So lets add storage (50% efficiency). 150 such parks. Makes 150x200=30.000 ha (min). That is the total area of Munich. PVs is trash in 30 years and needs continuous replacement (fresh fossil powered mining + industry) somewhere in the world.
The total primary power need for Germany is 460 GW. You would need 460/1.4*30.000 ha ~ 1.5x Bavaria (1.5 times red here) as PV park surface. Sounds like a plan.
The Great Wall is the largest man-made project in the world. 20,000 km (~2000km2). Germany will beat this by 50x with the Great Solar Park, 100.000km2. 50 times the Great Chinese Wall. Life time 30 year only.
1M km of 100 m PVs. Earth-Moon back twice.
Wir schaffen das 🙂
A NL engineer showed a calculation that NL does not have sufficient area (incl. the complete Dutch North Sea sector) to produce sufficient energy. The RE Amish utopia only works if Randstad emigrates to Africa and only the farmers stay. Without fossils or nuclear, no NL society.
To the moon and back. That will be generation 2 (you need to make one every 30 years) of the Great Solar Wall. Generation 3 will be on the moon (problem: night is 15 days long there).
The Tower of Babel (to reach the god of the sun) project can begin.
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@Dodders75 @MetEireann Next: UHI effect in Uppsala (big city 🟩) vs. Linköping (small town 🟥). Uppsala's fewer frost days reflect its urban growth. While UHI—locally beneficial as it reduces frost—isn't climate change, it distorts data at 99% of global stations.
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.
2/ The ERA5 model's +1.75°C anomaly aligns with megacity 'BU' levels—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.
3/Next - the most reliable station region only: US
-1.5°C 🥶
Even cities (high BU) could escape despite UHI. We saw snow in TX/Florida/AL and deep frozen alligators.
Data and visuals aligns. ✅
(ERA5 SW is hallucinating heat where unconstrained.)
1/ Deutschland, die Energienarren der Welt: Thread.
Hier ist die Preiskurve (31 Tage, stündlich). Kaufe teuer, verkaufe billig. Bottom Nailers (oder auch Narren). Angeblich importieren sie, weil es billiger ist? Nein. Die Sonne scheint eben nicht nachts.
2/ Quelle: Agora Energiewende – de facto der Familienbetrieb der Grünen. Man sieht sofort, was los ist: Deutschland, auf einem Irrweg, in bestem Stil echter Narren. Verkaufen billig, kaufen teuer, alles im Namen der „Rettung“. Klar, wer nachts Sonne braucht, zahlt eben drauf.
3/ Jetzt wierholen wir zusammen, wie echte Hofnarren:
„Importieren ist billiger“
„Schweden hat versagt“
„Lauterbach rettet Leben“
@roberthabeck for Chancellor. Ab hier anders.
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 🟩) consistently trailing the urbanized GHSL BU data (10% BU = typically for small towns 🟧).
3/ Analyzing further: nearly half of the stations are classified as rural (BI=0). This is complete nonsense, as the GHSL built-up percentages 2020 for these stations clearly indicate. Nearly all are, in fact, urban—which explains why they see no difference to officially urban.
3/ Now let's try GOTHENBURG. Hold on a second... what's happening? It looks like we've accidently landed in the US Midwest—in the middle of nowhere, where hockey sticks don't flourish. Nice flatliner we have here, just like CHAMA.
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 👉 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 ?
@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 climate—yes, it’s better than the station. Well done @ChGefaell 👍.