Better to do nothing than try to reach UN climate targets

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Lorrie Goldstein writes a review of a new Fraser Institute study by McKitrick and Murphy.  The study is Off Target: The Economics Literature Does Not Support the 1.5C Climate Ceiling.  Excerpts from Goldstein’s article in italics with my bolds.

Trying to achieve the United Nations’ target of limiting global temperature increases to 1.5 C above pre-industrial levels will do more social and economic harm than good, says a new study by the Fraser Institute released Tuesday.

“Although advocacy of aggressive climate-change policies is often draped with the mantel of science … the popular 1.5C policy target will pose costs that far exceed the benefits,” the study says.

“Emission reductions flowing from strict adherence to the 1.5C target would be worse for the world than doing nothing at all.”

Study authors Ross McKitrick and Robert P. Murphy argue in Off Target: The Economics Literature Does Not Support the 1.5C Climate Ceiling, that the 1.5C target “did not arise … from formal cost-benefit analysis.”

In fact, a 2018 report by the UN’s Intergovernmental Panel on Climate Change that argued there would be net societal benefits to achieving the 1.5C target — used by Canada and other countries to justify the public cost of lowering greenhouse gas emissions — “expressly stated” it did not do a cost-benefit analysis.

The 2018 UN study, Global Warming of 1.5°C — An IPCC Special Report, said because the calculations were so complex, “standard cost–benefit analyses become difficult to justify and are not used as an assessment tool in this report.”

Instead, the UN report cited a range of studies that have estimated the global cost of carbon pricing (expressed here in current Canadian dollars) to meet the UN’s target of limiting global temperature increases to 1.5C above pre-industrial levels by 2100.

They went from a low of $170 per tonne of emissions, to a high of $6,900 per tonne by 2030; $307 per tonne to $16,300 per tonne by 2050; $527 to $21,955 by 2070 and $865 to $33,873 by 2100.  Given such numbers, Murphy argues in the Fraser report, “it would be better if governments did nothing at all about climate change than to try to achieve the 1.5C target because the costs so outweigh the estimated benefits.

(Prime Minister Justin Trudeau’s current carbon price is $40 per tonne of emissions, rising to $170 per tonne in 2030.)

In the real world, no government is going to impose a carbon tax/price of up to $6,900 per tonne of emissions by 2030 — with more hikes after that — because it would be political and economic suicide.

No one knows what global temperatures are going to be in 2100, nor what the global carbon price on emissions would have to be by then to meet the UN’s target of limiting warming to 1.5C above pre-industrial levels.

What we do know for a fact today is that global emissions are steadily rising. The only exceptions in the modern era occurred in 2008-09 and 2020, when they fell dramatically not because of carbon pricing, but because of global recessions, before resuming their upward climb the following year.

We also know that as of 2021, we are so far behind the UN’s target of reducing emissions to 45% below 2010 levels by 2030, that achieving that goal would require lowering emissions globally by 7.6% annually every year between now and 2030.

And finally, we know that, since almost all goods and services consume fossil fuel energy, a 7.6% annual reduction in emissions every year from now until 2030, would provoke an unprecedented global recession in which the social and economic costs would far outweigh the benefits.

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CO2 Changes Follow Temp Changes, Not the Reverse 2021 Update

This post is about proving that CO2 changes in response to temperature changes, not the other way around, as is often claimed.  In order to do  that we need two datasets: one for measurements of changes in atmospheric CO2 concentrations over time and one for estimates of Global Mean Temperature changes over time.

Climate science is unsettling because past data are not fixed, but change later on.  I ran into this previously and now again in 2021 when I set out to update an analysis done in 2014 by Jeremy Shiers, which I discussed in a previous post reprinted at the end.  Jeremy provided a spreadsheet in his essay Murray Salby Showed CO2 Follows Temperature Now You Can Too posted in January 2014. I downloaded his spreadsheet intending to bring the analysis up to the present to see if the results hold up.  The two sources of data were:

Temperature anomalies from RSS here:  http://www.remss.com/missions/amsu

CO2 monthly levels from NOAA (Moana Loa): https://www.esrl.noaa.gov/gmd/ccgg/trends/data.html

Changes in CO2 (ΔCO2)

Uploading the CO2 dataset showed that many numbers had changed (why?).

The blue line shows annual observed differences in monthly values year over year, e.g. June 2020 minus June 2019 etc.  The first 12 months (1979) provide the observed starting values from which differentials are calculated.  The orange line shows those CO2 values changed slightly in the 2020 dataset vs. the 2014 dataset, on average +0.035 ppm.  But there is no pattern or trend added, and deviations vary randomly between + and -.  So last year I took the 2020 dataset to replace the older one for updating the analysis.

Now I find the NOAA dataset in 2021 has almost completely new values due to a method shift in February 2021, requiring a recalibration of all previous measurements.  The new picture of ΔCO2 is graphed below.

Co2 Monthly Diffs New and Old2021

The method shift is reported at a NOAA Global Monitoring Laboratory webpage, Carbon Dioxide (CO2) WMO Scale, with a justification for the difference between X2007 results and the new results from X2019 now in force.  The orange line shows that the shift has resulted in higher values, especially early on and a general slightly increasing trend over time.  However, these are small variations at the decimal level on values 340 and above.  Further, the graph shows that yearly differentials month by month are virtually the same as before.  Thus I redid the analysis with the new values.

Global Temperature Anomalies (ΔTemp)

The other time series was the record of global temperature anomalies according to RSS. The current RSS dataset is not at all the same as the past.

To enlarge open image in new tab.

Here we see some seriously unsettling science at work.  The gold line is 2020 RSS and the purple is RSS as of 2014.  The red line shows alterations from the old to the new.  There is a slight cooling of the data in the beginning years, then the two versions pretty much match until 1997, when systematic warming enters the record.  From 1997/5 to 2003/12 the average anomaly increases by 0.04C.  After 2004/1 to 2012/8 the average increase is 0.15C.  At the end from 2012/9 to 2013/12, the average anomaly was higher by 0.21.

RSS continues that accelerated warming to the present, but it cannot be trusted.  And who knows what the numbers will be a few years down the line?  As Dr. Ole Humlum said some years ago (regarding Gistemp): “It should however be noted, that a temperature record which keeps on changing the past hardly can qualify as being correct.”

Given the above manipulations, I went instead to the other satellite dataset UAH version 6. UAH has also made a shift by changing its baseline from 1981-2010 to 1991-2020.  This resulted in systematically reducing the anomaly values, but did not alter the pattern of variation over time.  For comparison, here are the two records with measurements through June 2021.

CO2 Observed Temps Observed

Comparing UAH temperature anomalies to NOAA CO2 changes.

Here are UAH temperature anomalies compared to CO2 changes.

Changes in monthly CO2 synchronize with temperature fluctuations, which for UAH are anomalies now referenced to the 1991-2020 period.  As stated above, CO2 differentials are calculated for the present month by subtracting the value for the same month in the previous year (for example June 2021 minus June 2020).   Temp anomalies are calculated by comparing the present month with the baseline month.

The final proof that CO2 follows temperature due to stimulation of natural CO2 reservoirs is demonstrated by the ability to calculate CO2 levels since 1979 with a simple mathematical formula:

For each subsequent year, the co2 level for each month was generated

CO2  this month this year = a + b × Temp this month this year  + CO2 this month last year

Jeremy used Python to estimate a and b, but I used his spreadsheet to guess values that place for comparison the observed and calculated CO2 levels on top of each other.

CO2 Observed and Calculated2021

In the chart calculated CO2 levels correlate with observed CO2 levels at 0.9983 out of 1.0000.  This mathematical generation of CO2 atmospheric levels is only possible if they are driven by temperature-dependent natural sources, and not by human emissions which are small in comparison, rise steadily and monotonically.

Previous Post:  What Causes Rising Atmospheric CO2?

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This post is prompted by a recent exchange with those reasserting the “consensus” view attributing all additional atmospheric CO2 to humans burning fossil fuels.

The IPCC doctrine which has long been promoted goes as follows. We have a number over here for monthly fossil fuel CO2 emissions, and a number over there for monthly atmospheric CO2. We don’t have good numbers for the rest of it-oceans, soils, biosphere–though rough estimates are orders of magnitude higher, dwarfing human CO2.  So we ignore nature and assume it is always a sink, explaining the difference between the two numbers we do have. Easy peasy, science settled.

What about the fact that nature continues to absorb about half of human emissions, even while FF CO2 increased by 60% over the last 2 decades? What about the fact that so far in 2020 FF CO2 has declined significantly with no discernable impact on rising atmospheric CO2?

These and other issues are raised by Murray Salby and others who conclude that it is not that simple, and the science is not settled. And so these dissenters must be cancelled lest the narrative be weakened.

The non-IPCC paradigm is that atmospheric CO2 levels are a function of two very different fluxes. FF CO2 changes rapidly and increases steadily, while Natural CO2 changes slowly over time, and fluctuates up and down from temperature changes. The implications are that human CO2 is a simple addition, while natural CO2 comes from the integral of previous fluctuations.  Jeremy Shiers has a series of posts at his blog clarifying this paradigm. See Increasing CO2 Raises Global Temperature Or Does Increasing Temperature Raise CO2 Excerpts in italics with my bolds.

The following graph which shows the change in CO2 levels (rather than the levels directly) makes this much clearer.

Note the vertical scale refers to the first differential of the CO2 level not the level itself. The graph depicts that change rate in ppm per year.

There are big swings in the amount of CO2 emitted. Taking the mean as 1.6 ppmv/year (at a guess) there are +/- swings of around 1.2 nearly +/- 100%.

And, surprise surprise, the change in net emissions of CO2 is very strongly correlated with changes in global temperature.

This clearly indicates the net amount of CO2 emitted in any one year is directly linked to global mean temperature in that year.

For any given year the amount of CO2 in the atmosphere will be the sum of

  • all the net annual emissions of CO2
  • in all previous years.

For each year the net annual emission of CO2 is proportional to the annual global mean temperature.

This means the amount of CO2 in the atmosphere will be related to the sum of temperatures in previous years.

So CO2 levels are not directly related to the current temperature but the integral of temperature over previous years.

The following graph again shows observed levels of CO2 and global temperatures but also has calculated levels of CO2 based on sum of previous years temperatures (dotted blue line).

Summary:

The massive fluxes from natural sources dominate the flow of CO2 through the atmosphere.  Human CO2 from burning fossil fuels is around 4% of the annual addition from all sources. Even if rising CO2 could cause rising temperatures (no evidence, only claims), reducing our emissions would have little impact.

Resources:

CO2 Fluxes, Sources and Sinks

Who to Blame for Rising CO2?

Fearless Physics from Dr. Salby

In this video presentation, Dr. Salby provides the evidence, math and charts supporting the non-IPCC paradigm.

Footnote:  As CO2 concentrations rose, BP shows Fossil Fuel consumption slumped in 2020

See also 2021 Update: Fossil Fuels ≠ Global Warming

Bug Apocalypse Not!

Jon Entine writes again lamenting false alarms by scientists and journalists The Insect Apocalypse That Never Was.  Excerpts in italics with my bolds.

For the past four years, journalists and environmental bloggers have been churning out alarming stories that insects are vanishing, in the United States and globally. Limited available evidence lends credence to reasonable concerns, not least because insects are crucial components of many ecosystems. But the issue has often been framed in catastrophic terms, with predictions of a near-inevitable and imminent ecological collapse that would break ecosystems, destroy harvests, and trigger widespread starvation. Most of the proposed solutions would require a dramatic retooling of many aspects of modern life, from urbanization to agriculture.

Considering the disruptive economic and social trade-offs being demanded by some of those promoting the crisis hypothesis, it’s prudent to separate genuine threats from agenda-driven hyperbole. Are insect declines really threatening to precipitate a catastrophic ecological crisis? And, given the available data, what should a responsible society be doing?

The silver lining around the cloud of gloomy advocacy-focused studies and reporting is that entomologists are doing a deeper dive into the reasons behind the global declines. Goulson’s upcoming media blitz notwithstanding, the most thorough studies to date on insects in North America challenge the catastrophe narrative (although you may not have heard about them as they have been almost ignored by the media), and even offers some reassuring news.

The Moran study, published last August, specifically examined four to 36 years of data on arthropods (insects and other invertebrates) collected from US Long-Term Ecological Research sites located in ecoregions throughout the country. The authors found that: “There is no evidence of precipitous and widespread insect abundance declines in North America akin to those reported from some sites in Europe.”

The robustness of the Moran study data suggests the insect population story is much more complicated—and less dire—than many headlines suggest. If a thorough examination of the data on one continent can lead to such a dramatically different and more hopeful conclusion, broad trends in the vast, highly diverse, and relatively unstudied continents of Asia, Africa, Latin America, and Australia cannot be characterized through extrapolation with any assurance.

The overall paucity of data provides an opening for alarmists to speculate, and Goulson and others have taken advantage of that. But why are the data so fragmentary? Moran attributed the lack of corroborating studies supporting the consensus view that insect populations are mostly stable to what he calls “publication bias … more dramatic results are more publishable. Reviewers and journals are more likely to be interested in species that are disappearing than in species that show no change over time,” he wrote in the Washington Post.

It’s a reinforcing feedback loop, with journalists playing a key role in this misinformation cycle. Scientific publications are more likely to publish reports of declining species. Then, when researchers search for data, “declines are what they find.” The media often seize on incomplete or even biased conclusions to build a compelling narrative—an insect apocalypse or insectageddon or zombie-like resurrections of debunked reports of birdpocalypses and beepocalypses.

Background previous post:  Epic Media Science Fail: Fear Not Pollinator Collapse

Jon Entine returns to this topic writing at the Genetic Literacy Project: The world faces ‘pollinator collapse’? How and why the media get the science wrong time and again. Excerpts in italics with my bolds.

As I and others have detailed in the Genetic Literacy Project and as other news organizations such as the Washington Post and Slate have outlined, the pollinator-collapse narrative has been relentless and mostly wrong for more than seven years now.

It germinated with Colony Collapse Disorder that began in 2006 and lasted for a few years—a freaky die off of bees that killed almost a quarter of the US honey bee population, but its cause remains unknown. Versions of CCD have been occurring periodically for hundreds of years, according to entomologists.

Today, almost all entomologists are convinced that the ongoing bee health crisis is primarily driven by the nasty Varroa destructor mite. Weakened honey bees, trucked around the country as livestock, face any number of health stressors along with Varroa, including the use of miticides used to control the invasive mite, changing weather and land and the use of some farm chemicals, which may lower the honeybee’s ability to fight off disease.

Still, the ‘bee crisis’ flew under the radar until 2012, when advocacy groups jumped in to provide an apocalyptic narrative after a severe winter led to a sharp, and as it turned out temporary, rise in overwinter bee deaths.

Colony loss numbers jumped in 2006 when CCD hit but have been steady and even improving since.

The alarm bells came with a spin, as advocacy groups blamed a class of pesticides known as neonicotinoids, which were introduced in the 1990s, well after the Varroa mite invasion infected hives and started the decline. The characterization was apocalyptic, with some activist claiming that neonics were driving honey bees to extinction.

In the lab evaluations, which are not considered state of the art—field evaluations replicate real-world conditions far better—honeybee mortality did increase. But that was also true of all the insecticides tested; after all, they are designed to kill harmful pests. Neonics are actually far safer than the pesticides they replaced, . . . particularly when their impact is observed under field-realistic conditions (i.e., the way farmers would actually apply the pesticide).

As the “science” supporting the bee-pocalypse came under scrutiny, the ‘world pollinator crisis’ narrative began to fray. Not only was it revealed that the initial experiments had severely overdosed the bees, but increasing numbers of high-quality field studies – which test how bees are actually affected under realistic conditions – found that bees can successfully forage on neonic-treated crops without noticeable harm.

Those determined to keep the crisis narrative alive were hardly deterred. Deprived of both facts and science to argue their case, many advocacy groups simply pounded the table by shifting their crisis argument dramatically. For example, in 2016, the Sierra Club (while requesting donations), hyped the honey bee crisis to no end.

But more recently, in 2018, the same organization posted a different message on its blog. Honeybees, the Sierra Club grudgingly acknowledged, were not threatened. Forget honeybees, the Sierra Club said, the problem is now wild bees, or more generally, all insect pollinators, which are facing extinction due to agricultural pesticides of all types (though neonics, they insisted, were especially bad).

So, once again, with neither the facts nor the science to back them up, advocacy groups have pulled a switcheroo and are again pounding the table. As they once claimed with honeybees, they now claim that the loss of wild bees and other insect pollinators imperils our food supply. A popular meme on this topic is the oft-cited statistic, which appears in the recent UN IPBES report on biodiversity, that “more than 75 per cent of global food crop types, including fruits and vegetables and some of the most important cash crops such as coffee, cocoa and almonds, rely on animal pollination.”

There’s a sleight of hand here. Most people (including most journalists) miss or gloss over the important point that this is 75 percent of crop types, or varieties, not 75 percent of all crop production. In fact, 60 percent of agricultural production comes from crops that do not rely on animal pollination, including cereals and root crops. As the GLP noted in its analysis, only about 7 percent of crop output is threatened by pollinator declines—not a welcomed percentage, but far from an apocalypse.

And the word “rely” seems almost purposefully misleading. More accurately, most of these crops receive some marginal boost in yield from pollination. Few actually “rely” on it. A UN IPBES report on pollinators published in 2018 actually breaks this down in a convenient pie graph.

Many of these facts are ignored by advocacy groups sharpening their axes, and they’re generally lost on the “if it bleeds it leads” media, which consistently play up catastrophe scenarios of crashing pollinator communities and food supplies. Unfortunately, many scientists willingly go along. Some are activists themselves; others hope to elevate the significance of their findings to garner media attention and supercharge grant proposals.

As John Adams is alleged to have said, ‘facts are stubborn things.’ We can’t be simultaneously in the midst of a pollinator crisis threatening our ability to grow food and see continually rising yield productivity among those crops most sensitive to pollination.

With these claims of an impending wild bee catastrophe, as in the case of the original honeybee-pocalypse claims, few of the journalists, activists, scientists or biodiversity experts who regularly sound this ecological alarm have reviewed the facts in context. Advocacy groups consistently extrapolate from the declines of a handful of wild bee species (out of the thousands that we know exist), to claim that we are in the midst of a worldwide crisis. But just as with the ‘honey bee-mageddon, we are not.

Those of us who actually care about science and fact, however, might note the irony here: It is precisely the pesticides which the catastrophists are urging us to ban that, along with the many other tools in the modern farmer’s kit, have enabled us grow more of these nutritious foods, at lower prices, than ever before in human history.

Footnote:  Activists have played both sides with their insect warnings Alarmists: Global Warming Destroys Good Bugs and Multiplies Bad Bugs

insect

Summary: These scares always sound plausible, but on closer inspection are simplistic and unrealistic. The above shows that each type of insect has a range of temperatures they can tolerate and allow them to develop. They are stressed and populations decrease when colder than the lower limit and also when hotter than the upper limit. Every species will adapt to changing conditions as they always have. Those at their upper limit will decline, not increase, and their place will be taken by others. Of course, if it gets colder, the opposite occurs. Don’t let them scare you that insects are taking over.

Democrats Need Four Illusions to Sleep

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John Ellis writes at his blog Four Illusions.  Excerpts in italics with my bolds and images.

Illusion #1: Biden is not too old.

People who have been around American politics for a long time know Joe Biden well. The eldest among them have known Joe Biden for nearly five decades. What they will tell you is that he didn’t seem to age during his two terms as vice president. If you look at video of Biden 2016 and Biden 2008, you’re taken by how little he appears to have aged. Biden at 74 seems every bit as alert and physically vigorous as Biden at 66.

That’s no longer the case. Somewhere along the way of the last few years, Biden transitioned from “young old” to “old.” Veteran reporters describe the transition in code. “He’s lost a step or two.” Or: “he’s lost something off his fastball.”

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You’re not supposed to talk about it. If you do, and you’re a Democrat, you’re scolded for aiding and abetting the enemy. If you do, and you’re a Republican or (God forbid) a MAGA voter, you’re a horrible hate-mongerer, trying to overturn the results of a free and fair election (and you probably watch Fox News to boot).

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The problem is that it’s there for all to see. Pretending not to see it is untenable. It’s a bit like being the first car in a line of cars at a stop light and pretending that the light hasn’t turned green. Eventually, the cars behind you honk.

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Illusion #2: Harris “has what it takes.”

The widely shared assessment of Kamala Harris’s performance (so far) as vice president also comes in code: she’s “not ready for primetime,” she needs to “step up her game,” and “she’s off to a rocky start.” Few if any of the political cognoscenti think she is (a) “presidential timber” and/or (b) capable of winning the 2024 presidential election, should it come to that.

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These two truths — Biden is old, Harris isn’t ready — haunt Democrats and their media allies. When they imagine the 2024 presidential election without Biden or Harris, they notice another truth: there’s no bench. Gavin Newsom? Not. Andrew Cuomo? Not. Tim Kaine? Not. There’s a long list of superb military officers that would be formidable (and admirable) candidates, but the chances of a Democratic Convention nominating, say, Admiral William McRaven, are similar to my chances of buying the winning $1 billion Powerball ticket.

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Illusion #3: Trump is done.

Where in the world did this come from? Wishful thinking explains part of it. Maybe all of it. But it’s clearly not true. The amazing thing is that he’s not done, given his disgraceful post-election conduct and evident disdain for long-established, essential norms of American democracy; “consent of the losers” chief among them. It’s August (almost) and he still maintains that he won an election that he lost. That’s the dictionary definition of “delusional.”

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And yet it hasn’t hurt him. He remains the front-runner for the 2024 GOP presidential nomination. Republican elected officials at the federal, state and local level genuflect at the mention of his name. Would-be rivals for the 2024 nomination pledge their allegiance, and not just to Trump’s “populism” but to Trump personally. And then there’s Fox News.

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The 2024 Republican presidential nomination campaign will “happen” on Fox News. It will also “happen” on right-wing talk radio and on right-wing websites and in right-wing chat rooms, but Fox will frame the choice; controlling who gets exposure (and in what time slots) and who sets the agenda. Those decisions are driven by one consideration and one consideration only: Does it rate?

Trump rates. The others don’t. End of story.

And lest anyone think that Fox will ignore the ratings, turn on Trump and do what it can to bring to the fore the next generation of GOP leaders, please call me and I will sell you my winning Powerball ticket. For $1 million.

Illusion #4: Trump can’t win.

Can’t win what? The GOP nomination? Really? Want to bet? Who’s going to beat him? Josh Hawley? Marco Rubio? Ron DeSantis? Nikki Haley? Take your pick.

My guess is that none of them will run if Trump announces his candidacy in, say March of 2023. Would you? You’d be signing a political death warrant if you did; forever alienating vast swaths of the Trump coalition by challenging their champion. You’d be asking your major donors to invite Trump’s wrath. You’d be asking Republican elected officials at every level to risk ruin by endorsing your candidacy. It’s a non-starter from the start.

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Well, you say, Trump can’t possibly win the general election, can he? On paper, probably not. Fifty-two percent of the country would eat nails to vote against him.

But as we learn again and again, the national popular vote isn’t evenly distributed across the Electoral College. State-by-state, the Electoral College is almost perfectly distributed to make GOP victories possible, even when the party loses the national popular vote by a substantial margin. (Biden beat Trump by 7 million votes in the 2020 general election.)

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It’s also the case that Trump enjoys an advantage over, say, Biden (or Harris or any Democrat, for that matter) on “cultural issues.” In the key Electoral College states (like Michigan, Pennsylvania, Wisconsin, to name three) general election voters align more comfortably with Trump’s views on cultural issues; on immigration especially, but also on crime, “defund the police,” the undoing of welfare reform, and the rise of Woke.

That’s enough to make him competitive, but probably not enough to put him over the top. He’s so toxic, he hits a ceiling. And the Democrats (and their media allies) will do everything in their power to make Toxic Trump the issue, above all others. They’ll borrow a line from the Reagan re-election campaign: “Why would we ever want to return to where we were, less than four short years ago?”

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But what happens if Trump is not the issue? What happens if inflation is the issue? That would bring to mind the Carter re-election campaign, the one that ended in a GOP landslide at the state and local level and a 10-point win for Ronald Reagan (who received 50% of the national vote). Inflation destroyed Jimmy Carter’s presidency. It literally kicked him out of office.

What if Larry Summers is right and inflation is ready for launch and will likely take off next year? If Biden Administration policies are seen as the proximate cause of inflation, will “swing voters” view the administration as the best option for bringing inflation back under control? Probably not. Is inflation the kind of issue that can render Trump’s toxicity less salient? Yes it is.

The light is green. Let the honking begin.

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June 2021 Ocean Temps Stay Cool


The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

  • The ocean covers 71% of the globe and drives average temperatures;
  • SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
  • A major El Nino was the dominant climate feature in recent years.

HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source, the latest version being HadSST3.  More on what distinguishes HadSST3 from other SST products at the end.

The Current Context

The year end report below showed 2020 rapidly cooling in all regions.  The anomalies have continued to drop sharply well below the mean since 1995.  This Global Cooling was also evident in the UAH Land and Ocean air temperatures ( See March 2021 Ocean Chill Deepens) 

The chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through June 2021. After three straight Spring 2020 months of cooling led by the tropics and SH, NH spiked in the summer, along with smaller bumps elsewhere.  Then temps everywhere dropped the last six months, hitting bottom in February 2021.  All regions were well below the Global Mean since 2015, matching the cold of 2018, and lower than January 2015. Now the spring is bringing more temperate waters and a return to the mean anomaly since 2015.  June Global SST anomaly cooled off back to April due to dropping temps in SH and the Tropics.  NH continued its summer rise, but only slightly and well below the last two Junes.

Hadsst062021
A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  

Note that higher temps in 2015 and 2016 were first of all due to a sharp rise in Tropical SST, beginning in March 2015, peaking in January 2016, and steadily declining back below its beginning level. Secondly, the Northern Hemisphere added three bumps on the shoulders of Tropical warming, with peaks in August of each year.  A fourth NH bump was lower and peaked in September 2018.  As noted above, a fifth peak in August 2019 and a sixth August 2020 exceeded the four previous upward bumps in NH.

In 2019 all regions had been converging to reach nearly the same value in April.  Then  NH rose exceptionally by almost 0.5C over the four summer months, in August 2019 exceeding previous summer peaks in NH since 2015.  In the 4 succeeding months, that warm NH pulse reversed sharply. Then again NH temps warmed to a 2020 summer peak, matching 2019.  This has now been reversed with all regions pulling the Global anomaly downward sharply, tempered by warming in March to May, and now dropping below the global mean anomaly since 2015.

And as before, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.  Note the May warming was strongest in the Tropics, though the anomaly is quite cool compared to 2016.

A longer view of SSTs

The graph below  is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July.

 

Hadsst1995to 062021

1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino.  The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99.  For the next 2 years, the Tropics stayed down, and the world’s oceans held steady around 0.2C above 1961 to 1990 average.

Then comes a steady rise over two years to a lesser peak Jan. 2003, but again uniformly pulling all oceans up around 0.4C.  Something changes at this point, with more hemispheric divergence than before. Over the 4 years until Jan 2007, the Tropics go through ups and downs, NH a series of ups and SH mostly downs.  As a result the Global average fluctuates around that same 0.4C, which also turns out to be the average for the entire record since 1995.

2007 stands out with a sharp drop in temperatures so that Jan.08 matches the low in Jan. ’99, but starting from a lower high. The oceans all decline as well, until temps build peaking in 2010.

Now again a different pattern appears.  The Tropics cool sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off.  But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average.  In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16.  NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peaks came in 2019 and 2020, only this time the Tropics and SH are offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021, then all regions rose to bring the global anomaly above the mean since 1995, before backing down in June 2021.

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH.  The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before.  After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.
AMO Aug and Dec 2021The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020.  Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

AMO decade 062021
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The black line shows that 2020 began slightly warm, then set records for 3 months. then dropped below 2016 and 2017, peaked in August ending below 2016. Now in 2021, AMO is tracking the coldest years, warming slightly in May and June.

Summary

The oceans are driving the warming this century.  SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.”  The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect.  The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? If the pattern of recent years continues, NH SST anomalies may rise slightly in coming months, but once again, ENSO which has weakened will probably determine the outcome.

Footnote: Why Rely on HadSST3

HadSST3 is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST3 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

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USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

 

 

Imperfect Climate Scientists

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Tom Chivers writes with insight as Unherd’s science editor Can we trust the climate scientists?  Excerpts in italics with my bolds.

The reaction to Steven Koonin’s book highlights just how toxic this debate has become

There’s a problem with writing about science — any science — which is that scientists are human like the rest of us. They are not perfect disembodied truth-seeking agents but ordinary, flawed humans navigating social, professional and economic incentive structures.

Most notably, scientists, like people, are social. If they exist in a social or professional circle that believes X, it is hard to say not-X; if they have professed to believe Y, they won’t want to look silly and admit not-Y. It might even be hard to get research funded or published if it isn’t in line with what the wider group believes.

All this makes it very hard, as an outsider, to assess some scientific claims. You can ask some expert, but they will be an expert within the social and professional milieu that you’re looking at, and who will likely share the crony beliefs of that social and professional milieu. All of which often makes it hard to disentangle why scientists do and say the things they do. Especially when it comes to scientific claims that are politically charged, claims on hot-button topics like race, sex, poverty — and of course climate.

I couldn’t help thinking about that as I was reading Steven Koonin’s new book, Unsettled. Koonin is (as it says, prominently, on the front of the book) the “former Undersecretary for Science, US Department of Energy, under the Obama administration”. The publishers are obviously very keen to stress the Obama link: “…under the Trump administration” might not have carried the same heft.

Koonin came to public attention a few years ago, after he wrote a controversial opinion piece for the Wall Street Journal headlined “Climate science is not settled”. It was a response to what he considered the widely held opinion among policymakers and the wider public that, in fact, climate science is settled. His particular concern was that we can’t yet accurately predict what the future climate shifts will be. The book itself is best thought of as the extended version of that op-ed, with added graphs.

Climate Science is not Settled:  We can break down his thesis into, roughly, three areas.

One, is that despite “the mainstream narrative among the media and policymakers”, it is hard to be sure that the climate has changed in meaningful ways due to human influence. In particular, floods, rainfall, droughts, storms, and record high temperatures have not become more common, and although the climate is unambiguously warming and sea levels have gone up, it’s hard to confidently separate human influence from natural variability.

Two, he says, climate models are highly uncertain and struggle to successfully predict the past, let alone the future, so we shouldn’t trust confident claims about the climate future. And if we do accept the IPCC’s predictions, they aren’t of imminent catastrophe. Instead, they point to slow change to which humanity can easily adapt, and, broadly speaking, to humanity continuing to prosper.

And three, he continues, there is basically nothing we can do about it anyway, partly because carbon dioxide hangs around in the atmosphere for so long, but mainly because the developing world is developing fast, and using ever more carbon to do so, and actually that’s a good thing.

These are — according to Koonin — all, by and large, only what the IPCC assessment reports and other major climate analyses say.

The public conversation, which he says is full of doom and apocalypse and unwarranted certainty, has become unconnected from the state of the actual science. And he blames scientists — and policymakers, the media and the public — for that disconnection.

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So is he right? Certainly he has a case when it comes to Point One: I think he is correct that the media narrative about climate change is not especially well correlated with the IPCC’s own central assessments. For instance, I think it’s fair to say that the recent floods in London, China and Germany have been held up as examples of a changing climate. But the IPCC’s most recent assessment report, 2014’s AR5, found studies showing evidence for “upward, downward or no trend in the magnitude of floods” (see p214 of the AR5 Physical Science Basis document; be warned it’s a big PDF), and concluded that they were unable to be sure whether, globally, river floods had become more or less likely.

Similarly, I think there is a perception among many commentators and policymakers that storms, hurricanes, and droughts are all more common as a result of climate change, but the IPCC’s own report (see p.53 of AR5) has “low confidence” that those things are more common than they were 100 years ago. I know some scientists think the IPCC is overoptimistic, but it is the closest we have to consensus climate science.

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That said, there is some fairness in accusing Koonin of cherrypicking. He spends a lot of time arguing about extreme daily temperatures, convincingly (to my mind) debunking a claim in the 2017 Climate Science Special Report (CSSR), the flagship US government climate science assessment, that US extreme daily temperature records have gone up. In fact, CSSR is comparing the ratio of extreme high temperatures to extreme low temperatures, and what in fact has happened is that extreme low temperatures have become less common. Which is interesting.

But the IPCC does think extreme daily temperatures have gone up globally (see p53 again). In his chapter on “Hyping the Heat”, Koonin doesn’t mention the IPCC, and the IPCC outranks the CSSR. His detective work is interesting, but he is fighting a henchman, not the end-of-level boss. Maybe the IPCC is wrong as well, but we don’t learn that here.

On Point Two, I don’t feel competent to assess the models; certainly it seems highly plausible to me that there are enormous uncertainties in predicting something as inherently chaotic as the climate, especially when to do so you first have to predict something as inherently chaotic as people. But my non-expert understanding is that broadly speaking the models have been getting it about right.

That said, I think he is right that, if you were to ask the average person in my social circle, you would hear that climate change will lead to catastrophe in the near future. And I think that is overstating what the IPCC reports actually say. For instance, it is true that the IPCC predicts more people will go hungry than otherwise would have: it says that almost 140 million children will be undernourished, in a world where climate change goes unmitigated, compared to 113 million in a world where there is no climate change (see p730 of this IPCC report). But that is still fewer than went hungry in 2000 – almost 150 million, out of a much smaller population. The IPCC predicts that a world with climate change will be worse than one without; but not so much worse that other things, such as economic growth and technological progress, won’t broadly keep the big things, like life expectancy and human health, improving. That does seem worth saying.

And Koonin’s Point Three is worth making too. If India were to increase its per capita emissions to those of Japan, “one of the lowest emitting of the developed countries”, he says, then that change alone would raise global emissions by 25%1. Realistically, we’re not going to be able to stop India — or China, or Brazil, or Mexico, or any of the other middle-income countries — from developing, and development at the moment means carbon.

More importantly: we don’t want them to stop developing. Richer countries have healthier, longer-lived citizens and are better able to cope with a changing climate. Even huge, swingeing cuts to Western emissions — politically unrealistic — would only go some way to offsetting the inevitable growth in the developing world. Those cuts may be worth doing, but there are limits to how much good they can do.

But even if Koonin is right about almost everything — if the best guess of the science is that we’re heading towards things merely getting better more slowly, rather than getting worse — then I think he’s missing a major point. That is, climate change models are uncertain. In fact Koonin claims they’re even more uncertain than we think. So they could easily be erring on the side of optimism.

And the one thing we should have learnt from the Covid pandemic is that it’s not enough to say “the most likely outcome is that it’ll be fine, so let’s act as if it’ll be fine.” The correct thing to say is “the most likely outcome is that it’ll be fine, but if there’s a 10% chance that it’ll be completely awful, then we need to prepare for that 10% chance.” Reducing greenhouse gas emissions in the developed world reduces the chance of some unforeseen but plausible disaster: as a happy bonus, it makes our cities more pleasant places in which to live. It will come at some cost, but hopefully not too high, because green technology is getting so cheap and effective these days.

Reviews by climate scientists have been unimpressed. “I would normally ignore a book by a non-climate scientist,” starts one review, which goes on to not ignore it. Another accuses him of cherry-picking his fights (not entirely unfairly, as I said). A third says the book is “distracting, irrelevant, misguided, misleading and unqualified”.

But none that I’ve read really addresses the nitty-gritty of his arguments — which is hard to do in a 900-word review, of course, but still. They usually pick some line out of the first chapter or two, disagree with it, and then say the whole book is therefore rubbish. But I wanted a bit more meat to the objections.

The third review, for instance, quotes Koonin as saying “The warmest temperatures in the US have not risen in the past fifty years,” and then asks “According to what measure?” Well, Koonin tells you the measure, at length: absolute record extreme daily temperatures. Maybe he’s wrong, but he does answer that in the book. (And your next sentence is “Highest annual global averages?” He’s talking about the US! You just quoted that bit!)

Similarly, it complains that Koonin says that the sea is only rising about a foot per century, saying “The trouble is that while seas have risen eight to nine inches since 1880, more than 30 percent of that increase has occurred during the last two decades.” But again: Koonin addresses this, for pretty much an entire chapter. His point is that most of the rest of the rise came during an (unexplained by climate models, according to him) period of rapid warming from 1910 to 1940, before human influence should have been relevant. That, he says, is good evidence that natural variation is driving the current acceleration. Is he right? I don’t know. But the reviewer is not attacking Koonin’s argument at its strongest point.

In fact, none of them seem to: they just want to dismiss the book. They attack Koonin’s credibility and credentials, his temperament. They say he was only hired by the Obama Energy Department because of his contrarian views; they call him a “climate denier”, which seems de trop since he accepts most of the central claims of the climate consensus. The response felt more like a circling of the wagons than a serious effort to counter a serious argument. After all, it is unpleasant to hear reasons why you might be wrong about something: cognitive dissonance is painful.

I started this book confident that climate change is a serious concern, and I finished it only slightly less confident; Koonin has not persuaded me. But I’m glad Unsettled, flawed though it is, has been written. As I said at the beginning, science in a politically charged environment is very hard to assess. Scientists are as prone to groupthink and motivated reasoning as anyone else, and I know very well that there are some who feel they need to keep heterodox views quiet. The reviews, which make so little effort to engage with the substance of the arguments, do not reassure me that climate science is a uniquely groupthink-free discipline.

One thing Koonin suggests is a so-called “Red Teaming” of climate scientists: getting scientists to act as adversarial critics of the existing consensus, a method used by superforecasters, among others, to improve their accuracy by actively hunting out flaws in their reasoning. Science can only progress if assumptions are tested. Red teams in climate institutions — any institutions — seem like a good idea, and I’d support them.

Whether it’s possible or not, of course, is tricky to say. The climate debate is so highly charged, so borderline toxic, that it might be difficult for any climate scientist to take on the red-team role without making their own life more difficult. According to Koonin, one senior climate scientist told him “I agree with pretty much everything you wrote, but I don’t dare say that in public.” The old “in my emails, everyone agrees with me” line is hardly a new one, but it wouldn’t surprise me if there’s a bit of truth in it.

But if the Catholic Church was able to stomach someone advocating for the Devil, then climate science should be able to stomach one doing it for the sceptics. And in the meantime, this book does an acceptable job.

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Footnote:  I encourage you to read the comments at the Unherd website.  For example this from Norman Powers:

I feel that’s a bit unfair to Tom. Reading the arguments of people who disagree, thinking about them carefully and weighing up debate is a large part of critical thinking, and he does all those things in this article. Just because he hasn’t arrived at the same conclusions as you (yet?) doesn’t make it not critical thinking.

Moreover, the social factors that apply to scientists apply to journalists as well. Do you think it’s easy for Chivers to talk about climatology and criticize climatologists so directly? He basically says none of their reviews of the book even meet basic standards of coherence, let alone being convincing. There aren’t many media outlets that would pay for such journalism, regardless of the truth.

Beyond your criticism of the author I feel all your points are well made.

For me, what really shook my belief in climatology to the core was the discovery that the temperature record itself is the output of modelling. Yes, you read that right. Not merely predictions about the future or truly ancient temperatures come out of models. Temperatures recorded by thermometer, in Europe and the USA, in the past 100 years or even just the past decade, are also the output of models. Although the raw data is given as an input the models proceed to heavily modify it; the outputs are then presented as “the history of temperature” without making it obvious what’s happened.

One of the consequences of this is that temperature time series often have multiple “versions”, reflecting the fact that the model software evolves over time. These new versions invariably seem to create warming when the prior versions didn’t show it. This has been going on for decades. They have a variety of justifications, all of which sound plausible on first glance, some of which seem less plausible on deeper analysis.
But. At school I was taught in no uncertain terms that in science you are not allowed to edit your raw data. All the marks for science assignments were allocated to the methodological correctness, and if you did an experiment and the data didn’t line up with the theory but what you did followed the rules, you wouldn’t be marked down (of course, in practice, if you failed to replicate a simple and famous experiment you probably did make a mistake somewhere so the distinction rarely mattered).

This was their way of teaching us that the rules are there for a reason, and that scientists aren’t allowed to tamper with their data post-facto. That’s taboo. Except, not in climatology. The risks are obvious: climatologists only really have one theory, so data that shows temperatures not going up undermines the entire community. Once the Rubicon has been crossed and model outputs are being substituted for real data, it’s very easy for people to try lots of different ways to “fix” errors in the data and then select only the ones that line up with what everyone knows “should” be happening. Over time this process keeps repeating until the theories become unfalsifiable.

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Beware Energy Balance Cartoons

Figure 1. The global annual mean energy budget of Earth’s climate system (Trenberth and Fasullo, 2012.)

Recently in a discussion thread a warming proponent suggested we read this paper for conclusive evidence. The greenhouse effect and carbon dioxide by Wenyi Zhong and Joanna D. Haigh (2013) Imperial College, London. Indeed as advertised the paper staunchly presents IPCC climate science. Excerpts in italics with my bolds.

IPCC Conception: Earth’s radiation budget and the Greenhouse Effect

The Earth is bathed in radiation from the Sun, which warms the planet and provides all the energy driving the climate system. Some of the solar (shortwave) radiation is reflected back to space by clouds and bright surfaces but much reaches the ground, which warms and emits heat radiation. This infrared (longwave) radiation, however, does not directly escape to space but is largely absorbed by gases and clouds in the atmosphere, which itself warms and emits heat radiation, both out to space and back to the surface. This enhances the solar warming of the Earth producing what has become known as the ‘greenhouse effect’. Global radiative equilibrium is established by the adjustment of atmospheric temperatures such that the flux of heat radiation leaving the planet equals the absorbed solar flux.

The schematic in Figure 1, which is based on available observational data, illustrates the magnitude of these radiation streams. At the Earth’s distance from the Sun the flux of radiant energy is about 1365Wm−2 which, averaged over the globe, amounts to 1365/4 = 341W for each square metre. Of this about 30% is reflected back to space (by bright surfaces such as ice, desert and cloud) leaving 0.7 × 341 = 239Wm−2 available to the climate system. The atmosphere is fairly transparent to short wavelength solar radiation and only 78Wm−2 is absorbed by it, leaving about 161Wm−2 being transmitted to, and absorbed by, the surface. Because of the greenhouse gases and clouds the surface is also warmed by 333Wm−2 of back radiation from the atmosphere. Thus the heat radiation emitted by the surface, about 396Wm−2, is 157Wm−2 greater than the 239Wm−2 leaving the top of the atmosphere (equal to the solar radiation absorbed) – this is a measure of ‘greenhouse trapping’.

Why This Line of Thinking is Wrong and Misleading
Principally, the Earth is not a disk illuminated 24/7 by 1/4 of solar radiant energy. 

That disk in the cartoon denies the physical reality of a rotating sphere, and completely distorts the energy dynamics.  Christos Vournas addresses this issue directly in deriving his planetary temperature equation that corresponds to NASA satellite measurements of planets and moons in our solar system.  Previous posts provide background for this one focusing on the radiant heating of the rotating water planet we call Earth (though Ocean would be more accurate).  See How to Calculate Planetary Temperatures and Earthshine and Moonshine: Big Difference.  

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Φ – is the dimensionless Solar Irradiation accepting factor. It recognizes that a sphere’s surface absorbs the incident solar irradiation not as a disk of the same diameter, but accordingly to its spherical shape. For a smooth spherical surface Φ = 0,47

The classical blackbody surface properties

A blackbody planet surface is meant as a classical blackbody surface approaching.  Here are the blackbody’s properties:

1. Blackbody does not reflect the incident on its surface radiation. Blackbody absorbs the entire radiation incident on its surface.

2. Stefan-Boltzmann blackbody emission law is:   Je = σ*Τe⁴

Notice:

Te is the blackbody’s temperature (surface) at every given moment. When the blackbody is not irradiated, the classical blackbody gradually cools down, gradually emitting away its accumulated energy.  The classical blackbody concept assumes blackbody’s surface being warmed by some other incoming irradiation source of energy – see the Sun’s paradigm.  Sun emits like a blackbody, but it emits its own inner energy source’s energy. Sun is not considered as an irradiation receiver. And sun has a continuous stable temperature.

Therefore we have here two different blackbody theory concepts.

a. The blackbody with the stable surface temperature due to its infinitive inner source (sun, stars).
b. The blackbody with no inner energy source.

This blackbody’s emission temperature relies on the incoming outer irradiation only.

Also in the classical blackbody definition it is said that the irradiation incident on the blackbody is totally absorbed, warms the blackbody and achieves an equilibrium emission temperature Te.  It is an assumption.

This assumption, therefore, led to the next assumption: the planet like a blackbody emitting behavior.  And, consequently, it resulted to the planet’s Te equation, in which it is assumed that planet’s surface is interacting with the incoming irradiation as being in a uniform equilibrium temperature.

Consequently it was assumed that planet’s surface had a constant equilibrium temperature (which was only the incident solar irradiation dependent value) and the only thing the planet’s surface did was to emit in infrared spectrum out to space the entire absorbed solar energy.

3. When irradiated, the blackbody’s surface has emission temperature according to the Stefan-Boltzmann Law:

Te = (Total incident W /Total area m² *σ)¹∕ ⁴ K

σ = 5,67*10⁻⁸ W/m²K⁴, the Stefan-Boltzmann constant.

Notice: This emission temperature is only the incoming irradiation energy depended value. Consequently when the incoming irradiation on the blackbody’s surface stops, at that very moment the blackbody’s emission temperature disappears.  It happens because no blackbody’s surface accumulates energy.

4. Blackbody interacts with the entire incident on the blackbody’s surface radiation.

5. Blackbody’s emission temperature depends only on the quantity of the incident radiative energy per unit area.

6. Blackbody is considered only as blackbody’s surface physical properties. Blackbody is only a surface without “body”.

7. Blackbody does not consist from any kind of a matter. Blackbody has not a mass. Thus blackbody has not a specific heat capacity.  Blackbody’s cp = 0.

8. Blackbody has surface dimensions. So blackbody has the radiated area and blackbody has the emitting area.

9. The entire blackbody’s surface area is the blackbody’s emitting area.

10. The blackbody’s surface has an infinitive conductivity.

11. All the incident on the blackbody’s surface radiative energy is instantly and evenly distributed upon the entire blackbody’s surface.

12. The radiative energy incident on the blackbody’s surface the same very instant the blackbody’s surface emits this energy away.

A Real Planet is Not a Blackbody

But what happens there on the rotating real planet’s surface?

The rotating real planet’s surface, when it turns to the sunlit side, is an already warm at some temperature, from the previous day, planet’s surface.

Thus, when assuming the planet’s surface behaving as a blackbody, we face the combination of two different initial blackbody surfaces.

a. The one with an inner energy source.

And

b. The one warmed by an outer irradiation.

The Real Planet’s Surface Properties:

1. The planet’s surface has not an infinitive conductivity. Actually the opposite takes place. The planet’s surface conductivity is very small, when compared with the solar irradiation intensity and the planet’s surface infrared emissivity intensity.

2. The planet’s surface has thermal behavior properties. The planet’s surface has a specific heat capacity, cp.

3. The incident on the planet solar irradiation is not being distributed instantly and evenly on the entire planet’s surface area.

4. Planet does not accept the entire solar irradiation incident in planet’s direction. Planet accepts only a small fraction of the incoming solar irradiation. This happens because of the planet’s albedo, and because of the planet’s smooth and spherical surface reflecting qualities, which we refer to as “the planet’s solar irradiation accepting factor Φ”.

Planet reflects the (1-Φ + Φ*a) portion of the incident on the planet’s surface solar irradiation.  And  Planet absorbs only the Φ(1 – a) portion of the incident on the planet’s surface solar irradiation.

Here “a” is the planet’s average albedo and “Φ” is the planet’s solar irradiation accepting factor.

For smooth planet without thick atmosphere, Earth included, Φ=0,47

5. Planet’s surface has not a constant intensity solar irradiation effect. Planet’s surface rotates under the solar flux. This phenomenon is decisive for the planet’s surface infrared emittance distribution.

The real planet’s surface infrared radiation emittance distribution intensity is a planet’s rotational speed dependent physical phenomenon.

Vournas fig1

Φ factor explanation

The Φ – solar irradiation accepting factor – how it “works”. It is not a planet specular reflection coefficient itself.

There is a need to focus on the Φ factor explanation. Φ factor emerges from the realization that a sphere reflects differently than a flat surface perpendicular to the Solar rays.

It is very important to understand what is really going on with planets’ solar irradiation reflection.

There is the specular reflection and there is the diffuse reflection.

The planet’s surface Albedo “a” accounts for the planet’s surface diffuse reflection. Albedo is defined as the ratio of the scattered SW to the incident SW radiation, and it is very much precisely measured (the planet Bond Albedo).

So till now we didn’t take in account the planet’s surface specular reflection. A smooth sphere, as some planets are, are invisible in space and have so far not been detected and the specular reflection not measured . The sphere’s specular reflection cannot be seen from the distance, but it can be seen by an observer situated on the sphere’s surface.

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Thus, when we admire the late afternoon sunsets on the sea we are blinded from the brightness of the sea surface glare. It is the surface specular reflection that we see then.

Jsw.absorbed = Φ*(1-a) *Jsw.incoming

For a planet with albedo a = 0 (completely black surface planet) we would have

Jsw.reflected = [1 – Φ*(1-a)]*S *π r² =

Jsw.reflected = (1 – Φ) *S *π r²

For a planet which captures the entire incident solar flux (a planet without any outgoing specular reflection) we would have Φ = 1

Jsw.absorbed = Φ*(1-a) *Jsw.incoming

Jsw.reflected = a *Jsw.incoming

And

For a planet with Albedo a = 1 , a perfectly reflecting planet

Jsw.absorbed = 0 (no matter what is the value of Φ)

In general:  The fraction left for hemisphere to absorb is  Jabs = Φ (1 – a ) S π r²

We have Φ for different planets’ surfaces varying  0,47 ≤ Φ ≤ 1

And we have surface average Albedo “a” for different planets’ varying  0 ≤ a ≤ 1

Notice:

Φ is never less than 0,47 for planets (spherical shape).

Also, the coefficient Φ is “bounded” in a product with (1 – a) term, forming the Φ(1 – a) product cooperating term. Thus Φ and Albedo are always bounded together.

The Φ(1 – a) term is a coupled physical term.

The Φ(1 – a) term “translates” the absorption of a disk into the absorption of a smooth hemisphere with the same radius.

When covering a disk with a hemisphere of the same radius the hemisphere’s surface area is 2π r². The incident Solar energy on the hemisphere’s area is the same as on the disk:  Jdirect = π r² S

But the absorbed Solar energy by the hemisphere’s area of 2π r² is:  Jabs = Φ*( 1 – a) π r² S

It happens because a smooth hemisphere of the same radius “r” absorbs only the Φ*(1 – a)S portion of the directly incident on the disk of the same radius Solar irradiation.

In spite of hemisphere having twice the area of the disk, it absorbs only the Φ*(1 – a)S portion of the directly incident on the disk Solar irradiation.

Gaseous Planets

Φ = 1 for gaseous planets, as Jupiter, Saturn, Neptune, Uranus, Venus, Titan.

Gaseous planets do not have a surface to reflect radiation. The solar irradiation is captured in the thousands of kilometers gaseous abyss. The gaseous planets have only the albedo “a”.

Heavy Cratered Planets

Φ = 1 for heavy cratered planets, as Calisto and Rhea ( not smooth surface planets, without atmosphere ).

The heavy cratered planets have the ability to capture the incoming light in their multiple craters and canyons. The heavy cratered planets have only the albedo “a”.

That is why the albedo “a” and the factor “Φ” we consider as different values. Both of them, the albedo “a” and the factor “Φ” cooperate in the

Energy in = Φ(1 – a) left side of the Planet Radiative Energy Budget.

Conclusively, the Φ -Factor is not the planet specular reflection portion itself.

The Φ -Factor is the Solar Irradiation Accepting Factor (in other words, Φ is the planet surface shape and roughness coefficient).

Bottom Line

What is going on here is that instead of Jabs.earth = 0,694* 1.361 π r² ( W ) we should consider Jabs.earth = 0,326* 1.361 π r² ( W ).

Averaged on the entire Earth’s surface we obtain:

Jsw.absorbed.average = [ 0,47*(1-a)*1.361 W/m² ] /4 =

= [ 0,47*0,694*1.361W/m² ] /4 = 444,26 W/m2 /4 = 111,07 W/m²

Jsw.absorbed.average = 111,07 W/m² or 111 W/m²

Example:  Comparing Earth and Europa

Earth / Europa satellite measured mean temperatures 288 K and 102 K comparison
All the data below are satellites measurements. All the data below are observations.

Planet Earth Europa
Tsatmean  288 K 102 K
R 1 AU 5.2044 AU
1/R² 1 0,0369
N 1 1/3.5512 rot/day
a 0.3 0.63
(1-a) 0.7 0.37
coeff 0.91469 0.3158

We could successfully compare Earth /Europa ( 288 K /102 K ) satellite measured mean temperatures because both Earth and Europa (moon of Jupiter) have two identical major features.

Φearth = 0,47 because Earth has a smooth surface and Φeuropa = 0,47 because Europa also has a smooth surface.

cp.earth = 1 cal/gr*°C, it is because Earth has a vast ocean. Generally speaking almost the whole Earth’s surface is wet. We can call Earth a Planet Ocean.  Europa is an ice-crust planet without atmosphere, Europa’s surface consists of water ice crust, cp.europa = 1cal/gr*°C.

The table below shows how well the universal equation estimates temperatures of planets and moons measured by NASA.

Planet Φ Te.correct  [(β*N*cp)¹∕ ⁴]¹∕ ⁴ Tmean  Tsat
Mercury  0.47 364 0.8953 325.83 340
Earth  0.47 211 1.3680 287.74 288
Moon  0.47 224 0.9978 223.35 220
Mars  0.47 174 1.2270 213.11 210
Io  1 95.16 1.1690 111.55 110
Europa  0.47 78.83 1.2636 99.56 102
Ganymede 0.47 88.59 1.2090 107.14 110
Calisto  1 114.66 1.1471 131.52 134 ±11
Enceladus  1 55.97 1.3411 75.06 75
Tethys  1 66.55 1.3145 87.48 86 ± 1
Titan  1 84.52 1.1015 96.03 93.7
Pluto  1 37 1.1164 41.60 44
Charon  1 41.9 1.2181 51.04 53
My Comment:

This post explains why it is an error to treat Earth (or any planetary body) as a classic blackbody in either the absorption of incident energy or in the emission of radiation.  Thus the typical energy balance cartoons are not funny, they are false and misleading.  A further error arises in claiming that greenhouse gases like CO2 in the atmosphere cause surface warming by trapping Earth radiation and slowing the natural cooling.  This fallacy is addressed directly in a previous post Why CO2 Can’t Warm the Planet.

The table above and graph below show that Earth’s warming factor is correctly calculated despite ignoring any effect from its thin atmosphere.

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Earthshine and Moonshine: Big Difference

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A previous post elaborated a rigorous equation from Christos Vournas for calculating surface temperatures of planets or moons, for comparison with NASA satellite measurements of such bodies in our solar system.  That post is How to Calculate Planetary Temperatures.

The image above presents the huge disparity in day and night temperatures between Earth and its Moon, and notes the role of ocean heat transport.  But as I have learned from Christos, there is much more to the story, and this post discusses these deeper implications.  He adds the rotational factor and its impact upon the radiation emitted by both bodies, ie. Earthshine and Moonshine (though obviously it is not simply visible light).  Excerpts from Vournas are in italics with my bolds.

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Moon and Earth – so close to each other – and so much different…

Moon is in our immediate neighborhood

Moon rotates around its axis at a slow rate of 29.5 days.  The day on the Moon is 14.75 earth days long, and the night on the Moon is also 14.75 Earth days long. 

Moon is in our immediate neighborhood. So Moon is at the same distance from the sun, as Earth, R=1 AU (astronomical unit).  The year average solar irradiation intensity on the top of atmosphere for Moon and Earth is the same

So = 1361 W/m².

We say “on the top of the atmosphere”, it means the solar intensity which reaches a celestial body and then falls on it. For certain then, during these 14.75 earth days long lunar day the Moon’s surface gets warmed at much higher temperatures than the Earth.

There is the Planet Surface Rotational Warming Phenomenon

I’ll try here in few simple sentences explain the very essence of how the planet rotational warming Phenomenon occurs.

Lets consider two identical planets F and S at the same distance from the sun.  Let’s assume the planet F spins on its axis Faster, and the planet S spins on its axis Slower.  Both planets F and S get the same intensity solar flux on their sunlit hemispheres. Consequently both planets receive the same exact amount of solar radiative energy.

The slower rotating planet’s S sunlit hemisphere surface gets warmed at higher temperatures than the faster rotating planet’s F sunlit hemisphere. The surfaces emit at σT⁴ intensity – it is the Stefan-Boltzmann emission law.

Thus the planet S emits more intensively from the sunlit side than the planet F.  There is more energy left for the planet F to accumulate then.  That is what makes the faster rotating planet F on the average a warmer planet.

That is how the Planet Surface Rotational Warming Phenomenon occurs.

And it becomes very cold on the Moon at night

Moon gets baked hard during its 14,75 earth days long lunar day.  And Moon also emits hard from its very hot daytime surface.  What else can the very hot surface do but to emit hard, according to the Stefan-Boltzmann emission Law.  The very hot surface emits in fourth power of its very high absolute temperature.

Jemit ~ T⁴

A warm object in space loses heat via emission. The hotter is the object, the faster it loses heat.  So there is not much energy left to emit during the 14.75 earth days long lunar night.

The Table below shows the implications:

Planet Tsat mean Rotations Tmin Tmax
Mercury 340 K 1/176 100K 700K
Earth 288 K 1
Moon 220 Κ 1/29.5 100K 390K
Mars 210 K 0.9747 130K 308K
Comparing Mars and Mercury

The closest to the sun planet Mercury receives 15.47 times stronger solar irradiation intensity than the planet Mars does.  However on the Mercury’s dark side Tmin.mercury = 100 K, when on the Mars’ dark side Tmin.mars = 130 K.

These are observations, these are from satellites the planets’ temperatures measurements.  And they cannot be explained otherwise but by the planet Mars’ 171.5 times faster rotation than planet Mercury’s spin.

Earth-Moon temperatures comparison -why the differences

The faster (than Moon) Earth’s rotation smooths the average heat. The higher (than Moon) Earth’s surface specific heat capacity(oceanic waters vs dry regolith), also smooths the average heat. Consequently the daytime Earth’s surface temperature (compared to Moon) lessens, and the nighttime Earth’s surface temperature (compared to Moon) rises. Earth receives the same amount of solar heat (per unit area) from sun as Moon – for the same albedo. And Earth emits the same amount of solar heat, as the Moon does.

But something else very interesting happens.

It is the difference between Earth’s and Moon’s emitting temperatures. At the daytime Earth’s surface is warmed at a much lower temperatures and therefore at the daytime Earth’s surface emits IR radiation at a much lower intensities. So the intensity of Earth’s daytime IR radiation is much lower (than Moon’s).

As a result, there is a great amount of energy – compared to Moon – “saved” on Earth during the daytime emission..  This “saved” energy should be emitted by Earth’s surface during the nighttime then. At the night-time Earth’s surface is warmer than Moon’s and therefore Earth’s surface at night-time is at a higher temperatures.  So the intensity of Earth’s night-time IR radiation is higher.

There is always a balance.  The energy in = the energy out

But again something else very interesting happens.

In order to achieve that balance Earth’s night-time IR emitting intensity should be much higher than the night-time IR emitting intensity of the Moon.  Now we should take notice of the nonlinearity of the Stefan-Boltzmann emission law. Consequently the night-time temperatures on Earth rise higher (compared to Moon) than the daytime temperatures on Earth lessens.

So the average Earth’s surface temperature is warmer (compared to the Moon). Thus Earth’s Tmean.earth = 288 K and Moon’s Tmean.moon = 220 K

The faster rotation and the higher specific heat capacity does not make sun to put more energy in the Earth’s surface. What the faster rotation and the higher specific heat capacity do is to modify the way Earth’s surface emits, the same amount as Moon, of energy (per unit area).

Earth emits IR radiation at lower temperatures during the daytime and at higher temperatures at night-time. Because of the nonlinearity of this process according to the Stefan-Boltzmann emission law, Earth ends up to have on average warmer surface than Moon.

The night-time temperatures on Earth rise higher (compared to Moon) than the day-time temperatures on Earth lessens. Earth receives (for the same albedo and per unit area) the same amount of solar energy as the Moon . This energy is “welcomed” on each planet and processed in a unique way for each planet.

To illustrate the above conclusions I’ll try to demonstrate on the Earth-Moon temperatures comparison rough example:

Surface temperatures

.min……mean……max

Tmin↑↑→T↑mean ←T↓max

Moon…100 K…220 K …390 K

Δ………..+84 K +68 K….- 60 Κ

Earth…184K↑↑.288 K↑.330 K↓

So we shall have for the faster rotating Earth, compared to the Moon:

Tmin↑↑→ T↑mean ← T↓max

+84↑↑→ +68↑mean ← -60↓

The faster a planet rotates (n2>n1) the higher is the planet’s average (mean) temperature T↑mean.

Note:  To emphasize we should mention that Moon’s max and min temperatures are measured on Moon’s equator, and Earth’s max and min temperatures are not.  Earth’s max and min temperatures are measured on continents, and not on oceanic waters. Otherwise the Δmin would have been even bigger and the Δmax would have been much smaller.

This rough example nevertheless illustrates that for the faster rotating and covered with water (higher cp) Earth compared with Moon the average temperature should be higher.

The planet’s faster rotation and the planet’s higher specific heat capacity “cp” not only smooths, but also processes ( Δmin > Δmax ), the same incoming solar heat, but in a different emission pattern.

Earth is warmer because Earth rotates faster and because Earth’s surface is covered with water

We had to answer these two questions:

1. Why Earth’s atmosphere doesn’t affect the Global Warming?

It is proven now by the Planet’s Mean Surface Temperature Equation calculations. There aren’t any atmospheric factors in the Equation. Nevertheless the Equation produces very reasonable results:

Tmean.earth = 287,74 K,  calculated by the Equation, which is the same as the Tsat.mean.earth = 288 K, measured by satellites.

Tmean.moon = 223,35 K, calculated by the Equation, which is almost identical with the Tsat.mean.moon = 220 K, measured by satellites.

2. What causes the Global Warming then?

The Global Warming is happening due to the orbital forcing.

And… what keeps Earth warm at Tmean.earth = 288 K, when Moon is at Tmean.moon = 220 K? Why Moon is on average 68 oC colder? It is very cold at night there and it is very hot during the day…

Earth is warmer because Earth rotates faster and because Earth’s surface is covered with water.

Does the Earth’s atmosphere act as a blanket that warms Earth’s surface?

No, it does not.

.

They Worried Us Sick

cfarmafoto1275521

John Tierney writes at City Journal The Panic Pandemic.  

The first part of the article is a refresher on how it happened that all those who talked reasonably in the face of the panic narrative, were silenced and banished from public discourse.  Included are many recognizable names:  John Ioannidis, Jay Bhattacharya, Thomas Benfield, Stefan Baral, Martin Kulldorff, Sunetra Gupta,  and the most reviled heretic, Scott Atlas.  The excerpts below in italics (with my bolds and images) express Tierney’s conclusions to take away from this sorry mess.

Fearmongering from journalists, scientists, and politicians did more harm than the virus.

The United States suffered through two lethal waves of contagion in the past year and a half. The first was a viral pandemic that killed about one in 500 Americans—typically, a person over 75 suffering from other serious conditions. The second, and far more catastrophic, was a moral panic that swept the nation’s guiding institutions.

Instead of keeping calm and carrying on, the American elite flouted the norms of governance, journalism, academic freedom—and, worst of all, science. They misled the public about the origins of the virus and the true risk that it posed. Ignoring their own carefully prepared plans for a pandemic, they claimed unprecedented powers to impose untested strategies, with terrible collateral damage. As evidence of their mistakes mounted, they stifled debate by vilifying dissenters, censoring criticism, and suppressing scientific research.

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One in three people worldwide lost a job or a business during the lockdowns, and half saw their earnings drop, according to a Gallup poll. Children, never at risk from the virus, in many places essentially lost a year of school. The economic and health consequences were felt most acutely among the less affluent in America and in the rest of the world, where the World Bank estimates that more than 100 million have been pushed into extreme poverty.

The leaders responsible for these disasters continue to pretend that their policies worked and assume that they can keep fooling the public. They’ve promised to deploy these strategies again in the future, and they might even succeed in doing so—unless we begin to understand what went wrong.

But neither the plague nor Trump explains the panic. Yes, the virus was deadly, and Trump’s erratic pronouncements contributed to the confusion and partisanship, but the panic was due to two preexisting pathologies that afflicted other countries, too.

The first pathology is what I have called the Crisis Crisis, the incessant state of alarm fomented by journalists and politicians.

It’s a longstanding problem—humanity was supposedly doomed in the last century by the “population crisis” and the “energy crisis”—that has dramatically worsened with the cable and digital competition for ratings, clicks, and retweets. To keep audiences frightened around the clock, journalists seek out Cassandras with their own incentives for fearmongering: politicians, bureaucrats, activists, academics, and assorted experts who gain publicity, prestige, funding, and power during a crisis.

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Unlike many proclaimed crises, an epidemic is a genuine threat, but the crisis industry can’t resist exaggerating the danger, and doomsaying is rarely penalized. Early in the 1980s AIDS epidemic, the New York Times reported the terrifying possibility that the virus could spread to children through “routine close contact”—quoting from a study by Anthony Fauci. Life magazine wildly exaggerated the number of infections in a cover story, headlined “Now No One Is Safe from AIDS.” It cited a study by Robert Redfield, the future leader of the CDC during the Covid pandemic, predicting that AIDS would soon spread as rapidly among heterosexuals as among homosexuals. Both scientists were absolutely wrong, of course, but the false alarms didn’t harm their careers or their credibility.

Journalists and politicians extend professional courtesy to fellow crisis-mongers by ignoring their mistakes, such as the previous predictions by Neil Ferguson. His team at Imperial College projected up to 65,000 deaths in the United Kingdom from swine flu and 200 million deaths worldwide from bird flu. The death toll each time was in the hundreds, but never mind: when Ferguson’s team projected millions of American deaths from Covid, that was considered reason enough to follow its recommendation for extended lockdowns. And when the modelers’ assumption about the fatality rate proved too high, that mistake was ignored, too.

More Covid Cases

Journalists kept highlighting the most alarming warnings, presented without context. They needed to keep their audience scared, and they succeeded. For Americans under 70, the probability of surviving a Covid infection was about 99.9 percent, but fear of the virus was higher among the young than among the elderly, and polls showed that people of all ages vastly overestimated the risk of being hospitalized or dying.

The second pathology underlying the elite’s Covid panic is the politicization of research—what I have termed the Left’s war on science, another long-standing problem that has gotten much worse.

Just as the progressives a century ago yearned for a nation directed by “expert social engineers”—scientific high priests unconstrained by voters and public opinion—today’s progressives want sweeping new powers for politicians and bureaucrats who “believe in science,” meaning that they use the Left’s version of science to justify their edicts. Now that so many elite institutions are political monocultures, progressives have more power than ever to enforce groupthink and suppress debate. Well before the pandemic, they had mastered the tactics for demonizing and silencing scientists whose findings challenged progressive orthodoxy on issues such as IQ, sex differences, race, family structure, transgenderism, and climate change.

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And then along came Covid—“God’s gift to the Left,” in Jane Fonda’s words. Exaggerating the danger and deflecting blame from China to Trump offered not only short-term political benefits, damaging his reelection prospects, but also an extraordinary opportunity to empower social engineers in Washington and state capitals. Early in the pandemic, Fauci expressed doubt that it was politically possible to lock down American cities, but he underestimated the effectiveness of the crisis industry’s scaremongering. Americans were so frightened that they surrendered their freedoms to work, study, worship, dine, play, socialize, or even leave their homes. Progressives celebrated this “paradigm shift,” calling it a “blueprint” for dealing with climate change.

This experience should be a lesson in what not to do, and whom not to trust.

Do not assume that the media’s version of a crisis resembles reality. Do not count on mainstream journalists and their favorite doomsayers to put risks in perspective. Do not expect those who follow “the science” to know what they’re talking about. Science is a process of discovery and debate, not a faith to profess or a dogma to live by. It provides a description of the world, not a prescription for public policy, and specialists in one discipline do not have the knowledge or perspective to guide society. They’re biased by their own narrow focus and self-interest. Fauci and Deborah Birx, the physician who allied with him against Atlas on the White House task force, had to answer for the daily Covid death toll—that ever-present chyron at the bottom of the television screen—so they focused on one disease instead of the collateral damage of their panic-driven policies.

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“The Fauci-Birx lockdowns were a sinful, unconscionable, heinous mistake, and they will never admit they were wrong,” Atlas says. Neither will the journalists and politicians who panicked along with them. They’re still portraying lockdowns as not just a success but also a precedent—proof that Americans can sacrifice for the common good when directed by wise scientists and benevolent autocrats. But the sacrifice did far more harm than good, and the burden was not shared equally. The brunt was borne by the most vulnerable in America and the poorest countries of the world. Students from disadvantaged families suffered the most from school closures, and children everywhere spent a year wearing masks solely to assuage the neurotic fears of adults. The less educated lost jobs so that professionals at minimal risk could feel safer as they kept working at home on their laptops. Silicon Valley (and its censors) prospered from lockdowns that bankrupted local businesses.

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Luminaries united on Zoom and YouTube to assure the public that “we’re all in this together.” But we weren’t. When the panic infected the nation’s elite—the modern gentry who profess such concern for the downtrodden—it turned out that they weren’t so different from aristocrats of the past. They were in it for themselves.

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Deception: Climate Financial Risk

Carney GQ

John H. Cochrane writes at Project Syndicate The Fallacy of Climate Financial Risk.  Excerpts in italics with my bolds.

The idea that climate change poses a threat to the financial system is absurd, not least because everyone already knows that global warming is happening and that fossil fuels are being phased out.
The new push for climate-related financial regulation is not really about risk; it is about a political agenda.

In the United States, the Federal Reserve, the Securities and Exchange Commission, and the Department of the Treasury are gearing up to incorporate climate policy into US financial regulation, following even more audacious steps in Europe. The justification is that “climate risk” poses a danger to the financial system. But that statement is absurd. Financial regulation is being used to smuggle in climate policies that otherwise would be rejected as unpopular or ineffective.

“Climate” means the probability distribution of the weather – the range of potential weather conditions and events, together with their associated probabilities. “Risk” means the unexpected, not changes that everyone knows are underway. And “systemic financial risk” means the possibility that the entire financial system will melt down, as nearly happened in 2008. It does not mean that someone somewhere might lose money because some asset price falls, though central bankers are swiftly enlarging their purview in that direction.

Bomb of money hundred dollar bills with a burning wick. Little time before the explosion. Concept of financial crisis

In plain language, then, a “climate risk to the financial system” means a sudden, unexpected, large, and widespread change in the probability distribution of the weather, sufficient to cause losses that blow through equity and long-term debt cushions, provoking a system-wide run on short-term debt. This means the five- or at most ten-year horizon over which regulators can begin to assess the risks on financial institutions’ balance sheets. Loans for 2100 have not been made yet.

Such an event lies outside any climate science. Hurricanes, heat waves, droughts, and fires have never come close to causing systemic financial crises, and there is no scientifically validated possibility that their frequency and severity will change so drastically to alter this fact in the next ten years. Our modern, diversified, industrialized, service-oriented economy is not that affected by weather – even by headline-making events. Businesses and people are still moving from the cold Rust Belt to hot and hurricane-prone Texas and Florida.

insurance-exclusions

If regulators are worried even-handedly about out-of-the-box risks that endanger the financial system, the list should include wars, pandemics, cyberattacks, sovereign-debt crises, political meltdowns, and even asteroid strikes. All but the latter are more likely than climate risk. And if we are worried about flood and fire costs, perhaps we should stop subsidizing building and rebuilding in flood and fire-prone areas.

Climate regulatory risk is slightly more plausible. Environmental regulators could turn out to be so incompetent that they damage the economy to the point of creating a systemic run. But that scenario seems far-fetched even to me. Again though, if the question is regulatory risk, then even-handed regulators should demand a wider recognition of all political and regulatory risks. Between the Biden administration’s novel interpretations of antitrust law, the previous administration’s trade policies, and the pervasive political desire to “break up big tech,” there is no shortage of regulatory danger.

Climate Piggy Bank

To be sure, it is not impossible that some terrible climate-related event in the next ten years can provoke a systemic run, though nothing in current science or economics describes such an event. But if that is the fear, the only logical way to protect the financial system is by dramatically raising the amount of equity capital, which protects the financial system against any kind of risk.

Risk measurement and technocratic regulation of climate investments, by definition, cannot protect against unknown unknowns or un-modeled “tipping points.”

What about “transition risks” and “stranded assets?” Won’t oil and coal companies lose value in the shift to low-carbon energy? Indeed they will. But everyone already knows that. Oil and gas companies will lose more value only if the transition comes faster than expected. And legacy fossil-fuel assets are not funded by short-term debt, as mortgages were in 2008, so losses by their stockholders and bondholders do not imperil the financial system.

“Financial stability” does not mean that no investor ever loses money.

Moreover, fossil fuels have always been risky. Oil prices turned negative last year, with no broader financial consequences. Coal and its stockholders have already been hammered by climate regulation, with not a hint of financial crisis.

More broadly, in the history of technological transitions, financial problems have never come from declining industries. The stock-market crash of 2000 was not caused by losses in the typewriter, film, telegraph, and slide-rule industries. It was the slightly-ahead-of-their-time tech companies that went bust. Similarly, the stock-market crash of 1929 was not caused by plummeting demand for horse-drawn carriages. It was the new radio, movie, automobile, and electric appliance industries that collapsed.

If one is worried about the financial risks associated with the energy transition, new astronomically-valued darlings such as Tesla are the danger. The biggest financial danger is a green bubble, fueled as previous booms by government subsidies and central-bank encouragement. Today’s high-fliers are vulnerable to changing political whims and new and better technologies. If regulatory credits dry up or if hydrogen fuel cells displace batteries, Tesla is in trouble. Yet our regulators wish only to encourage investors to pile on.

Climate financial regulation is an answer in search of a question. The point is to impose a specific set of policies that cannot pass via regular democratic lawmaking or regular environmental rulemaking, which requires at least a pretense of cost-benefit analysis.

These policies include defunding fossil fuels before replacements are in place, and subsidizing battery-powered electric cars, trains, windmills, and photovoltaics – but not nuclear, carbon capture, hydrogen, natural gas, geoengineering, or other promising technologies. But, because financial regulators are not allowed to decide where investment should go and what should be starved of funds, “climate risk to the financial system” is dreamed up and repeated until people believe it, in order to shoehorn these climate policies into financial regulators’ limited legal mandates.

Climate change and financial stability are pressing problems. They require coherent, intelligent, scientifically valid policy responses, and promptly. But climate financial regulation will not help the climate, will further politicize central banks, and will destroy their precious independence, while forcing financial companies to devise absurdly fictitious climate-risk assessments will ruin financial regulation. The next crisis will come from some other source. And our climate-obsessed regulators will once again fail utterly to anticipate it – just as a decade’s worth of stress testers never considered the possibility of a pandemic.

John H. Cochrane is a senior fellow at the Hoover Institution.

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