Orwell2024πŸ’ Profile picture
Dec 14, 2021 β€’ 7 tweets β€’ 5 min read β€’ Read on X
1/ Another broken Covid claim.

Work done by @USMortality 😎

I just plot it here on a map. Same scale as my maps for Europe.

Note the he uses a German std. population (2020) while me ESP2013 or NL2011.

The timeframe is week 1 - current week 50 fro all years. Image
2/ Animated version.

The mortality in the east, is nothing new. The low vaccination rate has little to do with a problem that is seen 2016-2019 aswell.

Try with obesity/smoking maps to understand the issue...πŸ˜‰
3/ Here the full year data up to 2020.

What do we see: not getting vaccinated in 2021 already increased death rate in 2016-2019.

Magic time machine? πŸ˜€

No: the root cause for E-W, N-S mortality disparity has a different root cause than vaccines. Lifestyle, wealth,... Image
4/ Here it comes. The DE obesity map (2017) next to it on the right.

Can you see it? Berlin also shining green in the middle of unhealthiest (maybe result of poverty). Image
5/ Here is the correlation with % obesity in Germany.

Do we have correlation? And could it be causality as it happens every year and in every country?

I would say so. Image
6/ All years in one plot: The trend seems to worsen over the years. We may need more years to tell... Image

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More from @orwell2022

Sep 10
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 πŸ‘‰ 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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@meteoblue @AEMET_CValencia He clearly doesn’t understand their response nor my request. At this stage, I just want him to provide THE HOURLY DATA. What the answer actually means is that the 30 km cell is more representative of the region’s climateβ€”yes, it’s better than the station. Well done @ChGefaell πŸ‘.

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Read 10 tweets
Sep 3
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? πŸ‘‰ open.substack.com/pub/orwell2024…


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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?
3/ It escalated quickly. Similar to @BMcNoldy from Miami, master's student @Daaanvdb also used airport data instead of professional equipment, like what's available at @UNISvalbard.

Let's do better and use proper data from a better looking station.


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Read 19 tweets
Jun 27
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
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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
3/ Source: YCEO Surface Urban Heat Islands: Spatially-Averaged Daytime and Nighttime Intensity for Annual, Summer, and Winter.

It's from 2003. Now it's even more urbanized = worse.

developers.google.com/earth-engine/d…
Read 12 tweets
Jun 18
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? 🧡 ncei.noaa.gov/pub/data/uscrn…
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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3/ So, what do they look like, the ones they don't like to show? Urban areas. Airports...

Remember their requirements: It should be like the Everglades. No man-made environmental alterations. Stable. Representative.


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Read 12 tweets
May 22
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/s…

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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
3/ Next - Hawaii. Buoys are below average. SST product is showing heat anomalies there.

14th May: buoy 24.5C vs. 25.5C SST.
+1C heat bias

Interesting. It's apparently too warm, as long as you don't stick a real thermometer into the water to measure and realize: it's cold. Image
Read 7 tweets
May 13
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)?

Let’s do a check.
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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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3/ Now we return to Happer's paper, showing that doubling CO2 from 400 --> 800 ppm results in +3W of forcing.


This is consistent with +3.5W reported by the NOAA AGGI (+3.5W).

arxiv.org/pdf/2006.03098

gml.noaa.gov/aggi/aggi.html

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Read 7 tweets

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