Global warming, climate change, all these things are just a dream come true for politicians. I deal with evidence and not with frightening computer models because the seeker after truth does not put his faith in any consensus. The road to the truth is long and hard, but this is the road we must follow. People who describe the unprecedented comfort and ease of modern life as a climate disaster, in my opinion have no idea what a real problem is.
Climate obsession at government level comes at a high economic price to its citizens. ‘Saving the planet’ is mythology, not science. – – – From The Heritage Foundation, Washington DC (via Climate Depot)…
Benny Peiser: “I remember giving evidence to a Senate hearing here some years back, and I was saying: ‘Look, as long as these [climate] policies are unilateral, as long as you do this on your own, this is not going to address your main concern, which is CO2 emissions, because the rest of the world will not follow.’
And the rest of the world will definitely not follow Europe’s green experiment which is going so badly. No one wants to do what the Europeans are doing, because they can see the damage we are doing to ourselves.
Unless — and this is the whole point — unless you can come up with an energy policy that is attractive to other countries, in particular to poorer countries, they will not follow your lead.
It comes with some surprise that previously, the same mother, person and human being promoted using use fake news, horror-stories and cli-fi to cause deep despair in the minds of vulnerable children and young adults, thinking about their future
With all the chatter about rising temperatures and record hot years emanating from Australia’s Bureau of Meteorology (BoM), CSIRO, the Australian Academy of Science, hard-core professors and climate-clowns at the Climate Council, a series of hard-hitting reports are becoming available on www.bomwatch.com.au that investigate how under the guise of data homogenisation, a cabal of scientists within the BoM adjust Australia’s temperature records to produce trends that are unrelated to the true climate.
In a similar vein to activist organisation 350.org’s traditional view of power, Australia’s race-to-the-bottom net-zero pledge depends entirely on the single pillar of ACORN-SAT (Australian Climate Observations Reference Network – Surface Air Temperature). Unpicking ACORN-SAT, using robust, replicable methods has multiple benefits, including showing unequivocally that the models are wrong, and undermining the credibility of State of the Climate Reports and other propaganda published by CSIRO.
Omitting the detail, which is in the reports, Blair Trewin, who developed the 112‑station ACORN-SAT dataset creates bogus trends by:
Adjusting site changes that made no difference, while ignoring those that did.
Selecting comparators as reference series without ensuring individual datasets are homogeneous.
Using reference series comprised of data that likely embed parallel faults, to make disproportionate adjustments to ACORN-SAT.
While data-fiddling should be viewed with great distain, it’s not the case for some, including Trewin, the BoM, CSIRO and professors and worker-ants who depend on money they get from the Australian Research Council to reshape our climate history.
It comes with some surprise that previously, the same mother, person and human being promoted using use fake news, horror-stories and cli-fi to cause deep despair in the minds of vulnerable children and young adults, thinking about their future (https://theconversation.com/ can-cli-fi-actually-make-a-difference-a-climate-scientists-perspective-83033). Amid all the other stressors of growing-up, climate-porn pedalled by people they should be able to trust, is known to do real and lasting damage to vulnerable people and should be regarded as a form of child abuse.
It is also useful for folks to remember that despite the hype, the atmosphere is still 99.96% CO2-free, and discounting station moves, changes and tricks like spraying-out the grass, detailed BomWatch studies have found no warming in the climate at Carnarvon, Meekatharra, Marble Bar, Parafield, Amberley, Rutherglen, and many other places including at weather stations along the Great Barrier Reef.
For her part, as mother, person, and human being, Perkins-Kirkpatrick could encourage her girls to enjoy re-runs of Frozen while she objectively analysed datasets that underpin her irrational warming-fears using BomWatch protocols. She could start with the freely available statistical packages detailed in the Parafield case study and datasets linked to each report, then openly discuss the outcomes at www.bomwatch.com.au or here on WUWT.
Import of Russian pipeline gas to Europe is falling, LNG imports from Russia are rising. Germany also purchases liquefied natural gas from Russia. Image: kees torn, CC BY-SA 2.0, via Wikimedia Commons
Germany continues to buy gas from Russia, even though the pipelines have dried up.
Despite declining volumes, this is a lucrative business for the Kremlin. German energy suppliers and the state are currently building new plants on the North Sea and Baltic Sea coasts to supply the country with liquefied natural gas and become less dependent on Russia.
However, data indicate that Germany also obtains liquefied natural gas from Russia (Zeit: 21.12.22).
Germany may purchase liquefied natural gas from Russia, despite pipeline closure
Germany is currently building new facilities to gain independence from Russia and switch to liquefied natural gas (LNG) to offset gas supplies from Russia that have been lost as a result of the Ukraine war.
But according to data from the market research company ICIS, Germany could continue to purchase liquefied natural gas from Russia.
Europe imported 21% more liquefied natural gas from Russia this year than last year, up from 18 billion cubic metres by the end of November.
Russia does not supply gas directly to Germany, but it does supply to some neighbouring European countries whose gas networks are closely linked to Germany.
By the end of 2024, Russia plans to build a new LNG terminal, Arctic LNG 2 in Siberia, which could increase the amount of LNG shipped to Europe. “The gas network in northwestern Europe is so closely connected that part of the Russian LNG inevitably reaches Germany,” explains gas expert Ed Cox from the market research company ICIS.
Origin of imported liquefied natural gas in Germany can be determined more precisely by new terminals
With the delivery of liquefied natural gas via the new terminals in Wilhelmshaven, Brunsbüttel and Lubmin, the origin of the liquefied natural gas imported into Germany can soon be determined more precisely.
However, there is no legal obligation for their operators to renounce Russian LNG, because the embargo imposed by the EU still applies only to Russian oil, but not to Russian gas. However, the contracts are concluded by private companies and not by the state.
The German Government supports possible trade relations through political talks. According to the energy suppliers RWE, Uniper and VNG, they have no interest in importing Russian liquefied natural gas via the new LNG terminals in Brunsbüttel and Wilhelmshaven.
Import of Russian pipeline gas to Europe falls, LNG imports from Russia increase
The amount of imported Russian pipeline gas to Europe has fallen significantly compared to the increasing LNG imports from Russia.
In November 2021, Germany still obtained 4.4 billion cubic meters, about half of its needs for the month, via the Nord Stream 1 pipeline directly from Russia, in addition to indirect imports via Poland. In the meantime, however, no Russian gas flows to Germany via these pipelines.
Gas consumption in Germany reduced by 27% in November compared to the previous year
Industry and private consumers saved about 27 percent of gas consumption in November 2022 compared to the previous year, which corresponds to about 2.6 billion cubic meters. However, this is not enough to completely replace supplies from Russia.
The rest of the gas is obtained from other sources. Norway is currently Germany’s most important gas supplier with about four billion cubic meters per month, followed by Belgium, the Netherlands and France. In addition to a small production off the Dutch coast, this mainly involves liquefied petroleum gas passed on from overseas.
The USA is the most important liquefied natural gas supplier to Europe, followed by African and Arab countries
The United States is the main liquefied natural gas supplier to Europe, with about four billion cubic meters in November 2022.
Almost five billion cubic meters were imported from various countries in Africa and the Arabian Peninsula, including Algeria, Angola and Qatar.
Russian liquefied natural gas accounted for about 1.8 billion cubic meters in November, according to Belgian think tank Bruegel. This corresponds to about one sixth of total LNG imports into the EU.
Qatar plans to expand LNG capacity and sign supply agreement with ConocoPhillips
Qatar is currently planning to expand its capacities and has agreed an energy partnership with the German government.
A recently concluded deal with the US company ConocoPhillips provides for deliveries only from 2026, which ConocoPhillips is to transport from Qatar to Brunsbüttel. Then up to 2.8 billion tons of LNG are to be imported into Germany annually over a period of at least 15 years.
However, the gas from Qatar will arrive too late for the current crisis.
It’s been on the cards for sometime, but we now know that 2022 was the warmest year on the CET record. UK figures will doubtlessly follow suit.
There will the inevitable claims that this confirms both the UK and the world continues to get warmer. As far as the first is concerned, that is not the case, as the 10-year average remains virtually the same as it was in the early 2000s. In simple terms, we continue to see a pause in UK temperatures, which has now lasted for nearly twenty years.
As for 2022, the record high is actually well withing the bounds of normal variability. As the chart below shows, annual temperatures are frequently around 1C either above or below the 30-year average. Last year was 0.8C warmer than the 30-year average, whilst 2010, for instance, was 1.1C below. Both anomalies were the result of weather variability, not climate change.
As the top chart reminds us, there was a significant uptick in CET in the late 1980s and 90s. Given that higher climate baseline, it is inevitable that we will continue to see new record highs occasionally set, even if there no underlying increase in temperature.
The story of the year’s weather is told in the chart below:
Most of the year saw temperatures in the top half of the range, but still within the 95th percentile. In short, there was a marked absence of colder than average weather, but no evidence of an upward shift in the temperature range as a whole which would be the case if there was a climatic shift.
We can break this down by calculating the number of days in each category for each month, based on percentiles of daily temperatures between 1991 and 2020:
Over the year as a whole, there were 29 days above the 95th percentile, the statistical average of course being 18, while 16 days came in below the 5th percentile. Extreme temperatures at either end of the scale therefore made little difference to the annual mean.
But by far the biggest impact was had by the 216 days in the yellow band, above the median but below the 95th percentile. That compared to just 104 days below the median.
All of these days between the 5th and 95th must be regarded as “normal weather”
Backing up this conclusion is the fact that no monthly or seasonal records were set last year, far from it:
Month
Rank
Jan
91
Feb
9
Mar
11
Apr
62
May
22
Jun
107
Jul
21
Aug
3
Sep
56
Oct
5
Nov
8
Dec
117
On a monthly basis, there was not a single month which saw weather we had not had experienced before. Even August. which was the 3rd hottest, was 0.4C cooler than 1995. Most months, while warmer than average, were in no way unusually so.
We’ve looked at the numbers, but let’s look at the type of weather that lay behind them:
February was mild largely due to a succession of Atlantic depressions:
The spring and summer that followed were both particularly sunny, with high temperatures inevitable:
Towards the end of the year, the autumn, particularly October and November, experienced mostly unsettled weather and above average rainfall:
In a nutshell, we had just the sort of temperatures we would expect from the weather which we had. Sunny springs and summers invariably lead to high temperatures, whilst unsettled, wet conditions in autumn and winter usually bring mild weather.
There is no evidence in any of the above that 2022 is part of a longer term pattern of warming in the UK.
December was a busy month on the sun. How busy? Senol Sanli of Bursa, Turkey, answered the question by stacking 26 days of sun photos (Dec. 2nd – 27th) from NASA’s Solar Dynamics Observatory
December was a busy month on the sun. How busy? Senol Sanli of Bursa, Turkey, answered the question by stacking 26 days of sun photos (Dec. 2nd – 27th) from NASA’s Solar Dynamics Observatory:
„There were more than 24 sunspot groups, some of them quite large, congested in two bands on opposite sides of the sun’s equator,“ says Sanli.
The congestion of dark cores catapulted the monthly sunspot number to its highest value in 7 years:
This plot from NOAA shows the ascending progression of Solar Cycle 25. It has outperformed the official forecast for 35 months in a row. If the trend continues, Solar Maximum will either happen sooner or be stronger than originally expected–possibly both. Stay tuned for lots more sunspots.
“People use terms such as “sure” to describe their uncertainty about an event … and terms such as “chance” to describe their uncertainty about the world.” — Mircea Zloteanu
“People use terms such as “sure” to describe their uncertainty about an event … and terms such as “chance” to describe their uncertainty about the world.” — Mircea Zloteanu
In many fields of science today, the word “uncertainty” is bandied about without much thought, or at least expressed thought, about which meaning of “uncertainty” is intended. This simple fact is so well known that a group in the UK, “Sense about Science”, published a booklet titled “Making Sense of Uncertainty” (.pdf). The Sense about Science group promotes evidence-based science and science policy. The Making Sense of Uncertainty booklet, published in 2013, is unfortunately an only vaguely-disguised effort to combat climate skepticism based on the huge uncertainties in Climate Science.
Nonetheless, it includes some basic and necessary understandings about uncertainty:
Michael Hanlon: “When the uncertainty makes the range of possibilities very broad, we should avoid trying to come up with a single, precise number because it creates a false impression of certainty – spurious precision.”
A good and valid point. But the larger problem is “trying to come up with a single … number” whether ‘spuriously precise’ or not.
David Spiegelhalter: “In clinical medicine, doctors cannot predict exactly what will happen to anyone, and so may use a phrase such as ‘of 100 people like you, 96 will survive the operation’. Sometimes there is such limited evidence, say because a patient’s condition is completely novel, that no number can be attached with any confidence.”
Not only in clinical medicine, but widely across fields of research, we find papers being published that — despite vague, even contradictory, and limited evidence with admitted weaknesses in study design — state definitive numerical findings that are no better than wild guesses. [ See studies by Jenna Jambeck on oceanic plastics. ]
And, perhaps the major understatement, and the least true viewpoint, in the booklet:
“There is some confusion between scientific and everyday uses of the words ‘uncertainty’ and ‘risk’. [This first sentence is true. – kh] In everyday language, we might say that something that is uncertain is risky. But in scientific terms, risk broadly means uncertainty that can be quantified in relation to a particular hazard – and so for a given hazard, the risk is the chance of it happening.”
A Lot of Confusion
“The risk is the chance of it happening.” Is it really? William Briggs, in his book “Uncertainty: The Soul of Modeling, Probability & Statistics”, would be prone to point out that for there to be a “chance” (meaning “a probability”) we first need a proposition, such as “The hazard (death) will happen to this patient” and clearly statedpremises, most of which are assumed and not stated, such as “The patient is being treated in a modern hospital, otherwise healthy, the doctor is fully qualified and broadly experienced in the procedure, the diagnosis is correct…”. Without full exposition of the premises, no statement of probability can be made.
I recently published here two essays touching on uncertainty:
Each used almost childishly simple examples to make several very basic true points about the way uncertainty is used, misused and often misunderstood. I expected a reasonable amount of push-back against this blatant pragmatism in science, but the ferocity and persistence of the opposition surprised me. If you missed these, take a look at the essays and their comment streams. Not one of the detractors was able to supply a simple example with diagrams or illustrations to back their contrary (almost always “statistical”) interpretations and solutions.
So What is the Problem Here?
1. Definition In the World of Statistics, uncertainty is definedasprobability. “Uncertainty is quantified by a probability distribution which depends upon our state of information about the likelihood of what the single, true value of the uncertain quantity is.” [ source ]
[In the linked paper, uncertainty is contrasted to: “Variability is quantified by a distribution of frequencies of multiple instances of the quantity, derived from observed data.”]
2. Misapplication The above definition becomes misapplied when we consider absolute measurement uncertainty.
Absolute error or absolute uncertainty is the uncertainty in a measurement, which which is expressed using the relevant units.
The absolute uncertainty in a quantity is the actual amount by which the quantity is uncertain, e.g. if Length = 6.0 ± 0.1 cm, the absolute uncertainty in Length is 0.1 cm. Note that the absolute uncertainty of a quantity has the same units as the quantity itself.
Note: The most correct label for this is absolute measurement uncertainty. It results from the measurement process or the measurement instrument itself. When a temperature is always (and only) reported in whole degrees (or when it has been rounded to whole degrees), it has an inescapable absolute measure uncertainty of ± 0.5°. So, the thermometer reading reported/recorded as 87° must carry its uncertainty and be shown as “87° ± 0.5°” — which is equivalent to “any value between 87.5 and 86.5” —there are an infinite number of possibilities in that range, all of which are equally possible. (The natural world does not limit temperatures to those exactly lining up with the little tick marks on thermometers.)
Dicing for Science
Let’s take a look at a simple example – throwing a single die and throwing a pair of dice.
A single die (a cube, usually with slightly rounded corners and edges) has six sides – each with a number of dots: 1, 2, 3, 4, 5 and 6. If properly manufactured, it has a perfectly even distribution of results when rolled many times. Each face of the die (number) will be found facing up as often as every other face (number).
~~~
This represents the distribution of results of 1,000 rolls of a single fair die. If we had rolled a million times or so, the distribution values of the numbers would be closer to 1-in-6 for each number.
What is the mean of the distribution? 3.5
What is the range of the result expected on a single roll? 3.5 +/- 2.5
Because each roll of a die is entirely random (and within its parameters, it can only roll whole values 1 through 6), for the every next rollwe can predict the value of 3.5 ± 2.5 [whole numbers only]. This prediction would be 100% correct – in this sense, there is no doubt that the next roll will be in that range, as it cannot be otherwise.
Equally true, because the process can be considered entirely random process, every value represented by that range “3.5 ± 2.5” [whole numbers only] has an equal probability of coming up in each and every “next roll”.
What if we look at rolling a pair of dice?
A pair of dice, two of the die’s described above, rolled simultaneously, have a value distribution that looks like this:
When we roll two dice, we get what looks like an unskewed “normal distribution”. Again, if we had rolled the pair of dice a million times, the distribution would be closer to perfectly normal – very close to the same number for 3s and for 11s and the same numbers for 1s as for the 12s.
What is the mean of the distribution? 7
What is the range of the result expected on a single roll? 7 ± 5
Because each roll of the dice is entirely random (within its parameters, it can only roll whole values 2 through 12), for the every next rollwe can predict the value of “7 ± 5”.
But, with a pair of dice, the distribution is no longer even across the whole range. The value of the sums of the two dice range from 2 through 12 [whole numbers only]. 1 is not a possible value, nor is any number above 12. The probability of rolling a 7 is far larger than rolling a 1 or 3 or 11 or 12.
To make the dicing example into true absolute measurement uncertainty, in which we give a stated value and its known uncertainty but do not (and cannot) know the actual (or true) value, we will place the dice inside a closed box with a lid. And then shake the box (roll the die). [Yes, Schrödinger’s catand all that.]Putting the dice in a lidded box means that we can only give the value as a set of all the possible values, or, the mean ± the known uncertainties given above.
So, then we can look at our values for a pair of dice as the sum of the two ranges for a single die:
It would be exactly the same if adding two Tide Gauge Measurements, which have an absolute measurement uncertainty of ± 2 cm, or adding two temperatures that have been rounded to a whole degree. One sums the value and sums the uncertainties. (Many references for this. Try here.)
Statisticians (as a group) insist that this is not correct – “Wrong” as one savvy commenter noted. Statisticians insist that the correct sum would be:
7 ± 3.5
One of the commenters on Plus or Minus gave this statistical view: “the uncertainties add IN QUADRATURE. For example, (25.30+/- 0.20) + (25.10 +/- 0.30) = 50.40 +/- SQRT(0.20^2 + 0.30^2) = 50.40 +/-0.36 … You would report the result as 50.40 +/- 0.36”
Stated in words: Sum the values with the uncertainty given as the “square root of the sum of the squares of the uncertainties”.
So, let’s try to apply this to our simple dicing problem using two dice:
Oh, my. That is quite different from the result of following the rules for adding absolute uncertainties.
Yet, we can see in the blue diagram box that the correct solution including the full range of the uncertainty is 7 ± 5.
So, where do the approaches diverge?
Incorrect assumptions: The statistical approach uses a definition that does not agree with the real physical world: “Uncertainty is quantified by a probability distribution”.
Here is how a statistician looks at the problem:
However, when dealing with absolute measurement uncertainty (or in the dicing example, absolute known uncertainty – the uncertainty is known because of the nature of the system), the application of the statistician’s “adding in quadrature” rule gives us a result not in agreement with reality:
One commenter to the essay Limitations of the Central Limit Theorem, justified this absurdity with this: “there is near zero probability that both measurements would deviate by the full uncertainty value in the same direction.”
In our dicing example, if we applied that viewpoint, the ones and sixes of our single dies in a pair would have a ‘near zero’ probability coming up together (in a roll of two dice) to produce sums of 2 and 12. 2 and 12 represent the mean ± the full uncertainty value of plus or minus 5.
Yet, our distribution diagram of dice rolls shows that, while less common, 2s and 12s are not even rare. And yet, using the ‘adding in quadrature’ rule for adding two values with absolute uncertainties, 2s and 12s can just be ignored. We can ignore the 3s and 11s too.
Any dicing gambler knows that this is just not true, the combined probability of rolling 2, or 3, or 11, or 12 is 18% – almost 1-in-5. Ignoring a chance of 1-in-5, for example “there is a 1-in-5 chance that the parachute will malfunction”, is foolish.
If we used the statisticians regularly recommended “1 Standard Deviation” (approximately 68% – divided equally to both sides of the mean) we would have to eliminate from our “uncertainty” all of the 2s, 3s, 11s, and 12s, and about ½ of the 3s and 4s. — which make up 34% (>1-in-3) of the actual expected rolls.
Remember – in this example, we have turned ordinary uncertainty about a random event (roll of the dice) into “absolute measurement uncertainty” by placing our dice in a box with a lid, preventing us from knowing the actual value of the dice roll but allowing us to know the full range of uncertainty involved in the “measurement” (roll of the dice). This is precisely what happens when a measurement is “rounded” — we lose information about the measured value and end up with a “value range”. Rounding to the “nearest dollar” leaves an uncertainty of ± $ .50 ; rounding to the nearest whole degree leaves an uncertainty of ± 0.5°; rounding to the nearest millennia leaves an uncertainty of ± 500 years. Measurements made with an imprecise tool or procedure produce equally durable values with a known uncertainty.
This kind of uncertainty cannot be eliminated through statistics.
Bottom Lines:
1. We always seem to demand a number from research — “just one number is best”. This is a lousy approach to almost every research question. The “single number fallacy” (recently, this very moment, coined by myself, I think. Correct me if I am wrong.) is “the belief that complex, complicated and even chaotic subjects and their data can be reduced to a significant and truthful single number.”
2. The insistence that all “uncertainty” is a measure of probability is a skewed view of reality. We can be uncertain for many reasons: “We just don’t know.” “We have limited data.” “We have contradictory data.” “We don’t agree about the data.” “The data itself is uncertain because it results from truly random events.” “Our measurement tools and procedures themselves are crude and uncertain.” “We don’t know enough.” – – – – This list could go on for pages. Almost none of those circumstances can be corrected by pretending the uncertainty can be represented as probabilities and reduced using statistical approaches.
3. Absolute Measurement Uncertainty is durable – it can be diluted only by better and/or more precise measurement.
4. Averages (finding means and medians) tend to disguise and obscure original measurement uncertainty. Averages are not themselves measurements, and do not properly represent reality. They are a valid view of some data — but often hide the fuller picture. (see The Laws of Averages)
5. Only very rarely do we see original measurement uncertainty properly considered in research findings – instead researchers have been taught to rely on the pretenses of statistical approaches to make their results look more precise, more statistically significant and thus “more true”.
# # # # #
Author’s Comment:
Hey, I would love to be proved wrong on this point, really. But so far, not a single person has presented anything other than a “my statistics book says….”. Who am I to argue with their statistics books?
But I posit that their statistics books are not speaking about the same subject (and brook no other views). It takes quite a search to even find the correct method that should be used to add two values that have absolute measurement uncertainty stated (as in 10 cm ± 1 cm plus 20 cm ± 5 cm). There are just too many similar words and combinations of words that “seem the same” to internet search engines. The best I have found are physics YouTubes.
So, my challenge to challengers: Provide a childishly simple example, such as I have used, two measurements with absolute measurement uncertainties given added to one another. The arithmetic, a visual example of the addition with uncertainties (on a scale, a ruler, a thermometer, in counting bears, poker chips, whatever) and show them being added physically. If your illustration is valid and you can arrive at a different result than I do, then you win! Try it with the dice. Or a numerical example like the one used in Plus or Minus.
Spare a thought for millions who will be living through an uncertain winter due to unaffordable heating prices. The situation is worse this year because of the energy crisis in Europe, where fuel is scarce and expensive.
Spare a thought for millions who will be living through an uncertain winter due to unaffordable heating prices. The situation is worse this year because of the energy crisis in Europe, where fuel is scarce and expensive.
In the U.S., a bomb cyclone that suddenly chilled much of the country sent power demand soaring and disrupted supplies to consumers.
Being a species born in the tropics, humans are prone to greater morbidity and mortality in winter. People exposed to cold conditions have a “higher risk of stroke, respiratory infection and other injuries” due to reduced strength and dexterity in low temperatures.
Whether the threat is a flu infection or a fall, the risk is generally greater in the more challenging environment of cold weather.
According to the U.S. Environmental Protection Agency, “Death rates in winter months have been eight to 12% higher than in non-winter months.” It adds that “even moderately cold days can increase the risk of death for many people.”
The dangers of winter temperatures are not unique to temperate regions. Even subtropical people are susceptible. According to a study published by PLOS ONE, the subtropical Chinese city of Guangzhou “showed a clear seasonal pattern in mortality, with a sharper spike in winter.”
The heating of homes and other buildings is what reduces winter risks.
However, access to heating is not uniform across the world. In underdeveloped regions, the primary method of heating is to light a fire using wood, dried animal dung or some flammable waste available in the vicinity. People often forage for days looking for wood.
In more developed economies of the West, most people use gas or electricity-based heaters, which are more reliable, clean and convenient than open-flame heating. According to a recent survey in the U.S., 48% of people prefer to use gas. Electricity is preferred by 38%. Fuel oil and kerosene are the third most common source of heat.
So, it unsurprising that a high cost of gas and electricity leads people in developed economies to cut back on winter heating. In New Zealand, fuel poverty is reported to be a contributing factor to the country’s high rate of excess winter mortality and hospitalizations. According to a European Parliament report, “In 2020, about 36 million Europeans were unable to keep their homes adequately warm.”
Commenting on the sharp spike in the UK’s power prices in 2022, analyst Peter Matejic says, “It is impossible to think a care worker or a shop assistant will have to scramble to find hundreds more pounds to pay for their heating or that the entirety of someone’s income for a whole year will be less than their energy bill.”
The UK’s National Health Service, the second largest publicly funded healthcare system in the world, has issued a stark warning about increasing energy prices.
“The country is facing a humanitarian crisis,” NHS‘s confederation chief executive said. “Many people could face the awful choice between skipping meals to heat their homes and having to live in cold, damp and very unpleasant conditions.
This in turn could lead to outbreaks of illness and sickness around the country and widen health inequalities, worsen children’s life chances and leave an indelible scar on local communities.”
In the U.S., a study by the National Bureau of Economic Research found that “a lower heating price reduces winter mortality, driven mostly by cardiovascular and respiratory causes.”
In other words, winter mortality drops with the price of heating, and vice versa. Usually, this unaffordability of heating occurs when there is an overall slowdown in economic growth, resulting in lower purchasing power among consumers.
However, the current heating crisis is a direct consequence of “green” policies that have pushed up the price of energy in developed economies. An irrational insistence to transition to wind and solar has increased prices and reduced reliability of energy supplies. Blackouts like ones experienced by millions over the Christmas weekend are a serious threat to lives.
Policy makers ignore these realities at the risk of losing the public’s trust. Consumers who once casually put their lives in the hands of large utilities have reason to feel less secure.
Vijay Jayaraj is a Research Associate at the CO2 Coalition, Arlington, Virginia. He holds a master’s degree in environmental sciences from the University of East Anglia, UK and resides in India.
Originally published by RealClearEnergy. Republished with permission.
Climate Realism has covered studies that show cold weather is more dangerous than high temperatures–to read more, click here, here, and here.
When Arctic ice is melting in summer until mid-September, warmists stoke fears about ice disappearing in the North. In fact, the pattern of Arctic ice seen in historical perspective is not alarming.
When Arctic ice is melting in summer until mid-September, warmists stoke fears about ice disappearing in the North. In fact, the pattern of Arctic ice seen in historical perspective is not alarming.
People are over-thinking and over-analyzing Arctic Ice extents, and getting wrapped around the axle (or should I say axis). So let’s keep it simple and we can all readily understand what is happening up North.
I have noticed at some other blogs people complain about my monthly Arctic ice updates focusing on extents starting in 2007.
This post will show why that time period is entirely reasonable as a subject for analysis. I will use the ever popular NOAA dataset derived from satellite passive microwave sensors.
It sometimes understates the ice extents, but everyone refers to it and it is complete from 1979 to present. Here’s what NOAA reports (in M km2):
We are frequently told that only the March maximums and the September minimums matter, since the other months are only transitional between the two. So the graph above shows the mean ice extent, averaging the two months March and September.
If I were adding this to the Ice House of Mirrors, the name would be The X-Ray Ice Mirror, because it looks into the structure of the time series. For even more clarity and simplicity, here is the table:
NOAA NH Annual Average Ice Extents (in M km2). Sea Ice Index v3.0 (here)
Year
Average
Change
Rate of Change
1979
11.697
1996
11.353
-0.344
-0.020 per year
2007
9.405
-1.949
-0.177 per year
2022
9.728
+0.323
+0.022 per year
The satellites involve rocket science, but this does not. There was a small loss of ice extent over the first 17 years, then a dramatic downturn for 11 years, 9 times the rate as before. That was followed by the current 15-year plateau with a slight gain comparable to the beginning loss.
All the fuss is over that middle period, and we know what caused it.
A lot of multi-year ice was flushed out through the Fram Strait, leaving behind more easily melted younger ice. The effects from that natural occurrence bottomed out in 2007.
Kwok et al say this about the Variability of Fram Strait ice flux:
The average winter area flux over the 18-year record (1978–1996) is 670,000 km2, 7% of the area of the Arctic Ocean. The winter area flux ranges from a minimum of 450,000 km2 in 1984 to a maximum of 906,000 km2 in 1995.
. .The average winter volume flux over the winters of October 1990 through May 1995 is 1745 km3 ranging from a low of 1375 km3 in the 1990 flux to a high of 2791 km3 in 1994.
Some complain it is too soon to say Arctic Ice is recovering, or that 2007 is a true change point. The same people were quick to jump on a declining period after 1996 as evidence of a “Death Spiral.”
Speaking to World Socialist Web Site, convicted Aussie climate activist Deanna Coco explains why we need a form of democracy which doesn’t involve public elections to solve the climate crisis.
SUV Drives Through Protestors. Image contrast enhanced from the original. Source Sky News, Fair Use, Low Resolution Image to Identify the Subject
Essay by Eric Worrall
Speaking to World Socialist Web Site, convicted Aussie climate activist Deanna Coco explains why we need a form of democracy which doesn’t involve public elections to solve the climate crisis.
Australian climate activist Violet Coco speaks on her jailing for Sydney Harbour Bridge protest
In a serious attack on basic democratic rights, Coco was initially sentenced to 15 months’ imprisonment, with at least eight months without parole, and denied bail. She was the first to be sentenced under laws introduced by the New South Wales (NSW) state Liberal-National government to impose fines of up to $22,000 and jail terms of up to two years for protests on roads, rail lines, tunnels, bridges and industrial estates.
…
VC: People are becoming increasingly concerned about the lack of action on the climate and ecological emergency and that is a threat to the people who are making a lot of money off the fossil fuel industry. The more we make noise about the climate and ecological emergency the more they are threatened. It makes sense that they are going to try and silence us, and we can’t let their bullying tactics get in the way of protecting the habitability of our planet.
WSWS: What are the political implications of the fact that both Labor and the Liberal-National Coalition support the implementation of these laws to defend the profits of big business?
VC: It is clear that our politics has failed us and what we need is a different form of democracy to resolve this emergency situation. I have done a lot of work with Extinction Rebellion, who promote citizens assemblies. It is a form of deliberative democracy with a random and representative selection of the population, informed and facilitated. A bit like jury duty, but for legislation.
We cannot trust either Labor or the Liberal-National Coalition to act in our best interest.
Climate activist attacks on forms of democracy which aren’t delivering the outcomes they want are nothing new.
The reality is all activists need to do to get their way is persuade ordinary people to support them. But despite decades of disappointment, activists still can’t bring themselves to admit the failure is their fault. They just aren’t persuasive enough.
Near the end of 2020, as the covid-19 pandemic continued to rage, a few climate scientists and energy experts made a prediction. They estimated that emissions from fossil fuels — which had just plummeted thanks to the global pandemic — might never again reach the heights of 2019. Perhaps, they speculated, after over a century of ever more carbon dioxide flowing into the atmosphere, the world had finally reached “peak” emissions.
They were wrong.
According to a report released last month by the Global Carbon Project, carbon emissions from fossil fuels in 2022 are expected to reach 37.5 billion tons of carbon dioxide, the highest ever recorded. That means that despite the continued fallout from the coronavirus pandemic — which caused emissions to drop by over 5 percent in 2020 — CO2 emissions are back and stronger than ever.
Scientists have reacted with dismay. For years before the pandemic, emissions appeared to be leveling off — sparking hope that the world was finally reaching the moment when emissions would start to come down. Then in 2020, “Covid came, there was a huge drop in emissions — and I guess we got a little overexcited,” said Glen Peters, a climate scientist at the Center for International Climate Research in Oslo.
Here’s why researchers were wrong about emissions peaking — and what it means for the future — in three charts:
This statement is very telling, coming as it does from a climate scientist:
“Fossil fuels are still the cheapest way to provide reliable electricity,” said Ken Caldeira, a climate scientist at the Carnegie Institution for Science. (While wind and solar can be cheaper than fossil fuels in some cases, their intermittency — and the absence of cheap, big batteries — mean that it’s difficult to build an entire electricity system out of just renewable energy.) “It’s like Maslow’s hierarchy of needs,” Caldeira said. “Developing countries have to put climate concerns second to their economic concerns.”
If anything, the situation is worse than portrayed, as China’s economy has still been hamstrung by brutal Covid lockdowns during 2022.
Anybody with an ounce of common sense would have known this was going to happen. And that emissions will carry on rising while ever developing nations want to grow their economies, or until something better than fossil fuels comes along.
It shows just how divorced from reality those pushing Net Zero agendas really are.
.jpg){kind=link}
You must be logged in to post a comment.