@MntyP1@knigotnik@systemanalysen They can't explain it. But it's quite easy. The excess is dominated by 85+. Those are fragile people, and having had 2 years lockdowns and panic is not healthy. In Sweden this group is doing fine, as living a social life as mammals are supposed to live. See here.
@MntyP1@knigotnik@systemanalysen Both SWE and NL have vaxx levels of 95% in this group. It's irrelevant for the excess. No vaxx can make a damage at this level like NL. It's the lockdown, fear and isolation. Prisoners don't live long. If we continue, we can probably reduce life expectancy by 10 years.
@MntyP1@knigotnik@systemanalysen This excess is also in the 75-84 cohort in NL. Also 93% vaxxed in both countries. Nothing in SWE. It's the lockdown. Isolation and fear is unhealthy for social mammal life. Destroys resilience. I bet it's all cardiovascular and respiratory. @rubenivangaalen@KoudijsHenk
Have we not heard that old people often die when they loose their partner? Why is this the case?
We are not designed to live in fear, anxiety and isolation. Add low vitamin D levels, lack of sports, lack of healthy food and missed treatments.
@MntyP1@knigotnik@systemanalysen@rubenivangaalen@KoudijsHenk This excess is BTW also seen in all neighbouring countries of Sweden. Only Sweden is doing fine. Only Sweden didn't implement tyranny. That's the underlying root cause.
Shame on the Netherlands! For what they did to old, young and their society as a whole.
@MntyP1@knigotnik@systemanalysen@rubenivangaalen@KoudijsHenk What's even further appoling is the behavior of @statistiekcbs. They push the Simpson's confounding story using all age averages of vaccination levels and all age excess to claim too low vaccination as root cause. How wrong. E.g. here:
DNK: 99% and they have 85+ excess.
SWE: >93% and they have 85+ under mortality.
FI: >95% and they have 85+ excess.
NL: >93% and they GIANT excess in 85+
1/ Can you actually find a hockey stick in truly rural stations?
Not in a stitched statistical construct — in a real, coherent station record.
Here’s a tool to test it yourself.
2/ This map shows all stations with 100 years of data and at least 9 valid months per year.
That leaves about 500
🌎 🌎
Stations are colored by the level of built-up area around the site. Click any station to view its details and temperature curve. orwell2024.github.io/builtmap/
3/ Low built-up ≠ high-quality station. It’s a mandatory condition, not a guarantee.
Switch to sat view and inspect the site closely— the problems often shows up immediately. Like here.
Coastal locations
commonly have this issue. Water makes them appear rural. They aren’t.
2/ The analysis is already done. DWD and peer-reviewed literature.
It matches what we saw from JMA and KNMI raw data:
a +10–20 W/m² increase in surface solar radiation.
So the question:
How did they get away with knowing this and selling the story of ~1.4 W from CO₂ instead?
3/ What does the literature say?
“...dimming/brightening not only occurred when clouds are considered, but also under cloud-free conditions when cloud effects are absent.”
A remarkably way to say:
It’s not clouds. Not CO₂. Not climate. Pollution.
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.