Note that we have one month different season definitions. Small detail. I used 1st September as it seems to be the historical death minimum over years and countries.
3/ Now let's play. More countries.
And here we start to see interesting things like the disastrous performance of AUT, CH, FR on 20/21 season. Surprised me
We learn: locking down in 19/20 season makes 20/21 explode.
This is how "saving lives" with lockdowns in 2020 (NL and AUT) looks one season later in 20/21. Bad.
5/Summary: the countries with the hardest lockdown approach in 19/20 season like Slovenia (the role model in May 2020 for "eliminating" Covid), had the worst season in 20/21.
Data shows: You cannot escape seasonal death with lockdowns, just postpone with a worse outcome later.
6/ Adding a demonstration of calendar year versus flu year importance:
Example Romania deaths.
Left (calendar year): As we can see, the calendar year artificially splits the 2020/2021 peak in two.
Right (flu year): A much better way to define the year is by flu season.
7/ Doing the analysis by flu season (26 weeks offset), the real tragedy of prolonged lockdowns become very clear on the July 2020 - July 2021 time frame analysis. The excess was explosive in lockdowned countries.
Sweden being right in one picture 👇.
8/ Romania versus Sweden in a picture:
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London is glowing today. Wide urban heat plume. Not “climate change.” Just real estate and concrete. The effect is visible. Quantifiable. Known. This should be a good study day to quantify UHI in more detail once the IR satellite pictures come in.
2/ We start low tech. Actually nothing more is needed. There is over 6°C urban heat. It's embarrassing to pretend today's 33°C are comparable to 100 years ago. Subtract 6–8°C for UHI and you get... 25–27°C. Welcome back to reality.
3/ Nighttime, Tmin. Watch how they flatten the colors. You’re not supposed to notice the 7°C UHI. We unflatten the colors. Look again: you see it now?
We can also do from SE raw. And we can also show how rural stations look. Frederik does like them. Climate agenda is measured in downtowns of the capitals?
Not sure if it’s normal that amateurs now have to lecture academics…?
The downtown station logs hourly=no need for even Ekholm, no need for re-sampling. Does Frederik even know what we mean? Nothing is adjusted. Also PHA leaves it as is as it only detects breakpoints (not UHI).
Yes. Hausfather & Berkeley Earth are pushing it.
But it’s not a measurement. Not one station shows that.
It’s what you get when you aggregate rot over time.
On the left: 8 pristine USCRN sites. Same y-scale.
Now look what they did.👇
2/ Was wir hier sehen: Die Datenreihe ist ein Komposit (sehr beliebt, wenig seroes, in der Klima-„Wissenschaft“).
Die Messmethode (und mehr) hat sich verändert – von analogen zu digitalen Sensoren. Die Entropie der Nachkommastellen zeigt das – deutlich.
1/ The result is simply wrong.
There are 2 stations there — we can compare.
🟥Red: Carlwood
🟩Green: Gatewick
We clearly see the overshoot.
Moreover: They’re using subhourly spikes (error) from a single, low-inertia sensor.
Total incompetence.
2/ Using TMAX from a low-quality single urban sensor is already peak incompetence.
But they go further — they take the spikes.
Even top-tier stations like USCRN show 2–3°C error at peak forcing.
USCRN uses triple sensors — worst spikes get voted out.
3/ The UK has nothing like the USCRN triple-sensor setup.
So when two nearby stations disagree, the right move is simple:
Discard the implausible one — in this case, Charlwood.
What does the agenda-captured @metoffice do?
They run with the error.
They hoax the public.
ISO9001🤡
Not a high-quality reference site like
Valentia Observatory (Ireland) or h-USCRN sites.
But: Lower urban bias than cities like Kyoto or Tokyo. It starts to show the well known flatliner we see at stable sites.
3/ To see it better, here’s 4 months side by side:
🟥 Kyoto
⬛️ Tokyo
🟦 Suttsu
This is man-made. The T trend is just unrelated to climate. It measures the site and environment change. Suttsu as expected least impacted. But it still is.