2023 was the second hottest UK year since 1884? Pull the other one, it's got bells on it.

According to the UK Met Office, 2023 was the second hottest year in the UK since 1884. Quite obviously, this is complete nonsense. Unless they are troglodytes that never venture out in daylight, why would anyone in the UK believe such absurd drivel?

The Met Office states:

2023 is provisionally the second warmest year for the UK according to mean temperature. [. . .] 2023’s provisional mean temperature of 9.97°C puts it just behind 2022’s figure of 10.03°C and ahead of 2014’s 9.88°C.

Right, it's "provisional" drivel.

The UK summer of 2023—where I live—was a thoroughly miserable affair. We had a few weeks of decent sunshine in the spring and a couple of hot weeks of Indian summer. That was it! The rest of it was cold, wet and comprehensively devoid of anything we might traditionally call "summer." The winter preceding and following it wasn't particularly cold, but nor was it unusually warm.

I'm knocking on a bit and can remember about 50 years of my life. I know, for a fact, that I have lived through many warmer years. Sure, this is anecdotal, but I haven't completely taken leave of my senses and I still have a functioning memory. No way am I unquestioningly buying the Met Office's silly claim.

Neither do I believe any of the legacy media reports trying to convince me that the Met Office's preposterous assertion is evidence of an alleged climate crisis. It simply isn't true, so it is not "evidence" of anything at all. Although it does suggest deception.

The Met Office—obviously unreliably—tells us "UK mean temperatures have been shifting over the decades as a result of human-induced climate change. [. . .] 2023’s provisional mean temperature of 9.97°C puts it just behind 2022’s figure of 10.03°C." For a start, "human induced climate change," or Anthropogenic Global Warming (AGW), is a questionable and unproven scientific theory, not scientific fact. This too is just another claim from the Met Office which it wrongly asserts as fact.

The Met Office also tells us that "sunshine was near-average for much of the UK." If we have got this right, the Met Office is claiming that, with average hours of UK sunshine in 2023—which also seems pretty dubious to me—somehow, since 1884, the only year that has been "hotter" was 2022. Which doesn't ring true either.

What's going on?

What does the Met Office mean—pardon the pun—by "mean temperature"? It reports that its 2023 alleged "provisional mean temperature of 9.97°C" had been obtained via the HadUK-Grid data set. The Met Office also cites its 2023 rapid attribution study. It is from this that we can—eventually—glean how the "UK mean temperature" is calculated by the Met Office.

In its rapid attribution study, the Met Office states:

Observed values of the UK annual mean temperature are obtained from the HadUK-Grid dataset v1.2.0.0. The time series spans 1884 – 2023, with the 2023 values being provisional as of 2nd January 2024.

"Observed," that's what we want to hear. So what observations are reported in the HadUK-Grid dataset? The Met Office claims:

HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations.

If we look at the HadUK-Grid methodology, the Met Office adds:

The gridded data sets are based on the archive of UK weather observations held at the Met Office.

So far so good. The HadUK-Grid reportedly records real data, such as sunshine hours, rainfall and even temperature. We live in hope. Unfortunately, there is some caveats. The Met Office continues:

The methods used to generate the daily grids are described in more detail in [this] report.

OK. So beyond just recording real-world data, what are the "methods" outlined in said report?

[. . .] the Met Office climate data archive [. . .] contains a simplified version of the raw observations generated according to well-defined rules. [. . .] Mean temperature [. . .] is the average of the maximum and minimum temperatures.

At last we have a definition of the "mean temperature" the Met Office claims to be the second highest since 1884. Apparently, it is "generated according to well-defined rules." 

In Met Office speak "mean temperature" isn't the actual arithmetic mean of daily temperatures but rather the "average" of minimum and maximum temperatures recorded between 09:00 and 21:00 on any given day. Begging the question how are the minimum and maximum UK temperatures "observed"?

Although the data ha[s] undergone some quality checking, the extent and effectiveness of this has changed through time since the 1960’s. [. . .] NCIC climate data analysis software was again used to create the gridded data. [. . .] The station data were normalised with respect to the monthly 1km x 1km gridded 1961-1990 climate normals described by Perry and Hollis (2005a).

So the minimum and maximum allegedly "observed" 2023 "mean UK temperature" wasn’t actually observed at all. It was calculated from normalised data using computers running software based upon the "climate normals" defined in Perry and Hollis (2005). The related paper considered how to calculate long term averages (LTAs) and suggested a methodology by which "mean" temperatures could be calculated:

For air temperature, 1490 stations reported at some point between 1961 and 2000 but only an average of 560 of these were open at any one time. This gives an array which is 38% complete. [. . .] [T]he solution is to fill in the gaps using an appropriate estimation technique. [. . .] Once the gaps in the array have been filled, long term averages for the periods 1961-1990, 1971-2000 and 1991-2000 can be calculated for each station from the complete array. [. . .] The regression model parameters provide an estimation of [. . .] the UK climate, explaining between 29% and 94% of the variance in the data depending on the climate variable.

Potentially, up to 62% of the data forming the Met Office's “Mean UK temperature” is "generated" by "fill[ing] in the gaps." This is based upon an "estimation technique" which supposedly explains between "29% and 94% of the variance in the data depending on the climate variable." This doesn't mean that the estimated fill-ins are inaccurate but they cannot be called "observations" either.

We seem to be moving further away from empirical science. Surely the Met Office isn't claiming that it knows what the average UK "provisional" mean temperature was in 2023 based upon such limited observations? With regard to how it interprets the HadUK-Grid dataset the Met Office states:

The HadUK-Grid dataset is produced on a 1km x 1km grid resolution on the Ordnance Survey's National Grid. To facilitate comparison of the observational dataset with the UKCP18 climate projections [. . .]. All the gridded datasets use the same grid projection. The re-gridding is conducted through averaging of all 1km grid points that fall within each of the coarser resolution grid cells.

Whoa there! We already know that the "observational dataset" is created by "fill[ing] in the gaps"—around a 60% gap apparently—with computer modelled estimates. Now we are told some sort of "re-gridding" is necessary to "facilitate comparison" with UKCP18 climate projections. Why is that necessary?

The UK Met Office adds:

Area averages are also produced based on averaging the 1km grid [data] across a set of geographical regions to provide spatial statistics for country, administrative regions and river basins. The details of these areas can be found in the UKCP18 guidance notes.

Now we've got "spacial statistics," instead of empirical measurements, based upon "area averages" that facilitate, for some unknown reason, comparison with "UKCP18 climate projections." OK, so how are the "area averages" constructed in accordance with the UKCP18 guidance notes:

Before using [UKCP18 guidance notes], it is important to understand the assumptions made, the caveats and limitations and the appropriate use of the results.

Assumptions made, caveats and limitations! What bloody assumptions, caveats and limitations? Just measure the temperature and calculate some sort of meaningful average for crying out loud!

Let's look at the caveats and limitations:

Our understanding and ability to simulate the climate is advancing all the time but our climate models are not able to represent all of the features seen in the present day real climate and there are still limitations in our ability to project 21st century weather and climate.

Why are the Met Office "generating" temperature datasets to "facilitate comparison" with climate models if those models "are not able to represent all of the features seen in the present day real climate." Surely the models should be based upon the empirically observed and measured features of the "real climate," as opposed to creating "area averages"containing "spacial statistics" to fit in with the models?

Almost unbelievably, this is evidently what the UK Met Office is doing:

The relative probabilities indicate how strongly the evidence from models and observations, taken together in our methodology, support alternative future climate outcomes. [. . .] The probabilities are conditioned on methodological choices and expert judgement. The results may change if a different methodology is used.

In essence, the Met Office uses a tortuous and unnecessarily convoluted methodology to make up the bulk of its UK "temperature" data. While the Met Office claims that the provisional UK mean temperature was for 2023 was 9.97°C it also states that its results might change "if a different methodology" was used. 

What's more, the data it uses is normalised, based upon a wide gamut of climate assumptions, in order to fit in with its own climate models. Again, it admits its so-called observations, of things like mean temperature, are "taken together in [its] methodology" expressly in order to "simulate the climate."

Most of these modelling shenanigans are utterly superfluous if your objective is to calculate the arithmetic mean annual UK temperature. Of course anomalies, such as heat islands, need to be normalised in the data but the rest of the Met Office’s “methodology," which doesn’t even attempt to calculate an arithmetic mean temperature anyway, is about as far removed from empirical science as it is possible to venture.

Inevitably, it produces completely meaningless pap. The problem with such allegedly “scientific” rubbish is that, rather than being laughed off, it is then taken seriously by millions—thanks the unquestioning propaganda reports of the legacy media—and used to advance policy agendas, such as Net Zero.

Apart from the fact that it is blatantly obvious, to anyone who has lived in the UK from more that a couple of decades, that 2023 was not a warm year, there are other notable reasons not to automatically trust the Met Office's makey-uppy "climate science." Its entire claim is reliant upon the HadUK-Grid dataset which is a project funded by the UK government. As is the Met Office itself.

Apparently, the UK government is irreversibly committed to UN Sustainable Development and the associated UK Net Zero policies. The Met Office's alleged scientific "observations" suffer from an enormous financial conflict of interest. Providing any evidence that contradicts the notion of "unprecedented global warming" couldn't be further removed from the Met Office's and the UK government's own declared interests.

There is absolutely no reason to believe any of it. As "science" goes, it's complete junk. I've read comics with more credibility that the Met Office's claim that 2023 was the second warmest year in the UK since 1884. 

Pull the the other one, it's got bells on it. 

—Please support my work—

I am entirely dependent on your support. Everything I write, whether on Substack or on my blog, will always be freely available to everyone. I can’t guarantee that my articles for other publications will be—it’s out of my control—but currently they are.

There is no need to subscribe to read my Substack posts and there are no inducements or advantages for being one of my paid Substack subscribers. So why bother?

Much of the research used by well known podcasters and video makers is undertaken by independent investigative journalists and researchers such as myself. Unfortunately, credit is only occasionally given.

I need your support if I am going to continue that work. James Delingpole and Alex Kriel gave a good account of why support for the “grass roots” of independent media and activism matters.

So, if you think my work is worth it, I hope you will consider becoming one of my paid Substack subscribers. If that’s too much you can always “buy me a coffee” via my website if you like.

All the best.