Find here a vizualisation of the NL data. This are all admission.
We don't have this infromation available for #Covid by age nor for C19 vaccination status by age. @rivm@hugodejonge Please publish this data.
@rivm@hugodejonge 2/ Let's zoom in on the latest months. The numbers in the age group < 30 years is vanish small. But this is the so called unvaccinated "at risk" group. It's already obvious from this that the statement from Hugo:
"the unvaccinated are flooding the hospitals"
is impossible!
3/ Let's further zoom in on ICU:
People below 30 (so the dominating unvaccinated group) are NOT in ICUs.
The vast majority (80%) is above age 50. But this group is almost fully (~90%) vaccinated.
There is some magic going on if 90% of patient are unvaccinated.
4/ What is the vaccination level by age? Around 90% above age of 50. All statements regarding that 90% of ICU occupancy are unvaccinated is mathematically impossible and not credible @hugodejonge. Please publish the above requested data.
5/ Let's show the < 29 years only. And those are all cause admissions. Children, teens and students are "stealing" the ICU places?
Please explain this @hugodejonge. They are at risk and need protection? No. But this is not new. And I'm sure that you are clever enough to know.
6/ I saved the dashboard in Tableau public.
Also this comparison 0-25 years versus all on the same y-axis scale makes it even further clear how flawed the push to vaccinate the below 25 is.
A +14 W/m² total solar increase over 50 years is realistic. Japan alone shows +20 W/m². That’s 10× larger than the minuscule additional CO₂ forcing (~1W). And nearly 50× greater than the impact of sunspot cycles (±0.5 W).
Japan has one of the best measurement data. The analysis is clear. The brightening amount to almost 20 W. That is a lot. But the main and dominant effect is still urbanization, which makes up to 6°.
Link 1: the brightening. It explains why the climate scam likes to start in the maximum smog dimming period of 1970. It is a shameless bad faith deception. The effect is ball part of +1°C. In dry areas up to 3°C.
UAH is a model inference, not a measurement. It can’t be tested, yet many treat it like real raw. Calling that a ‘measurement’ is wrong. Neither Lindzen nor us take it seriously. It starts in a cold period, with no long-term data — adjusted, multi mission stitched SW composite.🚮
UAH is not measurement — it’s model-driven inference. Satellites detect radiance, not temperature. The ‘trend’ is built through weighting functions, drift corrections, and stitched instruments. It’s untestable, synthetic, and not suitable for long-term climate baselines.
It’s astonishing how confidently some treat satellite-based inferences as god in heaven like truth. These are SW model outputs, not reliable measurements. Treating them as accurate fact is scientifically indefensible. If you do so, expect your credibility to be challenged.
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.