate Science is Awash with Manipulated Data, Which Provides No Reliable Scientific Evidence to Support the Proposed [‘The Enhancement and Standardization of Climate-Related Disclosures for Investors’] Rule.
Climate Science is Awash with Manipulated Data, Which Provides No Reliable Scientific Evidence to Support the Proposed [Enhancement of Civilization]
Fixed!
Having your work published on WUWT gives it a claim to priority. In due course this site will be the go to source for knowledge on climate change. Most journals claiming authority on climate change have been reduced to propaganda vehicles. Your experience is proof of this.
RSS and UAH are tropospheric measurements and lag the surface temperature up to a month.
NOAA/NCEP Reynolds sea surface temperature uses satellite observation to interpolate measurements taken at buoys. It appears to be the most reliable temperature record but only covers water surface.
There are other systematic errors with surface stations. Most are located in developed areas. The change to electronic instruments has removed thermal lag from the measurement and corrections for that do not replicate earlier instruments.
And correlation is not causation. The reason for temperature increase in the Northern Hemisphere is the same reason temperature is reducing in the Southern Ocean – orbital changes, primarily driven by the precession cycle.
If CO2 played any role in the warming and there was next to no natural variation then the Southern Ocean could not have a long-term cooling trend.
Homogenized milk is not milk.
Homogenized data is not data. It is modeling.
Infilling isn’t data. Infilling is modeling.
Adjusted data is not data. Adjusted data is modeling.
The Earth’s climate is not univariate. It is multivariate. I suspect cloud fraction has a greater influence on perceived temperature than a trace gas. Cloud modeling is an oxymoron.
And so on……
At the end of last year, I noticed that Moritz Büsing had floated a draft paper and commented on how hard it was to interest a publisher. We then had some emails that I hope have helped to us seeing this article on WUWT.
In real life, Moritz is in helicopter engineering. He is not a greenhorn with raw views about measurements. He has investigated and publicized here a problem that earlier had little more than a passing mention in the literature. Some of the topic was related to the early work on ageing Stevenson screens by Anthony Watts. Moritz especially noted the ways that the error was more than a one-off in a typical time series and was able to be propagated with increasing effect.
I am surprised by people like Mosh and Nick taking a dismissive, antagonistic approach. What is wrong with acknowledgement that there is a genuine source of error, then constructively trying to get its correction into the general methodology for improving the historical record?
Geoff S
Geoff said: “What is wrong with acknowledgement that there is a genuine source of error, then constructively trying to get its correction into the general methodology for improving the historical record?”
Nothing. I’ve been trying to convince the WUWT audience of this for awhile, but the overwhelming response I get here is that acknowledgement of errors and especially trying to correct them is fraudulent even to the point of being criminal. Maybe it would be a good article idea for you or someone else well respected by the WUWT audience.
Moritz Busing said: “On average, a stepwise break is corrected once in every 19 years of weather station data. Therefore, there are on average roughly 7 “corrections” of the weather station data of the last 140 years.”
Did these cylindrical radiation shield stations go into service 140 years ago?
Moritz Busing said: “This result also shows a better fit with satellite data provided by the University of Alabama in Huntsville (UAH):”
What does the comparison look like with ERA5 and other datasets?
Moritz Busing said: “The ageing effect only reaches 0.1-0.2°C (0.18-0.36°F) difference which would be negligible, and indeed undetectable by the homogenization algorithms. The homogenization algorithms can neither detect such a small warming trend from aging nor the tiny downward stepwise break from renewal.”
GISTEMP uses the GHCN-M repository which uses pairwise homogenization. The code can be found here. Were you able to demonstrate that the PHA was unable to detect to the aging drift and cleaning changepoint?
Answer: Irrelevant
2. What does the comparison look like with ERA5 and other datasets?
Answer: Unnecessary to Möritz Büsing’s conclusions.
3. … Were you able to demonstrate that the PHA was unable to detect …
Answer: Büsing has presented a robust prima facie case. The burden of proof is on GISS to prove their code DID detect … .
If the cylindrical radiation shields did not exist 140 years ago then how could there be 7 “corrections” based on a 19 year recurrence interval?
If Moritz Busing wants legitimize his analysis based off comparisons then why not compare with other datasets. ERA5 was my recommendation because it doesn’t do homogenization. It does 4D-VAR. But I’d like to see other datasets in the mix as well.
GISS does not perform homogenization. But that is moot because I’m not so much concerned with who does it as compared to whether it is right or not. If Moritz Busing thinks it is wrong then he needs to demonstrate that. And if wants to be really convincing he needs to show how to fix it like what everyone else is expected to do.
I think none of the weather stations, maybe an insignificantly small number, have operated for the full 140 years. That was not my point. The data-base consists of an highly overlapping chain of first hundreds , later thousands of concurrent weather station measurements. One can choose any number of non-overlapping chains in this data-base and on average each of these chains would have roughly 7 stepwise homogenizations.
I compared with the GISTemp data set, because I used the exact same input data provided by NOAA as my baseline and I used the weighted averaging algorithm provided by GISS for analyzing the “corrected” input data. This shows purely the effect of the my “correction”
If you are interested in comparing with other data sets, then feel free to do so. There a plenty of comparisons between GISTemp, HADCRUT, BEST, etc. compiled by other people. There are also comparisons with ERA5, but be warned, ERA5 is the unholy mix of climate prediction models and empirical data analysis. There is no way to validate the climate models it uses with empirical evidence due to a circular dependence between input and output.
Your last paragraph just shows that you did not read the paper.
Do journals operate under any kind of regulation? What kind of regulations must they abide by? Do scientific journals operate under stricter regulations? I would think that if a journal claimed to be scientific it would need to show reason to not publish studies that question the popular consensus. That seems outdated, ignorant, dangerous and I don’t understand how it can be legal to block an opposing view.
No, there is no regulation. They are completely free to publish, or not publish whatever they want. They are completely free in choosing the “peers” for peer review. They are also free to charge any amount they want.
But to be honest: Despite being unable to publishing my work in an official way, I would be even more worried about the course of scientific development, if there were government control of which content may, or may not be published.
Sydney 1.5C CAGW solved for a century and a half-
Dark roofs to be banned in NSW, planning minister says | Urban planning | The Guardian
Do the Sydney uni numpties really know what they’re challenging here with their 2.4C light rooves?
All men and women worldwide who are concerned about the climate of the earth should wear white coats and hats. Until they do, their concern about the climate is overwhelmed by fashion.
Even better would be tinfoil hats!
Dear Mr. Büsing,
Three things are very clear:
1. You have done careful, honest, data analysis and made a powerful case refuting the conjecture of the AGW scammers.
2. Your being attacked vehemently and repeatedly by known data fiddlers and unprincipled AGW promoters here merely shows that you are over the target: they know they won’t convince anyone who is informed; they are here to shore up any of their base (party affiliation varies depending on which country they are from) who might be convinced by your evidence to vote against policies/people promoting bogus data products, solar, wind, electric vehicles, and other junk.
3. The above attacks are SO poorly executed that they are doing much to SUPPORT YOUR CASE (heh — I “yelled” to mock a certain data scammer) 🙂 and indicate strongly that AGW is a big fat lie.
In short: Well done!
Sincerely and with admiration,
Janice Moore
The well know “we have more cold steps than warm and we dont know why, but we adjust them out anyway” which you can read in NOAAs publications.