Guest essay by Larry Hamlin
NOAA’s U.S. contiguous U.S. summer (June through August) measured minimum and maximum temperatures trends over the period 1895 through 2024 (shown below from NOAA’s Climate at a Glance Times series data website) show clear and distinct differing temperature trend increasing growth compared to the calculated average temperature trend outcome.
The minimum temperature trend outcomes after 1985 climb significantly faster than do the maximum measured temperature trend outcomes. U.S. population data shows an increase of about 100 million during the 1980 to 2023 period.
Since the average temperature is not a measured value but instead the calculated mathematical average of the minimum and maximum measured temperatures {(TMax + TMin)/2} the average temperature calculated trend outcome is controlled and dominated by the much larger increase occurring in the minimum measured temperature trend versus the maximum measured temperature trend.
This differing trend distinction can be more clearly seen in the graphs below where the NOAA Climate at a Glance website time period interval is broken into the time intervals from 1895 to 1950 and 1950 to 2024 (where the Tavg value is controlled by Tmin not Tmax) respectively as shown below.
This outcome is consistent with and reflects the results of Dr. Spencer’s recent study shown below and found here.
Dr. Spencer also provided another study which displayed in graphical form the UHI impacts of U.S. and Global wide temperatures during the period June 1850 through June 2023 as shown below and found here.
In addition to large population growth UHIs acting as a prime driver of rising calculated Tavg temperature outcomes, these temperature measurements are also being significantly impacted by NOAA’s improper siting of thousands of temperature measurement stations.
These thousands of improperly sited temperature measurement devices do not meet NOAA/NWS siting standards and are located far too close to artificial heat sinks that falsely increase both maximum and minimum temperature measurements as addressed in detail here with an example clearly illustrating this huge system wide measurement problem shown below.
As noted in this report (page 18) the year 2019 Oak Ridge National Laboratory measurement station data accuracy experiment showed that flawed station siting temperature measurement impact outcomes were much greater during the evening periods (heat sink contributions to minimum temperatures were a factor of 3 larger than maximum day temperature contributions) versus during the day.
NOAA bases its evaluation of U.S. and global average temperature anomaly value changes over time by using and comparing the calculated Tavg values over time.
As indicted by the temperature measurement graphs and studies noted above NOAA’s contiguous U.S. calculated Tavg increasing trend values since about 1985 are clearly driven upward by station measurement siting flaws and UHI Tmin outcomes versus Tmax measured outcomes.
This results in NOAA’s calculated Tavg assessments of increasing temperature anomalies over time being a flawed and exaggerated claim driven by NOAA’s measurement siting inadequacies and population growth driven UHI impacts – and not “climate change”.
This outcome is also applicable to NOAA’s global wide calculated Tavg temperature anomaly increasing trend assessments as well.
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Any reporting like this violates the Green Blob’s faith, and they are as blind to it as Young Earth Creationists or Marxist-Leninists are to anything causing them to possibly doubt their worldview.
“The minimum temperature trend outcomes after 1985 climb significantly faster than do the maximum measured temperature trend outcomes.”
I’d like to see some figures for that. I can’t check as the NOAA site is down, and it’s difficult to judge from the graphs, especially considering they have different scales. But there doesn’t seem to be much of a difference between max and min, let alone evidence of a significant difference.
It’s a pity Larry Hamlin didn’t click on the box to show the actual trend when creating the graphs.
LOL, you are way behind then since this has been known for years that minimum temperature increase is much more rapid than the Maximum temperature trends which is rising slowly.
Call me a sceptic, but when someone makes a claim I prefer it if they also supply the data. Handwaving about one trend being “significantly” different to another id much more persuasive if you actually supply the figures.
I suspect that minimums are rising faster than maximums, but it’s difficult to see how you can claim there’s a significant difference.
The same problem when you say “much more”. How much more?
My own experience is that whilst I would have expected mins to rise faster than maxes, as predicted, that doesn’t mean there is a huge difference. And in some cases it’s actually max that has been warming faster.
I’ll have to check the data when I have time, but the UK summer figures were showing a faster rate of warming than minimums.
No sir! there was no such prediction as YOU claim made which actually hurts the AGW conjecture because CO2 doesn’t deviate from his absorption and release effects on the heat budget which is negligible at the 350 plus level thus couldn’t be causing such a one-sided warming trend for many years now.
Yet we were told by the Met Office that May 2024 was the warmest May ever based on the minimum temperatures!
Which is one half of the average.
FYI: Tave = Tmin+Tmax/2
So in your mind Tmins don’t qualify?
In that case please give us the average temp for the UK in May 2024.
Tmax is from a sinusoidal daytime distribution. Tmin is from an exponential decay nighttime distribution. The two together do *NOT* generate an “average” value. It generates a mid-point value. Calling it an “average” means climate science is assuming the daily temperature distribution is a symmetrical Gaussian distribution. Assuming random, Gaussian distributions for *everything* is endemic in climate science when in the physical world we live in it just doesn’t happen very often.
Thank you. Your explanation is much more concise than the ones I have made in the past.
In May 2024 mins were relatively warm due to it being cloudy. But maxes were also quite warm. TMin was a record by some way, TMax was equal warmest.
But none of this has anything to do with my point, which was that Summer trends since 1985 are warming faster for max than for min.
Here’s the actual figures for the trend in summer temperatures 1985 – 2024:
TMAX: +0.37 ± 0.23°C / decade
TMIN: +0.29 ± 0.12°C / decade
Still trying to find a copy of the NOAA data. But there is the BEST regional data for max and min averages. This isn’t a good comparison with NOAA as it’s covering all of the USA, and I suspect including Alaska will make a difference, and it only goes up to 2013.
But for the record the trends in summer maximum and minimum temperature for 1985 – 2013 are
TMAX: 0.31 ± 0.22°C / decade
TMIN: 0.29 ± 0.14°C / decade
The difference is definitely not significant.
Source for the data:
https://berkeleyearth.org/temperature-region/united-states
I’m surprised this article uses 1985 as a start point. You get a much better argument if you start earlier.
Trends 1950 – 2013
TMAX: 0.11 ± 0.06°C / decade
TMIN: 0.18 ± 0.04°C / decade
That difference does look significant. Here’s a graph showing the difference between TMAX and TMIN for each summer.
Just found a copy of the NOAA data, from
https://climatereanalyzer.org/clim/noaa-us-monthly/
This gives me the following trends for summer (JJA) 1985 – 2024
TMAX: 0.30 ± 0.16°C / decade
TMIN: 0.33 ± 0.10°C / decade
So minimums have warmed about 10% more than maximums. Not sure I’d say this was a significant difference in any sense of the word. It amounts to a total difference over the 40 year period, of about 0.1°C
The trend in the diurnal range over this period is
-0.03 ± 0.10°C / decade.
“So minimums have warmed about 10% more than maximums. Not sure I’d say this was a significant difference in any sense of the word. It amounts to a total difference over the 40 year period, of about 0.1°C”
10% is typically considered to be a significant factor in physical processes.
relative uncertainties
Tmax .22/.31 ==> 71%
Tmin .14/.29 ==> 48%
A relative uncertainty in double digits, let alone 50% or more, is a sure-fire tip-off that something is wrong with the analysis. Typiically the data set has such a wide variance that the uncertainty of the “average” is huge.
Yes, that’s the point. The uncertainties if the trend do not allow the claim that mins ate warming significantly faster than maxs. You need a longer time frame to establish this, giving you are only looking at highly variable US summer temperatures.
But the relative uncertainties are not the issue. By that logic the uncertainty of the pause would be infinite.
Wrong. The uncertainties of the trend are the residuals between the trend line and the assumed 100% accurate stated values of the data points. That has *NOTHING* to do with the measurement uncertainties of the data. What it shows is that the linear regression fit is POOR. It does not mean that minimum temps are not increasing more than maximum temps. As I said, the relative uncertainties are a sure-fire tip off the analysis has something wrong with it.
An integrative degree-day analysis of the min-max temperatures probably would not get such a poor fit of the trend line.
“Wrong.”
Yes, he is. I’ve tried to explain this several times before, but he’s unwilling on incapable of accepting he’s wrong about anything.
The residuals are not the uncertainty of the trend. What I think he’s trying to describe is the prediction interval of the trend. That’s describing the range of likely values for a given independent variable (time in this case). But that’s not the uncertainty of the trend – that’s given by the confidence interval for the trend, and that also depends on the sample size.
“It does not mean that minimum temps are not increasing more than maximum temps.”
With no significant difference between the trends, the maximums may be warming faster, minimums may be warming faster, or they may both be the same. What it’s telling you is you do not have enough evidence to say with confidence which is the case.
“As I said, the relative uncertainties are a sure-fire tip off the analysis has something wrong with it.”
Wrong, there’s nothing wrong with the analysis, it’s doing what you want – warning you that you cannot make an assumption as to which is warming faster.
“An integrative degree-day analysis of the min-max temperatures probably would not get such a poor fit of the trend line.”
Yet you won’t test that for yourself.
I*’d be surprised if that was true because a degree-day analysis is removing data, so is likely to have larger variation, and hence more uncertainty in the trend.
The data is there for you to see, you just don’t want to recognize it. The trend is not important, what is important is the difference between the increase in min and the increase in max which is significant.
“The trend is not important, what is important is the difference between the increase in min and the increase in max which is significant.”
How do you know which is increasing faster, if you ignore the trend?
It is a pity that you refuse to see something that is staring you in the face
Trends coming from URBAN WARMING
Difficult for a bellend to comprehend, because its little mind is focused on the FALLACY of CO2 warming.
How many graphs have I shown you graphs that verifies this? Your claim of not knowing so you need to see some figures is an excuse just like the current Biden/Harris uses to pardon itself for not doing what is right.
If you would do proper research, you would already know this. How many times on WUWT have Tim, and I, and others told you that minimum temperatures drive the increase in Tavg? Tavg is a misnomer to begin with. It is not an average. At best it is a midrange between two different functions, daytime and nighttime. You have no excuse for not knowing this other than blind faith is CO2 caused warming.
This same site from NOAA also shows that winter time temperatures are warming much faster than summer time temperatures. It hasn’t been 60 days since I showed you that with graphs from this NOAA site. Here is just one.
Look at the cooling of minimum monthly temps from 1935 to 1980. Then look at the warming of minimum monthly temps from 1985 to current. CO2 simply can’t explain these trends.
Anomalies are even worse because of the ignored measurement uncertainty accumulated during its calculation. Basically, anomalies based on Tavg are unreliable because they are far, far covered by measurement uncertainty. You wouldn’t be allowed to take medicine where the efficacy was so small and uncertainty so large.
I would love to have time to create a set of histograms for the NOAA data. I have no doubt that it will show the combined data to be a multi-modal distribution. Meaning the “average” of the data would be no more useful than the “average” of the heights of Shetland ponies and Arabians.
I find the tave = (tmax-tmin)/2 to be fundamentally wrong.
Even an average of 1 hour temperatures over a 24 hour period, although better, suffers from quantization error.
That’s why an integration of the entire daily temperature curve (a DegreeDay value) would be far better for climate science to use. It has been possible to get 1 minute data from automated temp measurement stations for 40 years. That would greatly decrease the quantization error.
The maximum point of a sinusoidal daytime curve combined with the minimum point of an exponential decay nighttime curve is *NOT* an average, it is a mid-point and tells you almost nothing about what is happening with the daily temperature curve.
Science is not done by graphics.
Science is done by data, hypothesis, nul testing, experimentation, and, yes, modelling.
Pretty pictures are nice for those who are not into science in depth.
Yet one must start somewhere when examining data. The graph I show illustrates that maximum monthly temps in summer are not rising significantly. This is from CRN data, I didn’t make it up. However, it also shows that minimum monthly temps in winter have been rising significantly.
This is evidence of something changing. What is changing? This is where I began investigating Tmax and Tmin individually.
It doesn’t take long before the question arises as to the effect of Tmax and Tmin on the average. Lots of good info comes about. Tmin is the dominant factor in many places. Summer has a smaller variance than winter.
Here is a graphic that illustrates the issue. Have any of the warmists here ever done the work to see this?
Jim,
My comment to you was in no way meant to be disrespectful of your analysis or presentation.
It only made the point that a picture is worth a thousand words to those who do not have a thousand words.
Which is exactly why Ornithologists discovered El Nino Southern Oscillations and not weather scientists.
Amazing how you are so willing to accept things you want to believe, and then attack people for asking for evidence.
If you think that max US temperatures have warmed significantly faster than minimum since 1985 you should have no problem quantifying it. As I said, there’s a simple check box on the NOAA graph. Thefact that you are unwilling to provide the data suggests that whilst it is probably true that mins have warmed slightly faster, the difference isn’t that great.
But inevitably, rather than justify that claim, you switch to something completely different, changes up to 1980 in one city.
Maybe you should post the quote where I said Tmax has warmed significantly faster than Tmin. Here is what I said.
It was a quote from the article – I quoted it in my first comment. If you don’t agree with what the article says, why are you attacking me for asking for evidence?
But what you actually said in your opening sentence was “How many graphs have I shown you graphs that verifies this?”. So what were you verifying if not the claim in the article that said “The minimum temperature trend outcomes after 1985 climb significantly faster than do the maximum measured temperature trend outcomes.”?
You have a valid point.
For we, who are pragmatic and skeptical, joining a bandwagon to deny climate change does not facilitate cancelling the climate alarmists claims effectively. We need the data, the equations, the assumptions, and not just pretty pictures.
That said, when presenting a summary report, one has to be judicious in the content to ensure a decent signal to noise ratio that allows the message to convey to the reader.
Urban heat island are massive heat sinks and the energy sequestered during the day is released at night raising night time temperatures. This is strikingly similar to the effect of 71% of the planetary surface being water, much of which is deep enough that the optical depth for sunlight never reaches the bottom.
In addition to the heat sinking is the expansion of surface area. Consider a cube 1 meter per side. The footprint is the 1 m^2, but the area is 5 m^2, which means it affects the atmosphere much more that a 1 m^2 slab of sidewalk concrete.
You only have to walk or run your golf cart near a building in an Arizona summer evening after the sun goes down to figure that on out. I noticeable warmer near the building. The Early human settlers here in the Southwest US and I assume other places made checker patterns in their clay pots so the they would heat up faster. More surface area more heat absorption also means more heat stored.
I have. In New Mexico on multiple occasions.
Below are charts of the annual averages of Tmax and Tmin for 2007 — the first year the USCRN system had at least 114 stations. I used only the stations in the contiguous US states.
I used actual averages of the data, and not anomalies, as I think all of the averaging that goes into the anomalies hides important information.
https://drive.google.com/file/d/19sTmi3b2pFbg5WQHh8QhE72ryTjRAMlW/view?usp=drive_link
Just looking at the slopes of the two regression lines, Tmin is ~85% higher than Tmax. Almost double. That would lead a normal person to say that Tmin growth is what raises the Tavg figure the most, not Tmax.
Hiding information! No doubt. Standard statistics practice is that variances add when adding or subtracting means of random variables. That leads one to add the variance of a monthly average to the variance of the baseline average using root-sum-square. Consequently, the anomaly would have a substantial uncertainty. Instead, climate science finds the variance of the small anomaly numbers and calls that the uncertainty. In other words, the variance of the actual measurements is zeroed out thereby pretending they are 100% accurate.
But that’s a much shorter period with much larger uncertainties. I doubt you can even establish the individual trends are significantly positive, despite the rate of warming being huge.
But if it does turn out to be the case that CRN mins are warming faster than maxs, that undermines the claim that this is a result of UHI, given that CRN stations are placed to avoid urban effects.
Huh? CRN going up does *NOT* mean that UHI is not affecting the GAT since the GAT doesn’t depend solely on CRN stations!
It must be nice to have the books cook themselves (yes, Virginia, that is /sarc). Still, there is ample evidence of additional data manipulation in the alarmist’s modeling camp.
One might wonder about effects of urban and industrial waste heat on the overnight lows as well as the daily highs. After all, if we are concerned with average temperatures, the bottom matters as much as the top. Humidity is probably of interest, too.
One might also consider the design of an ideal weather instrument station, and calibration of the existing sensor network to the new standard… or, at least, a calibration to current satellite data to estimate the system error.
I once went to the site of a weather station that had both a Stevenson screen and an electronic temperature sensor within a few feet of each other. It was in a power station switchyard with massive transformers! It is a very convenient way to manually measure temperatures in the Stevenson screen because the power station is always staffed. And while I was there, they were installing a new, large transformer in the switchyard. I reported this to Anthony for his database.
So was this stevenson screen being used for a climate database?
Or was it (most likely) being used by those monitoring the power station.
Not all air temperature recordings are used for climate.
Waste heat is generally ignored by the Climate Syndicate.
I did a calculation a couple of years ago, using specific heat of air, and the published quantity of coal (total for the year) used for electricity generation including the efficiency of steam turbine generation.
Since electricity ultimately ends up as heat, the calculations simplified. The burning of coal, world wide, in that timeframe (2022, if memory serves) dumped enough waste heat to raise the air temperature from ground level to 105 feet by a full degree C.
Am I the only one that thinks this sounds confusing? Average temperature temperature. I also hate that nowhere does the author define what Tavg means. This is the first time I have seen this acronym. I have no idea why ‘average temperature’ isn’t avgT. Reading Tavg in the title I thought it was a typo. If you want to get more laypersons interested in weather and the geographical issues related to the measurement of weather perhaps explaining things would help.
I could use all sorts of terminology from the printing industry, computer drafting, and the fire alarm industry and confuse a great many people if I didn’t make sure they knew what I was talking about.
Yes.
It would be much more accurate and informative if “average temperature” was just referred to by its realistic term –
“bullshit”
Every technical discipline has its own argot and nomenclature. My experience in physical sciences and engineering have found Tavg to be the normal way to abbreviate Temperature-average. But it would be very useful in any technical discussion to remember what we were taught in the first year of engineering school – any time you introduce a new acronym or abbreviation, spell it out first, then give the acronym or abbreviation in parentheses. This isn’t a new concept – I was taught this way of doing things well over 50 years ago.
“This isn’t a new concept”
That’s right, and spelling out an abreviation first is meant to avoid the confusion that Ben feels over this issue.
Every writer needs to keep in mind who the readers are. Some are knowedgeable about the subject and some are not. The ones who are not need a little bit of extra explantion to get up to speed.
I have to do it daily with every document and presentation I create and have been doing so for 50 years.
His comment was not on Tavg (my version is Tave) but rather the sentence conjunction of Tavg with temperature (Tavg temperature) which results in average temperature temperature.
About 28 words before the first graph , you will see it defined.
As to which way round Tavg is written, then chase up the climate alarmist who are in control of ALL of this stuff.
Read more.
> I have no idea why ‘average temperature’ isn’t avgT
Tavg, Tmin, Tmax and similar constructs are very common in scientific, engineering, mathematical fields.
Unit followed by type is a standard convention in just about every where you have a specific unit of measure which is qualified by type:
e.g.
“V speeds” in aviation: https://en.wikipedia.org/wiki/V_speeds
Electrical calculations Vac, Vdc, Vrms
and countless other similar constructs.
Whoever was responsible for generating the graph doesn’t understand significant digits in axis tick mark labels.
That depends. If the NOAA data has that precision, using that precision on the graph is permitted.
However, it is a point of discussion that perhaps NOAA data has precision not supported by scientific notation.
They do not have that precision for most of the temperature record.
For ASOS
For CRN
Now imagine what LIG resolution and uncertainty really was. The best resolution would be ±1°F and uncertainty of ±2°F.
Thank you. I did not have the time to research the point.
Traditionally, thermometers were read at least twice a day to obtain Tmax and Tmin temperatures. It was easy to miss the actual highest and lowest temperatures. These were then averaged to calculate Tavg.
When individual Tmax and Tmin thermometers were introduced they could actually store the true Tmax and Tmin temps. The tradition of Tavg was kept alive by continuing the (Tmax + Tmin)/2 = Tavg calculation.
With the advent of automated stations providing temperature data at least every five minutes, NOAA now provides an integrated(?) Tavg for the whole day. The problems are that this figure is not comparable to traditional calculations and it is still averaging two separate functions, i.e., daytime and nighttime.
Wouldn’t they have used max and min thermometers which logged the temperature extremes?
The time of observation bias (TOB) seemed to come into play in the US because they switched from 7am readings to 3pm readings, neither of which is much use in attributing max or min to the correct day.
Starting about 1850, single thermometers were used for official measurements. Starting about 1885, min/max LIG thermometers were being deployed. About 1980, electronic min/max were deployed.
This paper by Dr. Pat Frank is an excellent summary of thermometer uncertainty.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346593/#:~:text=The%20plots%20terminate%20at%201980%20because
Tave is better expressed as T[subscript ave].
Unfortunately, there are reason unrelated to “climate” why temperatures are wanted in the vicinity of urban areas and airports. The use of these measurements to push an agenda to remake the world is seriously wrong.
It also allows politicians and others to blame problems on CO2 rather than confront the issues directly. Example: Washington State’s “Climate fees” are being used to support many things that will do the opposite if that intended. Here is one: Clean Energy Credits for Washington Families Grant Program – – Each “qualified” person or family gets a credit ($200 for a single, and more) on their utility bill. This might allow a family to set the thermostat up a degree or two, use more energy, and produce more CO2.
Master BS artist Hamlin piles it high and deep yet again
Every US and global average temperature shows accelerating warming since 1975
Thos who want to blame UHI can look at USCRN’s rural average or the UAH ocean average. No UHI in either of those. But there is plenty of warming.
UAH Global
Last 10 years: +0.41 C.decade-1
Last 15 years: +0.39 C.decade-1
Last 20 years: +0.30 C.decade-1
Last 25 years: +0.23 C.decade-1
Last 30 years: +0.17 C.decade-1
Remember that global inclues 70% oceans with no UHI.
According to the Global Rural Urban Mapping Project (GRUMP), approximately 3% of the Earth’s land surface is considered urbanized.
According to the most recent data, approximately 3% of the US land surface is considered urban, meaning that urban areas cover around 3% of the total land area in the United States.
Larry Hamlin is perpetually confused.
He’s a leftist fact checker’s dream
So you’re saying the 150-year-old global temperature record is fake as we’ve been unable to measure the temperature of the oceans, and indeed much of the land, until the satellite era.
Not fake, but useless.
GAT before satellites is unreliable data. Before 1900 is worthless data. Since most warming was after 1975, the UAH average from 1979 is useful for land and oceans.
However, I don’t need any numbers to report that SE Michigan suburbs winters are warmer than in the late 1970s with FAR less snow.
“SE Michigan suburbs”
You mean a large expanding URBAN area !!
For Google-fatigued readers:
Population Michigan 1975: 9.12M
Population Michigan 2022: 10.03M
Growth rate about 0.2%/year
“Since most warming was after 1975,”
The warming in the 1930’s was equivalent to the current warming.
The climate warms for a few decades and then it cools for a few decades and then the cycle repeats, as can be seen in the charts presented in this article. Your concept that the warming has been continuous since the end of the Little Ice Age is wrong. The temperature data mannipulators have confused you with their bogus “hotter and hotter” Hockey Stick charts.
There is no evidence CO2 has any discernable effect on the Earth’s atmosphere.
Yes, Climate Alarmists have no idea what the temperatures of the oceans were before World War II.
Phil Jones himself, the chief bastardizer of the historical temperature record, said the ocean temperatures he was using were just a guess.
And where are the temperature-reporting stations? In cities and at airports?
Irrelevant post
Oh look, more smug-mug RGBS..
STILL doesn’t comprehend the basis of URBAN warming
STILL doesn’t have any empirical scientific evidence of warming by atmospheric CO2
STILL cannot show us any human caused warming in the UAH data.
STILL in rabid DENIAL of the El Nino warming events that comprises all of the warming in UAH and the bulge around 2016 in USCRN
STILL cannot show any human causality whatsoever except his lack of comprehension of urban warming effects.
Now he calls himself a “leftist factchecker”…
and like any leftist factchecker, every “fact” he puts forward is based on scientific ignorance.
Be fair, RG maybe a leftist fact-checker, but he didn’t actually claim to be one; he said …
“Larry Hamlin is perpetually confused.
He’s a leftist fact checker’s dream”
Even though Larry is correct.
If it quacks like a duck….. !!
Nutter Bnasty who believes all global warming is caused by El Ninos, is perpetually confused
The last El Nino ended in May 2024 (It’s now October 2024 … IN CASE YOU ARE CONFUSED BY THE CALENDAR), yet the GAT is still high.
Go back to the drawing board to invent another crackpot theory Mr. Nasty.
Where I grew up was mostly farm land, Today? Blacktops, Rooftops and black rubber roofs. Population grew exponentially. Urban sprawl indeed.
Poor RG,
STILL hasn’t realised that the energy from the El Nino has dissipated yet.
STILL doesn’t understand that the ENSO 34 region is just a surface indicator.
Poor muppet must have some imaginary fantasy of what is retaining the energy in the atmosphere.
Maybe he can see CO2 like his darling Greta?
Again. show us the NON-El Nino warming in the UAH data.
Show us the empirical scientific evidence of warming by atmospheric CO2
.. or continue to show yourself as a complete and nutter failure.
” approximately 3% of the Earth’s land surface is considered urbanized.”
oh dearie me..
STILL hasn’t figured out that after homogenisation, URBAN warming accounts for a large part of the warming in the surface data fabrications
“No UHI in either of those..”
He does get something right.. accidentally.
There is no sign of any human caused warming in the UAH ocean data.
No warming from 1980-1997.. Then the 1998 El Nino
No warming from 2002-2015.. Then the 2016 El Nino
COOLING from 2017 to start of 2023 El Nino.
Larry is absolutely CORRECT…
… and, as usual, RG is absolutely WRONG.
As I recall, Tom Karl decided to use sea temperatures from the cooling water manifold of ocean-going ships as the data of record. He decided not to use the temperatures from buckets that were thrown overboard and then measured.
I doubt the temperatures were measured from the output manifold after cooling the engine/boiler but we all know pumping adds heat to the fluid and it can also absorb heat from the manifold metal even on the intake.
There’s your seawater UHI.
Tricks like that eventually flatten out over time. That’s why I like satellites. The raw data might or might not be accurate but it’s really f-in hard for anyone to monkey with the hardware so error should stay about the same.
Ah, Richard.
Once again, while you may be presenting a valid point, you starting with an insult cancels your whole post. Moving on.
And the southern hemisphere is about 80% ocean, 10% population. So any manmade co2 or UHI effect is not really global.
Ocean, I agree CO2 doesn’t warm. UHI though, is global from the standpoint that weather stations are quite likely to be situated in or near to populations. Consequently there will be a contribution to GAT wherever it may originate.
This report alone overshadows anything the CAGW crowd has. The CAGW, Net Zero, abandon fossil fuel scheme is nothing but a political power grab. It has to end.
In addition it is fairly well established that the other contributor to higher night time temperatures is cloud cover or in fact aircraft contrails.
Perhaps we should ground all aircraft to stop ‘climate change’
Here is something I concocted for a joke 14 years ago…
I started and never finished a similar chart of population growth versus temperature and another of energy production versus temperature.
If one scales things to fit an idea, one can show a co-relationship that absolutely “proves” causation.
This fellow has done a bunch of work using Brightness Index from satellites and some other population data to show that not even CRN stations are totally immune to UHI.
His X id is @Orwell2022.
I may as well get the fun going and get the conspiracy theorists hot under the collar with the inconvenient truth ….
“As indicted by the temperature measurement graphs and studies noted above NOAA’s contiguous U.S. calculated Tavg increasing trend values since about 1985 are clearly driven upward by station measurement siting flaws and UHI Tmin outcomes versus Tmax measured outcomes.
Err no.
(except that minima are expected (and are seen to) rise more than maxes as mins represent an area under a night-time inversion that involves no vertical mixing (in radiation night conditions ie no wind/cloud). Maxes involve vertical mixing as thermals rise. And no – extreme maxes will occur as hot desert air that has stagnated under a heat-dome is advected into more temperate latitudes.
https://journals.ametsoc.org/view/journals/bams/94/4/bams-d-12-00170.1.xml
The (USCRN) network consists of 114 sites across the conterminous 48 states, with additional sites in Alaska and Hawaii. Stations are installed in open (where possible), rural sites very likely to have stable land-cover/use conditions for several decades to come. At each site a suite of meteorological parameters are monitored, including triple redundancy for the primary air temperature and precipitation variables and for soil moisture/temperature. Instrumentation is regularly calibrated to National Institute for Standards and Technology (NIST) standards and maintained by a staff of expert engineers. This attention to detail in USCRN is intended to ensure the creation of an unimpeachable record of changes in surface climate over the United States for decades to come.
And for the last 19 years this UHI-free network actually shows agreater warming trend than the (supposely UHI) corrupted one !
This statement is not made in the paper you referenced, so it your assertion alone. Show some reference that substantiates it. “no wind/cloud”, really?
Nighttime temperature minimums are basically held up based on dew point temperature. Why don’t you explain why dew point temperatures have been rising?
As to your graphs, show the uncertainty values for these anomalies. I suspect that if you do them correctly, you will find the error bars are at least ±0.3°C. Why? Because the uncertainty of single readings per NOAA is ±0.3°C for CRN stations. This doesn’t include the reproducibility uncertainty calculated from the standard deviation of the monthly values.
The whole trend you show in the bottom graph is within the uncertainty of ±0.3°C. That makes the trend statistically insignificant.
You should ask yourself why both “Degree C Anomaly w.r.t. 2005 – 2022” graphs have different anomaly values! That is a red flag of statistical mathterbation.
“This statement is not made in the paper you referenced, so it your assertion alone. Show some reference that substantiates it. “no wind/cloud”, really?”
The earth cools from it’s surface most strongly. It is a radiative cooling as air is an insulator. The radiative exchange with the radiative emission surface (the ground) in the lowest few feet has strongest cooling and the depth of that surface lyr is dependent on air movement (mixing of the colder surface air with warmer air just above). This forms a surface inversion (lower air movement/calm > lower inversion) and greater scope for the stevenson screen to report a lower minma. So we have a shallow lyr of air subject to a forcing – radiative cooling (in the absence of clouds).
Given greater GHGs present then that minima will not be as low.
Note: the GHGs could be WV – as the warmer temps overall can hold greater WV.
The vertical mixing of any extra maxima achieved should be intuitive in their smearing of the higher surface temp to higher layers under extra daytime mixing and convection.
Over the last century, daily minimum nighttime temperatures rose faster than daily maximum temperatures, in tandem with steadily rising greenhouse gas concentrations in the atmosphere. Davy et al., (2016) have observed diurnal asymmetry in the global warming trend: the nighttime temperatures have increased more rapidly than daytime temperatures. Davy et al., (2016) explained this diurnal asymmetry by the reciprocal relationship between boundary-layer depth and temperature response.
https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.4688
So insulators don’t warm! The earth does not warm the atmosphere through conduction and convection. Got it!
You are close here. Dew point is where water vapor condensed and release heat to the atmosphere thereby warming the atmosphere and stalling cooling.
Here is a paper that also posts that your “insulator” warms and convects the atmosphere using heat transfer other than radiation.
“So insulators don’t warm! The earth does not warm the atmosphere through conduction and convection. Got it!”
Ahem … the discussion is about night-time cooling – wake up.
Done (from the surface) entirely by radiation under light winds/calm conditions. (absence of mixing/convection)
“Dew point is where water vapor condensed and release heat to the atmosphere thereby warming the atmosphere and stalling cooling.”
Yes, released LH of condensation (shoud the air be moist enough) occurs but the main effect is from back-radiation from the fog with the ground heat flux overcoming the LWIR energy lost to space.
Why in freezing fog, the ground temp is above that of the air and may well not be icy.
Once the fog-point is reached and forms, the radiative cooling then takes place from the fog top. The fog insulates the ground from the sky.
https://www.slideshare.net/slideshow/night-time-cooling/41710668
If you want to know more just ask.
“Done (from the surface) entirely by radiation under light winds/calm conditions. (absence of mixing/convection)”
Really? You’ve never seen or heard of a thunderstorm happening at night? That’s an indication that convection/mixing *does* occur at night, it just isn’t usually large enough to generate large storms.
Take a look at this file for the past 24 hours. Winds at night were *not* zero all night. So some convection/mixing was occurring.
“Really? You’ve never seen or heard of a thunderstorm happening at night? That’s an indication that convection/mixing *does* occur at night, it just isn’t usually large enough to generate large storms.”
Look, Mr Gorman:
I am a retired professional meteorologist.
Of course I “have heard of thunderstorms at night”
Try comprehending what I have written.
So you are omniscient, right?
Warmests have all the answers and the science is settled!
Glad to have you out there to tell all us unbelievers that anthropogenic CO2 is the devil incarnate.
Maybe you can show equations explaining why so many location on the globe are not being warmed by CO2. The Great Plains of the U.S. for example
What you have written is WRONG. It doesn’t matter what your profession was or is. Wind at night indicates convection and mixing is occurring. Radiation is *NOT* the only heat loss mechanism.
BTW, in your reply using a refrigerator – the cooling agent is usually *NOT* at the bottom of the refrigerator, the compressor is. The compression generates heat AT THE BOTTOM of the refrigerator so you get warm air at the bottom. That causes cold air to fall from the top and warm air to rise from the bottom – thus generating convection and mixing inside the refrigerator.
Absence of mixing/convection? You have sucked up the propaganda from CO2 warmists hook line and sinker about radiation being the only method of heat transfer.
I notice you never addressed the question of insulators not warming. Why is that? It is a crucial part of the earth/atmosphere heat transfer process.
God you are hard work !
Look, I am giving you the dynamics of meteorology.
I do not bear responsibility for your inability to understand.
It’s the same effect as cooling in a refrigerator.
( given that the cooling agent is on the bottom surface)
The air is cooled, it becomes denser.
It therefore lies at the bottom and its depth thickens with further cooling
NB: There is no mixing or convection (you do know what causes convection?) within the body of the fridge – I ask because you show precious little evidence that gives me confidence you do.
Of course it’s “not the only method of heat transfer”.
It’s just the one that causes night-time cooling under radiation conditions – hence the name “radiative cooling”. And radiation fog.
Insulators cause warming, as you well know, via reducing the heat/radiative flux through them. Be it warm air in clothing or LWIR in the case of GHGs.
In the case of radiative cooling over land the air does not cool and thicken because of conduction upwards. Because air is an insulator for conduction. The conduction is small and downwards into the ground.
Finally, As I have said before on a previous threads (or maybe the other Gorman). That is enough for me of you drawing me down into a rabbit hole.
IIRC, NOAA uses USCRN data to adjust ClimDiv data.
“I may as well get the fun going and get the conspiracy theorists hot under the collar with the inconvenient truth ….”
Mission accomplished
OMG you really are totally clueless, aren’t you.
This is not a difference from actual measurements.
ClimDiv is actually “ADJUSTED” data with the urban signal removed by homogenising to more “pristine” sites (on a regional basis).. They actually describe the process on their web site.
The trend difference is nothing to do with real data,
… but to do with the fact that they have refined their homogenisation parameters over time.
They have got better at matching ClimDiv to USCRN.
“I may as well get the fun going and get the conspiracy theorists hot under the collar with the inconvenient truth ….”
Mission accomplished
How many times do we have to say that trend plots do not prove causation esp. in systems with complex atmospheric multivariable interrelated systems.
Coupled chaotic systems.
I think Glen’s Ferry is in Idaho not Oregon.
Close enough for government work
Anecdotal, but I will share it. In the summer it was a consistent 6 to 7 degree F temp change driving less than 2 miles between an old mill town in suburban Boston and my very leafy semi-rural suburb. With the growth of the exurbs transitioning from pasture and farms to cement all over the US I don’t see how a significant portion of weather stations could not be impacted.
I once had a copy of a paper analyzing 20th century temp trends in rural vs now-urban counties in California that dramatically documented this phenomena. I can’t find it anymore on the Internet, but it was a paper that SEPP referred to in some of their earlier reports.