From NOT A LOTOF PEOPLE KNOW THAT
By Paul Homewood
Nice summary by Richard Lindzen:
We are generally told that the following defines ‘climate’…
Figure 1 Global average temperature anomaly.
Actually, we are not looking at ‘average temperature’. Averaging Mt. Everest and the Dead Sea makes no sense. Instead, we average what is called the temperature anomaly. We average the deviations from a 30-year mean. The figure shows an increase of a bit more than 1°C over 175 years. We are told by international bureaucrats that when this reaches 1.5°C, we are doomed. In all fairness, even the science report of the UN’s IPCC (i.e. the WG1 report) and the US National Assessments never make this claim. The political claims are simply meant to frighten the public into compliance with absurd policies. It remains a puzzle to me why the public should be frightened of a warming that is smaller than the temperature change we normally experience between breakfast and lunch.
My puzzlement becomes clearer when one includes the data points in Figure 1, as shown in Figure 2. This was first noted by Stanley Grotch, and updated by John Christy and I).
Figure 2 Temperature anomalies at individual stations as well as the mean.
We see that the data points are spread pretty densely over a range of about 16°C – over an order of magnitude greater than the range of the mean. The change in Figure 1 looks big simply because the data points are left out and the scale is expanded by over an order of magnitude.
What exactly does this say about climate? In point of fact, the Earth has dozens of different climate regimes. This is shown in Figure 3 showing the Koppen climate classification for the period 1901-2010. Each of these represents different interactions with their environments. Are we really supposed to think that each of these regimes responds in lock-step with the global mean temperature anomaly? On the contrary, Figure 2 tells us that at any given time, there are almost as many stations cooling as are warming.
Figure 3 Koppen climate classification.
Of course, the notion that global average temperature anomaly constitutes ‘climate’ is attractive due to its simplicity.
Unfortunately, that doesn’t mean that it is correct.
https://www.netzerowatch.com/all-news/what-is-climate?mc_cid=6084154d58&mc_eid=4961da7cb1
I was particularly intrigued with Figure 2:
I know it’s only eyeballing, but if you back to 1980, there appears to be little increase in the positive anomalies, but there is a noticeable reduction in negative ones. It is something I have often seen in UK data, that average temperature rise is being driven by less extreme cold weather, rather than more extreme heat.
What is climate?
it’s bigger than your government. It’s an unprecedented opportunity to line pocketses and control the little people.
On BBC radio they are discussing how many job losses are acceptable per a given metric of emissions reduction
“Any Questions – BBC R4”
This is the reality. Climate wasn’t even mentioned but net zero was front and centre
Climate, as defined by ClimateScientists™, is a generalized average of 30 years worth of weather.
Climate Change is, by that definition, ANY change in weather that differs from the 30 year average and doesn’t conform to the norm.
Further, by the same definition, climate without change is climate stagnation… a state of climate that will never exist
Why is Figure 1 preferred over Figure 2?
Because it serves The Narrative.
Figure 2 adds unwanted context.
Fig. 2 brilliantly shows that the 1.2 degrees warming over the last 120 years is minor compared to annual variation of the very same weather stations….therefore no crisis….
It’s risen twice that while I’ve enjoyed my coffee this morning, sitting under an electric blanket.
Exactly and frightens people into accepting absurd policies as the professor points out so eloquently. Politicians like cherry picked data that emphasizes the Mann hockey stick sign posted conclusion to net zero no matter what it costs.
Here, in a Cwa climate region near 36,-84, my weather station shows that the nighttime temperature and dew point are coupled. So my question is what’s driving the increase in humidity? Last weeks snow seems to have been Gulf of Mexico water. BTW, we had a temperature low of 6F, dew point low 4F. Both are higher now mid morning.
The dew point and relative humidity are closely related. As the temp approaches the dew point the relative humidity goes up (e.g. at night). As the temp gets further from the dew point the relative humidity goes down (e.g. during the day).
Dew point is a measure of how much water is in the air. The observation is that when nighttime time temperatures fall to the dew point then dew forms thus slowing the temperature drop, at 100% humidity. So higher dew point => higher nighttime low due to the energy release from condensation. When dew is forming then what does the temperature mean?
ni4et,
Has there been unusually wet weather recently?
Looking at your neck of the woods (East Tennessee) I don’t see a lot of evidence. The precipitation record for this day in January was set in 1883.
https://www.weather.gov/mrx/tysjanuary
To be a bit more rigorous, dew point is the measure of the partial pressure of water vapor. The relative humidity is the ambient partial pressure of water divided by the saturation vapor pressure of water for the ambient temperature. A quick rule of thumb is a 20ºF difference between air temperature and dew point corresponds to a 50% RH.
When the dew freezes this leads to a hoar frost , that can be quite spectacular requiring more latent heat absorption.
To oversimplify, water surfaces like the ocean “try” to saturate the air above to 100% Relative humidity by evaporation at that temperature. Drier air that has had the water rained out of it, descending from higher altitudes is going to mix and generally means that dew-point at ground level will be a few degrees lower than the actual temperature. If the ground for miles around is not rainfall “wet”, (say desert sand) then RH is going to be much less than 100% unless winds are carrying water vapor from elsewhere.
Air that has a certain RH, then is warmed up, will still have the same number of water molecules in it, but will have a lower Relative Humidity due to its increased temperature making it capable of holding more water molecules without condensing (if they were available from some liquid water somewhere).
To answer your question, at the average weather station, dewpoint will be a little lower than the actual temperature as long as water can condense forming dew, or re-evaporate off plants or soil in the morning….unless air of different temp or water content blows in….
Following is my Temp and dewpoint for the last 24. The “water” involved is half a foot of snow stretching miles in every direction…..maybe a Chinook tomorrow will make the graph deviate…
I guess I see your point now. As the air cools at night it approaches the dew point and will level off as condensation releases latent heat. If the low temperatures have been observed to be higher, is this due to higher dew points (higher humidity)? And if that is the explanation, what is making the air more humid?
Was that your point?
Yes, and if the “average’ temperature for the day is what’s being preached as the most important indicator of the state of climate my engineer’s brain leads me to think that not everything important is being reported.
Most days here as the sun sets the temperature will fall sharply until the dew point is reached and then T and DP will remain locked within a degree until the morning. Both continue to fall but much more slowly. The overnight temperature has a flat bottom compared to how fast it was falling when it reached the DP.
For me reporting that the overall temperature increase is due to rising nighttime temperatures and humidity seems to be factor affecting temperature then what is being measured? It sets off questions with me.
I have no doubt that everyone in the field understands this effect, and it may be self-canceling, I just haven’t seen a good explanation or justification for ignoring the odd flat bottom shape of overnight temperature curves.
Granted, too, a consumer grade weather station may be misleading.
“I know it’s only eyeballing, but if you back to 1980, there appears to be little increase in the positive anomalies, but there is a noticeable reduction in negative ones.”
Ifyou go back 35 years to the late 1980s, there’s little change in either one.
Interesting the shift is concurrent with electric temperature measurements.
Nice: – how many times does it need repeating: “Temperature is not climate”
Double whammy of nice:“there appears to be little increase in the positive anomalies, but there is a noticeable reduction in negative ones.
See what he’s saying there – he’s running a High Pass Filter.
He is actually looking for change and variability – rather than – a Low Pass Filter which destroys change & variability.
Now go and talk to any UK farmer and they will tell you the very real reality of that change of variability
The things that see late/hurried/rushed plantings, extremely ‘catchy’ harvests and increasingly: harvesting machines stuck in mires of mud, vast tonnages of produce lost in that mud and skyrocket prices for what they did mange to bring home
This points out another bit of nonsense. Assume the anomaly increase since 1800 is man-made. Why do we want the climate of the eighteenth century (1700s)? That was the tail end of the Little Ice Age, which spawned crop failures, famines, and disease outbreaks. Starvation was one of the primary drivers of the French Revolution. It seems to me that a 1.5 ℃ bump from the Little Ice Age, far from being some imagined catastrophe, would be a blessing.
The Earth is still in a 2+ million-years ice age named the Quaternary Glaciation, in a warmer, but still cold, interglacial period between very cold glacial periods.
Over 20 percent of the Earth’s land is frozen either as permafrost or underneath glaciers.
The ice age won’t officially end until the Earth is ice-free.
Yes and coupled with that observation I always ask, if it isn’t warming since the end of the period known as the L.I.A. then what do they think it should be doing?
Dr. Lindzen reports “..an increase of a bit more than 1°C over 175 years”. Thank you Dr. Lindzen. Next topic please. How about a daily discussion of why we should defund the IPCC and how we gain support for doing it.
You could start by electing Trump with a land slide
He would eliminate all of woke and RE wind/solar/battery/EV/battery, heat pump and cook stove BS, downsize the federal government and reduce the deficit and taxes and inflation, including energy prices.
This article takes on the Met Office and really nails them:
https://www.zerohedge.com/weather/was-2023-really-second-hottest-year-1884
Exeterapolation is all the rage and it’s a basic scientific no-no – unless its been modelled
Yooper – thanks.
Well worth reading, even if my Statistics aren’t up to the level of many contributors here.
One quote: –
The relative probabilities indicate how strongly the evidence from models and observations, taken together in our methodology, support alternative future climate outcomes. [. . .] The probabilities are conditioned on methodological choices and expert judgement. The results may change if a different methodology is used.
‘Evidence‘ from models ….
I translate that as
We make it up as we go merrily along.
YMMV, of course.
And, as I type this the UK is in the grip of an [obviously existential, like the last one, a fortnight ago] storm – Isha [IIRC] – with gusts here, inside the M25, of over 45 mph.
Yes, it’s worse in Wales – gusts there of 90 mph, up a mountain.
The BBC [of course] say
And carefully doesn’t say that that will be the norm in a couple of years!!!
And, on Thursday – cower you sheeple! – we expect Obscurely Average Morning Kinshara, with winds of 6 mph, gusting to 10 mph, about 50% cloud more or less, and temperatures of 7C [45F].
Tremble in your hovels, Unwanted Low-lifes!
Even forecasts for 12-24 hours ahead now seem to be ‘erring on the side of caution’.
The idea that the Met Office can accurately predict weather in the UK 7 days ahead is still a sad sick delusion.
And thirty years?
Nahhh!
Auto
Re: Fig 2
Variance of a Gaussian distribution is an indirect indicator of the certainty of the value of the average. See the attached photo. With the wide range of data values shown in Fig. 2 (which is used to calculate the variance) the variance of the distribution is high, meaning that the certainty of the value of the GAT is low.
I believe this is one reason that climate science is so adamant about not using the variance of measurement data as the required partner for making sense of an average. Every statistics textbook I have collected over the years say you *must* have both the average and the variance to understand a Gaussian distribution. If the distribution is not Gaussian then you must use a different set of statistical descriptors such as the 5-number descriptor.
As you add random variables into your data set the variance increases, e.g. combining Southern Hemisphere temperature data with Northern Hemisphere data. This happens whether you use absolute temps or anomalies since anomalies inherit the variances of the components used to find the anomalies. Var(X+Y) = Var(X-Y) = Var(X) + Var(Y).
There *is* a reason why climate science ignores variances in their statistical analyses and try to get by using only the average. That way they can pretend their averages are 100% accurate and therefore their anomalies are 100% accurate. In fact, I’ve never seen a climate science paper analyze whether the various temperature data sets are even Gaussian at all! My guess is that they are multi-modal (e.g. SH vs NH would be just like the heights of Shetland ponies combined with the heights of quarter horses) meaning the average is pretty much meaningless in physical terms.
I think it is worse than you point out. Time series data should be analyzed using the robust techniques of time series analysis. Temperature data is seasonal. The first step is to deseasonalized by taking the 12th difference. Yes, you lose the first 12 months of data, but at least there is intellectual rigor in this approach. Once you deseasonalize, the next step is to test for stationarity. The whole anomaly approach is just not right. Each station should be analyzed. There is no need to grid-scale the data.
It’s even worse than you describe. You get different variances for December in the SH than in the NH even if you do the differencing. So how do you average the two averages appropriately?
This doesn’t even begin to address how you can “average” a daytime sinusoidal temp distribution with a nighttime exponential decay distribution and get a meaningful average. What you get is a median value of a multi-modal distribution which tells you nothing about the distribution at all. And then climate science just ignores the variance of that multi-modal distribution! That’s why Las Vegas and Miami can have the same median temperature with vastly different climates. What good is a metric for climate that can’t distinguish between different climates? Deseasonalizing doesn’t help at all!
‘Every statistics textbook I have collected over the years say you *must* have both the average and the variance to understand a Gaussian distribution.’
And if you don’t ‘know’ your distribution is Gaussian, you need to speak with Mr. Chebyshev before making any inferences from your data.
I suspect the anomaly clean-up team will be by to discuss this shortly.
Nah! They have no answers so they’ll just ignore it all. Just like they do variance of a distribution.
Fig 14 in here is Gaussian flavor: https://journals.ametsoc.org/view/journals/mwre/115/1/1520-0493_1987_115_0317_tgcfmc_2_0_co_2.xml
Paper is from 1987 when climate “science” was a data driven endeavor, as opposed to a “modelling” facade
I quickly read the paper you referenced and didn’t see where it really addressed measurement uncertainty or the variance in temperature averages.
There is no one mention of the words “uncertainty”, “variance”, or “confidence”. As usual, it assumes all stated values are 100% accurate with no uncertainty or variance.
Temperature change from breakfast to lunch.
No, it’s the temperature change while drinking my morning coffee. That one degree is brutal. /sarc
Coffee drinkers understand.
From the top of a tall building to the street level, same deal.
Figure 1 looks to this layperson as a 1C increase over the last 100 years. Is there an increase over the prior 75 years?
Not relevant, since the 1950s are generally regarded as when most of the CO2 was emitted. Therefore any warming before that is bad for the narrative. That’s why M.Mann produced his ‘hockey stick’ graph which removed the 1930s warming, and all the climate optima that produced the golden ages of history..
In the United States there has been no increase in temperatures since the 1930’s:
Hansen 1999:
In the United States, the year 1934 was 0.5C warmer than the year 1998 (according to James Hansen of NASA), and 0.4C warmer than 2016, and 0.2C warmer than the latest temperature spike in 2023.
The bogus, computer-generated Hockey Stick chart in Figure 1 does not represent reality. It is a device meant to scare people and promote CO2-phobia.
Historical, written temperature records from all around the world resemble the temperature profile of the U.S. regional chart where the Early Twentieth Century is as warm as it is today. None of the historical, written temperature records have a Hockey Stick chart “hotter and hotter and hotter” temperature profile.
The bogus Hockey Stick chart in Figure 1 is a BIG LIE meant to fool people into submission.
Even figure 2 is not a climate parameter as it is a daily average of averages and a more useful analysis of climate change would be the 30 year rate of change of the yellow data points.
All I know is that here in Wokeachusetts- and nearby woke states- they constantly talk about “the climate emergency”- yet, I look around, and can’t find it! Yet, they seem to not mind the invasion of illegals.
Yes, I phoned our local City Council and asked what self-preservation measures we all needed to take to survive the “climate emergency” they had just declared.
Should we call 911?
I was threatened with police attendance for causing a public nuisance.
I replied that I was responding to an officially-declared public safety situation, and if that wasn’t real, then it was the City who were in fact causing a public nuisance.
They declined any further discussions.
Hmmmm… my typical Council-
Climate Action | City of Holdfast Bay
Council Climate ActionWe recognise that the world is in a state of climate emergency and that all levels of Government have a responsibility to act.
Yada yada but then this-
Urban HeatAn urban heat island is a hotspot in an urban area that is significantly warmer than its surrounding areas. They occur because has been replaced the natural land cover with dense concentrations of pavement, buildings, roads, etc. absorb and trap heat. This trapped heat is then radiated into the surrounding area, including inside living spaces. These hotspots are particularly noticeable if the area does not cool down to comfortable levels at night, which is important for good health.
Well that explains it and forget the windmills solar panels and batteries for 1.5C-
Climate change: Ditching dark roofs in Sydney will reduce temperatures, UNSW study finds (smh.com.au)
Join the white paint movement!
What an excellent observation. And how many $billions has the United States spent on Climate Change over the last 40+ years and how much on controlling illegal immigration?
No doubt many political fence sitters are going to vote for Trump over the net zero and illegal immigrant situations.
The US drug laws is what is causing the increase in illegal immigration to the US.
The US drug laws have made the price of opioids so high that it is profitable to make it illegally in South and Central American countries causing drug cartels to exist and control vast regions of the country causing people to flee for their lives from those areas to the US as illegal immigrants.
We could bring back some of the factories that were moved to China and place them in Mexico or another friendly country to employ the immigrants and make just as much money.
The US drug laws are what is causing the increase in illegal immigration to the US.
The US drug laws have made the price of opioids so high that it is profitable to make it illegally in South and Central American countries causing drug cartels to exist and control vast regions of the country causing people to flee for their lives from those areas to the US as illegal immigrants.
The high prices also are what is causing people to have to inject it and that is what is causing around 100,000 opioid overdose deaths in the US per year.
Before aspirin was invented in 1897 everybody used opium and opiates for pain and there were no great numbers of deaths. In the US mortality and morbidity reports from the 1920s and 1930 when it was still legal there were only an average of 35 deaths opium and opiate deaths per year. That compares to around 3,000 deaths per year from alcohol.
The Best data is adjusted. Use unadjusted data and see what the charts look like.
They also use data that is from sites which are heavily affected by urban development and other human factors.
It would be a total fluke if they ended up with anything that remotely representative of “global temperatures” (whatever that means.)
Thank you again as ever Prof. Lindzen for your rationality.
The data provenance, mathematical and statistical shenanigans perpetrated by climate “scientists” are disgraceful.
I and others here must feel particularly exonerated by Prof Lindzen’s confirmation that there is no such thing as “global average temperature”, and also that there are many different “climates” around the world, and “averaging” their characteristics is arrant nonsense.
Ergo, getting all bent out of shape over “average temperature” constructs changes of hundredths of a degree C over decades is unalloyed irrationality on steroids.
Who, if anyone, has analyzed the temperature variations at the granularity of the Koppen climate classifications? Roy Spencer breaks out the monthly averages of the globe by hemisphere, tropic versus arctic, and US versus Australia. However, those are political boundaries and include several different Koppen climate classifications.
The satellite grid is too coarse to resolve the different climate zones.
Looking at Figure 3 in the article, it shows that some of the climate zones may be difficult to resolve properly with the spatial resolution of microwave sensors. However, mixed pixels are something that remote sensing scientists always live with. There are techniques that have been developed to try to unmix the pixels. But, even the UAH temperatures are the result of averaging different temperatures, especially in mountainous terrain. What that means is that the error bars are not going to be uniform for all zones. One approach would be to select large, homogeneous areas like the Outback in Australia, and the Sahara in Africa (e.g. BWh), as representative samples of what is happening within typical zones. As the saying goes, “One goes to war not with the weapons one would like to have, but the weapons that one does have.”
A similar issue with the NOAA satellites is the nonuniform grid areas, they are nearly 10x larger at the equator compared with the polar regions. This is caused by using constant lines of latitude. One result of this is grids that are both land and ocean.
FYI: Observed and projected changes in global climate zones based on Köppen climate classificationDiyang Cui, Shunlin Liang, Dongdong Wang
Wiley Interdisciplinary Reviews: Climate Change 12 (3), e701, 2021
Thank you for the citation. I haven’t thoroughly digested it yet, but I think that the thrust of this is to forecast how the boundaries of the different climate zones can be expected to change with future warming, as forecast by the various global circulation models and observations recorded in the literature. Something that caught my eye was the following:
I should also note that they are apparently relying on the high-emission RCP8.5 scenario for this 2021 publication.
However, what I have proposed previously, and what was being discussed in this thread, is what the behavior of historical temperatures might look like if they were plotted at the granularity of the Köppen Climate Zones instead of the broad brush of hemisphere or sub-continents, with the goal of better understanding the variance of the climate changes.
I have studied Koppen classes and their temperature distributions in Australia. One interesting group is 45 “pristine” stations that should not have measurable UHI in 12 different Koppen classes.
I was unable to extract any useful conclusions, apart from the usual one, that the historic temperature data were designed to support other purposes like helping pilots on takeoff and more, and are unfit for purposes of detailed statistical sophistication.
Vastly too much unattributed noise, scarce metadata to help explain it.
Geoff S
p.s. I write up this stuff from time to time, as do other colleagues here in Australia, but.the international class of climate enforcers does not want to do its paid job and address it. Readers who seek this data are welcomed to email, sherro01 at outlook dot com.
One would not suspect from Figure 3 in this article that Australia has 12 different Koppen classes. You must have a lot of microclimates that are too small to map at the scale used.
Clyde,
There are 16 Koppen classes. actually. See
https://www.geoffstuff.com/Chapter_5.docx
Cheers geoff S
Climate science will tell you that Las Vegas and Miami have the same climate because both can have the same “median” daily temperature. What a joke!
When I got up this morning at about 0730, the outdoor temperature was 64F. Now at 1100 it is 69F. And the world here has not ended.
Don’t be so sure it won’t. With a rapid change like that it could still happen. 🤦🏻♂️😂
bob,
You deny the fear of tipping points at your peril!
(sarc)
The “tipping point” happened around 200 years ago during the Little Ice Age when it started warming and it hasn’t stopped.
Are you suggesting that Earth will never again experience significant glaciation? Now THAT would be a tipping point.
But VERY different enthalpies.
However, that “30-year mean” is actually an average that includes Mt. Everest and the Dead Sea. If it makes “no sense,” then why use it to talk about a global average?
Presumably, each data series (instrument / station) has its own 30-year average, which is then subtracted from each reading to obtain that series’ anomalies, which in turn are averaged to obtain the so-called global temperature anomalies. At least, that’s what I think they’re doing…
But winter temps have a different variance then summer temps – meaning the anomaly variances will be different as well. So comparing monthly anomaly averages from Boston with those from Rio de Janeiro aren’t comparing the same thing. Yet climate science jams them together with no regard for the different variances each set of anomaly averages have.
I’ve always been a proponent of comparing like to like, meaning annual anomalies would be computed by subtracting an average of the 30 annual averages comprising the baseline from each of the individual annual averages for which you want to calculate an anomaly. Ditto for June or winter or some other ‘demarcation’ that eliminates seasonality. If that’s not what our friends do, they’re even more out to sea than I thought they were.
Well what is referred to as “climate science” these days isn’t actually science at all, so there’s that.
How is the average of all the anomalies converted back to a single global average temperature? Doesn’t that require Mt. Everest and the Dead Sea to be included, either before or after the baseline is added back? It seems to me that any way you cut it, to obtain a single global average temperature, it will require all the temperatures to be added and divided by the number of stations.
‘How is the average of all the anomalies converted back to a single global average temperature?’
Beats me, nor do I think such a calculation can convey any useful information.
The claimed increasing average global temperature is the basis of the alarm about anthropogenic influences.
Anomalies are calculated using a 30 year average from each specific station. That makes the anomaly only relatable to that station. Climate scientists make believe that you can average all those station specific anomalies to achieve a “global” average ΔT.
I need to do more research, but it seems more logical to use a common “global” base temperature to determine “global” change. It would also force the climate elites to define what the best “global” temperature should be.
+100
It would also make more sense to take all temperature measurements around the globe at the same exact times, e.g. 0000GMT and 1200GMT. The temps would not be relatable to actual local climates but then the data we get today isn’t either since temperature is such a poor metric for climate. But taking all *global” measurements at the same time would provide a better metric for “global” temperature.
When looking at the graph of Figure 1 or that of Figure 2 in the above article, it is a gross oversight to not point out that the early “data”, say from 1850 to 1925, is of significantly different accuracy/reliability than that of the later “data”, say from 1925 to 2020.
The earlier data has the following differences compared to the later data:
— less accurate thermometers/essentially no electronic temperature monitoring instrumentation
— less frequent/less accurate temperature sensor calibrations (including siting/enclosure factors)
— greater probability of instrumentation reading/recording errors
— greater areal coverage per monitoring station
— less error introduced by urban heat island (UHI) effect on monitoring stations
Consequently, trying to resolve temperature differences of averages-of-anomalies from 1850 to 2020 to a precision of ± 0.5 C or better is just ridiculous.
Pat Frank provides an excellent discussion of this issue, focusing on liquid-in-glass thermometer errors, at https://wattsupwiththat.com/2023/06/29/the-verdict-of-instrumental-methods/
I am sure that both Richard Lindzen and Paul Homewood are aware of this, but I was surprised to see it wasn’t mentioned anywhere in the above article.
Whenever anyone brings up the 1.5C number they are implicitly making an extrapolation from linear regression. As any undergraduate statistics student should be able to tell you, regression fits are only valid over the range of X-data used for a fit. But per usual in climate science, such matters are trivialities to be ignored in the quest for the holy hockey stick.
Not to mention that linear regression is not appropriate for an autocorrelated time series like temperature.
Not to mention that linear regression is not appropriate for an autocorrelated time series like temperature. – with cyclic components!
More to the point, the 1.5C number was just made up to create a scary scenario that would occur some time in the future, but not so soon that it was obvious that it had passed without the world ending. That would obviously be bad, because somebody’s funding would be cut if it happened.
The worst part is that the line has been repeated so often even people with lots of technical education don’t question its validity, it is simply accepted as a fact.
_________________________________________________________
For every complex problem there is an answer
that is clear, simple, and wrong. H. L. Mencken
_________________________________________________________
_________________________________________________________
IPCC AR4 Chapter 10 Page 750 (pdf4)
Temperature Extremes
Almost everywhere, daily minimum temperatures are projected to
increase faster than daily maximum temperatures, leading to a
decrease in diurnal temperature range.
Of course, most people with an IQ above room temperature (on the Celsius scale) know the value of IPCC projections.
Steve,
Routine raw daily data from Australia for its eight main cities does not show any systematic increase of temperature of the hottest heatwaves each year averaged over durations of 1, 3, 5 and 10 consecutive days.
Most cities show no change since records begin, some as early as 1860s.
Some show a tiny rise, some a tiny fall, but the frequent Establishment claim that Australian heatwaves are getting longer, hotter and more frequent cannot be supported.
There is a battle between unbiased analysis of historic raw data and tortured analysis of subjectively adjusted data to fit a global warming idea. Sadly, the academic shouties and gatekeepers are dominant for the moment. Geoff S
p.s. I have a large page with 128 Excel graphs showing variations of such heatwaves for these 8 cities of Brisbane, Sydney, Melbourne, Hobart, Adelaide, Perth, Darwin and Alice Springs. Half of the graphs show BOM adjusted ACORN-SAT temperatures to demonstrate how a different result can be manufactured. It is a 30 MB file, but I am happy to send it on request. Geoff S
Oh but it’s worse than that.
Assuming those cities have been growing in population over the time period of measurement, that means an increase in the UHI effect, which means the data should show an increase in non-climate related temperatures.
The fact that it doesn’t (absent the BOM data torturing) makes the propaganda about heat being even further distanced from reality.
Excellent article.
Figure 1 shows clearly shows that the warming trend post 1980 is a man made facade.
As there no way in the global weather system you would get that sort of consistency.
lf you want proof! then just look at yearly totals post 1980 for “rainfall” “sunshine hours” and storms “etc”. Or on a more local level the “first and last” dates for snowfall and frost.
No that warming trend has been largely man made in my view due to the switch from recording temps from glass thermometers to electic ones. lts the current reseach am doing into this matter that has lead me to that conclusion
There’s a lot more to that warming trend than just the switch to electric thermometers. There’s also urban heat island, selective removal of rural weather stations while retaining urban ones, data homogenization (please don’t call it ‘fudging’).
I don’t see climate ‘scientists’; just activists.
Am currently doing reseach on this topic by comparing the results of my glass thermometer with 2 local AWS’s and its been a real eye opener.
During the daytime the difference between in temp recordings between my thermometer and the AWS’s can be as much as 2.7C and with the AWS’s the difference is always higher during the daytime. Only during largly clear nights does the AWS’s readings goes down to or below my glass thermometer readings.
l think this is far bigger issue then many people realize.
I call it Fake Data.
I call it NOT data. Data is the instrument readings, anything else is glorified guesswork that is generally heavily tainted with confirmation bias.
A distinction without a difference methinks.
“but there is a noticeable reduction in negative ones. It is something I have often seen in UK data, that average temperature rise is being driven by less extreme cold weather, rather than more extreme heat.”
Be careful what you say here. A data denier named Vinos will soon be here to claim winters are getting more extreme, by ignoring all data to the contrary. And he will be upset when you disagree.
Warmer winters since the 1970s
In SE Michigan
In the UK
In the US
In the NH
Most places except Antarctica
Meanwhile, in the real world:
“Winter 2023/2024 is starting to trend colder in the latest forecast, with large-scale El Nino influence across the United States, Canada and Europe.”
— https://www.severe-weather.eu/long-range-2/winter-2023-2024-forecast-polar-vortex-el-nino-qbo-strong-impact-cold-weather-united-states-canada-europe-fa/
Winter ends March 19, 2024
Can we at least wait until after the winter ends before jumping to conclusions?
Can we at least wait until Javier Vinós makes a post before jumping to put words in his mouth and intentions in his mind?
As science DENIER, dickie-green says…… blah, blah….
.. oh wait.. most of what he says is proven garbage… and can be circular filed. !
Another in a LONG series of outbursts of verbal flatulence from the resident deputy assistant village idiot … hoping for a promotion to washroom attendent
Do you really believe your comments are serious ?
I never saw one.
Poor dickie-boy.
Yet another 5-year-old style tanty. !
Very funny , if you like clowns and buffoons.. 🙂
Unfortunately, the ‘trend’ isn’t consistent and one can draw different conclusions with different start-stop dates:
The absolute average temperature says the same thing as temperature anomalies but in a visually honest way, while anomaly charts are visually deceptive
The twin charts on the home page here show the difference visually … although the absolute temperature chart here does not end at about 15 degrees C. which is where NASA GISS claims we are.
Not that it matters. The absolute chart is close to a straight line.
What really matters is rarely discussed because Climate Howlers jump a few steps up the assumption ladder to scaremonger
(1) When did average temperature measurements become accurate enough to reach any conclusions?
Probably in 1979
(2) Is warming bad news?
No, warming is good news
(3) When and where is the most warming?
Think of warmer winter nights in Siberia as the post-1975 global warming poster child
(4) How does my local climate compare with the average climat?
If you have warmer winters, contradicting Vinos, then you are probably happy. If a ski bum, maybe not
A surface average temperature on a visually deceptive anomaly chart best supports global warming propaganda. So that’s what we get.
A gif Koppen five climate zone chart that showed the zones morphing from perhaps 1923 to 2023 would be interesting. At least colorful.
No one wasted time thinking about their climate before the 1970s. Winters were cold and summers were hot. No one cared about the average temperature
Your uncle in San Diego had a better climate than you did. Your aunt in Miami had a hot climate, so we’ll visit her in he winter. If it was a colder than usual winter, you complained. If it was a hotter than usual summer, you complained. If you were old and cranky, you complained about the weather every other day.
Only if one excludes UHI effects and area “normalization” tricks, as has been documented numerous times in WUWT articles over the last five years.
And as many others have, and continue, to point out: a single temperature value claimed to represent a global “average” is really just a meaningless number, akin to talking about the average temperature of the Sun.
Dickie loves all that data manipulation and mal-adjustment.
According to all the idiotic anti-science AGW mantra things he “believes”…
…he is actually a rabid AGW cultist nutter!
“(1) When did average temperature measurements become accurate enough to reach any conclusions?
Probably in 1979″
A totally unwarranted assumption, especially for surface data., which , if anything has got considerably worse…
… with urban effects, rapid-acting thermometers which can be affected by a myriad things, are often less reliable than human-read thermometers.
Here is missing data tag from one such Australian site
Also, around 1990, there was a large drop in the number of surface stations reporting, which looks to have made a significant difference to the fabricated surface temperature..
Reliability.. accuracy.. NOPE. !
The chart is BS
NASA-GISS uses about 21000 land stations
RG,
How do you know that NASA-GISS uses about 21,000 stations? Did you include or exclude stations with made-up, extrapolated or interpolated data or data adjustments? How many stations today used strictly raw, as-measured data? Geoff S
So they use even more TOTAL GARBAGE.
Thanks for that, dickie-boy
When did average temperature measurements become accurate enough to reach any conclusions?
Never, as averages are not measured but calculated
They are based on measurements, nitpicker
Nevertheless not measured, fact denier.
As the GUM says, a measurand is a physical entity. Averages are not physical entities, they are a statistical descriptor of a distribution, so they can’t be a measurand. Only a measurand can be measured. Averages are calculated, you can have average values that don’t even physically exist, like the average height of 100 Shetland poines and 100 Belgian draft horses.
Averages 😀
[emphasis mine]
Yes, thank you. No one ever listens when I say this, I become ‘old man shouting at clouds.’
If you kick out the ‘average of an average, of an average’ and plot the average daily high, with the average daily low across time, you’ll see that the daily high is dropping slightly, and the nightly low is rising slightly, but quite a bit more than the daily high is dropping. Thus, the average daily temp rises, but the high didn’t get higher, the low got higher.
Interesting takeouts, but it’s still just diddling about with “averages of averages of averages of averages ad infinitum” of totally imprecise, inadequately represented measurements values.
And to boot, this nonsense is reported as differentials of hundredths of 1 degree C over decades.
Billy Connolly called this kind of nonsense out decades ago when he asked –
“how do they fookn’ know???”
Climate science believes temperature is a good proxy for heat content, i.e. enthalpy.
Now heat content is heat content, be it night or during the day. So how can CO2 be trapping HEAT, if daytime temps are going down? That means that more heat is being lost over a 24 hour period than is being “trapped” at night. Otherwise that “trapped” heat would cause daytime temps to go up as well since higher heat content would cause higher daytime temps.
It’s a connundrum that I’ve never seen climate science even address let alone explain!