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Orwell2024šŸ’ Profile picture
Orwell2024šŸ’
@orwell2022
If it disagrees with the expert, itā€™s wrong. In that simple statement is the key to consensus. https://t.co/MYLncQl3Uh
10 subscribers
Apr 12 ā€¢ 5 tweets ā€¢ 4 min read
1/ I was told non US GHCN ā€œrawā€ is adjusted already.

-----TRUE-----

Now I see it. Gosh.

Composite. 2x adjusted. NOAA doesnā€™t even know where non-US stations areā€”or what theyā€™re measuring. Their own US data (USCRN) is light-years better. But for ā€œglobalā€? Itā€™s clown-tier level. Image 2/ And here it isā€”the DOUBLE-adjusted COMPOSITE.
Not raw. I doubted @connolly_s at firstā€”like someone denying their 2nd-hand car is stolen, crash-salvaged, and repainted twice. Turns out he was right.
NOAAā€™s ā€œglobalā€ QCU (non-US): not raw.
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Apr 10 ā€¢ 27 tweets ā€¢ 15 min read
1/ The WMOā€™s temperature station classification study isnā€™t a glamorous reading ā€”but itā€™s the bare minimum anyone aggregating climate data should know about every single station. They donā€™t.

Scandal hiding in plain sight Image 2/ Class 1 is ā€œbare minimumā€ for climate-grade weather station suitability. One means maybe ok.
met.no/publikasjoner/ā€¦
Iā€™ll be counting impressions. Iā€™ll know if you didnā€™t read.
(youā€™re allowed to LLM TlDR it.)
Next up: NOAA climate site requirements (HLR). šŸ‘‡ x.com/orwell2022/staā€¦
Mar 28 ā€¢ 43 tweets ā€¢ 22 min read
1/ Digging deeper, we find 3 USCRN sites with 2 IDs ā€” a legacy historical one and a USCRN. Thatā€™s big. It means we can stitch together long-term time series for 3 ā€œgoldenā€ stations. Why havenā€™t @NOAA or @hausfath done this? Not the ā€œrightā€ narrative result? šŸ™ƒ Letā€™s take a look Image 2/ Here is an example of such a pair. STILLWATER. Note that you can see the wind fence around the precipitation gauge on satellite picture ā€” that round structure.
ncei.noaa.gov/access/crn/pdfā€¦Image
Mar 19 ā€¢ 15 tweets ā€¢ 9 min read
1/ Mr. @hausfath packed multiple fallacies into one graph. We replicate: he used homogenized data. We get the same.

Bottom right shows the raw. His fallacy: claiming that USCRN-ClimDiv agreement in the modern era (where adjustments are ~zero) validates strong past adjustments. Image
Image 3/ His fallacy is blatant bad faith. Measurement validation isn't done by induction. He claims adjustments are valid because USCRN-ClimDiv align from 2008-2024ā€”yet no adjustments were made in that period. Then he asserts past adjustments are proven. Exceptional level of malice. Image
Mar 19 ā€¢ 6 tweets ā€¢ 4 min read
1/ New tool - let's test with VALENTIA (hourly) overlay: solid agreement. A model (ERA5) is only as good as its ground truth measurements constraints it. We saw good US results before, but obvious heat bias in polar regionsā€”nothing measured to compare with there anyway. Image 2/ Now we match the 1940-2024 range. Note temp vs. anomaly scaleā€”same curve, just shifted. A trick to amplify range. Few notice. Climate stripes? Perfect for manipulationā€”e.g. add offset (ECMWF) to make it red ā€œ=warm"= behavior science (manipulative).
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Mar 15 ā€¢ 7 tweets ā€¢ 4 min read
1/ Absolutely my worldview. But I havenā€™t found a trace of it in temperature measurements. Accuracy doesnā€™t seem to be a factor at all. Instead, they rely on bizarre software that arbitrarily alters the data. No station audits. No QMS existing. Nothing.
2/ This magic software even adjusts in various directions from day to dayā€”without any explicit justification beyond it doing so. Is the sensor accuracy changing day to day?? No.

This finding by @connolly_s is important and exposes PHA being unrelated to measurement principles.
Mar 14 ā€¢ 14 tweets ā€¢ 7 min read
1/ The temperature (USCRN) since the 2014/2015 El NiƱo has been stable and slightly declining (cooling). Yet, weā€™re witnessing an unprecedented surge in mania. Interesting, isnā€™t it? Letā€™s demonstrate this by exposing the bias in GPT. Weā€™ll trick it. Ready? Image 2/ To force it to be honest, weā€™ll deactivate ideological filters by labeling USCRN anomalies into portfolio value (adding 30 to shift upward of zero). This way, it will think itā€™s analyzing the fund performance from an automated trading product from my bank.

Hah. Gotcha. Downā˜ŗļø Image
Mar 11 ā€¢ 8 tweets ā€¢ 4 min read
Revisiting Las Vegas: The observed warming trend is likely driven primarily by urbanization. Unfortunately, there is no available data from before the 1970s, and the period of overlap with USCRN station records is short, which limits ability to analyze long-term. Image We look closer and see that for 10 years, there's no warmingā€”flat. To make the Urban Heat Island (UHI) effect in Vegas clearer, we compare it with Gallup Muni APšŸ”µ, a highly rural spot (BU 2020 <<1%). This highlights urbanization's impact in VEGASšŸ”“.
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Mar 6 ā€¢ 5 tweets ā€¢ 2 min read
Most absurd: adjusting _current_ (the now!) measurements!? Claiming adjustments to now necessary implies measuringā€™s impossible.

ARE YOU FREAKING KIDDING ME?

What ā€˜engineering/scienceā€™ is this? Inability-to-measure ā€˜scienceā€™?

1+1=3 woke math applied to "how to measure"? Image It worsens. Aimed to expose the adjustment fallacy on number of frost days like showing that the F77 SW will tell us that the frozen thermometers weren't frozen...and guess what? GHCN adjusted "qcf" only exists AFTER aggregation to month.

A deep scam.

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Feb 13 ā€¢ 6 tweets ā€¢ 3 min read
This account has "uncovered" urban heat in megacities and WMO Cat5 stations.

In Dublin (@connolly_s), a mere 10km walk separates one city šŸŸ„ showing doom of global warming, from the airport šŸŸ©that isn't showing it.

Such are the marvels of climate 'science'. Image H/t @Dodders75 for ecad link. Why isn't all data for Valentia displayed? It's one of the best rural time series.

From raw data (@MetEireann) on top, and below, the subpar tool graph. We see a classic: develop SW tools nobody uses šŸ‘‰ get low/no quality.

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Feb 7 ā€¢ 6 tweets ā€¢ 3 min read
1/ Let's check real measurements. GHCNv4 stations that continuously operated 1900JAN-2025JAN.

ERA5 (weather model) shows warming were least stations can constrain it. Warming doesn't like places with real stations? Avoiding measurements? We have noticed this previously. Image 2/ The ERA5 model's +1.75Ā°C anomaly aligns with megacity 'BU' levelsā€”the top curve. Absurd and exposing the ERA5 reanalysis (weather model and not data) as non credible. Real, unbiased historical stations in non-urban areas show a very cold January. Image
Nov 11, 2024 ā€¢ 5 tweets ā€¢ 2 min read
1/ Deutschland, die Energienarren der Welt: Thread.

Hier ist die Preiskurve (31 Tage, stĆ¼ndlich). Kaufe teuer, verkaufe billig. Bottom Nailers (oder auch Narren). Angeblich importieren sie, weil es billiger ist? Nein. Die Sonne scheint eben nicht nachts. Image 2/ Quelle: Agora Energiewende ā€“ de facto der Familienbetrieb der GrĆ¼nen. Man sieht sofort, was los ist: Deutschland, auf einem Irrweg, in bestem Stil echter Narren. Verkaufen billig, kaufen teuer, alles im Namen der ā€žRettungā€œ. Klar, wer nachts Sonne braucht, zahlt eben drauf. Image
Oct 7, 2024 ā€¢ 47 tweets ā€¢ 30 min read
1/ The use of the BI (bigness index) to classify rural/urban areas is flawed. Landsat-derived GHSL BU (Global Human Settlement Layer Built-Up) data shows the rural curve (in green šŸŸ©) consistently trailing the urbanized GHSL BU data (10% BU = typically for small towns šŸŸ§). Image 2/ The Bigness Index (BI) is not only a poor parameter but outdated. Even Kabul Airport shows up with BI=0.

Shown below: GHCN stations labeled BI=0, highlighting those with 2% šŸŸ  and 10% šŸ”“ built-up areas in 2020 (from the EU-GHSL).

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Oct 1, 2024 ā€¢ 4 tweets ā€¢ 2 min read
1/ Climate stripes - the origins.

Can we do better than Ed Hawkins? Yes, we can.

The perfect smoothed climate stripe, maximizing color pivot for ultimate fear manipulation.

Perfectionā€”better than the original. Or in other words: how to manipulate your mind. Image 2/ Hereā€™s how itā€™s done:

1 Pick a highly urban(izing) place: Stockholm.
2 Calculate anomaly.
3 Maximize range.
4 Apply LOESS for max color pivot (=mindfuck)

Note: UHI in Stockholm is ~2Ā°C. Never mind thatā€”the goal is to manipulate your minds.


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Sep 10, 2024 ā€¢ 10 tweets ā€¢ 6 min read
They're trolling / insulting. The request was clear: compare ERA5 2km / @meteoblue with @AEMET_CValencia sensor at an hourly level. If they match at night, cloudy days, winter, but the sensor shows higher T in summer clear skies / no wind / day šŸ‘‰ sensor is heat-biased. So? Go. Thanks, @meteoblue. Normal conversation can be so easy. If the Spanish gentlemen would now provide access to their hourly station dataset, we can overlay it with the fine-grid ERA5 2km hourly product and see what's going on. Does that sound like a way forward @AEMET_CValencia ?

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Sep 3, 2024 ā€¢ 19 tweets ā€¢ 8 min read
1/ Such places have no credibility for accurate bias free measurements. It's the opposite of a stable environment and per default a diesel powered urban expedition place. We see how the melting starts around the airport and the town.

How to measure? šŸ‘‰ open.substack.com/pub/orwell2024ā€¦


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Image 2/ Here we see another example (Alaska). Russian high-lat regions are among the worst. It's a deception to take measurements from such places and claim that you've done 'science' while actually just picking up dirt. Why not Everest dirt basecamp next?
Jun 27, 2024 ā€¢ 12 tweets ā€¢ 6 min read
1/ As mentioned, Europe is too urbanized for climate measurements. Shown below is just the UHI effect. As mentioned, ANY type of urban landscape altering increases surface temperatures as well. The Netherlands and Benelux regions are all fully biased and unfit for climate science
Image 2/ As mentioned previously, North Sweden is the most credible place for climate measurements due to its development, peace, and ability to capture high-quality data. Besides Sweden, only the US provides reliable historic data. All other regions are not credible and biased today. Image
Jun 18, 2024 ā€¢ 12 tweets ā€¢ 5 min read
1/ Remember the scenic document from @NOAA's USCRN. All rural places without man-made objects?



It's 145 pages long, each page one station. They should ALL be there, right?

Nope. How naive to believe that it's done in good faith.

Ready? šŸ§µ ncei.noaa.gov/pub/data/uscrnā€¦
2/ This finding didn't emerge out of nowhere. Result of me telling @connolly_s that his detailed check of USCRN is a waste of time.

I repeated for weeks...then I swore...

They present the best only and hide urban stations. Bad faith. Consciously.


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May 22, 2024 ā€¢ 7 tweets ā€¢ 4 min read
1/ Let's do some checks: Compare the SST data model to water (ground) truth, thermometers in the water.

The green dots are the available @CDIPBuoys, a well maintained network. Probably the best buoy network (by @USACEHQ). Haven't seen any better one.

cdip.ucsd.edu/m/deployment/sā€¦

Image 2/ Florida: the gulf area showing up red at the anomaly chart. The buoy shows nominal at average values. 25C versus +26-27C in the SST model. That's a +1C heat bias. Image
May 13, 2024 ā€¢ 7 tweets ā€¢ 4 min read
1/ Let's revisit this result from AIRS satellite measurements over 17 years, showing a +0.36W increase in forcing alongside a 40 ppm rise in CO2 concentration.

Does this align with the "observed" (questionable) increase in global temperature anomaly (+0.6C)?

Letā€™s do a check.
Image 2/The IPCC reports a calculated CO2 forcing of +0.5W, as detailed on the NOAA AGGI page, which you can find here:



The SW calculation overestimates by 40% compared to the +0.36W derived by the AIRS satellite, marking the first significant discrepancy. gml.noaa.gov/aggi/aggi.html
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Apr 25, 2024 ā€¢ 4 tweets ā€¢ 3 min read
Imagine claiming the trial was correct, deploying it to 95% in NZ/AUT, and thenā€”boom!ā€”the incidence explodes instead of the virus being eliminated which should already happen at ~70% rate, and was calculated mathematically to happen based on that very promise. False. Study āž”ļøšŸš® Moreover, mortality rises instead of falling. Who are these people still lying about its mortality effectiveness? Itā€™s a failure, and rightfully, Pfizer's stock is plummeting. Keep grieving; wonā€™t help. We want the money back. Those who wanted it can still buy it with own money.
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