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Orwell2024 Profile picture
Orwell2024
@orwell2022
If it disagrees with the expert, it’s wrong. In that simple statement is the key to consensus.
Jul 8 • 7 tweets • 3 min read
1/ NL data. We now plot the total forcing 🔴, including the measured SSR and CO₂ contribution 🟢. The black curve ⚫ shows the temperature response, the blue curve 🔵 shows the upper physics estimate (dry Stefan–Boltzmann) for the expected temperature response. Image 2/ NL data. We now plot the total forcing 🔴, including the measured SSR and CO₂ contribution 🟢. The black curve ⚫ shows the temperature response, the blue curve 🔵 shows the upper physics estimate (dry Stefan–Boltzmann) for the expected temperature response. Image
Jul 1 • 7 tweets • 4 min read
1/ A famous @BerkeleyEarth paper found no rural–urban difference despite the well known UHI impacting most historical stations. How is this paradox possible?

They used MODIS=🚮. At 10 m Sentinel-2, their “rural” stations light up urban.

Examples 🟥=real estate👇 Image 2/ MODIS uses a binary classification with a high threshold to flip to “urban,” so many urban sites are labeled “rural.” That compares urban to urban. BE also uses fragmented records and a changing station ensemble = 🚮. Apply one basic filter—data must exist ≥9 months/year👇 Image
Mar 18 • 8 tweets • 6 min read
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.

Link below. Image 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/Image
Jan 30 • 6 tweets • 4 min read
Spectacular model failure: the simulation is detached from reality.

MEASURED (MODIS): cooling.
ERA5 model: warming.

Same grid cell, same year but OPPOSITE trend?

If a “model” can’t even get the sign right it’s a full fledged GIGO failure. Worse than worthless. Image Flagged this two years ago, and it’s still absurd.

Measured surface temperature (LST) is declining since 2000.

ocean.dmi.dk/arctic/ist_cli…

ERA5 shows 2 m air warming. Wrong trend, same place, same period.

Worse: ERA5 “surface” proxy warms too. Misses LST too.!! x.com/orwell2022/sta…Image
Jan 26 • 16 tweets • 8 min read
1/ People use “reanalysis” as if it is thermometer data. It is NOT.
Reanalysis is a computer weather model.

So we test it: ERA5 vs USCRN on grid level. Result: cooler past, warmer present pivot in ERA5 vs stations. Model ❌

~1.5 °C 🔴 model error vs ground truth (measured 🔵) Image 2/ Maybe it works for Blackville — another of the few pristine hUSCRN sites.
Same model failure.

When a SW model disagrees with ground-truth HW thermometers at the grid level, nature isn’t wrong.
The model is. Image
Nov 13, 2025 • 8 tweets • 4 min read
1/ This brigheting since 1980 is known in prof. circles.

Here’s the data from Germany (Potsdam).

+15 W/m² 🌞since the 1980s. ✅

Yet the public narrative claims climate change/CO₂ (~+1.4 W/m² over the same period). ❌

The gap between evidence and narraitive is 10x....off. Image 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? Image
Aug 6, 2025 • 9 tweets • 4 min read
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
Jul 6, 2025 • 4 tweets • 2 min read
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
Jul 1, 2025 • 6 tweets • 3 min read
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
Jun 29, 2025 • 5 tweets • 3 min read
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
Jun 27, 2025 • 6 tweets • 4 min read
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
Jun 23, 2025 • 12 tweets • 6 min read
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
Jun 22, 2025 • 6 tweets • 3 min read
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. Image 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.

Image
Jun 12, 2025 • 17 tweets • 7 min read
1/ Back to Japan temperature trends.

We now add a smaller town: Suttsu. Still not truly rural nor stable site, but better.

We now show:
🟥 Kyoto
⬛️ Tokyo
🟦 Suttsu

Can you see it?

They then aggregate urban-biased data (rot) like this and call it “global temperature.” Image 2/ Here it is: Suttsu.

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. Image
Image
May 27, 2025 • 6 tweets • 3 min read
The red areas are fully man-made—built or cultivated.
You cannot measure climate anywhere near them.
And MODIS still misses a lot.
In reality, it’s worse.

When we inspected what @BerkeleyEA calls “rural”?
Almost all those stations are worthless Image Imagine a field looks like it does on the left…alive.
And later, like the right. Dead and brown.
Still think you'll measure the same 2m temperature?
Or might that just—possibly—have a major impact as the surroundings changed? GPT estimates 3C. It's not wrong. Image
Image
Image
May 23, 2025 • 9 tweets • 4 min read
Maybe some still don’t grasp the novelty here. This shows what the “climate consensus” is built on: MODIS — a coarse, fully outdated DB.

Now compare that to P2023A.

So—@BerkeleyEarth @hausfath—still think your pick is better? Let me know. And explain why. Image Thanks to this trick, they labeled urban sites as “rural”—then obviously saw no difference.
That paper must be retracted.
Back then: resolution limits.
Today? Ignoring P2023A is agenda.
Anyone can open Google Earth and see houses where MODIS finds none.

Image
May 16, 2025 • 5 tweets • 3 min read
1/ @NOAA’s USCRN site STILLWATER hosts one of the longest high-quality temperature records.
Before retiring the legacy sensor, both systems ran side by side for 10 years—ensuring continuity.
A consistent, rural site with 130 years of stable data. Image 2/ Here's what that stable rural site looks like. 130 years of data, side-by-side sensor overlap, no urban noise.
Same as Valentia, Ireland.
Why? Because it reflects reality.
The hockey stick doesn't exist in high-quality urban bias free measurements.
Image
May 9, 2025 • 6 tweets • 3 min read
1/ April resists warming.
Remember: warming causes cooling.
If you’re freezing, you're actually warming.
Colder weather confirms it’s warmer.
We must prevent cooling to stop warming.
Yes, it still was the warmest April in SW models.
Now pay your CO2 tax please and eat vegan. Image 2/ We check ourselves. The ClimDiv curve is even cooling 1.37C compared with the stable USCRN sites. Image
May 5, 2025 • 6 tweets • 4 min read
1/ This proxy is the most dishonest narrative in the entire climate agenda.
Anyone pushing it isn’t doing science — they’re signaling allegiance.
If you still treat them seriously, that’s on you.
They’re not analysts. They’re ideological fools. #ClimateScam Image
Image 2/ Last week of April 2025. Rural Nagano. ~700m elevation. Full bloom.
I challenge the town-proxy scammers to show us blooming in late May or June a hundred years ago.
Go ahead— make fools out of yourself by failing.
👉The consensus now = defund climate activists (“academics”). Image
Image
Image
Image
Apr 12, 2025 • 5 tweets • 4 min read
1/ I was told non US GHCN “raw” is adjusted already.

-----TRUE-----

Now I see it. Gosh.

Composite. 2x adjusted. NOAA doesn’t even know where non-US stations are—or what they’re measuring. Their own US data (USCRN) is light-years better. But for “global”? It’s clown-tier level. Image 2/ And here it is—the DOUBLE-adjusted COMPOSITE.
Not raw. I doubted @connolly_s at first—like someone denying their 2nd-hand car is stolen, crash-salvaged, and repainted twice. Turns out he was right.
NOAA’s “global” QCU (non-US): not raw.
Image
Image
Apr 10, 2025 • 27 tweets • 15 min read
1/ The WMO’s temperature station classification study isn’t a glamorous reading —but it’s the bare minimum anyone aggregating climate data should know about every single station. They don’t.

Scandal hiding in plain sight Image 2/ Class 1 is “bare minimum” for climate-grade weather station suitability. One means maybe ok.
met.no/publikasjoner/…
I’ll be counting impressions. I’ll know if you didn’t read.
(you’re allowed to LLM TlDR it.)
Next up: NOAA climate site requirements (HLR). 👇 x.com/orwell2022/sta…