For years, climate scientists have assured us that NOAA’s homogenized temperature datasets—particularly the Global Historical Climatology Network (GHCN)—are the gold standard for tracking global warming. But what if the “corrections” applied to these datasets are introducing more noise than signal? A recent study published in Atmosphere has uncovered shocking inconsistencies in NOAA’s adjustments, raising serious concerns about the reliability of homogenized temperature records.
The study, conducted by a team of independent climate researchers led by Peter O’Neill, Ronan Connolly, Michael Connolly, and Willie Soon, offers a meticulous examination of NOAA’s homogenization techniques. These researchers, known for their expertise in climate data analysis and critical evaluation of mainstream climate methodologies, gathered an extensive archive of NOAA’s GHCN dataset over more than a decade. Their research involved tracking over 1800 daily updates to analyze how NOAA’s adjustments to historical temperature records changed over time.
Their findings reveal a deeply concerning pattern of inconsistencies and unexplained changes in temperature adjustments, prompting renewed scrutiny of how NOAA processes climate data.
The study analyzed NOAA’s GHCN dataset over a decade and found that:
- The same temperature records were being adjusted differently on different days—sometimes dramatically.
- 64% of the breakpoints identified by NOAA’s Pairwise Homogenization Algorithm (PHA) were highly inconsistent, appearing in less than 25% of NOAA’s dataset runs.
- Only 16% of the adjustments were consistently applied in more than 75% of cases, meaning the majority of “corrections” are shifting unpredictably.
- Less than 20% of NOAA’s breakpoints corresponded to actual documented station changes, suggesting that many adjustments were made without supporting metadata.
In layman’s terms: NOAA is repeatedly changing historical temperature records in ways that are inconsistent, poorly documented, and prone to error.
What Is Homogenization Supposed to Do?
Homogenization is a statistical process meant to remove non-climatic biases from temperature records, such as changes in station location, instrument type, or observation time. NOAA’s PHA algorithm adjusts temperature records based on statistical comparisons with neighboring stations—without needing actual metadata to confirm whether an adjustment is necessary.
This method has been defended by NOAA researchers, who claim it effectively removes bias. However, the new study suggests it might be introducing arbitrary and inconsistent changes that could distort temperature trends.
If NOAA’s adjustments are inconsistent, how can we trust the long-term climate trends derived from them? Here’s why this matters:
- Garbage In, Garbage Out: Climate models and policy decisions rely on adjusted temperature data. If those adjustments are unreliable, the conclusions based on them are questionable.
- Artificial Warming or Cooling? The study did not specifically analyze whether these inconsistencies bias the data towards warming or cooling, but past research has shown that homogenization tends to amplify warming trends.
- Lack of Transparency: NOAA’s daily homogenization updates mean that the past is constantly being rewritten, with little accountability or external validation.
The study’s authors argue that homogenization should not be done blindly without using actual station metadata. Instead, adjustments should be:
- Ground-truthed with station metadata whenever possible—not just assumed based on statistical models.
- Made transparent—users of temperature data should be informed about exactly when and why adjustments are made.
- Re-evaluated for bias—does homogenization systematically increase warming trends?
If NOAA’s temperature records are truly the best we have, they should be robust, reproducible, and verifiable. Instead, this study suggests they are a moving target, adjusted differently depending on the day, and often without a clear reason.
The question we must ask is this: Is the global temperature record a reliable dataset, or just a statistical house of cards?
We need transparency, accountability, and scientific rigor in climate science. Until then, every NOAA temperature dataset should be taken with a grain of salt.
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Isn’t it a stretch anyway to say we ‘know’ the industrial era global temperature to within half a degree, even before the quibbling over homogenization? First, until a few years ago, the industrial era began in 1850, then it became 1880 which was a bit odd. Livingstone only got up the Congo in 1870. A mere 10 years later, had some one installed a weather station and was actually keeping daily recordings?. Zimbabwe (Rhodesia) wasn’t a colony until about 1895: did the Matabele teach themselves to write, and start keeping records, which they have stored and kept? The Congo itself is about the size of Europe. South American temp stats are equally patchy. During WW2 did countries all around the world prioritise maintaining their thermometers, and saving the data from the bombs?Why would anyone believe any data about anything from the Soviet Union, 1917-1990 – a country covering about a seventh of the earth’s land – nor from China 1949 to present? China was so chaotic 1920-1949 if data exists its inherently unreliable. I don’t recall British rulers in India being too bothered about temperature, apart from in a loose way, and I doubt if the post-independence Indians had the competence to, or interest in, maintaining scrupulous records. In short, global temperature is a guess. Smarty boots can extrapolate and homogenize and do all sorts of clever stuff, but they’re still guessing. So the claim, that we are 1 degree, or 1.5 or 2 degrees above pre-industrial temperatures is itself a guess: we neither knew pre-industrial temperature, nor is our industrial era global temperature construct accurate in any meaningful sense.
Climate science believes you can increase resolution and accuracy by averaging measurements which have uncertainty. Of course that requires them to use their common meme that all measurement uncertainty is random, Gaussian, and cancels out. That way they can assume the stated values are 100% accurate and can generate unlimited measurement resolution through averaging.
The standard deviation for an annual Global Mean Temperature is several tens of degrees. To get a higher precision, one has to specify the locality and date. That is to say, the uncertainty for the global temperature for an unspecified location and time is so large that to display it with the proper number of significant figures, the Kelvin scale should be used.
1850 was when the first oil well was dug in Pennsylvania.
1880 was the coldest year in the 19th century and the lowest CO2 measurement in that century.
When did industrialization start?
Was it in the Bronze age when humans started using metals? Was it the Roman Empire that produced weapons and armor and ships of a scale never seen before the rise of the empire? Was it in the mid-1700s when the concept of mass production/interchangeable parts came into being. Was it when steam powered machines were used in garment factories?
I suspect it was defined as the date of the first oil well given the whole push it to eliminate hydrocarbon fuels.
caerbannog666
@DaleGribble_666
Here are 4 global temp curves that I recently computed from raw & adjusted data (using my own global temp app):
1) All stations raw
2) All stations adjusted
3) Rural stations raw
4) Rural stations adjusted
You apparently don’t know the difference between “raw”, original, historic temperature data and bastardized data. You are comparing one set of bastardized date to another set of bastardized data.
The Original, Written Temperature record, from which the Hockey Stick is supposedly derived, does not have a Hockey Stick “hotter and hotter and hotter” temperature profile, anywhere on Earth.
The Hockey Stick temperature profile was created in a computer, from bogus data, by dishonest people with a Climate Change agenda.
Here, find a Hockey Stick temperature profile in one of these 600 unmodified, original charts from all around the world. Hint: Don’t waste your time looking for a Hockey Stick profile among them because there isn’t one. The Real World doesn’t have a Hockey Stick chart “hotter and hotter and hotter” temperature profile. It only exists in the fevered minds of Climate Alarmists, put there by dishonest Temperature Data Mannipulators.
https://notrickszone.com/600-non-warming-graphs-1/
fire everyone involved
publish the raw average
How is it that the surface temperature trend is higher than the measurements via balloons and satellites with respect to the tropical tropospheric region? Whatever happened to the missing hotspot?