1/ #oversterfte Netherlands: The observed mortality rates from EMA Pharmacovigilance (C19 vax) look bad, but in a range that shouldn't show up in the total mortality. It would be a disaster if it did.
What we need are mortality rates by cause and age (e.g. cardiac...).
2/ NL 15-19 years: nothing to see, except MH17 incident 2014.
3/ NL 20-24 years: nothing to see here, except MH17 incident 2014.
4/ NL 25-29 years: nothing to see here. MH17 incident 2014 still visible above the normal rates.
5/ NL 30-34 years: nothing to see here. MH17 incident 2014 still there.
6/ NL 35-39 years: nothing to see here.
7/ NL 40-44 years: nothing to see here.
8/ NL 45-49 years: nothing to see here.
9/ NL 50-54 years: nothing to see here.
10/ NL 55-59 years: nothing to see here.
11/ NL 60-64 years: nothing to see here. Seasonality starts to get visible in this age group.
12/ NL 65-69 years: seasonality visible. Also the sharp but short peak of the first C19 wave. But not at amplitudes that would justify a general panic.
13/ NL 70-74 years: seasonality visible. Sharp but short peak of the first C19 wave. The 2020 spring peak was higher (but shorter) than the typical flu wave. The total peak area is comparable with the 2018 flu season. The 2nd 2020 autumn wave was longer.
14/ NL 75-79 years: seasonality visible. Sharp but short peak of the first C19 wave. The 2020 spring peak was higher (but shorter) than the typical flu wave. The total peak area is comparable with the 2018 flu season. The 2nd 2020 autumn wave was longer.
15/ NL 80-84 years: seasonality visible. Sharp but short peak of the first C19 wave. The 2020 spring peak was higher (but shorter) than the typical flu wave. The total peak area is comparable with the 2018 flu season. The 2nd 2020 autumn wave was longer.
16/ NL 85-89 years: seasonality visible. Sharp but short peak of the first C19 wave. The 2020 spring peak was higher (but shorter) than the typical flu wave. The total peak area is comparable with the 2018 flu season. The 2nd 2020 autumn wave was longer.
17/ Conclusion for 2021: 1) Seasons start at different times--> little can be said now for 21/22 season. 2) The background is higher (even in the young) than any potential vax signal. It would be a disaster if vax would be visible in total mortality. 3) We need data by cause.
18/ To assess any vax safety issues in detail we need: 4) mortality figures by cause, gender and age bin for the young cohorts(<65), e.g. cardiac events. 5) IC data by cause, gender and age for the young cohorts (<65) e.g. cardiac events and thrombotic events.
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.