One of the most ridiculous claims recently related to Menne et al 2010 and my surfacestations project was a claim made by DeSmogBlog (and Huffington Post who carried the story also) is that the “Urban Heat Island Myth is Dead“.
To clarify for these folks: Elvis is dead, UHI is not.
For disbelievers, let’s look at a few cases showing UHI to be alive and well.
CASE 1: I’ve measured it myself, in the city of Reno for example:
The UHI signature of Reno, NV – Click for larger image
Read the story of how I created this graph here The procedure and raw data is there if you want to check my work.
I chose Reno for two reasons. It was close to me, and it is the centerpiece of a NOAA training manual on how to site weather stations to avoid UHI effects.
CASE 2: NOAA shows their own measurements that mesh well with mine:
To back that up, the NOAA National Weather Service includes the UHI factor in one of it’s training course ( NOAA Professional Competency Unit 6 ) using Reno, NV.
In the PCU6 they were also kind enough to provide a photo essay of their own as well as a graph. You can click the aerial photo to get a Google Earth interactive view of the area. The ASOS USHCN station is right between the runways.
This is NOAA’s graph showing the changes to the official climate record when they made station moves:
Source for 24a and 24b: NOAA Internal Training manual, 2004-2007
Oops, moving the station south caused a cooling. Fixed now, all better.
What is striking about this is that here we have NOAA documenting the effects of an “urban heat bubble” something that DeSmog Blog says ” is dead”, plus we have NOAA documenting a USHCN site with known issues, held up as a bad example for training the operational folks, being used in a case study for the new USHCN2 system.
So if NOAA trains for UHI placement, I’m comfortable in saying that DesmogBlog claims of UHI being “dead” are pure rubbish. But let’s not stop there.
CASE 3: From an embattled scientist.
A paper in JGR that slipped in 2007 without much notice (but known now thanks to Warwick Hughes) is one from Phil Jones, the “former” director of the Hadley Climate Center in the UK. The paper is titled: Urbanization effects in large-scale temperature records, with an emphasis on China
In it, Jones identifies an urban warming signal in China of 0.1 degrees C per decade. Or, if you prefer, 1 degree C per century. Not negligible by any means. Here is the abstract:
Global surface temperature trends, based on land and marine data, show warming of about 0.8°C over the last 100 years. This rate of warming is sometimes questioned because of the existence of well-known Urban Heat Islands (UHIs). We show examples of the UHIs at London and Vienna, where city center sites are warmer than surrounding rural locations. Both of these UHIs however do not contribute to warming trends over the 20th century because the influences of the cities on surface temperatures have not changed over this time. In the main part of the paper, for China, we compare a new homogenized station data set with gridded temperature products and attempt to assess possible urban influences using sea surface temperature (SST) data sets for the area east of the Chinese mainland. We show that all the land-based data sets for China agree exceptionally well and that their residual warming compared to the SST series since 1951 is relatively small compared to the large-scale warming. Urban-related warming over China is shown to be about 0.1°C decade−1 over the period 1951–2004, with true climatic warming accounting for 0.81°C over this period.
Even though Jones tries to minimize the UHI effect elsewhere, saying the UHI trends don’t contribute to warming in London and Vienna, what is notable about the paper is that Jones has been minimizing the UHI issues for years and now does an about face on China.
Jones may have tried to hide CRU data, but he’s right about China.
CASE 4: From “The Dog ate My Data” who writes:
The Australian Bureau of Meteorology (BOM) blames Melbourne’s equal warmest overnight temperature of 30.6 degrees, on January 12 on the heat island effect. The previous time the city was that hot overnight was February 1, 1902.
The Age newspaper cites a meteorologist at the bureau, Harvey Stern,
Melbourne recorded its equal warmest overnight temperature, 30.6 degrees, on January 12. The previous time the city was that hot overnight was February 1, 1902.
A meteorologist at the bureau, Harvey Stern, said that Melbourne suffered from a heat island effect, in which a city is warmer than the surrounding countryside.
This was the case especially at night, because of heat stored in bricks and concrete and trapped between close-packed buildings.
I am stunned if that is correct firstly because BOM isn’t blaming Global Warming and secondly that the urban heat island effect directly receives the blame. With faults in the 2007 IPCC’s AR4 now pouring out I guess it is not suprising that attributions of weather events are now, shall we say, possibly becoming more circumspect.
CASE 5: Heatzilla stomps Tokyo
From the website “science of doom” who writes:
New Research from Japan
Detection of urban warming in recent temperature trends in Japan by Fumiaki Fujibe was published in the International Journal of Climatology (2009). It is a very interesting paper which I’ll comment on in this post.
The abstract reads:
The contribution of urban effects on recent temperature trends in Japan was analysed using data at 561 stations for 27 years (March 1979–February 2006). Stations were categorized according to the population density of surrounding few kilometres. There is a warming trend of 0.3–0.4 °C/decade even for stations with low population density (<100 people per square kilometre), indicating that the recent temperature increase is largely contributed by background climatic change. On the other hand, anomalous warming trend is detected for stations with larger population density. Even for only weakly populated sites with population density of 100–300/km2, there is an anomalous trend of 0.03–0.05 °C/decade. This fact suggests that urban warming is detectable not only at large cities but also at slightly urbanized sites in Japan. Copyright, 2008 Royal Meteorological Society.
Why the last 27 years?
The author first compares the temperature over 100 years as measured in Tokyo in the central business district with that in Hachijo Island, 300km south.
Tokyo – 3.1°C rise over 100 years (1906-2006)
Hachijo Island – 0.6°C over the same period
This certainly indicates a problem, but to do a thorough study over the last 100 years is impossible because most temperature stations with a long history are in urban areas.
However, at the end of the 1970’s, the Automated Meteorological Data Acquisition System (AMeDAS) was deployed around Japan providing hourly temperature data at 800 stations. The temperature data from these are the basis for the paper. The 27 years coincides with the large temperature rise (see above) of around 0.3-0.4°C globally.
And the IPCC (2007) summarized the northern hemisphere land-based temperature measurements from 1979- 2005 as 0.3°C per decade.
How was Urbanization measured?
The degree of urbanization around each site was calculated from grid data of population and land use, because city populations often used as an index of urban size (Oke, 1973; Karl et al., 1988; Fujibe, 1995) might not be representative of the thermal environment of a site located outside the central area of a city.
What were the Results?
Mean temperature anomaly vs population density, Japan
The x-axis, D3, is a measure of population density. T’mean is the change in the mean temperature per decade.
Tmean is the average of all of the hourly temperature measurements, it is not the average of Tmax and Tmin.
Notice the large scatter – this shows why having a large sample is necessary. However, in spite of that, there is a clear trend which demonstrates the UHI effect.
There is large scatter among stations, indicating the dominance of local factors’ characteristic to each station. Nevertheless, there is a positive correlation of 0.455 (Tmean = 0.071 logD3 + 0.262 °C), which is significant at the 1% level, between logD3 and Tmean.
Here’s the data summarized with T’mean as well as the T’max and T’min values. Note that D3 is population per km2 around the point of temperature measurement, and remember that the temperature values are changes per decade:
The effect of UHI demonstrated in various population densities
Note that, as observed by many researchers in other regions, especially Roger Pielke Sr, the Tmin values are the most problematic – demonstrating the largest UHI effect. Average temperatures for land-based stations globally are currently calculated from the average of Tmax and Tmin, and in many areas globally it is the Tmin which has shown the largest anomalies. But back to our topic under discussion..
And for those confused about how the Tmean can be lower than the Tmin value in each population category, it is because we are measuring anomalies from decade to decade.
And the graphs showing the temperature anomalies by category (population density):
Dependence of Tmean, Tmax and Tmin on population density for different regions in Japan
Quantifying the UHI value
Now the author carries out an interesting step:
As an index of net urban trend, the departure of T from its average for surrounding non-urban stations was used on the assumption that regional warming was locally uniform.
That is, he calculates the temperature deviation in each station in category 3-6 with the locally relevant category 1 and 2 (rural) stations. (There were not enough category 1 stations to do it with just category 1). The calculation takes into account how far away the “rural” stations are, so that more weight is given to closer stations.
Estimate of actual UHI by referencing the closest rural stations – again categorized by population density
And the relevant table:
Temperature delta from nearby rural areas vs population density
Conclusion
Here’s what the author has to say:
On the one hand, it indicates the presence of warming trend over 0.3 °C/decade in Japan, even at non-urban stations. This fact confirms that recent rapid warming at Japanese cities is largely attributable to background temperature rise on the large scale, rather than the development of urban heat islands.
..However, the analysis has also revealed the presence of significant urban anomaly. The anomalous trend for the category 6, with population density over 3000 km−2 or urban surface coverage over 50%, is about 0.1 °C/decade..
..This value may be small in comparison to the background warming trend in the last few decades, but they can have substantial magnitude when compared with the centennial global trend, which is estimated to be 0.74°C/century for 1906–2005 (IPCC, 2007). It therefore requires careful analysis to avoid urban influences in evaluating long-term temperature changes.
So, in this very thorough study, in Japan at least, the temperature rise that has been measured over the last few decades is a solid result. The temperature increase from 1979 – 2006 has been around 0.3°C/decade
However, in the larger cities the actual measurement will be overstated by 25%.
And in a time of lower temperature rise, the UHI may be swamping the real signal.
The degree of urbanization around each site was calculated from grid data of population and land use, because city populations often used as an index of urban size (Oke, 1973; Karl et al., 1988; Fujibe, 1995) might not be representative of the thermal environment of a site located outside the central area of a city.
Case 6: California Counties by population show a distinct UHI signature.
My friend Jim Goodridge, former California State Climatologist identified the statewide UHI signature issues way back in 1996. This graph had a profound effect on me, becuase it was the one that really made an impact on me, switching my views to being skeptical. Yes, I used to be a warmer, but that’s another story.
Goodridge, J.D. (1996) Comments on “Regional Simulations of Greenhouse Warming including Natural Variability” . Bull, Amer. Meteorological Society 77:1588-1599.
Goodrich (1996) showed the importance of urbanization to temperatures in his study of California counties in 1996. He found for counties with a million or more population the warming from 1910 to 1995 was 4F, for counties with 100,000 to 1 million it was 1F and for counties with less than 100,000 there was no change (0.1F).
He’s been quietly toiling away in his retirement on his computer for the last 15 years or so making all sort of data comparisons. One plot which he shared with me in 2003 is a 104 year plot map of California showing station trends after painstakingly hand entering data into an Excel spreadsheet and plotting slopes of the data to produce trend dots.
He used every good continuous piece of data he could get his hands on, no adjusted data like the climate modelers use, only raw from Cooperative Observing Stations, CDF stations, Weather Service Office’s and Municipal stations.
The results are quite interesting. Here it is:
I’ll have more interesting revelations from Jim Goodridge soon.
Case 7: NASA JPL’s climatologist says UHI is an issue
This press release from NASA Jet Propulsion Lab says that most of the increase in temperature has to do with ubanization:
[NASA’s JPL Bill] Patzert says global warming due to increasing greenhouse gases is responsible for some of the overall heating observed in Los Angeles and the rest of California. Most of the increase in heat days and length of heat waves, however, is due to a phenomenon called the “urban heat island effect.”
Heat island-induced heat waves are a growing concern for urban and suburban dwellers worldwide. According to the U.S. Environmental Protection Agency, studies around the world have shown that this effect makes urban areas from 2 to 10 degrees Fahrenheit (1 to 6 degrees Celsius) warmer than their surrounding rural areas.
Patzert says this effect is steadily warming Southern California, though more modestly than some larger urban areas around the world. “Dramatic urbanization has resulted in an extreme makeover for Southern California, with more homes, lawns, shopping centers, traffic, freeways and agriculture, all absorbing and retaining solar radiation, making our megalopolis warmer,” Patzert said.
CASE 8: You can see it from space. NASA (not the GISS division) measures it. Here’s a report they presented at the last AGU meeting in December 2009. Gee, that curve below looks like Reno, NV, doesn’t it?
The urban heat island effect can raise temperatures within cities as much as 5 C higher than the surrounding countryside. New data suggests that the effect is more or less pronounced depending on the type of landscape — forest or desert — the city replaced. Credit: NASA
NASA researchers studying urban landscapes have found that the intensity of the “heat island” created by a city depends on the ecosystem it replaced and on the regional climate. Urban areas developed in arid and semi-arid regions show far less heating compared with the surrounding countryside than cities built amid forested and temperate climates.
“The placement and structure of cities — and what was there before — really does matter,” said Marc Imhoff, biologist and remote sensing specialist at NASA’s Goddard Space Flight Center in Greenbelt, Md. “The amount of the heat differential between the city and the surrounding environment depends on how much of the ground is covered by trees and vegetation. Understanding urban heating will be important for building new cities and retrofitting existing ones.”
Goddard researchers including Imhoff, Lahouari Bounoua, Ping Zhang, and Robert Wolfe presented their findings on Dec. 16 in San Francisco at the Fall Meeting of the American Geophysical Union.
Satellite imagery of suburban (top) and urban Atlanta shows the differences in daytime heating, as caused by the urban heat island effect. Credit: NASA Goddard’s Scientific Visualization Studio
Yep, UHI is alive and well. Anybody with an automobile dashboard thermometer who drives a commute from country to city can easily measure UHI, and you don’t have to be a climate scientist to prove it to yourself.
UPDATE: For a primer on how UHI is not dealt with by NOAA and CRU, have a look at this Climate Audit post:
Realclimate and Disinformation on UHI
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I was unfortunate in having to live in Central London for a couple years and I know the UHI effect is very real there.
It doesn’t seem to effect the maximum temperature much, rather it’s the warmer nights which are noticeable, particularly in the winter.
There have been many changes in London over the last 50 years, most of which serve to amplify the UHI. The Clean Air Act and loss of heavy industry around the centre of London have also had a big warming effect.
Lots of interesting discussion on this topic. I have made my point about the UHI effect probably being greater in emerging cities then in existing big cities. Another point are the surroundings. The UHI effect seems bigger – relative to the surroundings – when the surroundings are desert like and without much trees. That is probably because cooling at night will be much greater at these “bald surfaces”. In my country, the Netherlands I can see temperatures dropping at night much further at these open areas then there were there are much trees or of course cities. What is not often or maybe never taken into account is that trees grow and that in some areas of the world surfaces have become more wooded in the last century. To see how even rural areas might change I include this link with pictures of Dolmen in the province of Drenthe with picture of the landscape now and 90 years ago.
http://www.hunebed.com/index_multimedia.html
(click on the numbers of the dolmen d1 to d50, it is good fun)
Interesting article written by Warm Monger Fred Pearce in the Guardian on Chinese UHI and how Jones et al at CRU may have manipulated the data in the IPCC report
http://www.guardian.co.uk/environment/2010/feb/01/dispute-weather-fraud
I lived for 28 years in Hong Kong and can testify to the abrupt changes in temperature when moving from urban/semi-urban areas to some of the few rural areas left in that crowded area.
I lived in a place called Tai Mei Tuk, a rural area (my garden was frequently visited by porcupines and wild pigs) and I worked in a place called Ta Kwu Ling on what was then the Sino-British Border. Today (01/02/2010 at 21:50 UK Time) the minimum temperatures are, according to the HK Observatory, 17.1C and 18.4C. Just a few miles further south in southern Kowloon the present temperature is 19.9C. The maximum temperatures were 19.5C for Tai Mei Tuk, 18.4 for Ta Kwu Ling and southern Kowloon is 20.8C.
QED
UHI lives!
Case 9.
When we had all that snow in southern Britain recently, the only place that was snow free was central London.
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If I understand correctly, those who are trying to justify the drastic reduction of the number of monitoring sites, while using those which are more predominantly in or near more developed or urbanized areas (which already have demonstrated disproportionate “warming”), have rationalized that they are only interested in the magnitude of the “anomaly” (delta). This is a fallacy. In the last couple of decades, we have experienced a massive increase in home, automobile and workplace automatic temperature control which automatically puts out much more heat into our environment, whenever our ambient temperature goes above or below “optimum”. Thus, wherever people live, work or play, measured temperature tends to rise!
We already know that even in the United States, different regions have radically different characteristics:
A. Population densities (urban as well as rural)
B. Personal responses to hot and cold weather or climate (e.g. inclination to suffer and sweat or bundle up vs. turn on air conditioning or heat.)
C. Availability of air conditioning or heat when they want it (or can afford it)
D. Predominant types of architecture (e.g. High thermal mass structures accumulate heat.)
E. Geography/Geology
Internationally, differences in culture, architecture, and stage of economic development have even greater impacts on urban vs. rural heat effect per capita and city sizes. Thus, it appears to me that “Urban Heat Islands” cannot be categorized or factored by population size. We must have the maximum number and diversity of locations of well designed temperature monitoring stations that utilize platinum resistance sensing elements or equivalent, that are insensitive to radiation heating,.and only measure air temperature. Ideally they will be placed in areas well removed from direct effects of human activity. Only then can we begin to know whether there is significant, unnatural “global warming”.
Incidentally in that satellite image of the UK under snow the other week, you can actually see the major cities in a slightly darker grey. Birmingham, Stoke, Manchester, Leeds / Bradford all visible, and I think also Hull and Aberdeen.
What would it take to get Google to put a thermometer on their street-view vans as they drive around? Each measurement would have a time stamp and be geolocated. The UHI would be quite obvious after a short time!
>>I think what he means is that London and Vienna have not
>>grown much the last century and have always been heat islands
Firstly, London has grown considerably. The population has increased, from about 5m in 1900 to about 7m in 1990.
http://data.london.gov.uk/datastore/package/historic-census-population
Secondly, the density has increased dramatically, as this graphic shows.
http://spatialanalysis.co.uk/2010/01/12/london-population-density-1801-2001/
Thirdly, the amount of energy each person used has probably doubled or trebled. The amount of energy we feed into London, be that oil, gas or electricity, must have a bearing on the resultant temperature. (UHI temperature increase is not simply the result of buildings capturing incident light better than fields and being drier).
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“”” bob paglee (10:30:51) :
Was the locating of a temp sensor between two airport runways done deliberately to catch the extra heat from airliners taking off with full jet exhaust blowing horizontally while accelerating along the runway before heading upward? Or was it designed to respond also to the big volume of hot gases emanating right at ground level from the jets when the thrust reversers are blowing full-blast along the runway upon landing? Will we now see an effect of global cooling if the recession causes a reduction in takeoffs and landings? “””
When I get on a twin engined 757 or the like to fly out of SFO to say Auckland; fully laden with fossil fuel, and luggage and passengers; I care not a jot for Dr James Hansen’s masticated GISStemp ravings. What matters to me is the density altitude of that bleeping runway; So I know; or at least the flight crew knows whether it is quite safe to perform the ONLY optional part of any commercial airline flight; which is commonly referred to as “The Take-off”.
They can blast all the jet exhaust they like into that runway Owl box, for all I care so, long as the temperature sensor gets it right.
Richard Sharpe (09:05:41) :
“You are being dishonest again. No one proposes using thermometers mounted on cars for determining the average temperature of the world. However, you can get a clear indication of the extent of the UHI effect using them when driving through a city.”
Could you point out which sentence was dishonest or misleading? I admit I try to ask thought-provoking questions, but I try very hard to communicate clearly and without guile. I believe you and I have had a similar, more cordial exchange on a different thread. All of the uncertainties I mentioned then still apply here, in my opinion.
Richard Lawson (13:45:26) : Interesting article written by Warm Monger Fred Pearce in the Guardian on Chinese UHI and how Jones et al at CRU may have manipulated the data in the IPCC report
http://www.guardian.co.uk/environment/2010/feb/01/dispute-weather-fraud
Do I really see what I think I see? The Guardian supporting Douglas Keenan’s allegations of fraud against Wang and Jones???
Richard Sharpe (08:02:38) :
“I think the dashboard thermometer in my car is designed to be mounted on a vehicle.
However, with respect to your second point, by god, I think they have discovered that cars react to UHI! Who would have thought that they produce more heat in urban areas than other areas.
(Of course, it’s possible that the shape of the city on the transects used by people is such that more power is required going in and less is required going out. That too could explain the temperature profile after subtracting out the bias caused by the nearby heat source that is the car’s motor.)”
I’m find some of the language you use there a little unclear, so let’s set aside points #1 and #2 for a moment. Perhaps the other uncertainties I raised (#3 and #4) are the more salient questions?
Or if you find my alternative view point particularly offensive, I would think #5 would set the tone for an interesting, more amicable dialogue.
I will chip in one more – my son’s eighth grade science fare project measured the Phoenix urban heat island (about 7-10F heating in city)
http://www.climate-skeptic.com/2008/02/measureing-the.html
@Allen (04:36:29) :
“The question I have is: how do you normalize for this effect when the effect varies so dramatically from day to day?”
The short answer is you can’t. For UHI corrections, there is simply too much noise in both the UHI values and the values you are attempting to reference to, thus the correction factor is in reality, a wildly swinging random variable.
One intelligent guess does not equal scientific datum, and two intelligent guesses does not equal scientific data.
Assumptions and guesses are made everyday by scientists, engineers, and mathematicians. When an otherwise well intentioned scientific project results in failure or a non sequitur occurs, it is almost always caused by (a) faulty assumption(s) or guess(es). However, assumptions and guesses (not to be confused with a hypothesis) are not science and math, at best they are in the realm of art (if skillful), and at worst hacking (i.e. “to damage or injure by crude, harsh, or insensitive treatment; mutilate; mangle”). The field of Medicine is considered an art, thus “The Art of Climatology” has a certain ring to it IMO.
No need to worry, all we have to do is paint our roofs white.
http://www.sciencedaily.com/releases/2010/02/100201145445.htm
toyotawhizguy (00:09:37) :
“When an otherwise well intentioned scientific project results in failure or a non sequitur occurs, it is almost always caused by (a) faulty assumption(s) or guess(es).”
On what are you basing this statement?
This Python quote is for Joel Shore, from the minstral’s song; “when danger reared it’s ugly head, he bravely turned his tail and fled”.
I looked at the report by Menne, but without the raw data, it is not very informative. Is the raw data available somewhere?
The findings by Menne are so counterintuitive that I am reasonably certain that something is fishy. The idea that UHI is not a factor and that poorly sited stations are just as good as well sited ones is really hard to believe. Asphalt hot, grass cool. Quantum mechanics is counterintuitive, UHI should not be.
I’d like to see some experimental/observation data to support that assertion …
The ONLY area I have seen cool ‘minutes after sunset’ are vegetative areas devoid of the constructs of man …
(Perhaps your experiences were with thinly laid asphalt, with very little underlayment – not a load-bearing road surface or airport runway/taxiway).
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Observationally it was apparent that thin clouds do little to block LWIR; during tests with the former mother company (TI) aboard their Convair 380 doing FLIR testing/demo-ing it was easy to see and note surface features (roads, traffic, buildings) through light overcast whereas optically (with eyeballs) one could not see those same features – but of course not so with heavier cloud cover … yet another reason A/C are equipped with FLIR (its not just for night vision) in a ‘war zone’.
Proof: Recall the ‘optical window’ in the 10 um area bordered either side by WV and CO2. This is also roughly the Planck curve spectral peak for 288 K earth.
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“”” _Jim (08:08:38) :
George E. Smith (10:22:43) :
Well there’s one aspect of these UHIs that is seldom mentioned. Those tar and concrete structures, that absorb solar radiation readily and rise to hotter temperatures; are also better radiators of LWIR thermal radiation which is a cooling effect.
I have often observed that a hot tar parking lot quickly cools within just a few minutes after sunset.
I’d like to see some experimental/observation data to support that assertion …
The ONLY area I have seen cool ‘minutes after sunset’ are vegetative areas devoid of the constructs of man …
(Perhaps your experiences were with thinly laid asphalt, with very little underlayment – not a load-bearing road surface or airport runway/taxiway). “””
Well now that you mention it, it actually was a tar (blacktop) road surface, that I noticed cooled rapidly when the sun went down. And as a matter of fact, it actually had cooled before actual sunset, but the sun was blocked from that road surface area by houses and trees.
Are you suggesting that that the concept of blackbody radiation is wrong, and a higher temperature black surgface will NOT radiate energy at a higher rate than a cool one. Because that was my point; that it is the earth’s hottest surfaces that are responsible for most of the cooling radiation; in fact the hottest surfaces can be radiating at more than ten times the rate of the coldest surfaces; and that could all be happening at the same time; on some northern summer day, while Antarctica is in its winter midnight.
As to the high thin clouds business; it is asserted by climatologists, that high thin clouds warm the earth by blocking LWIR, so that such clouds are a POSITIVE feedback warming effect. On the other hand low dense clouds are a cooling negative feedback effect, by blocking sunlight from the surface.
Someone cited a standard climate textbook graph; that I have squirrelled away somewhere, that has plots of earth surface temperature versus cloud cover percentage, as a function of cloud height. And those graphs claim that the higher the clouds, the warmer they heat the surface by blocking LWIR from escape.
Well you know what they say about scientific experiment; you can’t ever prove anything is true with any finite amount of experimental evidence; but you can prove it false with but a single negative result.
So we can assert immediately, that those graphs of cloud cover and height, and surface temperature; cannot be correct, since nowhere on those graphs, is there any evidence that the humidity of the intervening atmosphere has any effect on the surface temperature/cloud cover relationship. According to those graphs; you can have zero relative humidity right up to where those high altitude clouds form, and you get exactly the same surface temperature, as you would if the humidity was 99% all the way up to those clouds. Those textbook graphs show no evidence that the amount of water vapor in the atmosphere has any effect on the warming caused by clouds.
Yet it is claimed that water vapor is a greenhouse gas; in fact the most important one.
So those climate textbook graphs have to be pure nonsense.
The Planck curve may place the spectral peak at 10.1 microns for a 288 K radiating surface, but it can be as low as 8.7 microns for a +60 deg C hot desert surface, or as long as 15.9 microns for the ultimate cold of about -90C at Vostok, and such places.
And lets not forget that ozone dip at around 9-10 microns, in the middle of that atmospheric window.
Personally, I am of the belief that it is the surface temperatures, and the atmospheric humidity conditions, that are the CAUSE of those high wispy clouds; not the RESULT of those clouds. But the textbooks conveniently leave out the water vapor GH effect, when they credit those high wispy clouds with positive feedback warming of the surface.