1/ Europe infant mortality trend. Let's have a look how NL compares with other peers.
Not so good.
Note that this is dominated by the 0-1 year group. But unfortunately, the population is only available by 0-5 years. So by averaging death_Y_LT5 / pop_LT5 we dilute a bit.
2/ Let's add some more countries. Romania and Bulgaria are on the way to leave NL behind.
I'm wondering what the plan is in NL @hugodejonge? Becoming the last soon?
3/ How does 2020 look like compared to peers?
4/ We can add the less rich countries.
5/ Lastly, let's see year 2000.
6/ NL doesn't seem to have the priorities right. Billions are spent in testing, hiring police and lockdown subventions instead of investing in healthcare. @RIVM_vDissel public.tableau.com/app/profile/or…
7/ Infanit mortality is dominated by the 0-1 year old. But unfortunately, mortality is only available in one 0-4 year bin while the population is available by 1 year. So by averaging death_Y_LT5 / pop_LT5 we dilute a bit. The real mortality for the 0-1 years is thefore ~4-5x.
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 👍.
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.
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.
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
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.
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.
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.
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.
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)?
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
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).