Daily Archives: 13. March 2021
Iceland – 34,000 quakes in two weeks could lead to an eruption
No eruptions have taken place at this particular volcano for at least 10,000 years, so what comes next is a total unknown. Especially when you consider that the average yearly number of earthquakes across the Reykjanes peninsula is only 1,000 to 3,000. (Depending on where you live, you may think “only” is not the right word to describe the situation.)
An eruption could lead to catastrophic global cooling
A “seismic crisis” has been occurring in the area near Fagradalsfjall since late Feb 2021, says electoverse.net. This activity has been interpreted as intrusion of magma at shallow depths, which could lead to a new eruption.
Fadradalsfjall is a table mountain in the Reykjanes Peninsula, NE of Grindavik, Iceland.
Very little is known about the eruptive history of the volcano; but according to both VolcanoDiscovery.com and Volcano.si.edu, no eruptions have occurred during the past 10,000 years — in other words, it’s anyone’s guess what this volcano is capable of when it does blow.
“I think this is a sign the magma dike is growing very fast,” said Kristín Jónsdóttir, of the Icelandic Meteorological Office (IMO), referring to the huge increase in earthquake activity.
The IMO has also officially stated that these magmatic movements are the likely cause of the ongoing earthquake swarm in the peninsula–a swarm that has now totaled 34,000 quakes in two weeks.
Will Iceland be home to the next “big one”?
Of today’s reawakening volcanoes, those located in Iceland are perhaps the most concerning.
It is this highly-volcanic region that will likely be home to the next “big one” (a repeat of the 536 AD eruption that took out the Roman Republic…?) — the one that will return Earth to another volcanic winter.
Volcanic eruptions are one of the key forcings driving Earth into its next bout of global cooling.
Volcanic ash (particulates) fired above 10km –and so into the stratosphere– shade sunlight and reduce terrestrial temperatures. The smaller particulates from an eruption can linger in the upper atmosphere for years, or even decades.
Today’s worldwide volcanic uptick is thought to be tied to low solar activity, coronal holes, a waning magnetosphere, and the influx of Cosmic Rays penetrating silica-rich magma.
In 536 AD, a thick fog blanketed much of Asia, the Middle East, and Europe, shrouding these regions in darkness for one and a half years straight. According to natureworldnews.com, the ambient temperatures during that year’s summer decreased by 1.5 to 2.5° Celsius, contributing to that decade being the coldest for the last 2.3 millennia. Continents experienced unseasonable snowfall during this time, crops died, and many millions starved to death.
Millions upon millions of people died
New ice analysis reveals that a violent volcanic eruption in Iceland was the culprit. The explosion released a thick plume of ash into the stratosphere in the early part of 536 AD blocking the Sun and causing crop failure across the hemisphere, killing millions upon millions of people. In addition, two more massive eruptions also occurred in 540 AD and 547 AD — these repeated eruptions caused untold suffering and economic stagnation in Europe for the next 100+ years, until the year 640 AD.
Thanks to Steven Rowlandson for this link
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March 12, 2021 at 01:34PM
The Safe Climate Of August 1922
14 Aug 1922 – CHINESE TYPHOON. – Trove
14 Aug 1922 – Misplaced Tropical Heat. – TroveThis entry was posted in Uncategorized. Bookmark the permalink.← Scientists Vs. SkepticsBiden : “I Will Always Tell The Truth” →
1 Response to The Safe Climate Of August 1922
via Real Climate Science
Posted on March 12, 2021 by tonyheller
March 12, 2021 at 01:13PM
Milloy talks soaring gas prices with Kara McKinney on OANN’s “Tipping Point”
from last night’s show.
via JunkScience.com
March 12, 2021 at 01:06PM
Volcanoes Popping Off Around The Globe – Video
New activity or notable unrest:
Etna, Sicily (Italy)
Klyuchevskoy, Central Kamchatka (Russia)
Krysuvik, Iceland
Kuchinoerabujima, Ryukyu Islands (Japan)
Pacaya, Guatemala
Sinabung, Indonesia.
San Cristobal, Nicaragua.
Continuing activity:
Aira, Kyushu (Japan)
Dukono, Halmahera (Indonesia)
Ebeko, Paramushir Island (Russia)
Fuego, Guatemala Ibu, Halmahera (Indonesia)
Kilauea, Hawaiian Islands (USA)
Kirishimayama, Kyushu (Japan)
Lewotolok, Lembata Island (Indonesia)
Merapi, Central Java (Indonesia)
Raung, Eastern Java (Indonesia)
Sangay, Ecuador
Santa Maria, Guatemala
Semeru, Eastern Java (Indonesia)
Sheveluch, Central Kamchatka (Russia)
Soufriere St. Vincent, St. Vincent
Suwanosejima, Ryukyu Islands (Japan)
See full-size map:
https://volcanodiscovery.de/uploads/pics/active-volcano-map2-2021-03-09.jpg
____________
Here’s more:
Iceland prepares for a volcanic eruption
20,000 earthquakes in two days
Video:
https://www.msn.com/en-in/money/other/gravitas-iceland-prepares-for-a-volcanic-eruption/vi-BB1epRr7
____________
Strombolian & lava fountain eruptions at Klyuchevskaya Sopka volcano, Russia
The highest active volcano in Russia Eurasia and one of the world’s most active volcanoes.
It has a large active crater with frequent strombolian and lava fountain eruptions.
Thanks to Benjamin Napier, Laurel, Stephen Bird and tom0mason for these links
“This eruption is very pretty, especially towards the end,” says Stephen.Do you suppose all these volcanoes pumping untold amounts of ash into the sky might contribute to global cooling?
The post Volcanoes Popping Off Around The Globe – Video appeared first on Ice Age Now.
via Ice Age Now
March 12, 2021 at 12:37PM
Central Banks Can’t Print Energy
Analyst Gail Tverberg has done an excellent job of explaining that it’s not just the availability of energy that matters, it’s the affordability of that energy to the bottom 90% of consumers.
The following is from The Myths of Green Energy by Charles Hugh Smith:
Central Banks Can’t Print Energy
Again, “money” is nothing but a claim on future energy, because energy is the foundation of the global economy. Without energy, we’re all stranded in the desert and all our “money” is worthless because it can no longer buy what we need to live.
Central banks can print infinite amounts of currency but they can’t print energy, and so all central banks can do is add zeroes to the currency. They can’t make energy more affordable, or guarantee that a day’s labor will buy more than a fraction of the energy that labor can buy today.
The global financial system has played a game in which “money” is either printed or borrowed into existence, on the theory that energy will be more abundant and more affordable in the future. If this theory turns out to be incorrect, the “money” used in the future to pay back debts incurred today will have near-zero value.
The question is: how much energy, water and food will the “money” created out of thin air in the future buy?
If the lender can only buy a tiny sliver of the energy, water and food that the “money” could have bought at the time the “money” was borrowed, then it won’t really matter how many zeroes the “money” will have. What matters is how much purchasing power of essentials the “money” retains.
Borrowing trillions of dollars euros, yen and yuan every year expands the claims on future energy at a rate that far exceeds the actual expansion of energy in any form.
This has created an illusion that we can always create money out of thin air and it will magically hold its current purchasing power for ever greater amounts of energy, food and water.
The monumental asymmetry between the staggering rate of expansion of “money” — claims on future energy — and the stagnant supply of energy means this illusion is only temporary.
See more of this great article:
https://dailyreckoning.com/the-myths-of-green-energy/
Thanks to Jasper for this link
The post Central Banks Can’t Print Energy appeared first on Ice Age Now.
via Ice Age Now
March 12, 2021 at 12:37PM
There Are Models And There Are Models
Guest Post by Willis Eschenbach
I’m 74, and I’ve been programming computers nearly as long as anyone alive.
When I was 15, I’d been reading about computers in pulp science fiction magazines like Amazing Stories, Analog, and Galaxy for a while. I wanted one so badly. Why? I figured it could do my homework for me. Hey, I was 15, wad’ja expect?
I was always into math, it came easy to me. In 1963, the summer after my junior year in high school, nearly sixty years ago now, I was one of the kids selected from all over the US to participate in the National Science Foundation summer school in mathematics. It was held up in Corvallis, Oregon, at Oregon State University.
It was a wonderful time. I got to study math with a bunch of kids my age who were as excited as I was about math. Bizarrely, one of the other students turned out to be a second cousin of mine I’d never even heard of. Seems math runs in the family. My older brother is a genius mathematician, inventor of the first civilian version of the GPS. What a curious world.
The best news about the summer school was, in addition to the math classes, marvel of marvels, they taught us about computers … and they had a real live one that we could write programs for!
They started out by having us build design and build logic circuits using wires, relays, the real-world stuff. They were for things like AND gates, OR gates, and flip-flops. Great fun!
Then they introduced us to Algol. Algol is a long-dead computer language, designed in 1958, but it was a standard for a long time. It was very similar to but an improvement on Fortran in that it used less memory.
Once we had learned something about Algol, they took us to see the computer. It was huge old CDC 3300, standing about as high as a person’s chest, taking up a good chunk of a small room. The back of it looked like this.
It had a memory composed of small ring-shaped magnets with wires running through them, like the photo below. The computer energized a combination of the wires to “flip” the magnetic state of each of the small rings. This allowed each small ring to represent a binary 1 or a 0.
How much memory did it have? A whacking great 768 kilobytes. Not gigabytes. Not megabytes. Kilobytes. Thats one ten-thousandth of the memory of the ten-year-old Mac I’m writing this on.
It was programmed using Hollerith punch cards. They didn’t let us anywhere near the actual computer, of course. We sat at the card punch machines and typed in our program. Here’s a punch card, 7 3/8 inches wide by 3 1/4 inches high by 0.007 inches thick. (187 x 83 x.018 mm).
The program would end up as a stack of cards with holes punched in them, usually 25-50 cards or so. I’d give my stack to the instructors, and a couple of days later I’d get a note saying “Problem on card 11”. So I’d rewrite card 11, resubmit them, and get a note saying “Problem on card 19” … debugging a program written on punch cards was a slooow process, I can assure you
And I loved it. It was amazing. My first program was the “Sieve of Eratosthenes“, and I was over the moon when it finally compiled and ran. I was well and truly hooked, and I never looked back.
The rest of that summer I worked as a bicycle messenger in San Francisco, riding a one-speed bike up and down the hills delivering blueprints. I gave all the money I made to our mom to help support the family. But I couldn’t get the computer out of my mind.
Ten years later, after graduating from high school and then dropping out of college after one year, I went back to college specifically so I could study computers. I enrolled in Laney College in Oakland. It was a great school, about 80% black, 10% Hispanic, and the rest a mixed bag of melanin-deficient folks. (I’m told than nowadays the polically-correct term is “melanin-challenged”, to avoid offending anyone.) The Laney College Computer Department had a Datapoint 2200 computer, the first desktop computer.
It had only 8 kilobytes of memory … but the advantage was that you could program it directly. The disadvantage was that only one student could work on it at any time. However, the computer teacher saw my love of the machine, so he gave me a key to the computer room so I could come in before or after hours and program to my heart’s content. I spent every spare hour there. It used a language called Databus, my second computer language.
The first program I wrote for this computer? You’ll laugh. It was a test to see if there was “precognition”. You know, seeing the future. My first version, I punched a key from 0 to 9. Then the computer picked a random number, and recorded if I was right or not.
Finding I didn’t have precognition, I re-wrote the program. In version 2, the computer picked the number before, rather than after, I made the selection. No precognition needed. Guess what?
No better than random chance.
Ten years after that, I bought the first computer I ever owned — the Radio Shack TRS-80, AKA the “Trash Eighty”. It was the first notebook-style computer. I took that sucker all over the world. I wrote endless programs on it, including marine celestial navigation programs that I used to navigate by the stars between islands the South Pacific. It was also my first introduction to Basic, my third computer language.
And by then IBM had released the IBM PC, the first personal computer. When I returned to the US I bought one. I learned my fourth computer language, MS-DOS. I wrote all kinds of programs for it. But then a couple years later Apple came out with the Macintosh. I bought one of those as well, because of the mouse and the art and music programs. I figured I’d use the Mac for creating my art and my music and such, and the PC for serious work.
But after a year or so, I found I was using nothing but the Mac, and there was a quarter-inch of dust on my IBM PC. So I traded the PC for a piano, the very piano here in our house that I played last night for my 19-month-old granddaughter, and I never looked back at the IBM side of computing.
I taught myself C and C++ when I needed speed to run blackjack simulations … see, I’d learned to play professional blackjack along the way, counting cards. And when my player friends told me how much it cost for them to test their new betting and counting systems, I wrote a blackjack simulation program to test the new ideas. You need to run about a hundred thousand hands for a solid result. That took several days in Basic, but in C, I’d start the run at night, and when I got up the next morning, the run would be done. I charged $100 per test, and I thought “This is what I wanted a computer for … to make me a hundred bucks a night while I’m asleep.”
Since then, I’ve never been without a computer. I’ve written literally thousands and thousands of programs. On my current computer, a ten-year-old Macbook Pro, a quick check shows that there are well over 2,000 programs I’ve written. I’ve written programs in Algol, Datacom, 68000 Machine Language, Basic, C/C++, Hypertalk, Mathematica (3 languages), Vectorscript, Pascal, VBA, Stella computer modeling language, and these days, R.
I had the immense good fortune to be directed to R by Steve McIntyre of ClimateAudit. It’s the best language I’ve ever used—free, cross-platform, fast, with a killer user interface and free “packages” to do just about anything you can name. If you do any serious programming, I can’t recommend it enough.
I bring all of this up to let you know that I’m far, far from being a novice, a beginner, or even a journeyman programmer. I was working with “computer based evolution” to try to analyze the stock market before most folks even heard of it. I’m a master of the art, able to do things like write “hooks” into Excel that let Excel transparently call a separate program in C for its wicked-fast speed, and then return the answer to a cell in Excel …
Now, folks who’ve read my work know that I am far from enamored of computer climate models. I’ve been asked “What do you have against computer models?” and “How can you not trust models, we use them for everything?”
Well, based on a lifetime’s experience in the field, I can assure you of a few things about computer climate models and computer models in general. Here’s the short course.
• A computer model is nothing more than a physical realization of the beliefs, understandings, wrong ideas, and misunderstandings of whoever wrote the model. Therefore, the results it produces are going to support, bear out, and instantiate the programmer’s beliefs, understandings, wrong ideas, and misunderstandings. All that the computer does is make those under- and misunder-standings look official and reasonable. Oh, and make mistakes really, really fast. Been there, done that.
• Computer climate models are members of a particular class of models called “Iterative” computer models. In this class of models, the output of one timestep is fed back into the computer as the input of the next timestep. Members of his class of models are notoriously cranky, unstable, and prone to internal oscillations and generally falling off the perch. They usually need to be artificially “fenced in” in some sense to keep them from spiraling out of control.
• As anyone who has ever tried to model say the stock market can tell you, a model which can reproduce the past absolutely flawlessly may, and in fact very likely will, give totally incorrect predictions of the future. Been there, done that too. As the brokerage advertisements in the US are required to say, “Past performance is no guarantee of future success”.
• This means that the fact that a climate model can hindcast the past climate perfectly does NOT mean that it is an accurate representation of reality. And in particular, it does NOT mean it can accurately predict the future.
• Chaotic systems like weather and climate are notoriously difficult to model, even in the short term. That’s why projections of a cyclone’s future path over say the next 48 hours are in the shape of a cone and not a straight line.
• There is an entire branch of computer science called “V&V”, which stands for validation and verification. It’s how you can be assured that your software is up to the task it was designed for. Here’s a description from the web
What is software verification and validation (V&V)?
Verification
820.3(a) Verification means confirmation by examination and provision of objective evidence that specified requirements have been fulfilled.
“Documented procedures, performed in the user environment, for obtaining, recording, and interpreting the results required to establish that predetermined specifications have been met” (AAMI).
Validation
820.3(z) Validation means confirmation by examination and provision of objective evidence that the particular requirements for a specific intended use can be consistently fulfilled.
Process Validation means establishing by objective evidence that a process consistently produces a result or product meeting its predetermined specifications.
Design Validation means establishing by objective evidence that device specifications conform with user needs and intended use(s).
“Documented procedure for obtaining, recording, and interpreting the results required to establish that a process will consistently yield product complying with predetermined specifications” (AAMI).
Further V&V information here.
• Your average elevator control software has been subjected to more V&V than the computer climate models. And unless a computer model’s software has been subjected to extensive and rigorous V&V. the fact that the model says that something happens in modelworld is NOT evidence that it actually happens in the real world … and even then, as they say, “Excrement occurs”. We lost a Mars probe because someone didn’t convert a single number to metric from Imperial measurements … and you can bet that NASA subjects their programs to extensive and rigorous V&V.
• Computer modelers, myself included at times, are all subject to a nearly irresistible desire to mistake Modelworld for the real world. They say things like “We’ve determined that climate phenomenon X is caused by forcing Y”. But a true statement would be “We’ve determined that in our model, the modeled climate phenomenon X is caused by our modeled forcing Y”. Unfortunately, the modelers are not the only ones fooled in this process.
• The more tunable parameters a model has, the less likely it is to accurately represent reality. Climate models have dozens of tunable parameters. Here are 25 of them, there are plenty more.
• The climate is arguably the most complex system that humans have tried to model. It has no less than six major subsystems—the ocean, atmosphere, lithosphere, cryosphere, biosphere, and electrosphere. None of these subsystems is well understood on its own, and we have only spotty, gap-filled rough measurements of each of them. Each of them has its own internal cycles, mechanisms, phenomena, resonances, and feedbacks. Each one of the subsystems interacts with every one of the others. There are important phenomena occurring at all time scales from nanoseconds to millions of years, and at all spatial scales from nanometers to planet-wide. Finally, there are both internal and external forcings of unknown extent and effect. For example, how does the solar wind affect the biosphere? Not only that, but we’ve only been at the project for a couple of decades. Our models are … well … to be generous I’d call them Tinkertoy representations of real-world complexity.
• Many runs of climate models end up on the cutting room floor because they don’t agree with the aforesaid programmer’s beliefs, understandings, wrong ideas, and misunderstandings. They will only show us the results of the model runs that they agree with, not the results from the runs where the model went off the rails. Here are two thousand runs from 414 versions of a model running first a control and then a doubled-CO2 simulation. You can see that many of the results go way out of bounds.
As a result of all of these considerations, anyone who thinks that the climate models can “prove” or “establish” or “verify” something that happened five hundred years ago or a hundred years from now is living in a fool’s paradise. These models are in no way up to that task. They may offer us insights, or make us consider new ideas, but they can only “prove” things about what happens in modelworld, not the real world.
Be clear that having written dozens of models myself, I’m not against models. I’ve written and used them my whole life. However, there are models, and then there are models. Some models have been tested and subjected to extensive V&V and their output has been compared to the real world and found to be very accurate. So we use them to navigate interplanetary probes and design new aircraft wings and the like.
Climate models, sadly, are not in that class of models. Heck, if they were, we’d only need one of them, instead of the dozens that exist today and that all give us different answers … leading to the ultimate in modeler hubris, the idea that averaging those dozens of models will get rid of the “noise” and leave only solid results behind.
Finally, as a lifelong computer programmer, I couldn’t disagree more with the claim that “All models are wrong but some are useful.” Consider the CFD models that the Boeing engineers use to design wings on jumbo jets or the models that run our elevators. Are you going to tell me with a straight face that those models are wrong? If you truly believed that, you’d never fly or get on an elevator again. Sure, they’re not exact reproductions of reality, that’s what “model” means … but they are right enough to be depended on in life-and-death situations.
Now, let me be clear on this question. While models that are right are absolutely useful, it certainly is also possible for a model that is wrong to be useful.
But for a model that is wrong to be useful, we absolutely need to understand WHY it is wrong. Once we know where it went wrong we can fix the mistake. But with the complex iterative climate models with dozens of parameters required, where the output of one cycle is used as the input to the next cycle, and where a hundred-year run with a half-hour timestep involves 1.75 million steps, determining where a climate model went off the track is nearly impossible. Was it an error in the parameter that specifies the ice temperature at 10,000 feet elevation? Was it an error in the parameter that limits the formation of melt ponds on sea ice to only certain months? There’s no way to tell, so there’s no way to learn from our mistakes.
Next, all of these models are “tuned” to represent the past slow warming trend. And generally, they do it well … because the various parameters have been adjusted and the model changed over time until they do so. So it’s not a surprise that they can do well at that job … at least on the parts of the past that they’ve been tuned to reproduce.
But then, the modelers will pull out the modeled “anthropogenic forcings” like CO2, and proudly proclaim that since the model no longer can reproduce the past gradual warming, that demostrates that the anthropogenic forcings are the cause of the warming … I assume you can see the problem with that claim.
In addition, the gridsize of the computer models are far larger than important climate phenomena like thunderstorms, dust devils, and tornados. If the climate model is wrong, is it because it doesn’t contain those phenomena? I say yes … computer climate modelers say nothing.
Heck, we don’t even know if the Navier-Stokes fluid dynamics equations as they are used in the climate models converge to the right answer, and near as I can tell, there’s no way to determine that.
To close the circle, let me return to where I started—a computer model is nothing more than my ideas made solid. That’s it. That’s all.
So if I think CO2 is the secret control knob for the global temperature, the output of any model I create will reflect and verify that assumption.
But if I think (as I do) that the temperature is kept within narrow bounds by emergent phenomena, then the output of my new model will reflect and verify that assumption.
Now, would the outputs of either of those very different models “evidence” be about the real world?
Not on this planet.
And that is the short list of things that are wrong with computer models … there’s more, but as Pierre said, “the margins of this page are too small to contain them” …
My very best to everyone, stay safe in these curious times,
w.
PS—When you comment, quote what you’re talking about. If you don’t, misunderstandings multiply.
H/T to Wim Röst for suggesting I write up what started as a comment on my last post.
via Watts Up With That?
March 12, 2021 at 12:28PM
Europe’s Green Deal in trouble as Biden administration warns EU against carbon border tax
Europe’s Green Deal and its planned carbon border tax are in serious trouble as the Biden administration raises concerns about its potentially disastrous fallout on international trade and relations.
According to the European Commission the EU’s Green Deal and its 2050 Net Zero target are threatening the very survival of Europe’s industries unless a carbon border tax is enforced upon countries that are not adopting the same expensive Net Zero policies.
It’s a matter of survival of our industry. So if others will not move in the same direction, we will have to protect the European Union against distortion of competition and against the risk of carbon leakage,” European Commission executive vice-president Frans Timmermans warned in January.
On Wednesday, the European Parliament endorsed the creation of a carbon border tax that is planned to protect EU companies against cheaper imports from countries with weaker climate policies.
However, it would appear that the Biden administration is getting cold feet about the protectionist agenda and its potentially devastating impact of world trade, throwing a spanner in the EU’s plans.
John Kerry, Joe Biden’s climate envoy, has warned the EU that a carbon border tax should be a “last resort,” telling the Financial Times that he was “concerned” about Brussels’ forthcoming plans.
He urged the EU to delay any decision until after the COP26 climate summit in Glasgow.
It [a carbon border tax] does have serious implications for economies, and for relationships, and trade,” he said. “I think it is something that’s more of a last resort, when you’ve exhausted the possibilities of getting emission reductions and joining in some kind of compact by which everybody is bearing the burden.”
The fundamental problem with Kerry’s demand, however, is that it contravenes the Paris Climate Agreement which cements the UN’s key principle of ‘Common but Differentiated Responsibilities and Respective Capabilities.‘ This principle acknowledges that developing nations have different capabilities and differing responsibilities in reducing CO2 emissions.
The Biden administration’s demand that developing nations adopt similar Net Zero targets as Western nations is therefore quixotic.
In light of more than a decade of futile attempts by Western leaders to believe that the developing world — at the COP26 climate summit in Glasgow — would relinquish this key principle and curtail its economic development and prospects in order to save the West’s competitiveness borders on political insanity, i.e.trying the same thing over and over again and expecting different results.
The post Europe’s Green Deal in trouble as Biden administration warns EU against carbon border tax appeared first on The Global Warming Policy Forum.
via The Global Warming Policy Forum
March 12, 2021 at 12:21PM
Desertification cancelled: Climate Change won’t make the deserts grow
After a thousand headlines told us Climate Change would make deserts grow, a new study suggests it won’t. It’s a finding that shocks no one who knew that climate models have no predictive skill with rainfall, and that a warmer world means higher global precipitation. Plus there’s the awkward clue that for the last forty years the arid regions of the world have been getting greener instead of more deserty.
Looks a bit different?
The top map (below) shows the deserts expanding — but that’s the old predictions which are based only on “atmospheric data” like temperature and rainfall. The bottom map is the new work which uses soil and vegetation data too. Red means growing deserts. Blue means shrinking.
Remember, all contradictory conclusions are based on expert opinions using worlds best practice and done by Nobel-Prize-winning people. Shame about all the farmers and investors making decisions based on junk models.
The new study is based on modeling too so it is still wrong, but less useless than previous studies.
The hugely different forecasts show how vaporously thin the past doom and gloom was, and how so many headlines were generated out of a banal omission from an inadequate model.
Cancel the cover shots of cracked Earth
Now they tell us?
Now we find that all the past expert predictions were made with models that only used “atmospheric information” like rain and temperature — to predict the condition of plants and soil. You’d think they might have mentioned that. Now that they have some actual soil moisture data and flora involved — things look very different. As all good skeptics know (but apparently not science journalists) increasing CO2 means plants need less water. Thus more carbon dioxide makes plants “drought resistant”.
Note the attention getting headline:
Climate change may not expand drylands
Previous studies used atmospheric information, including rainfall and temperature, to make projections about future land conditions. The real picture is more complicated than that, said Kaighin McColl, Assistant Professor of Earth and Planetary Sciences and of Environmental Science and Engineering at SEAS and senior author of the paper.
“Historically, we have relatively good records of rainfall and temperature but really poor records of the land surface, things like soil moisture and vegetation,” said McColl. “As a result, previous definitions of drylands are based only on how the atmosphere is behaving, as an approximation of the land surface. But models can now simulate both atmospheric and land conditions. By just looking directly at the land surface in climate models, we find that the models aren’t showing a clear increase of drylands over time and that there is huge uncertainty about the global average state of drylands in the future.”
Plants need less water when there is more CO2:
While climate models have historically focused on the atmosphere, modern climate models now also simulate vegetation behavior and land hydrology.
For example, when plants absorb CO2, they lose water. If there is more CO2 in the air, plants can release less water and become more water efficient. More CO2 also results in more fertilizer for plants, which helps them grow and reduces water stress.
These effects have long been known, but previous atmospheric-only indicators of drylands just weren’t capturing these land surface effects.
What does “high confidence” mean anyway
The big news here, is less about deserts and more about what it says about consensuses and past media coverage. The IPCC says on “Desertification” that Risks from desertification are projected to increase due climate change (high confidence).” They knew that CO2 makes plants grow, but figured that the reduction in rain was more important. The problem was, and still is, that none of their models work for rainfall.
Past posts:
- Arid regions of the world are 11% greener, mostly thanks to CO2
- 18 million square kilometers more greenery due to “carbon pollution” that the Greens hate
h/t Willie Soon — join him on his Parler Account.
REFERENCE
Berg and McColl (2021) No projected global drylands expansion under greenhouse warming, Nature Climate Change.
The custom R code written to read and analyse the data and generate the figures is available on GitHub at https://doi.org/10.5281/zenodo.4490414 (ref. 51).
via JoNova
March 12, 2021 at 11:58AM
Major Survey Shocks: German Youth Rejecting Need For Radical Behavior Change To Fight ‘Climate Crisis’
Frustrated by lockdowns and restrictions, Germany’s youth may be showing signs of rebellion as a comprehensive European Investment Bank generational survey shows “climate protection aspect does not seem to have the high priority among young people.”
Youth-led movement a myth…
Fading climate crisis: Germany’s younger generation may be rejecting calls to austerity, turning their backs on climate activists, major survey finds. Image cropped here.
Journalists Daniel Wetzel and Karsten Seibel at German online flagship daily Die Welt here report on today’s German youth and how they in fact do not view the climate issue at all like Fridays for Future activists Greta Thunberg (Sweden) and Luisa Neubauer.
The media and activists like giving the impression that the younger generation of Germans today are acutely concerned about climate and that the older generation is indifferent about it.
In fact the older generation is considered by some as being so irresponsible that “there are now calls in the commentary columns of daily newspapers such as the ‘TAZ’ to take away the right to vote from ‘old people’ and let children vote instead,” Wetzel and Seibel write.
Others have even suggested killing the old generation with Corona if they don’t clean up their climate act.
German youth not willing to forego amenities
But the results of the major climate survey of the European Investment Bank (EIB) don’t suggest this sort of generational difference. For example when it comes to products with the highest greenhouse gas emissions, such as short-haul domestic flights, 47 percent of respondents over 65 could imagine an emissions ban from such products, but only 27 percent of 15- to 29-year-olds could.
Obviously today’s German youth are not being swayed by Greta Thunberg’s doomsday prophecies.
Climate protection low priority
Wetzel and Seibel observe that “the climate protection aspect does not seem to have the high priority among young people that the TV pictures of demonstrating ‘Fridays for Future’ children suggest”.
Only 26% say we should use less fossil fuels!
Shockingly, “Only 26 percent of young people believe that we should use less fossil energy, primarily for climate protection reasons,” the two Die Welt journalists reveal. “Young people up to the age of 29 are not so keen on being banned from speeding on the motorway either: Only 12 percent would agree to a speed limit – in the over-65 age group, the figure is 26 percent.”
Another striking result: “Only 20 percent of Germans under age 30 are in favor of subsidizing electric cars” and a puny “22 percent in this age group would give priority to technology in climate protection.”
This compares to about 35% in China and the USA.
Only 15% prepared to “radically change behavior”
Moreover only 15 percent of Germany’s youth were prepared to radically change their personal behavior to fit in with the Paris climate goals,” write Wetzel and Seibert. 42%, however, do agree that behavioral change is necessary.
The European Investment Bank survey sampled 30,000 people in 30 countries in the fall of 2020.
via NoTricksZone
March 12, 2021 at 10:47AM