From NOT A LOT OF PEOPLE KNOW THAT
By Paul Homewood
https://www.bbc.co.uk/weather/articles/clyp513ynv3o
Chris Morrison’s excellent piece in the Daily Sceptic today, which I trailed earlier, deals with the corruption of the Met Office’s temperature data by “temperature spikes”.
Chris wrote:
Last year, the Met Office claimed an all-time UK high May 1st temperature at Kew of 29.3°C. Analysis by citizen scientist Dr Eric Huxter showed the temperature was almost 2°C above that recorded in the hour before – well above what might be expected from such temperature rises seen during the day, with movements commonly around the plus or minus 0.2°C to 0.4°C mark.
The first record claimed last week was on Tuesday May 25th, when the temperature at the Kew site rose to 34.8°C – some 1.3°C above the previous hour. Dr Huxter has told the Daily Sceptic that some doubt remains over the figures for the next day, when the temperature hit 35.1°C. Since April last year, Huxter observes that Kew has provided no fewer than 13 daily UK extremes with an average heat spike of 1°C. By comparison, in the same period Heathrow supplied 35 temperature spikes averaging 1.2°C.
The main culprit in producing these heat spikes is the switch from liquid-in-bulb thermometers to PRT automatic electronic measuring devices during the last 30 years. These provide a more accurate reading every minute, but it is plain that they are picking up every passing heat spike – often unnatural – that were missed by slower-moving liquid in a glass bulb. Dr Huxter has calculated that in the glass-bulb era up to 1989, the 40 new records (0.3 a year) averaged steps from the previous high of 0.5°C, while from 1990 there have been 147 new records (four per year) with average steps of 1.5°C. This sudden change is used by alarmists – many of them employed by the Met Office – to suggest dramatic climate change. But an obvious and plausible explanation is provided by the switch to more accurate measuring devices.
The BBC, of course, place the blame for spikes firmly on global warming:
With temperatures hitting a record breaking 35.1C this week, it has been an exceptional May heatwave.
In its build up we saw temperatures increase rapidly – by up to 10C in just two days in some locations.
Historically, it would have been more common to see a gradual increase of a degree or two each day.
The rapid onset from an average to high, even extreme, temperature – or a “heat spike” – is something I and fellow meteorologists have noticed happening more often.
Ed Hawkins, professor of climate science at the University of Reading, told the BBC that “Today’s heat events are emerging earlier, intensifying faster and occurring across a much warmer background climate”.
While according to Dr Ségolène Berthou from the Met Office, “We can’t explicitly say that extreme heat temperatures spike faster now than they did in the past,” experts are beginning to piece together a number of other factors that could provide an explanation.
https://www.bbc.co.uk/weather/articles/clyp513ynv3o
It is of interest that the Met Office’s scientist can’t actually find any evidence that temperatures are spiking faster! But that does not stop the unreliable Hawkins from saying just that.
But given that Dr Eric Huxter has scientifically proven beyond any reasonable doubt that heat spikes at Met Office stations are a product of the switch from liquid-in-bulb thermometers to PRT automatic electronic measuring devices during the last 30 years, the whole Hawkins/BBC argument falls to pieces.
Combine that with the proliferation of dodgy, junk temperature stations in the Met Office network, which amplify temperatures on hot, sunny days, and all you get is a mirage of heat spikes.
There’s a huge spike in insanity coming…
MILIBAND COMMITS GOVERNMENT TO 87% EMISSIONS CUT BY 2040 IN NET ZERO PUSH
Ed Miliband has signed up to a legal target to cut the UK’s greenhouse gas emissions by 87% by 2040. Not stopping this train…
This is in order to reach Net Zero by 2050. The 2038-42 period is the seventh ‘carbon budget.’ The Climate Change Committee says “meeting the target will require households to install heat pumps instead of new boilers, switch to electric cars and vans and eat less meat and dairy.”
Strap in…
https://order-order.com/2026/06/02/miliband-commit-government-to-87-emissions-cut-by-2040-in-net-zero-push/
Of course there are more heatspikes.
Formerly normal weather has become heatwaves – that’s where most spikes come from.
And there is something off with Milibands math.
He want to cut greenhouse gas emissions by 87% within 13 years (pretty sure England has all the trillion and infrastructure,batteries and workforce to replace it).
But he needs 10 years for the last 13%.
Why are the last 13% being replaced 6* slower?
Given that 163 new warmest UK May temperature records were set just last month, with the previous warmest May record being broken by >2C twice on consecutive days, isn’t this debate somewhat moot?
You assume those numbers are correct. You assume too much. That is what this debate is about.
Does the UAH satellite show anything unusual in the way of temperatures? No, UAH shows no record heat now.
It was 95F at my house yesterday. It will be about 85F today.
It is not any hotter today than in the past, and that includes the unique UK climate, where they think heatwaves begin around 82F, which is considered a cool, mild day around here.
Of course it’s not! Pear tree blossom bursting in Feb/Mar year after year now, instead of Apr/May. My location where 30C was once a rare once in a decade event happens multiple times a year. Heatwaves causing discomfort on 1976 levels are now almost yearly, often several periods per year.
Argue about accuracy of heat records from some sites fine, but claiming the UK climate has not warmed, and it is not the warmest it has been in probably 400 years; that’s the realms of extreme fruitloopery.
From some sites?
From 26/04/2025 522 Temperature Maxima (473 UK Daily Maximum) from 114 Weather Stations, averaging 4.6 per station.
Of these readings 353 (67.6%) have a known time (to the minute GMT) Maximum Temperature was recorded, 202 (56.6%) occurring before the published maximum hourly reading.
The mean temperature spike above the Previous Hour is 1.25°C with a 7.5% probability of occurring at a CIMO 1 site.
For all readings the average spike above Maximum/Previous Hour is 0.70°C with a 18.8% probability of occurring at a CIMO1 site.
Given that 61.1% happen on/before Maximum hour the average spike for all dates without a known time taken from hour before the maximum is 1.7°C with a 2.9% probability
Mean ventilation is 36.2% of minimum assumed for PRTs
Only 58 (60.4%) of these stations have wind data
It appears that you have spent some time analyzing sub-minute data. If only climate science wasn’t stuck in the old tradition of Tmax+Tmin/2. And weren’t stuck to using temperature and enthalpy instead.
warmest it has been in probably 400 years
You mean since the little ice age…
400 years ago it was cold.
So yes. UK is warmer now than then.
No one is claiming no warming, just that the warming is predominantly natural.
This issue is about measurement instrumentation only and bogus proclamations that do not bother with a basic analysis of alternatives.
Phil Jones says there were three periods of warming since the end of the Little Ice Age about 1850, the first temperature high point was in the 1880’s, then temperatures cooled for several decades, and the second period of warming began around 1910 with a high point in the 1930’s, and then the temperatures cooled for a few decades, and the third warming period began around 1980 and continues through today.
Phil Jones says all three periods of warming are of equal magnitudes. That means we are not experiencing unprecedented warming today.
The Climate Alarmist God, Phil Jones, can’t be wrong. Right?
No unprecedented warming today.
If you were alive in 1880, you would be telling us how hot it is.
Can’t argue with that!
Not so acute up here in Scotland. But for us, it’s definitely night time temperatures that are warmer than in decades of the past.
I was ten when I watched the first flakes of snow fall on Boxing Day 1962 as that great winter started and yes when it did snow it stayed around much longer but we also lived in far colder domestic conditions then, lofts weren’t insulated, no double glazing heating for most was paraffin, coal and limited electricity as the domestic systems electrical couldn’t carry much current. Windows and doors were all draughty. Most houses could only afford to heat a couple of rooms and many a kid put their school uniform in bed with them in the mornings to warm it up. Frost on the inside of a window was common . So yes winters were slightly colder and yes subjectively even colder. However now I can’t help but think the warming extremes are being consciously spun to death, with hyperbole the order of the day. Why? You need to look into the wealthiest global government at Davos. These people are elite eugenicist and are using global warming /net zero as a means to an end. They now set the agenda for UKMO, its no longer a ministry of defence meteorological office, its now a propaganda outfit with the purpose of setting we’re all going to die narrative. Remember Derna Dam in Libya? Neglected since Obama and Clinton brought down Qaddafi after a deep med low at the end of summer supposedly burst the Derna Dams . We eye witnesses all said they heard explosions . The dam collapse was at the end of the summer of global boiling 2023, An opportunity arose to use the med low as another sign of global warming . I know this because this is how it was presented through all the news agencies. Around October Rishi the then PM gave a downing street speech about delaying net zero till 2035 as it was being rushed and people weren’t ready, I believe he mentioned Derna dam twice in that speech as a warning about the planet overheating. It was all choreographed. and part of a plan
“Does the UAH satellite show anything unusual in the way of temperatures? No, UAH shows no record heat now.”
How do UAH global satellite measurements apply specifically to the UK?
They don’t. I’m just waiting for the inevitable hand waiving. It should be amusing.
How do UK temperatures apply specifically to the globe?
The definition of a heatwave is three days of temperatures above 25 degrees Celsius except in London where it’s three consecutive days above 28 degrees Celsius (82 degrees Fahrenheit).
What is a heatwave?
The World Meteorological Organization* defines it as five or more consecutive days during which the daily maximum temperature surpasses the average maximum temperature by 5 °C (9 °F) or more.
https://www.iipa.org.in/cms/public/uploads/222841610370027.pdf
UK met office no longer use the WMO definition, in 2018 they changed it to:
“A UK heatwave threshold is met when a location records a period of at least three consecutive days with daily maximum temperatures meeting or exceeding the heatwave temperature threshold, dependant on location.” (currently that is just 28ºC max in urban areas, lower in rural areas and no minimum duration)
https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/temperature/heatwave
Clearly this is so they can claim that heatwaves occur more frequently, which is an obvious lie if they have to change the definition to make that claim. Of course, this also means they can claim “hottest since records began”, as a new record started with the definition change. I’m reasonably sure the UK has not seen a heatwave meeting the WMO definition for many years, maybe decades and CERTAINLY NOT this year. We have seen nothing outside of natural variability.
*The WMO has also re-defined heatwaves since this publication, and their website now gives this vague description:
“A heatwave can be defined as a period where local excess heat accumulates over a sequence of unusually hot days and nights.”
Translation: ‘it’s whatever we say it is, whenever we say it is’.. it would seem they are now fully behind the ‘climate crisis’ scam too.
June 5, 1950 – The Flying Scotsman train derails at Tollerton, Nottinghamshire due to heat-buckled track.
2 June 1975, A cricket match in Buxton, Derbyshire. between Derbyshire and Lancashire, had to be postponed due to a freak snow storm.
It’s called “natural variability”
“2 June 1975, A cricket match in Buxton, Derbyshire. between Derbyshire and Lancashire, had to be postponed due to a freak snow storm.”
Yes, I know I was there! What you don’t say is that on June 6 a heat wave started leading to a long hot summer followed by the heat and drought of 1976!
https://en.wikipedia.org/wiki/1976_British_Isles_heatwave
“Does the UAH satellite show anything unusual in the way of temperatures? No, UAH shows no record heat now.”
Since they haven’t released their May data yet obviously not! Of course their published numerical data isn’t sufficiently resolved to show what is happening in the UK, it doesn’t even show what’s happening in Europe.
Their map does show more detail though and for April it shows the south of England having a positive anomaly 1.5ºC above the “seasonal norm”, it’ll be interesting to see what their map shows for May.
https://www.uah.edu/aosc/data-products/global-temperature-report
Apparently some here don’t like the facts!
The UAH global TLT was released for May today a +0.53 deg. C departure from the 1991-2020 mean, which is up from the April, 2026 value of +0.39 deg. C.
I used to think 82°F was hot, 90 was unbearable, and 100 was impossibly hot.
Fifty years later — after moving from North Dakota to Arizona — I actually look forward to that summer heat. It makes these old bones feel a whole lot better. Supposed to hit 103 today, and honestly, I’m thrilled.
Of course, in Arizona you can mentally subtract about 10 degrees from the “feels like” as long as you stay out of the sun. The sun here is intense year‑round. In summer it turns the pavement into a nice toasty 160°F.
I’ve even mowed grass down here in 105‑plus temps — just a small dog park, about 30–40 minutes, usually in the evening when the sun angle is low. Not too bad, though I still ended up soaked. Kind of like my native Minnesota at 80°F with high humidity — different heat, same sweat
Met Office?
You can’t be serious.
Yes, the Met Office is a meteorological agency.
Were you people born yesterday?
Massive Cover-up Launched by U.K. Met Office to Hide its 103 Non-Existent Temperature Measuring Stations – DS
If you believe their “extrapolations“, then you clearly were born yesterday.
As usual, we’re meant to simply accept your implication that they’re deceitful. No questions asked.
And no, diatribes from cretins like Chris Morrison are not evidence.
Emotion over fact doesn’t work.
Surface Stations Project
https://tallbloke.wordpress.com/index-page-surface-stations-project/
Nice try.
I had assumed that the weather station at Heathrow was for pilot information as it is sited next to the North runway (and just feet away from the Northern Perimeter Road and acres of asphalt car parks) where it would give information like air temp and pressure, wind speed and direction etc, all valuable information when you are trying to put a fully laden 747 down safely. Turns out that Heathrow have their own weather network for pilot information, and they don’t use the Met office station at all. They may have in the past, but not any more. Why then, if not deceit, do the Met office give ‘highest evah’ temp readings from such a tainted site?
https://www.youtube.com/watch?v=V6jNYc43cdw
https://maps.app.goo.gl/rDGwYX136czLYJqb9
“Why then, if not deceit, do the Met office give ‘highest evah’ temp readings from such a tainted site?”
You have not yet demonstrated that this site is genuinely compromised.
As Dr. Spencer notes, a station can be located within a less than ideal urban heat island environment and still provide reliable data for climate monitoring purposes.
Genuinely compromised?
Since 26/04/2025 Heathrow has recorded 35 temperature spikes Mean 1.2°C (7.5% Probability at a CIMO 1 site) Mean Wind 40.8%MAV
In the last 10 days:
21/05/2026 Heathrow (CIMO 3) 25m Est. 1948(LIGT Era) recorded 24.6°C at 13:32 GMT 1.8°C above Previous hour with a 2.5% probability at a CIMO 1 site No Wind Data
On 24/05/2026 Heathrow(CIMO 3)at 14:22GMT recorded a 0.57°C spike in 2 minutes (0.29°C/minute) with a <0.960% probability at CIMO 1 site
On 25/05/2026 Heathrow(CIMO 3)at 14:23GMT recorded a 0.43°C spike in 3 minutes (0.14°C/minute) with a <5.802% probability at CIMO 1 site
26/05/2026 Heathrow (CIMO 3) 25m Est. 1948(LIGT Era) recorded 35°C at 13:54 GMT 1.0°C above Previous hour with a 10.9% probability at a CIMO 1 site33.3% of Minimum Assumed Ventilation for PRT in Stevenson Screen
On 27/05/2026 Heathrow(CIMO 3)at 13:24GMT recorded a 0.78°C spike in 4 minutes (0.20°C/minute) with a <2.834% probability at CIMO 1 site
28/05/2026 Heathrow (CIMO 3) 25m Est. 1948(LIGT Era) recorded 32°C at 13:58 GMT 2.0°C above Previous hour with a 1.7% probability at a CIMO 1 site 50.0% of Minimum Assumed Ventilation for PRT in Stevenson Screen
On 31/05/2026 Heathrow(CIMO 3)at 14:26GMT recorded a 1.03°C spike in 6 minutes (0.17°C/minute) with a <4.228% probability at CIMO 1 site
On 01/06/2026 Heathrow(CIMO 3)at 12:31GMT recorded a 0.55°C spike in 1 minutes (0.55°C/minute) with a <0.026% probability at CIMO 1 site
This doesn’t demonstrate instrument bias.
Similar spikes could have occurred elsewhere under the same weather conditions.
Rapid temperature fluctuations are not unusual and can result from factors – changes in cloud cover or turbulent mixing.
The relevant question is whether Heathrow’s average temperature record is systematically biased relative to nearby stations. That is something we can evaluate by comparing separate long term station records.
A list of short term spikes, by itself, does not establish that the climate record is compromised.
Jim Gorman could have responded to this comment by pointing out the nature of absolute temperatures, but he chose not to. I wonder why.
You still fail to understand the term measurement bias. Here is what NIST says about bias. It is similar to JCGM 100-2008.
2.1.1.3. Bias and Accuracy
Bias is a systematic error unique to a measurement device. It can only be evaluated by calibration, not by comparison to another device that has its own systematic error.
Let’s be honest, you and climate science describe the fact that two data streams cannot be directly connected because there is an offset. That offset occurs for some reason like a new instrument or a move. That presents a dilemma about how to connect them so you can have a long series of data to evaluate.
To solve that dilemma, one must make a decision that one or the other series or maybe even both must be adjusted to make them match. It is justified by bastardizing the term “bias” to mean something it is not. The fact that they both may be accurate to the nth degree is immaterial. There is no evidence that either station is inaccurate, only that they have different values.
That is fabricating data regardless of how you look at it.
This should be treated by analyzing each stream separately for trends and evaluating how each individual trend differs. The fact that one must live with the fact that there is no “long” record to show people is just a fact of being scientifically correct.
Plenty of stations maintain long, continuous records and can therefore be used to identify potential systematic errors or discontinuities in other station records. Field calibration is not the only way such issues can be detected.
Even the stations shown and alleged here by other commenters can produce reliable climate records provided their surrounding environment remains stable through time.
“To solve that dilemma, one must make a decision that one or the other series or maybe even both must be adjusted to make them match.”
Your description does not align with how homogenization is typically performed.
Homogenization does not simply force two station records to agree with one another.
Instead, it looks for relative discontinuities by comparing a station to the surrounding network.
For example:
Station A suddenly exhibits a +1°C jump in 1990.
Nearby stations B, C, D, E, and F do not show a comparable shift.
That suggests a non climatic change may have occurred specifically at Station A, such as a site move.
The adjustment is therefore informed by the behavior of the surrounding stations, not by arbitrarily forcing one record to match another.
“There is no evidence that either station is inaccurate, only that they have different values.
That is fabricating data regardless of how you look at it.”
I don’t understand how that conclusion follows.
You’re acknowledging that different stations can legitimately have different absolute temperatures and that there is no evidence either station is inaccurate.
That is entirely consistent with the position taken in climate science.
So where exactly is the fabrication?
The mere existence of different absolute temperatures does not imply that anyone is inventing data.
Did you not read what NIST and the GUM says. Systematic errors can only be quantified by a calibration procedure. That is THE SCIENCE. You can try and make assertions otherwise, but that is only broadcasting misinformation.
You are correct, IT DOES NOT agree with homogenization. Homogenization spreads measurement uncertainty around with no admission that the uncertainty has increased due to the procedure. It is exactly what I described. It is a computer algorithm to fabricate data.
You apparently didn’t read what I wrote about making up data.
https://courses.ems.psu.edu/bioet533/node/654
This is not a joke. This page also said:
Did you read the word misconduct?
Homogenization cannot even be passed off as interpolation. For proper interpolation one needs actual data from the given station. An example is interpolating a temperature from 2 days ago and today. Using different stations is nothing more than a guess. If you like I can give you a map of NWS stations in my area and black one out so you can find an homogenized value that is correct.
“That suggests a non climatic change”. How do you know that? How does a computer algorithm know that? A climatic change could be something that caused one data measurement to be incorrect. That data should simply be marked invalid. If it appears to be a permanent change, then an investigation or maintenance visit should occur. Continued fabrication of data is NOT the proper avenue.
Quite a straw man you have built. “So where exactly is the fabrication“? It occurs when data is fabricated for stations that no longer exist. It occurs when “adjustments” are made to long series of data because there is a perceived “bias” with out any evidence.
I would recommend you download the U.S. ASOS manual and read the portion of quality checking data. Data that doesn’t pass is marked as faulty for a reason. U.S. CRN information is available that shows the flow chart for checking data quality and marking readings with a 9999 when it doesn’t pass. I assure you, there are plenty of the 9999’s scattered throughout the 5 minute data from CRN stations. It is one of the things I am wrestling with on how to handle. My engineering background and ethics just won’t let me create data to replace the missing without also generating a file that details where and why it was done. The MET office can’t even do that.
“Did you not read what NIST and the GUM says. Systematic errors can only be quantified by a calibration procedure. That is THE SCIENCE. You can try and make assertions otherwise, but that is only broadcasting misinformation.”
The GUM is primarily concerned with metrology: instrument calibration, reference standards, measurement uncertainty, etc.
Calibration is indeed the primary way to identify instrument bias. However, climate homogenization is often trying to detect a different class of problem altogether, such as station relocations or changes in the surrounding environment.
Those are not calibration problems.
A thermometer can be perfectly calibrated and yet still exhibit a discontinuity in its temperature record following a site move or a substantial change in local surroundings.
In such cases, comparisons with neighboring stations can provide evidence that something changed in the record even when the instrument itself remains accurate.
And, again, Chris Morrison’s article does not discuss the GUM, metrology, calibration procedures, or instrument uncertainty.
He simply asserts that the estimates are unreliable without quantifying the resulting error or bias.
“You are correct, IT DOES NOT agree with homogenization. Homogenization spreads measurement uncertainty around with no admission that the uncertainty has increased due to the procedure. It is exactly what I described. It is a computer algorithm to fabricate data.
You apparently didn’t read what I wrote about making up data.”
Your claim that homogenization simply “spreads uncertainty around” is difficult to reconcile with the observational evidence.
Consider the USCRN, which is often regarded as the highest quality surface temperature network in the United States and requires little to no homogenization.
Compare its temperature trends with those from adjusted datasets such as nClimDiv.
Despite being independently constructed datasets, they show remarkably similar long term trends.
If homogenization were introducing substantial artificial warming or propagating uncertainty in the manner you describe, one would expect the adjusted datasets to diverge significantly from high quality reference networks. That is not what we observe.
And yes, I read what you wrote about making up data.
That’s why I responded with: “emotion over fact doesn’t work.”
Your characterization of the Met Office’s actions seems less grounded in the evidence than in an emotional desire to find wrongdoing in climate science. That desire may be influencing how you’re interpreting the situation.
And here is your problem. Yes, changing the microclimates can cause a difference in measurements, however, that is not proof that either series of records is inaccurate. The records at the old microclimate may be 100% accurate but may be different than 100% accurate readings at the new microclimate.
The difference is not sufficient to call one “biased” and requires a correction. As I have shown you in documentation measurement bias is a systematic uncertainty that does not change. It causes inaccurate measurements to be made.
LOL. nClimDev is adjusted to match CRN. Of course they are going to look alike!
My basis for questioning ANY data change without physical evidence is based on my scientific training as an engineer. Changing data is at best questionable considering scientific ethics and is legally not acceptable. Everything I have learned is that if data is questionable, it is declared not fit for use.
Measured data is declared not fit for use when it cannot meet the specific requirements of its intended application period, end of story. If you don’t believe that data is sacrosanct from a scientific standpoint then you are operating in a pseudoscientific arena where anything goes.
“Yes, changing the microclimates can cause a difference in measurements, however, that is not proof that either series of records is inaccurate. The records at the old microclimate may be 100% accurate but may be different than 100% accurate readings at the new microclimate.”
But they have introduced a discontinuity into the time series.
The issue is not whether the measurements at the old site or the new site are accurate. Both may be perfectly accurate for their respective locations.
The problem is that the earlier segment of the record was collected under one set of local conditions, while the later segment was collected under another. That makes direct comparison of the two segments problematic if the goal is to construct a continuous climate record.
Accuracy and continuity are not the same thing.
“The difference is not sufficient to call one “biased” and requires a correction. “
Your comments are contradictory.
If there is no discernible difference between the measurements, then on what basis would a correction be necessary?
A correction implies that a measurable error or bias has been identified.
If no such difference can be demonstrated, there is nothing to justify applying a correction.
“LOL. nClimDev is adjusted to match CRN. Of course they are going to look alike!”
No. This paper conducts an independent comparison. Still great alignment:
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2009JD013094
“That suggests a non climatic change”. How do you know that? How does a computer algorithm know that? A climatic change could be something that caused one data measurement to be incorrect.”
By comparing the station to the surrounding observational network.
“Quite a straw man you have built. “So where exactly is the fabrication“? It occurs when data is fabricated for stations that no longer exist.”
The simple fact is that extrapolation or estimation based on observed statistical relationships is not fabrication.
You can repeatedly characterize it that way, but that does not make it true.
“It occurs when “adjustments” are made to long series of data because there is a perceived “bias” with out any evidence.”
Now I really don’t understand your position.
If you don’t see evidence of bias, then why are you echoing the claims made by Chris Morrison and others at WUWT that the Met Office is engaging in fraud?
Fraud is a serious accusation. If there’s no evidence of bias or deliberate misconduct, what is the basis for making or supporting that claim?
How do you know what systematic biases those other other stations have? How do you know the uncertainty of temperature measurements at those stations and how those uncertainties propagate into the subject station? You can’t just assume they are 100% accurate.
I don’t usually quote Wikipedia, but it has a rather succinct description of extrapolation.
Extrapolation is basically a guess. How do you assign an uncertainty to a guess? Is it ±2 degrees or maybe ±4 degrees? Will the uncertainty allow you to consider it a new record with any semblence of confidence?
You continue to define bias as a recognizable difference but fail to show how that difference is due to a systematic uncertainty that causes the record to be inaccurate. In other words, there is no evidence that the current record is inaccurate due to a calibration issue.
The fact that two records differ in value is not evidence that one is inaccurate. Applying a correction without physical evidence of inaccuracy just in order to make them match so a long record can created is fabrication. Is it fraud or is it ignorance of scientific ethics? Only you can make that decision.
“How do you know what systematic biases those other other stations have? How do you know the uncertainty of temperature measurements at those stations and how those uncertainties propagate into the subject station? You can’t just assume they are 100% accurate.”
Stations can and do have systematic errors. However, systematic errors do not necessarily affect trends. A constant offset can leave the long term trend largely unchanged.
Second, uncertainty in neighboring stations does not make those observations useless. If multiple independent thermometers measuring the same regional climate signal show similar behavior while one station abruptly diverges, that constitutes evidence that something changed at the divergent station.
No one is assuming the neighboring stations are 100% accurate. The point is that independent observations provide a basis for comparison.
By the same logic, how do you know the station exhibiting the discontinuity is the correct one? Uncertainty cuts both ways.
“Extrapolation is basically a guess.”
Extrapolation is an estimate, but it is not an arbitrary guess.
It is based on observed statistical relationships between the station and neighboring stations while they were all operating. Those relationships are then used to estimate values when one station is no longer available.
You may disagree with the methodology, but estimating values from documented correlations in observational data is not fraud.
“The fact that two records differ in value is not evidence that one is inaccurate. Applying a correction without physical evidence of inaccuracy just in order to make them match so a long record can created is fabrication. Is it fraud or is it ignorance of scientific ethics? Only you can make that decision.”
Yep, you are conflating continuity with accuracy.
In the framework you’re describing, you’re correct: different temperatures and different microclimates are not evidence that either instrument is inaccurate.
But climate homogenization is often addressing a different question: the issue is not whether the measurements are accurate for their respective locations. The issue is whether a station move, change in surroundings, or other non-climatic change has introduced a discontinuity into the time series.
You just keep dancing around trying to justify your argument. It won’t work because too many folks here have experience dealing with data under legal and regulatory requirements.
That is simply an assertion.
I never contradicted the metrology references you provided. In fact, I used them to explain the distinction between measurement accuracy and record continuity.
You also seem to misunderstand homogenization, as the following claim is not one that someone familiar with the methodology would make:
“Part of the problem is that the absolute temperature may very well end up in a homogenization algorithm that propagates inaccurate data throughout the entire process.”
Similar spikes could have occurred elsewhere under the same weather conditions.
With the same consistently low probability of occurring at a CIMO 1 site. PRTs record short term highly localised temperature changes (micro-weather) whose maxima bias public perception and the national weather record.
If the fluctuations are short lived and occur in both directions, positive and negative, they will tend to average out over longer timescales.
That is one reason climate scientists generally focus on monthly averages, annual averages, and long-term trends rather than minute to minute extremes.
You got that right. Averages hide information that is pertinent. That is why every mean should have an associated standard deviation shown. Otherwise, incomplete statistics are being portrayed.
If you want to analyze the distribution of the data, then by all means calculate and examine the standard deviation. Many analyses do exactly that.
However, you can calculate and evaluate a trend without reporting the standard deviation alongside it.
Those are different statistical questions.
A changing standard deviation will result in a spurious trend. The mean could even stay the same but the variance in the data points can cause a trend that is not reliable.
The author repeatedly describes the Met Office estimates as “invented” or “fabricated” data, but never actually shows that the estimates are inaccurate.
If a station closes, and its historical temperature record was highly correlated with nearby stations while it was operating, there is no obvious reason why statistical estimates based on those neighboring stations would automatically be invalid.
The relevant question is not whether the values were estimated. The relevant question is whether the estimation method introduces significant error or bias.
The article never answers that question. Instead, it largely assumes that because a station no longer exists, any reconstructed data associated with it must be unreliable.
It seems tailored to the tin foil hat audiences although I wouldn’t be surprised if he genuinely believes it himself. After all, he previously used a VERY OBVIOUS El Niño driven peak in the UAH record as evidence for an alleged Hunga Tonga cooling effect.
Most amusing. Like one of our record breakers: LHR
Improper siting does not automatically mean a station’s climate time series is compromised.
https://www.drroyspencer.com/2025/12/
On the subject of which WMO (or UKMO) class of station is suitable for long-term climate monitoring, I think it’s important to note that a station could be placed in a non-natural, anomalously warm urban environment, but as long as that environment stays the same over time, it can probably still be used for climate change monitoring.
Yada yada yada.
Try as you might to defend the indefensible – the politicised MO – you are wasting your time. And everybody else’s.
Emotion over fact doesn’t work.
Dover’s supposed weather station doesn’t exist. The nearest station is in Folkestone – except that doesn’t exist either.
What do they have? Linear regression.
That’s funny – and expensive.
The Met Office uses multiple correlated stations in the reconstruction, not just one nearby location.
The Met office is a weather forecaster and political tool.
They should be retracting UKCP18 – ask the IPCC – but they’re keeping quiet on it even though it is based entirely on fabrications based on RCP8.5. They’re keeping quiet because…
Ed Miliband has signed up to a legal target to cut the UK’s greenhouse gas emissions by 87% by 2040.
Not stopping this train… – Guido Fawkes
Emotion over fact doesn’t work.
Is the record stuck?
Emotion over fact doesn’t work.
Facts 😉
LOL. A reconstruction is not observational data. It’s a statistical backfill — the climate‑science equivalent of estimating my inheritance by “reconstructing” my mother’s reconstructed asset sheet from 15 years ago. Looks impressive on paper, but it’s still an inference stacked on top of another inference.
At best, reconstructions are model‑conditioned estimates with wide error bars. Once you start layering in priors, assumptions, and the usual climate‑change bias corrections, you’re no longer measuring anything. You’re generating outputs that reflect the model architecture more than the physical world.
Defending that as hard data is defending the indefensible. It’s a narrative engine, not an instrument. The numbers stopped being a direct reflection of real‑world measurements a long time ago. Period.
Again, the reconstruction is based on the correlation of observational data, both from the station’s time series when it was operational and from nearby stations (both those that were operational in the past and those operating at present).
The assumption that the historical relationship between stations continues after a station closes is not arbitrary. Temperature anomalies are known to exhibit substantial spatial correlation over large distances, which is precisely why interpolation methods work at all.
Anomalies are not temperatures. They are a ΔT and carry no information about the absolute temperature that creates them. One of the excuses for creating them was being able to inform local residents of the absolute temperature. If you can’t accurately create the absolute temperature from an anomaly, what is the purpose of having it.
n anomaly is simply the difference between an observed temperature and a local climatological baseline.
It tells us whether temperatures are above or below what is normal for that location and by how much. This mathematical construct allows temperatures from different stations within a region to be compared consistently.
If a station’s anomaly is becoming increasingly positive over time (as is clearly the current case given the rapid warming and record breaking temperatures observed in climate datasets), it indicates that the station’s absolute temperature is increasingly exceeding its historical baseline.
This is all meaningful climate information even though the anomaly itself is not an absolute temperature.
Well said!
You are arguing against science. You won’t win. Here is a key. If a station doesn’t exist, how do you calculate its measurement uncertainty without having an actual instrument?
Chris Morrison isn’t calculating measurement uncertainty for his allegation that the Met Office estimates are invalid either.
In fact, he doesn’t quantify the error at all.
It’s interesting to observe you apply criticism selectively.
And that proves exactly what?
“And that proves exactly what?”
That Chris Morrison has not provided anything approaching convincing evidence that Met Office data is compromised.
He does not appear to meet the scientific standards you mention, yet you and others continue to defend both his arguments and his accusations against the UK Met Office.
“the politicised MO”
What is politicised?
Do you think regression is politicised?
Do you think statistical correlation is politicised?
Do you think mathematics in general is politicised?
Do you think Dr. Spencer and his blog are politicised?
So, you see no problem with UKCP18 whatsoever.
Noted.
You completely deflected from your ‘Met Office extrapolations are fraud’ blah blah blah.
Noted.
Massive Cover-up Launched by U.K. Met Office to Hide its 103 Non-Existent Temperature Measuring Stations – DS
If you believe their “extrapolations“, then you clearly were born yesterday.
You see no problem with what the IPCC has described as the implausible. That implausibility is baked hard into everything that the UK will be doing to address an imaginary climate crisis – at vast expense and with empty coffers to boot.
Therefore, your argument is implausible. It seems the IPCC agrees.
Emotion over fact doesn’t work.
BTW, here is the climate crisis:
https://www.pnas.org/doi/10.1073/pnas.1616287114
Here’s the big picture
Why omit the context of the Holocene?
In the absence of a trend, what else can you ask?
Lol.
I think all trends are important, but the most relevant one for assessing whether there is currently a climate crisis is the most recent.
Plants and animals seem more adapted to Holocene temperature variability than to a time when crocodiles lived at the North Pole.
Do contrarians really imagine crocodiles at the North Pole? I thought those were polar bears!
Yada x 3
Emotion over fact doesn’t work.
People should be seeing a pattern here.
You are quite the parrot.
That pattern is clear for all to see.
A parrot?
Where do you see a parrot? Aren’t you looking at a computer screen?
I suppose you see all sorts of strange animal behavior.
A parrot?
Emotion over fact doesn’t work.
Neither does claiming an imaginary climate crisis
PS Emotion over fact doesn’t work… haven’t you got any originality? Do you have to filtch from others?
“Neither does claiming an imaginary climate crisis”
Let’s revisit the conversation:
You said there is no climate crisis. I disagreed and presented paleoclimate evidence to support my position. You then responded with your own paleoclimate evidence. I replied by explaining what I saw as the flaw in your argument.
Your response was: “Yada × 3.”
I’m not sure what that means in this context.
Is it intended as additional paleoclimate evidence?
Is it a donkey?
Is it a cat?
Is it shorthand for dismissing my argument without addressing it?
I genuinely don’t know, and I’d like some clarification if you don’t mind.
“PS Emotion over fact doesn’t work… haven’t you got any originality?”
Yes, I do. It’s just fun seeing you project.
Are you for real?
Makes a change from MUR I suppose.
Yes, I am serious.
In science, claims are supported by evidence. If you are claiming that there is no climate crisis, you should provide evidence to support that claim.
How about a 20+% of greening of the earth. How about fewer cold deaths. How about abundant grain harvests. How about less energy used to heat during winters.
Now why don’t you tell us how CAGW climate change has killed polar bears, killed coral reefs, raised sea levels to cover houses, made deserts, etc.
“How about a 20+% of greening of the earth.”
Not a trend observed everywhere simultaneously. Some places are getting drier and thus less green.
“How about less energy used to heat during winters.”
Winters in many Arctic regions need to remain cold enough for thick ice roads to form to allow access to remote mines and communities. Warmer winters are NOT always a good thing.
“Now why don’t you tell us how CAGW climate change has killed polar bears, killed coral reefs, raised sea levels to cover houses, made deserts, etc.”
Delayed sea ice formation lengthens the fasting period for many polar bear population and this reduces the time available to hunt seals.
If sea ice continues to decline in regions where bears depend heavily on it for hunting, these nutritional challenges are expected to increase.
Immediate mortality is not the only indicator of a crisis. Nutritional stress can still provide considerable strain. And, of course, it is difficult to know how many bears may ultimately die as a result of those nutritional challenges.
https://polarbearsinternational.org/news-media/articles/polar-bear-eating-habits-fasting-periods
Same for global warming.
Just can’t admit that polar bear population has increased tremendously can you?
“Same for global warming.”
Most locations on the globe are warming. Rates are different, however.
“Just can’t admit that polar bear population has increased tremendously can you?”
Just can’t admit the polar bear population might starve can you?
Turned into an oracle have you?
Explain how.
Which doesn’t include the last 75 years!
Comedy gold, eh.
Inventing and fabricating data is an ethical violation of scientific protocols.
Here is a web page you need to read. I’ll include part of it here. (bold by me)
2.1 Falsification, Fabrication, Plagiarism | BIOET 533: Ethical Dimensions of Renewable Energy and Sustainability Systems
Emotion over fact doesn’t work.
This is one more example of climate science placing anomalies over the actual temperatures. The excuse here is that two wrongs make a right.
Part of the problem is that the absolute temperature may very well end up in a homogenization algorithm that propagates inaccurate data throughout the entire process.
One excuse I’ve read is that it is only used to inform people of “local” temperatures. Not informing people that the temperatures are also artificially increased because of its location is lying by omission.
“Part of the problem is that the absolute temperature may very well end up in a homogenization algorithm that propagates inaccurate data throughout the entire process.”
It doesn’t.
Using absolute temperatures instead of anomalies would be completely nonsensical for many climate applications because locations have vastly different baseline climates (a mountain station, a coastal station, a desert station, a valley station, etc.)
This issue can, however, be circumvented with temperature anomalies.
I should add that there is a new essay on WUWT that deals with the issue of anomalies. Perhaps you should read it for understanding.
Where?
You are obviously not trained in physical science at university. Invented and fabricated data would be automatically failed and could easily result in dismissal. The issue of “accurate/inaccurate” would never even be considered.
Would you allow a nuclear plant to invent or fabricate radiation release data estimated from correlated measuring devices? That would be considered a criminal act here in the U.S.
Would you approve a drug that had invented or fabricated data used in the approval process? How would you suggest that the data be proven “inaccurate”?
Why would you hold the MET to a lower standard when providing scientific data?
If the Met Office were creating values out of thin air and presenting them as direct observations, I would agree that would be unacceptable.
But that is not what is being described here.
The values are statistical estimates derived from observed relationships between real stations.
Whether those estimates are useful depends on their performance and validation, not on the fact that they are estimates.
Why defend a pitiful cretin like Chris Morrison?
Your definition of useful does not address the scientific ethics of changing data. Useful can be as little as making data agree with a predetermined outcome. Does that make it scientific?
If you were building a bridge, would you consider made up or fabricated data to be sufficient to put your signature on the final approval as properly designed to meet specifications? If not, why would you not hold scientific data to the same standard and simply declare not fit for use?
The relevant distinction is whether a value is being presented as a direct measurement or as an estimate derived from observations, and whether that estimate is transparently documented and validated.
The Met Office clearly does the latter.
You are just dancing around the issue. You cannot justify that “estimate” as either correct and that it is not fabricated.
Read this document again. It says unequivocally:
I simply cannot believe that you have taken advanced physical science courses that allowed one to “fabricate data” and treat it as real information.
In my classes, lab books were meticulously kept in ink. The devices and serial numbers were recorded. Processes documented. Data points were recorded for later analysis.
In business, data was also meticulously recorded and stored for future use in legal and regulatory processes. If errors were found, the data was marked through and notes provided explaining the reason. It was considered not fit for use from that point.
If it was necessary to estimate a replacement value, it had to be marked as such, and any calculation had to be positively noted and shown as conditional due to the use of estimated data. Show us where any of this is ever done in climate science.
No. Because it is understood meteorologically why it was unusually warm later in May – hot air coming from the south – and why it was unusually cool earlier in May – cold air coming from the north.
I live in northern Kansas. My brother lived in northern Oklahoma. His peak mowing started in early May while mine was in early June. Why? Because of seasonality. That is caused by the situation that 200 miles south they received more insolation sooner than I did. The same thing occurred in the fall, I lost insolation sooner than he did.
In a time series, seasonality causes a bias in trends that can be spurious. Climate science never addresses this fact. Anomalies as calculated do not remove this bias because they don’t normalize using a constant baseline value over the entire globe. Worse, averages hide the difference.
Show us some climate studies that have used SARIMA (S -> seasonality, AR -> autocorrelation, MA -> moving average) to deal with autocorrelation and seasonality. SARIMA is an acceptable treatment used to determine a stationary baseline trend.
“In a time series, seasonality causes a bias in trends that can be spurious. Climate science never addresses this fact. Anomalies as calculated do not remove this bias because they don’t normalize using a constant baseline value over the entire globe. Worse, averages hide the difference.”
Why would a constant baseline over the entire globe be necessary?
The seasonal cycle is not the same everywhere. The Northern and Southern Hemispheres are six months out of phase, and the magnitude of seasonality varies greatly with latitude.
Using a single global baseline would mix together regions with fundamentally different seasonal behavior.
It therefore makes more sense to calculate anomalies relative to each location’s own monthly climatology. That’s what climate science does.
Because it would accurately account for the variability of temperatures all over the globe. If everywhere was warming, the final figure would show that. Would it reflect an absolute temperature, you bet it would. A major improvement over a gigantic mixture of different components in the current anomaly structure.
“If everywhere was warming, the final figure would show that.”
Why would a global absolute temperature metric reveal this better than the anomaly dataset? If every location warmed relative to its own climatology, the anomaly record would show exactly that.
Your original claim was that anomalies fail to remove seasonality because they do not use a constant global baseline.
I asked why a constant global baseline would remove seasonality better than local monthly climatologies given that seasonal cycles differ substantially between hemispheres and latitudes.
Instead, you’ve shifted to arguing that a global absolute temperature metric would show warming if warming were occurring.
“… switch from liquid-in-bulb thermometers to PRT automatic electronic measuring device … provide a more accurate reading every minute, but it is plain that they are picking up every passing heat spike – often unnatural – that were missed by slower-moving liquid in a glass bulb. “
The term is “noisy”. So these newer detectors aren’t necessarily more accurate, they’re more sensitive to noise in the signal spectrum. Noise tends to be high frequency (faster rise times etc), so some kind of band-pass filtering might solve the problem.
Yes. In analytical chemistry we typically adjust the time constant of the measuring system to optimize signal to noise for the detection sensitivity needed. Traditionally, we used RC filtering to eliminate noise spikes. Today, digital data is post processed, mainly averaged.
There are hundreds of platinum resistance thermometers (PRT) available that have specific response characteristics to match the application to hardware. It’s obvious that these issues have not been adequately addressed in switching from conventional liquid in bulb thermometers to PRTs. Not surprisingly, the switches bias data to support the alarmist narrative.
First, different devices give different readings, even the same model. Comparing two different microclimates by averaging just hides those differences, it doesn’t remove them.
ASOS here in the U.S. has specific algorithms to attempt to emulate LIG readings, but they are still two different devices and comparisons are fraught with uncertainty. Here is some texts from the NOAA ASOS manual.
I haven’t included everything in the ASOS manual for brevity. This should give a pretty good picture. Sometime I may convert the CRN flow chart into text to show what it does.
The WMO specifies an air temperature sensor time constant (the time taken to reach 63% of a step change in temperature) of ≤20 seconds in flowing air.
To warmunists. this isn’t a bug, it’s a feature
I am into astrophotography and I use calibration frames to minimise the various noise sources when the image frames are stacked. There must be a way of identifying different noise sources in the temperature measuring system, from the thermometer probe itself through the various electronic components.
There is. It is called a measurement uncertainty budget that outlines all the influence quantities that cause uncertainty in measurements. This is covered in the GUM (JCGM 100-2008) and metrology training at various web sites.
Climate science has refused to do even the basic work in developing these budgets by using the mistaken assumption that averaging removes all the uncertainty.
Imagine taking a series of 30 photos and laying them on top of each other. You want to determine the brightness of a star by averaging the stack. Yet some photos have the area diminished by clouds, one may be occluded by a satellite. Would you trust the average? Averaging temperatures without considering all the uncertainties introduced ends up with the same problem. Is the mean value 100% accurate?
The stacking software is a bit more complicated than just taking the mean, I don’t really know what goes on in the software, but it could be that frames are rejected if data for a specific area falls outside the standard deviation of the same area across the remaining frames.
Would active cooling of the measuring electronics be of use? Dedicated astronomical cameras have active cooling to reduce thermal noise introduced by the sensor heating up.
My example was crude. I was attempting to show that you could find the luminosity of a star by averaging a number of different readings, some with full brightness and some with zero. Traditionally, that has been done with daily temperatures, one being the warmest, Tmax, and one being the coldest, Tmin, and finding the average. It started when someone had to mount a horse and go read a thermometer early in the morning for Tmin and again in the afternoon for Tmax.
Since the 1990’s automated stations have been deployed with various sub-hourly temperature data. There is little need to keep using Tavg as traditionally calculated. Does Tmax still have a use? Probably to get a value that people can relate to. However, to compare it to older temperatures is a stretch, especially to LIG thermometers that had much longer time constants for changing.
Apparently, to get around this somewhat the World meteorological organisation recommends using a 5-minute averaged reading. The UK Met office doesn’t
The Met Office system takes a reading every 15 secs and averages it over 1 min which is the temperature they report. Research has shown that this results in temperatures which meet the WMO standards.
https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.3836
The report you show does not address the issue of spiked temperature. From the report:
They only measured the difference that the screens may cause. I will point out that the report also shows:
This is only one component of an uncertainty budget. Factors such as drift, repeatability, reproducibility, resolution, wind, etc. have not been addressed to determine the total combined uncertainty.
Would it be feasible to take readings at a higher frequency, then reject data points that fall outside one standard deviation of the peak, for example? Then use a series of these data to calculate the mean. I am not a statistician by any stretch of the imagination as you can probably tell.
Chris,
The Australian experience is quite similar to your findings. I studied it 2 years ago and concluded that heatwaves in major Australian cities are not getting hotter and that the official wrongly-reported heat claims are a by-product of officially adjusted data.
Happy to sap notes. Geoff S
https://www.geoffstuff.com/nothot2024.docx
swap notes.
BTW, you will soon see some elegant forensic work that demonstrates that allegedly “RAW” data can be rather different to what the observers wrote down, because it has also been adjusted extensively in some countries. Geoff S
That’s interesting as the UHI effect should naturally result in more urban heatwaves because of growing cities.(and boiling Oceans, of course 🙂
Seems it got a bit cooler down there(or having thermometers upside down spoils the data).
I guess there is a reason why they cancelled the Australian all time heat record a 100+ years
and replaced it with the lower one a few years ago.
It’s easy to ‘read’ a thermometer, but it’s quite difficult to measure temperature accurately. When measuring ANYTHING, it’s important to understand the capability of the measuring system. “Capability” includes sample rate, response time, intrusiveness, accuracy, variability, and often much more. Measuring the magnitude of a “spike” involves all of that, and more. Comparing a spike measured with one set of instruments with that made with a different set of instruments simply indicates the capability of the author, not the magnitude of the spike.
“The main culprit in producing these heat spikes is the switch from liquid-in-bulb thermometers to PRT automatic electronic measuring devices during the last 30 years. These provide a more accurate reading every minute, but it is plain that they are picking up every passing heat spike – often unnatural – that were missed by slower-moving liquid in a glass bulb.”
They’ve been using the PRTs at Kew for about thirty years so it’s still a record for the period when that technology has been used.
Tmax should soon be placed in the rubbish heat. It was only used when there was no other data available. With one minute data, there is no reason why an integrated value over an entire 24 hour period shouldn’t be used. A hot day is hot ALL day. A one or even five minute spike disappears into sum throughout a whole day.
Even with this amount of detailed temperature, temperature is not the appropriate measurement, enthalpy is. Most automated stations provide the necessary data to compute enthalpy which is a much better value for “heat”.
A good solution to this problem of “instantaneous temperature measurements” is to embed the PT-100 devices in a block of copper, preferably a round rod ~8mm in diameter and 50 mm in length. This will provide a spike moderating smoothing of the instant temperature that closely represents a glass bulb thermometer.
I heartily welcome modifying these suggested dimensions so the temperature record automatically generated closely tracks what a good quality glass thermometer would yield if read by a professional. Once enough parallel data has been recorded, a back-cast of likely spikes with uncertainties can be generated to graph a probability envelope back to the 1600’s.
UK might have experienced heat spikes this Spring.
But 80 Degrees north in the Arctic during the month of May temperatures have definitely running a fair bit colder than average. https://ocean.dmi.dk/arctic/meant80n.uk.php
Looks like cold is very much locked up into the higher reaches of the Arctic currently, which might explain why less cold air from the north wasn’t able to oppose the hot air that migrated into our shores from the Sahara. Mostly, temperature is influenced by prevailing synoptics more than anything else
I have previously presented the case that there is evidence that USA heat waves are not becoming more severe or frequent:
https://wattsupwiththat.com/2019/09/06/the-gestalt-of-heat-waves/
My local sea front weather station in Hastings on the South UK coast goes back to 1870 and was updated last year and shows no spikes what soever. I’m not not sure if they still use liquid in bulb thermometers, if not they could get a spike from passing open fish and chips