All world temperature series may be illegitimate.

According to HadCet, the data has been adjusted to account for urban heat island affects

-- Long Term Temperature Records Contradict GISS Temperature Record, by Mark Fife

Two points:

1. Urban Heat Effect. That does not necessarily mean they adjusted it correctly. It seems most UHE adjustments have been too low. The correct average adjustment for an UHE-station seems to be about 2C. But only at night. I'd like to know by how much they adjust east station.
2. Homogenization. All these temperature data series seem to be homogenized today. Which, I gather, means deleting outliers (from my reading of the Wikipedia entry). In 2018 Lansner & Pedersen published as study "Temperature trends with reduced impact of ocean air temperature". The took all temperature data for the past 110 years. Split stations into 2 groups.
   • OAA : Ocean Air Affected
   • OAS : Ocean Air Sheltered

   OAS stations showed no recent warming. OAS stations in USA showed no warming since the mid-1930s! OAA stations show recent warming. So it looks like all warming is due to ocean air warming the land. This is not really compatible with what we're told about the greenhouse gas effect.

   The killer here is: it looks like stations are currently homogenized based on proximity. homogenization is only theoretically legitimate when one finds a set of similarly located stations which all change for the same reason. In this case it's done by dropping outliers. One should not homogenize OAA and OAS stations. Before accepting any homogenized data one must check that no OAS & OAA homogenizations affected the other type of station.

   Although Lansner & Pedersen don't make this point about homogenization, their results clearly show that homogenizations will be invalid unless differences between OAS and OAA are taken into account (which I doubt they are - otherwise the Wikipedia entry would tell us).

Clouds

Most clouds are formed within the first 2 km of the atmosphere. We can see this from the diagram below (source), with the 3rd chart: 'cloud thickness, km', which plots altitude (y-axis) against percentage occurence. Having reached a height of only 2km cloud cover has fallen to only about 6%.

Percentage of occurrence of the
(a) cloud base altitude,
(b) cloud top altitude, and
(c) cloud thickness
- observed during different seasons over Gadanki. Altitude bin size is 500 m.

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From the data above we draw several conclusions:

1. We already know that, at low altitudes water vapour predominates as the 'greenhouse gas'. At surface level, for example, carbon dioxide can be only 0.04% of the atmosphere, but water vapour may be as much as 4% (over equatorial oceans). In this example, water vapour is 100 times more prevalent than carbon dioxide.
2. If follows that most of a greenhouse gas effect must be close to the surface and be due to water vapour
3. At under 1km altitude water vapour begins to condense out as cloud. Most of it has condensed out by 2km.
4. When the altitude reaches the tropopause (beginning at about 10km) nearly all the water vapour has condensed out as cloud.
5. So nearly all of the greenhouse gas effect is done by 10km
6. As well water vapour falling off, the actual atmospheric density thins considerably. By about 26km there's hardly any atmosphere left!
   
7. This refutes the trick of the greenhouse gas model, which has been used in one form or another, since 1967. In that model a hypothetical change in the balance of radiation at the top of the troposphere (some where about 10 to 16km up - depending on where one is at the equator), is somehow projected to the surface!! Despite:
   • increasing atmospheric density as downwelling longwave radiation, DLWR, approaches the surface from the tropopause, meaning that downwards radiation, DLWR, is absorned before the projected change can happen. So the model has no agency through which change at the surface can be effected by what happens above.
   • The increasing temperature of the atmosphere as DLWR gets closer to the surface; which means that the effect it can have is entirely swamped by the more energetic (higher temperature) air below it.

Previously Ned Nikolov, Ph.D. @NikolovScience ( 5h5 hours ago)

A totally backward understanding of the role of clouds in #ClimateChange by CarbonBrief

"A new study helps unravel one of the biggest uncertainties for scientists making climate change projections – how clouds will be affected as the Earth’s warms up."

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Ned Nikolov, Ph.D. @NikolovScience

Clouds do NOT change in response to warming. Instead, #climate warms in response to a decrease of global cloud cover/albedo. Why is it so difficult to grasp this simple fact?

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Joh A @Latebird2013 ()https://twitter.com/Latebird2013/status/1153091156881883136

Replying to @hoffballs @NikolovScience

• Changes in Earth’s Energy Budget during and after the “Pause” in Global Warming: An Observational Perspective, 2018
• Cloud Feedback Key to Marine Heatwave off Baja California, 2018
• Evidence for Large Decadal Variability in the Tropical Mean Radiative Energy Budget, 2002
• Decreasing cloud cover drives the recent mass loss on the Greenland Ice Sheet, 2017
• Late Twentieth-Century Warming and Variations in Cloud Cover, 2014

How many insects are wind turbines killing?

An amateur study published in PLOS ONE "More than 75 percent decline over 27 years in total flying insect biomass in protected areas", claims a massive fall in German insect populations. Germany has the highest density of wind turbines in the world.

	Wind capacity		global %	MWe / 1000km²
China:	211,392	MW	35.70%	22
United States:	96,665	MW	16.30%	11
Germany:	59,311	MW	10.00%	166
India:	35,129	MW	5.90%	11
Spain:	23,494	MW	4.00%	46
United Kingdom:	20,970	MW	3.50%	86

Source: Wikipedia 2018

When we add another column showing wind capacity per 1000 km² we see Germany has the highest density of wind turbines per area. Twice UK.

Dr. Franz Trieb of the Institute of Engineering Thermodynamics concludes that a "rough but conservative estimate of the impact of wind farms on flying insects in Germany" is a “loss of about 1.2 trillion insects of different species per year” which “could be relevant for population stability.”

This was all too predictable: build wind-turbines all over the world and expect no affect on flying animal populations. <-- Only activists could be so dim. Now greens are mostly ignoring the study is in Germany, which has the most wind turbines. Greens are blaming it on global warming or environmental destruction due to capitalism. Anything to keep themselves out of the dock.

Note: Most land-based wind-turbines in UK are in Scotland. Most wind-turbines in UK are probably offshore in the North Sea. PS: This sentence is entirely subjective, and an aside; if I think it matters I will calculate it.

The climate consensus overstate man-made climate change 10 times over

From the paper in print, by J. Kauppinen & P. Malmi. 2019

Conclusion

We prove that the GCM-models used in IPCC report AR5 cannot correctly compute the natural component included in the observed global temperature. The reason is that the models fail to derive the influences of low cloud cover fraction on the global temperature. A too small natural component results in a too large portion for the contribution of the greenhouse gases like carbon dioxide. That is why IPCC represents the climate sensitivity more than one order of magnitude larger than our sensitivity 0.24°C. Because the anthropogenic portion in the increased CO₂ is less than 10%, we have practically no anthropogenic climate change. Low clouds mainly control the global temperature.

Preprint

No Empirical Evidence for Significant Anthropogenic Climate Change by J. Kauppinen and P. Malmi, 2019

Details

Climate sensitivity has massive uncertainty in scientific literature. From close to near 0 to 9. High climate sensitivities promoted by the establishment (IPCC) all come from models (GCMs). Many non-model studies have much lower climate sensitivities.

Observation shows a 1% increase in low cloud cover decreases temperature by 0.11°C

... The time interval (1983-2008) in Fig 2 is limited to 25 years because of the lack of the low cloud cover data. During this time period the CO₂ concentration increased from 343 ppm to 386 ppm and both Figures 1 (IPCC) and 2 show the observed temperature increase of about 0.4°C. The actual global temperature change, when the concentration of CO₂ raises from C₀ to C, is

where ΔT_{2 CO2} is the global temperature change, when the CO₂ concentration is doubled and Δc is the change of the low cloud cover fraction. The first and second term are the contributions of CO₂ [5] and the low clouds, respectively. Using the sensitivity ΔT_{2 CO2} = 0.24°C derived in the papers [3,2,4] the contribution of greenhouse gases to the temperature is only about 0.04°C according to the first term in the above equation.

It turns out that the changes in the relative humidity and in the low cloud cover depend on each other [4]. So, instead of low cloud cover we can use the changes of the relative humidity in order to derive the natural temperature anomaly. According to the observations 1% increase of the relative humidity decreases the temperature by 0.15°C, and consequently the last term in the above equation can be approximated by -15°C Δφ, where Δφ is the change of the relative humidity at the altitude of the low clouds.

The IPCC climate sensitivity is about one order of magnitude too high, because a strong negative feedback of the clouds is missing in climate models. If we pay attention to the fact that only a small part of the increased CO₂ concentration is anthropogenic, we have to recognize that the anthropogenic climate change does not exist in practice. The major part of the extra CO₂ is emitted from oceans [6], according to Henry`s law. The low clouds practically control the global average temperature. During the last hundred years the temperature is increased about 0.1°C because of CO₂. The human contribution was about 0.01°C

Comments

More 2019 Evidence of Nature’s Sunscreen, by Ron Clutz

Global warming explained.

This satellite measurement shows that the steep warming of the 1980s to 2000s corresponded with over a 6 Watt per square meter reduction in the global average cloud coverage.

Not only does this change represent over a 6 Watt per square meter increase in incoming solar radiation (aka Sunshine), but also there is an associated reduction in down-welling IR radiation from back reflection off of cloud bottoms.

For this reason, Global Warming is rightfully called Global Brightening.

This increase in Sunshine is over 20x larger than the theoretical radiative forcing associated with rising CO2 concentrations.

The questions remains: What caused this cloud-cover decrease?

See: Data: Global Temperatures Rose As Cloud Cover Fell In the 1980s and 90s

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"Conclusion: We have proven that the GCM-models used in IPCC report AR5 cannot compute correctly the natural component included in the observed global temperature. The reason is that the models fail to derive the influences of low cloud cover fraction on the global temperature. A too small natural component results in a too large portion for the contribution of the greenhouse gases like carbon dioxide. That is why IPCC represents the climate sensitivity more than one order of magnitude larger than our sensitivity 0.24°C. Because the anthropogenic portion in the increased CO2 is less than 10 %, we have practically no anthropogenic climate change. The low clouds control mainly the global temperature."

https://arxiv.org/pdf/1907.00165.pdf

Catastrophic, man-made, global cooling back in 1972