2/ For Austria and NL where 90% of the at risk group is vaccinated we expect 30%-50% of the ICU patients to be vaccinated if assuming a VE-ICU of ~90%.
3/ Let's show the results of the formula in 2D as function of
x) vaccination level
y) VE agains ICU
The resulting rate (calculation on right) of vaccinated in ICU is shown in the cell.
It can be used as look-up table to estimate (roughly) the VE.
4/ Example The Netherlands: With around 90% vaccinated we expect something between 15%-50% vaccinated in ICU depending on the VE-ICU.
RIVM reported around 15% (right). In order for this to work with 90% vaccinated, VE-ICU needs to be above 95%.
10/ Assuming March as the date where most elderly were fully vaccinated in NL, I compared the derived NL VE versus (time) with the Swedish study on waning efficiency.
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.