Orwell2024🏒 Profile picture
Dec 9, 2021 16 tweets 11 min read Read on X
1/ "Age adjusted all cause mortality trends 2000-2021 in Europe"

This was quite some work, so I hope you appreciate the article. I don't think that this kind of analysis using 5 year age bin granularity over 20 year trends has been done elsewhere.

orwell2024.substack.com/p/age-adjusted…
2/ The age adjustement was done on 5 year age bins.

Some groups @CebmOxford cebm.net/covid-19/exces… report age adjusted mortality for 2020. But the method is inaccurate as too wide age bins are used.
3/ For teaching purpose, we also applied the WHO2015-2025 standard population in some graphs to demonstrate the problem if applying this to an old population.
4/ For 2020, this is the ESP2013 age adjusted full year mortality country ranking obtained.
5/ For reference, the below shows the full pandemic 96 weeks (2020 W1-2021 W44) ESP2013 age adjusted mortality country ranking. Many countries had to be excluded due to limited availability of mortality data for 2021.
6/ An in depth look on the current year 2021 was done as there seems to be some concern about higher excess. To my view, this is mainly a random seasonal effect and maybe the price for lockdowns
7/ We further looked in depth to the NL situation in 2021. Nothing particular is happening in the age group <65. The excess is dominated by the elderly group (like in 2020). Covid is not visible <65.
8/ We further noticed, that using symmetric standard populations for sex is “old men friendly”. It will be less sensitive towards elderly female deaths. EC and @who standardisation groups are advised to adapt and remove this artefact.
9/ We further see that the open approach of Sweden lead to outperforming their lockdown neighbours on the 96 weeks 2020-2021 timeframe.

This is likely an anti-correlation with the cumulative stringency of lockdowns.

Sweden was right.
DNK and FI wrong.
NO is simply rich.
10/ 2021: Neither a positive nor negative impact of the vaccine can be seen. At least it’s not of any relevant dominance. Other causes dominate. Probably lockdown, or random seasonality as also lockdown hardliners like France is doing ok for now.
11/ The observed excess mortality in AT and NL, is dominated by mortality in the elderly age bins. But those are 95 % vaccinated like in SWE and FR. The vaccine doesn’t reduce nor increase all cause mortality. QR passports and the one dimensional C19 health focus has to stop.
12/ I'm adding 2021 interim result for the first 44 weeks. That will certainly change once we look to this in some month or two. The raw mortality data even for the available weeks may still change due to delayed reporting.

France.😀 Didn't have them on the radar. Bah oui 👋
13/ The French paradox. Is it BMI? Anyone who has lived there and in other countries knows their outperformance on food culture although I do prefer the high fat/carb Italian / Spanish kitchen.

🇫🇷 France wins on food category, like it or not. We know their secret now.
For comparison, 2020-2021 96 weeks and the vaccination map in the 60+ age group.

mortality (left)
C19 vaxx 60+ level (mid)
BMI (right).

There is no real correlation with vaccination levels. But there seems to be with BMI. Surprised? Not me.
14/ I downloaded more data.

Here the age standardised mortality on a map next to the obesity map. 2015 - 2020 (Covid "tragedy")

I'm very angry now seeing it like this.

The obese old society is blaming healthy people like me (BMI 20) and my kids = malfeasance.

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More from @orwell2022

Aug 6
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).

So why is the climate scam still lying? Image
Image
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°. Image
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.
Read 9 tweets
Jul 6
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. Image
Image
Image
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. Image
Read 4 tweets
Jul 1
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. Image
Image
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. Image
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? Image
Read 6 tweets
Jun 29
Stockholm downtown: Where’s the UHI correction?

QCU = raw data
QCF = adjusted data

Same numbers.

C A N -- Y O U -- S E E -- IT

Fredrik? Show us.
We can’t see it.

Where exactly is the downward adjustment of 2C-4C? That's the bias you have in 2025. Image
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? Image
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). Image
Read 5 tweets
Jun 27
1/ +++🚨BREAKING🚨+++

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.👇 Image
2/ 🚨 BREAKING 🚨

We overlay. Do you see it now?

👉 They erased the real past.
👉 They had no data to do so.
👉 It's pure statistical deception—and wrong.

How? All exposed in the Wickham et al. (2013) audit thread.🧵

Image
3/ AI to fraud is what DNA was to criminals.

Not optional. Not stoppable.

🧠 Fraud — exposed
📺 MSM — vanished
📄 Journals — obsolete
🎓 Academia — imploded
🏰 Ivory towers — rubble

Resistance is pointless.

github.com/orwell2024/usc…
orwell2024.github.io/GHCN-tools/Wic…
Read 6 tweets
Jun 23
1/ Weil’s beliebt ist: Hohenpeissenberg-Daten – fallen zwar schon nach BU-Filter raus, aber gut: Dr. Connolly war schlau.

Oben: Wie stark sich die Temperatur verändert hat.
Unten: Wie „unrund“ die Messwerte wurden – Entropie der Kommazahlen (h/t Connolly) Image
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.
Image
3/ Diese Wetterstation ist NICHT standortstabil:
praktisch 100 % vom Menschen genutzte Fläche.

🟥 MODIS Urban (Klasse 13)
🟧 MODIS Agrarfläche (12 + 14)
🩸 GHSL Bebauung (2020)

Wer hier „Klima messen“ sagt, betreibt Täuschung.
Blamage für DWD.

Image
Read 12 tweets

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