Today’s coronavirus pandemic puts into some perspective the climate emergency, which has been running for nigh on 32 years. The climate emergency was first announced in June 1988. “Humanity is conducting an unintended, uncontrolled, globally pervasive experiment whose ultimate consequences could be second only to a global nuclear war,” the Toronto climate conference declared that month.
One way of assessing the reliability of a body of science with major policy implications is whether the experts in the field are prone to over-predicting the severity of the problem. Take smoking: In 1953, Richard Doll, one of the pioneer epidemiologists in discovering the link between tobacco smoking and lung cancer, predicted that, in 1973, the number of deaths from lung cancer in Britain would be as high as 25,000. The actual number was 26,000. Doll’s prediction passed a hard test.
By contrast, the Toronto climate conference predicted global temperatures would increase by between 1.5 and 4.5°C (2.7°F and 8.1°F) by the 2030s. Since 1988, average global temperature has risen at a rate of 0.177°C (0.32°F) per decade, less than one-half the 0.36°C (0.65°F) per decade implied by a 1.5°C rise by 2030 and only one-sixth of the rate of a 4.5°C rise. If there’s been a mainstream climate scientist who has under-predicted global warming, he or she must have taken the scientific equivalent of a Trappist vow of silence.
More recently, Myles Allen, an Intergovernmental Panel on Climate Change (IPCC) lead author, admitted that climate computer models are running too hot compared to the actual climate. “We haven’t seen that rapid acceleration in warming after 2000 that we see in the models,” Allen told the London Times in September 2017.
The coronavirus pandemic shows what a genuine crisis looks like. No one has to catastrophize it; the facts speak for themselves. Inducing fear and panic is counter-productive.
Global warming is different. For more than three decades, climate change has been the catastrophe that’s always just over the horizon. It moves with glacial speed; there is plenty of time to prepare for it. Humans – the most adaptive species on the planet – have been adapting to a changing climate ever since they first wore animal skins for warmth. The idea that the generation born since 1988 has experienced anything approaching a global nuclear war is preposterous. Even last year’s destructive Australian wildfires were fueled by green policies that prevented controlled fires.
One thing hasn’t changed and won’t change: Catastrophizing climate change for political ends. At one of the secretive meetings in 1987, limited to only 25 key participants that led to the formation of the IPCC, it was recognized that climate change had to be catastrophized to persuade politicians that they should embark on damaging emissions cuts. Earlier this month, United Nations Secretary-General António Guterres complained about the attention being given to COVID-19: “Whilst the disease is expected to be temporary, climate change has been a phenomenon for many years, and will remain with us for decades and require constant action.”
Congressional Democrats’ failure to hold coronavirus relief legislation hostage in exchange for the Green New Deal shows poor judgment. It’s hard to escape the conclusion that the inability to distinguish between a genuine crisis and an imagined one in the midst of the worst pandemic in a century is a manifestation of a collective psychological disorder.
Two lessons can be drawn. The first is the importance of governments and responsible international bodies focusing on genuine threats that can rapidly overwhelm our capacity to handle them. Something has gone very wrong when the World Health Organization, the lead institution coordinating the response to global pandemics, climbed on the climate bandwagon and called the Paris Agreement “potentially the strongest health agreement of this century” and listed climate change as the No. 1 threat to global health.
The second is resilience. Richer societies are better able to handle a pandemic than poorer ones. After the 2003 SARS outbreak, Singapore invested in a purpose-built National Centre for Infectious Diseases. Of larger economies, South Korea’s response has, so far, been the most successful; like Singapore, it can afford preparedness because it has a strong economy, reflected in its soaring greenhouse gas emissions.
Since 1992, Korea’s carbon dioxide emissions have more than doubled and it is planning to grow them under the Paris Agreement.
Unlike House Speaker Nancy Pelosi (D-Calif.) and her colleagues, South Korea has no intention of sacrificing its economy on the altar of climate change. Nor should America.
Rupert Darwall is a senior fellow at RealClear Foundation, a nonprofit affiliate of RealClear Media Group that reports and analyzes public policy and civic issues. He is the author of “Green Tyranny: Exposing the Totalitarian Roots of the Climate Industrial Complex” (2017) and “The Age of Global Warming: A History” (2013). A strategy consultant and policy analyst, he was a special adviser to the United Kingdom’s chancellor of the exchequer under Prime Minister John Major.
Footnote: The recent solar eclipse provided another example that scientific predictions coming to pass prove astronomers’ knowledge of the solar system, while climatists’ failed predictions prove their lack of knowledge. See: Astronomy is Science. Climatology Not.
On the perversion of medical science by the dash for climate cash, see: Climate Medicine
It didn’t take long for climatists to tie coronavirus to global warming/climate change; IOW, “It’s our fault for using fossil fuels.” And also: “Changes to fight coronavirus also fight climate change.” Activists have a long record of claiming that de-carbonizing is a snake oil curing all of society’s ills. The latest memes give the flavor of the warped thinking.
Coronavirus hits a critical year for nature and climate chinadialogue11:08
The threats facing our planet are interconnected ArabNews10:27
Climate change helped coronavirus spread The Independent10:20
How Science Denial In High Places Accelerates Both COVID-19 and Climate Change Ecosystem Marketplace10:12
The Corona Connection The Nation08:14
Coronavirus and the climate: How we respond to deadly threats The Gazette07:15
The Coronavirus and the Climate Movement The New Yorker07:04
The carbon disruption is here, disguised as a pandemic ImpactAlpha04:10
For pandemics and climate change, voluntary measures aren’t enough Grist Magazine03:58
“In a way, the coronavirus is climate change’s publicist” Why now is the time to focus on our… Vogue India02:43
Liberals See Good from Coronavirus: Less Pollution NewsMax20:22 Tue, 17 Mar
How changes brought on by coronavirus could help tackle the climate crisis Corporate Knights17:19 Tue, 17 Mar
Think Tank Shifts From Climate Science Denial To COVID Denial Talking Points Memo16:11 Tue, 17 Mar
Coronavirus, climate crisis, conflicts: Meme-ing our way through the ‘apocalypse’ The Conversation (Canada)13:58 Tue, 17 Mar
Key readings about climate change and coronavirus Yale Climate Connections14:19
Green Jobs Are the Answer to the Coronavirus Recession The New Republic14:19
How COVID-19 Is Like Climate Change Scientific American11:07 Tue, 17 Mar
Climate change could make the coronavirus seem like the good old days. GreenBiz
Viruses expected to increase with global warming – expert The Times of Israel08:35 Tue, 17 Mar
Social distancing? You might be fighting climate change, too New Zealand Herald20:45 Mon, 16 Mar
Can the changes brought on by coronavirus help tackle climate change? Australian Geographic20:42 Mon, 16 Ma
Climatists have a pattern of blaming every bad thing on CO2 in order to promote their agenda. Thus adding in this virus is an extension of the practice of attributing exteme weather events to global warming/climate change. A previous post provides Mike Hulme’s analysis of the flawed logic, as well as the motivations behind these attempts.
The antidote to such feverish reporting is provided by Mike Hulme in a publication: Attributing Weather Extremes to ‘Climate Change’: a Review (here).
He has an insider’s perspective on this issue, and is certainly among the committed on global warming (color him concerned). Yet here he writes objectively to inform us on X-weather, without advocacy: real science journalism and a public service, really.
In this third and final review I survey the nascent science of extreme weather event attribution. The article proceeds by examining the field in four stages: motivations for extreme weather attribution, methods of attribution, some example case studies and the politics of weather event Attribution.
The X-Weather Issue
As many climate scientists can attest, following the latest meteorological extreme one of the most frequent questions asked by media journalists and other interested parties is: ‘Was this weather event caused by climate change?’
In recent decades the meaning of climate change in popular western discourse has changed from being a descriptive index of a change in climate (as in ‘evidence that a climatic change has occurred’) to becoming an independent causative agent (as in ‘climate change caused this event to happen’). Rather than being a descriptive outcome of a chain of causal events affecting how weather is generated, climate change has been granted power to change worlds: political and social worlds as much as physical and ecological ones.
To be more precise then, what people mean when they ask the ‘extreme weather blame’ question is: ‘Was this particular weather event caused by greenhouse gases emitted from human activities and/or by other human perturbations to the environment?’ In other words, can this meteorological event be attributed to human agency as opposed to some other form of agency?
Hulme shows what drives scientists to pursue the “extreme weather blame” question, noting four motivational factors.
Why have climate scientists over the last ten years embarked upon research to provide an answer beyond the stock phrase ‘no individual weather event can directly be attributed to greenhouse gas emissions’? There seem to be four possible motives.
1.Curiosity The first is because the question piques the scientific mind; it acts as a spur to develop new rational understanding of physical processes and new analytic methods for studying them.
2.Adaptation A second argument, put forward by some, is that it is important to know whether or not specific instances of extreme weather are human-caused in order to improve the justification, planning and execution of climate adaptation.
3.Liability A third argument for pursuing an answer to the ‘extreme weather blame’ question is inspired by the possibility of pursuing legal liability for damages caused. . . If specific loss and damage from extreme weather can be attributed to greenhouse gas emissions – even if expressed in terms of increased risk rather than deterministically – then lawyers might get interested. The liability motivation for research into weather event attribution also bisects the new international political agenda of ‘loss and damage’ which has emerged in the last two years. . . The basic idea is to give recognition that loss and damage caused by climate change is legitimate ground for less developed countries to gain access to new international climate adaptation funds.
4. Persuasion A final reason for scientists to be investing in this area of climate science – a reason stated explicitly less often than the ones above and yet one which underlies much of the public interest in the ‘extreme weather blame’ question – is frustration with and argument about the invisibility of climate change. . . If this is believed to be true – that only scientists can make climate change visible and real –then there is extra onus on scientists to answer the ‘extreme weather blame’ question as part of an effort to convince citizens of the reality of human-caused climate change.
Attributing extreme weather events to human influences requires different approaches, of which four broad categories can be identified.
1. Physical Reasoning The first and most general approach to attributing extreme weather phenomena to rising greenhouse gas concentrations is to use simple physical reasoning.
General physical reasoning can only lead to broad qualitative statements such as ‘this extreme weather is consistent with’ what is known about the human-enhanced greenhouse effect. Such statements offer neither deterministic nor stochastic answers and clearly underdetermine the ‘weather blame question.’ It has given rise to a number of analogies to try to communicate the non-deterministic nature of extreme event attribution. The three most widely used ones concern a loaded die (the chance of rolling a ‘6’ has increased, but no single ‘6’ can be attributed to the biased die), the baseball player on steroids (the number of home runs hit increases, but no single home run can be attributed to the steroids) and the speeding car-driver (the chance of an accident increases in dangerous conditions, but no specific accident can be attributed to the fast-driving).
2. Classical Statistical Analysis A second approach is to use classical statistical analysis of meteorological time series data to determine whether a particular weather (or climatic) extreme falls outside the range of what a ‘normal’ unperturbed climate might have delivered.
All such extreme event analyses of meteorological time series are at best able to detect outliers, but can never be decisive about possible cause(s). A different time series approach therefore combines observational data with model simulations and seeks to determine whether trends in extreme weather predicted by climate models have been observed in meteorological statistics (e.g. Zwiers et al., 2011, for temperature extremes and Min et al., 2011, for precipitation extremes). This approach is able to attribute statistically a trend in extreme weather to human influence, but not a specific weather event. Again, the ‘weather blame question’ remains underdetermined.
3. Fractional Attributable Risk (FAR) Taking inspiration from the field of epidemiology, this method seeks to establish the Fractional Attributable Risk (FAR) of an extreme weather (or short-term climate) event. It asks the counterfactual question, ‘How might the risk of a weather event be different in the presence of a specific causal agent in the climate system?’
The single observational record available to us, and which is analysed in the statistical methods described above, is inadequate for this task. The solution is to use multiple model simulations of the climate system, first of all without the forcing agent(s) accused of ‘causing’ the weather event and then again with that external forcing introduced into the model.
The credibility of this method of weather attribution can be no greater than the overall credibility of the climate model(s) used – and may be less, depending on the ability of the model in question to simulate accurately the precise weather event under consideration at a given scale (e.g. a heatwave in continental Europe, a rain event in northern Thailand) (see Christidis et al., 2013a).
4. Eco-systems Philosophy A fourth, more philosophical, approach to weather event attribution should also be mentioned. This is the argument that since human influences on the climate system as a whole are now clearly established – through changing atmospheric composition, altered land surface characteristics, and so on – there can no longer be such a thing as a purely natural weather event. All weather — whether it be a raging tempest or a still summer afternoon — is now attributable to human influence, at least to some extent. Weather is the local and momentary expression of a complex system whose functioning as a system is now different to what it would otherwise have been had humans not been active.
Results from Weather Attribution Studies
Hulme provides a table of numerous such studies using various methods, along with his view of the findings.
It is likely that attribution of temperature-related extremes using FAR methods will always be more attainable than for other meteorological extremes such as rainfall and wind, which climate models generally find harder to simulate faithfully at the spatial scales involved. As discussed below, this limitation on which weather events and in which regions attribution studies can be conducted will place important constraints on any operational extreme weather attribution system.
Political Dimensions of Weather Attribution
Hulme concludes by discussing the political hunger for scientific proof in support of policy actions.
But Hulme et al. (2011) show why such ambitious claims are unlikely to be realised. Investment in climate adaptation, they claim, is most needed “… where vulnerability to meteorological hazard is high, not where meteorological hazards are most attributable to human influence” (p.765). Extreme weather attribution says nothing about how damages are attributable to meteorological hazard as opposed to exposure to risk; it says nothing about the complex political, social and economic structures which mediate physical hazards.
And separating weather into two categories — ‘human-caused’ weather and ‘tough-luck’ weather – raises practical and ethical concerns about any subsequent investment allocation guidelines which excluded the victims of ‘tough-luck weather’ from benefiting from adaptation funds.
Contrary to the claims of some weather attribution scientists, the loss and damage agenda of the UNFCCC, as it is currently emerging, makes no distinction between ‘human-caused’ and ‘tough-luck’ weather. “Loss and damage impacts fall along a continuum, ranging from ‘events’ associated with variability around current climatic norms (e.g., weather-related natural hazards) to [slow-onset] ‘processes’ associated with future anticipated changes in climatic norms” (Warner et al., 2012:21). Although definitions and protocols have not yet been formally ratified, it seems unlikely that there will be a role for the sort of forensic science being offered by extreme weather attribution science.
Thank you Mike Hulme for a sane, balanced and expert analysis. It strikes me as being another element in a “Quiet Storm of Lucidity”.
Is that light the end of the tunnel or an oncoming train?
GWPF published today a letter from the late Sir Antony Jay, co-creator of Yes, Minister and Yes, Prime Minster, attacking the BBC for its blatant bias on climate change 8 years ago. It seems timely to repost the final episode from the last season addressing the topic of global warming/climate change. As you see, climate politics have not changed very much.
Part 1 of the program is here:
Previously I posted this:
A humorous look at why the global warming campaign and the triumphal Paris COP make sense.
Yes Minister explains it all in an episode from 2013.
h/t to Peter S.
This is an all-too-realistic portrayal of political climatism today.
Then I realized that BBC had blocked the viewing of the video. So I sought and found the subtitles for Yes Prime Minister 2013, Episode 6, “A Tsar is Born”. That final episode for the series began with the dialogue in yesterday’s post Climate Alarms LOL.
Today I provide the dialogue that formed the episode conclusion, and which was the content of the blocked video.
The Characters are:
Sir Humphrey Appleby
Special Policy Adviser
Principal Private Secretary to the Prime Minister
(Dialogue beginning at 20:16 of “A Tsar is Born”)
Humphrey I have returned with the answer to all your problems. Global warming.
Jim I thought you were against it?
Humphrey Everybody’s against it, Prime Minister. I suddenly realised that is the beauty of it. We can get a unanimous agreement with all of our European partners
to do something about it.
Jim But how can we do something about something that isn’t happening?
Humphrey It’s much easier to solve an imaginary problem than a real one.
Jim You believe it’s real?
Humphrey Do you? I don’t know.
Jim Neither do I. Haven’t got the faintest idea!
Humphrey But it doesn’t matter what we think. If everyone else thinks it’s real, they’ll all want to stop it. So long as it doesn’t cost too much. So the question now is, what are we going to do about it?
Jim But if it isn’t happening, what can we do about it?
Humphrey Oh, there’s so much we can do, Prime Minister. We can impose taxes, we can stiffen European rules about
carbon emissions, rubbish disposal. We can make massive investments in wind turbines. We can, in fact, Prime Minister, under your leadership, agree to save the world.
Jim Well, I like that! But Russia, India, China, Brazil, they’ll never cooperate.
Humphrey They don’t have to. We simply ask them to review their emissions policy.
Jim And will they?
Humphrey Yes. And then they’ll decide not to change it. So we’ll set up a series of international conferences. Meanwhile, Prime Minister, you can talk about the future of the planet.
Humphrey You can look statesmanlike. And it’ll be 50 years before anybody can possibly prove you’re wrong. And you can explain away anything you said before by saying the computer models were flawed.
Jim The voters will love me!
Humphrey You’ll have more government expenditure.
Jim Yes. How will we pay for it? We’re broke.
Humphrey We impose a special global warming tax on fuel now, but we phase in the actual expenditure gradually. Say, over 50 years? That will get us out of the hole for now.
Bernard The Germans will be pleased. They have a big green movement.
Claire And we can even get the progs on board!
Bernard As long as they get more benefits than everyone else.
Jim My broadcast is on Sunday morning.
Humphrey You have a day to get the conference to agree.
Jim That’s not a problem. The delegates will be desperate for something to announce when they get home. There is one problem. Nothing will have actually been achieved.
Humphrey It will sound as though it has. So people will think it has. That’s all that matters!
(Later following the BBC interview, beginning 27:34)
Bernard Oh, magnificent, Prime Minister!
Humphrey I think you got away with it, Jim, but the cabinet will have been pretty surprised. We’ll have to square them fast.
Humphrey We’re not there yet. After that interview, you’ll need to announce some pretty impressive action.
Jim An initiative.
Claire A working party?
Humphrey Bit lightweight.
Bernard A taskforce?
Humphrey Not sure.
Jim Do we have enough in the kitty?
Claire It could be one of those initiatives that you announce but never actually spend the money.
Jim Great. Like the one on child poverty.
Bernard Maybe it should be a government committee?
Jim Well what about a Royal Commission?
Humphrey Yes! It won’t report for three years, and if we put the right people on it, they’ll never agree about anything important.
Jim Right! A Royal Commission! No, wait a minute, that makes it sound as if we think it’s important but not urgent.
Claire Well, what about a Global Warming Tsar?
Jim Fine! Would that do it?
Humphrey No, I think it might need a bit more than that, Prime Minister. It’ll mean announcing quite a big unit, and an impressive salary for that Tsar, to show how much importance you place upon him.
Jim No problem. Who would it be?
Humphrey Ah, well, it can’t be a political figure. That would be too divisive. It has to be somebody impartial.
Jim You mean a judge?
Humphrey No, somebody from the real world. Somebody who knows how to operate the levers of power, to engage the gears of the Whitehall machine, to drive the engine of government.
Jim That’s quite a tall order. Anybody got any ideas?
Humphrey… Could you?
Humphrey Yes, Prime Minister.
CO2 hysteria is addictive. Here’s what it does to your brain:
This morning in the car doing some errands I listened to an NPR broadcast regarding a NYT article claiming the Trump administration is attacking the fundamentals of climate science. Two journalists involved in the NYT article made two revealing defenses of IPCC climate ideology.
First they objected to the Geological Survey decision to limit consideration (required by US law) of climate change to impacts foreseen between now and 2040, setting aside projections out to 2100. Their reasoning: We won’t see any significant effects from our reducing (or not) CO2 emissions until the second half of this century. All of the forecasted temperature rise of 8F, along with sea level rise, storms, droughts, floods, etc. is only seen to occur after 2040. How do they know this? It is certain because it comes directly from the Oracle of Delphi the Climate Models, which have so accurately forecast the climate in the past (sic). All the pressure to unplug industrial civilization now, with results to appear many decades later.
Then they expressed shock that a Presidential Commission may be set up to review and questions climate assumptions put into agency planning. They said everyone agrees on the science of global warming, and this is not the way climate science is done. The two journalists, without a single bit of self-awareness, proceeded to discredit the possible chairman William Happer by saying he was not a “climate scientist.” Like, how would they know? He is a world expert on atmospheric gases responses to infrared radiation, which is the supposed mechanism of man made global warming, and something about which they are clueless.
In other news today, Arnold Swartzenegger was “starstruck” to meet with teen climate activist Greta Thunberg. How bad will this nightmare get before people wake up?
Those who seek the truth about global warming/climate change should welcome this latest publication from the Nongovernmental International Panel on Climate Change (NIPCC). Excerpts from the Coauthors’ introduction in italics with my bolds. H/T Lubos Motl
Climate Change Reconsidered II: Fossil Fuels assesses the costs and benefits of the use of fossil fuels (principally coal, oil, and natural gas) by reviewing scientific and economic literature on organic chemistry, climate science, public health, economic history, human security, and theoretical studies based on integrated assessment models (IAMs). It is the fifth volume in the Climate Change Reconsidered series and, like the preceding volumes, it focuses on research overlooked or ignored by the United Nations’ Intergovernmental Panel on Climate Change (IPCC).
NIPCC was created by Dr. S. Fred Singer in 2003 to provide an independent peer review of the reports of the United Nations’ Intergovernmental Panel on Climate Change (IPCC). Unlike the IPCC and as its name suggests, NIPCC is a private association of scientists and other experts and nonprofit organizations. It is not a government entity and is not beholden to any political or corporate benefactors. This and previous volumes in the CCR series, along with other publications and information about NIPCC, are available for free on NIPCC’s website .
The NIPCC authors do something their IPCC counterparts never did: conduct an evenhanded cost-benefit analysis of the use of fossil fuels. Despite calling for the end of reliance on fossil fuels by 2100, the IPCC never produced an accounting of the opportunity cost of restricting or banning their use. That cost, a literature review shows, would be enormous.
We thank the more-than-100 scientists, scholars, and experts who participated over the course of four years in writing, reviewing, editing, and proofreading this volume. This was a huge undertaking that involved thousands of hours of effort, the vast majority of it unpaid. The result exceeded our hopes, and we trust it meets your expectations.
The NIPCC authors cite thousands of books, scholarly articles, and reports that contradict the IPCC’s alarmist narrative. We once again tried to remain true to the facts when representing the findings of others, often by quoting directly and at some length from original sources and describing the methodology used and qualifications that accompanied the stated conclusions. The result may seem tedious at times, but we believe this was necessary and appropriate for a reference work challenging many popular beliefs.
The NIPCC authors conclude, “The global war on energy freedom, which commenced in earnest in the 1980s and reached a fever pitch in the second decade of the twenty-first century, was never founded on sound science or economics. The world’s policymakers ought to acknowledge this truth and end that war.”
Previous NIPCC volumes have also been extensive and they dedicated more space to the physical and biological scientific foundations. The newest 2019 report dedicated to the fossil fuels is unavoidably more practical and economics-oriented.
But it rationally discusses all the extra layers of the causal chains of the climate warning. Even if one assumes that there will be a warming, does it hurt the environment? The economy? Don’t the benefits exceed the costs? Don’t the costs of the mitigation policies exceed their benefits? As you may guess, the correct answers to all these questions – advocated in the NIPCC report – are almost universally the “skeptical ones”.
It’s so unfortunate that despite the higher quality of the NIPCC report (or at least comparable quality, if one were really generous to the IPCC), the left-wing media establishment – in some loose alliance with the governments – was capable of promoting the IPCC reports as if they were the Holy Scriptures while the NIPCC reports remained almost completely hidden from the world public.
The good news comes from NASA published at Science Daily Greenhouse gas ‘detergent’ recycles itself in atmosphere. The study explains how the atmosphere functions as a methane sink, and why the process is resilient and handles whatever CH4 is emitted. Scientists had worried that the atmospheric capacity to wash away methane might decay over time, but that fear turns out to be unfounded. Excerpts in italics with my bolds.
Summary: A simple molecule in the atmosphere that acts as a ‘detergent’ to break down methane and other greenhouse gases has been found to recycle itself to maintain a steady global presence in the face of rising emissions, according to new research. Understanding its role in the atmosphere is critical for determining the lifetime of methane, a powerful contributor to climate change.
The hydroxyl (OH) radical, a molecule made up of one hydrogen atom, one oxygen atom with a free (or unpaired) electron is one of the most reactive gases in the atmosphere and regularly breaks down other gases, effectively ending their lifetimes. In this way OH is the main check on the concentration of methane, a potent greenhouse gas that is second only to carbon dioxide in contributing to increasing global temperatures.
With the rise of methane emissions into the atmosphere, scientists historically thought that might cause the amount of hydroxyl radicals to be used up on the global scale and, as a result, extend methane’s lifetime, currently estimated to be nine years. However, in addition to looking globally at primary sources of OH and the amount of methane and other gases it breaks down, this new research takes into account secondary OH sources, recycling that happens after OH breaks down methane and reforms in the presence of other gases, which has been observed on regional scales before.
“OH concentrations are pretty stable over time,” said atmospheric chemist and lead author Julie Nicely at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “When OH reacts with methane it doesn’t necessarily go away in the presence of other gases, especially nitrogen oxides (NO and NO2). The break down products of its reaction with methane react with NO or NO2 to reform OH. So OH can recycle back into the atmosphere.”
OH in the atmosphere also forms when ultraviolet sunlight reaches the lower atmosphere and reacts with water vapor (H2O) and ozone (O3) to form two OH molecules. Over the tropics, water vapor and ultraviolet sunlight are plentiful. The tropics, which span the region of Earth to either side of the equator, have shown some evidence of widening farther north and south of their current range, possibly due to rising temperatures affecting air circulation patterns. This means that the tropical region primed for creating OH will potentially increase over time, leading to a higher amount of OH in the atmosphere. This tropical widening process is slow, however, expanding only 0.5 to 1 degree in latitude every 10 years. But the small effect may still be important, according to Nicely.
She and her team found that, individually, the tropical widening effect and OH recycling through reactions with other gases each comprise a relatively small source of OH, but together they essentially replace the OH used up in the breaking down of methane.
“The absence of a trend in global OH is surprising,” said atmospheric chemist Tom Hanisco at Goddard who was not involved in the research. “Most models predict a ‘feedback effect’ between OH and methane. In the reaction of OH with methane, OH is also removed. The increase in NO2 and other sources of OH, such as ozone, cancel out this expected effect.” But since this study looks at the past thirty-five years, it’s not guaranteed that as the atmosphere continues to evolve with global climate change that OH levels will continue to recycle in the same way into the future, he said.
Ultimately, Nicely views the results as a way to fine-tune and update the assumptions that are made by researchers and climate modelers who describe and predict how OH and methane interact throughout the atmosphere. “This could add clarification on the question of will methane concentrations continue rising in the future? Or will they level off, or perhaps even decrease? This is a major question regarding future climate that we really don’t know the answer to,” she said.
Abstract from AGU publication Changes in Global Tropospheric OH Expected as a Result of Climate Change Over the Last Several Decades Julie M. Nicely The oxidizing capacity of the troposphere is controlled primarily by the abundance of hydroxyl radical (OH). The global mean concentration of tropospheric OH, [OH]TROP (the burden of OH in the global troposphere appropriate for calculating the lifetime of methane) inferred from measurements of methyl chloroform has remained relatively constant during the past several decades despite rising levels of methane that should have led to a decline.
Here we examine other factors that may have affected [OH]TROP such as the changing values of stratospheric ozone, rising tropospheric H2O, varying burden of NOx (=NO+NO2), rising temperatures, and widening of the climatological tropics due to expansion of the Hadley cell. Our analysis suggests the positive trends in [OH]TROP due to H2O, NOx, and overhead O3, and tropical expansion are large enough (Δ [OH]TROP = +0.95 ± 0.18%/decade) to counter almost all of the expected decrease in [OH]TROP due to rising methane (Δ [OH]TROP = −1.01 ± 0.05%/decade) over the period 1980 to 2015, while variations in temperature contribute almost no trend (Δ [OH]TROP = −0.02 ± 0.02%/decade) in [OH]TROP. The approximated impact of Hadley cell expansion on [OH]TROP is also a small but not insignificant factor partially responsible for the steadiness of tropospheric oxidizing capacity over the past several decades, which free‐running models likely do not capture.
Slowing expanding tropical regions seems like a good thing all around.
Watch the Sun rotate for over a month brought to you by SDO. Since the Sun rotates once every 27 days on average, this movie presents more than an entire solar rotation. From March 30 through Apr. 29, 2011, the Sun sported quite a few active regions and magnetic loops. The movie shows the Sun in the 171 Angstrom wavelength of extreme ultraviolet light (capturing ionized iron heated to about 600,000 degrees), color coded to appear gold. The movie is based on a frame taken every 15 minutes being shown at 24 frames per second, with very few data gaps in this almost two-minute movie. Source Solar Dynamics Observatory
Our early Sun’s rate of rotation may be one reason we’re here to talk about it, astrobiologists now say. The key likely lies in the fact that between the first hundred million to the first billion years of its life, our G-dwarf star likely had a ‘Goldilocks’ rotation rate; neither too slow nor too fast.
Instead, its hypothetical ‘intermediate’ few days rate of rotation guaranteed our Sun was active enough to rid our newly-formed Earth of its inhospitable, hydrogen-rich primary atmosphere. This would have enabled a more habitable, secondary atmosphere composed of nitrogen, carbon dioxide, hydrogen and oxygen to eventually form.
If it had been a ‘fast’ (less than one day rotator), our Sun might have continually stripped our young planet of its secondary atmosphere as well. However, if it took more than 10 days to rotate, it might not have been active enough to strip Earth of its hypothetical primary atmosphere.
Such ideas were recently bandied about in oral presentations at last month’s the General Assembly of the International Astronomical Union (IAU) in Vienna.
Earth’s very first atmosphere would have been too hot and too thick, more like Venus’ present-day atmosphere, Theresa Luftinger, an astrophysicist at the University of Vienna, told me. No known organisms could have evolved under such an atmosphere. A secondary atmosphere cannot evolve in the presence of a primordial atmosphere , says Luftinger.
It’s the star’s magnetic dynamo that drives its magnetic fields. And these magnetic fields, in turn, interact with the star itself, creating an interplay of extreme stellar activity.
“So, the quicker the star rotates, the higher the interaction between the magnetic field and the stellar body ,” said Luftinger.
Faster rotation means higher extreme ultra-violet and x-ray activity, Helmut Lammer, an astrophysicist at Austria’s Space Science Institute in Graz, told me. This would lead to atmospheric stripping and water loss on earthlike planets around an active young star, he says.
Our Sun is now a very slow rotator at 27 days. But that wasn’t always the case. As for why some stars seem to inherently rotate faster than others?
Astrophysicists suspect that initial conditions within star-forming clouds cause newborn stars to have different rotation rates.
Researchers are able to roughly pinpoint the Sun’s early rotation rates by studying the isotopic ratios of neon, argon, potassium, and uranium here in Earth’s crust. That is, elements which have atoms that have the same numbers of protons in their atomic nucleus, but different numbers of neutrons. The researchers also considered such isotopic ratios from decades’-old Venus surface samples taken by Soviet Venus lander missions.
Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system. Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy. Measuring water temperature directly avoids distorted impressions from air measurements. In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates. Eventually we will likely have reliable means of recording water temperatures at depth.
Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST. He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months. This latter point is addressed in a previous post Who to Blame for Rising CO2?
The July update to HadSST3 will appear later this month, but in the meantime we can look at lower troposphere temperatures (TLT) from UAHv6 which are already posted for July. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.
The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI). The graph below shows monthly anomalies for ocean temps since January 2015.
The anomalies are holding close to the same levels as 2015. In July, both the Tropics and SH rose, while NH rose very slightly, resulting in a small increase in the Global average of air over oceans. Taking a longer view, we can look at the record since 1995, that year being an ENSO neutral year and thus a reasonable starting point for considering the past two decades. On that basis we can see the plateau in ocean temps is persisting. Since last October all oceans have cooled, with offsetting bumps up and down.
UAHv6 TLT Monthly Ocean
Average Since 1995
As of July 2018, global ocean temps are slightly higher than June and the average since 1995. NH remains virtually the same, while both SH and Tropics rose making the global temp warmer. Global, NH and SH are matching July temps in 2015, while the Tropics are the lowest July since 2013.
The details of UAH ocean temps are provided below. The monthly data make for a noisy picture, but seasonal fluxes between January and July are important.
Open image in new tab to enlarge.
The greater volatility of the Tropics is evident, leading the oceans through three major El Nino events during this period. Note also the flat period between 7/1999 and 7/2009. The 2010 El Nino was erased by La Nina in 2011 and 2012. Then the record shows a fairly steady rise peaking in 2016, with strong support from warmer NH anomalies, before returning to the 22-year average.
TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps. They started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern. It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995. Of course, the future has not yet been written.
The last solar eclipse was in 2017. The totality in the picture lasted a little more than 2 minutes, while the process lasted about 2.5 hours.
One of the great disputes in climate research is between those (IPCC) who dismiss solar cycles as a factor in climate change and those who see correlations in the past and keep seeking to understand the mechanisms. To be clear, there is considerable agreement that earth’s atmosphere can and does reduce or increase the amount of incoming solar energy (albedo effect), thereby contributing to surface warming or cooling. The science and research into the “global dimming and brightening” is discussed in the post Nature’s Sunscreen.
The above image of the eclipse is intended to remind us that humans down through history have been terrified of the sun going dark because they knew intuitively that no sun means no life. A more modern and sophisticated concern is that even slightly falling energy from the sun brings cooling, ice and death. Quite apart from the sunscreen, this post is focused a different matter, namely that changes in the sun’s output radiation cause changes in earth climate parameters. One theory of such a mechanism is espoused by Henrik Svensmark and concerns solar particles effect upon albedo. That line of research is discussed in the post The Cosmoclimatology theory
A different investigation has been advanced by Dr.Indrani Roy, her most recent publication this month being a book Climate Variability and Sunspot ActivityAnalysis of the Solar Influence on Climate (H/T NoTricksZone).
The book is behind a paywall, but the abstract and chapter headings indicate a comprehensive approach.
Overview Climate Variability and Sunspot Activity (2018)
This book promotes a better understanding of the role of the sun on natural climate variability. It is a comprehensive reference book that appeals to an academic audience at the graduate, post-graduate and PhD level and can be used for lectures in climatology, environmental studies and geography.
This work is the collection of lecture notes as well as synthesized analyses of published papers on the described subjects. It comprises 18 chapters and is divided into three parts: Part I discusses general circulation, climate variability, stratosphere-troposphere coupling and various teleconnections. Part II mainly explores the area of different solar influences on climate. It also discusses various oceanic features and describes ocean-atmosphere coupling. But, without prior knowledge of other important influences on the earth’s climate, the understanding of the actual role of the sun remains incomplete. Hence, Part III covers burning issues such as greenhouse gas warming, volcanic influences, ozone depletion in the stratosphere, Arctic and Antarctic sea ice, etc. At the end of the book, there are few questions and exercises for students. This book is based on the lecture series that was delivered at the University of Oulu, Finland as part of M.Sc./ PhD module.
Climatology and General Circulation
Major Modes of Variability
Teleconnection Among Various Modes
Solar Influence Around Various Places: Robust Solar Signal on Climate
Total Solar Irradiance (TSI): Measurements and Reconstructions
Atmosphere-Ocean Coupling and Solar Variability
The Sun and ENSO Connection–Contradictions and Reconciliations
A Debate: The Sun and the QBO
Solar Influence: ‘Top Down’ vs. ‘Bottom Up’
An Overview of Solar Influence on Climate
Other Major Influences on Climate
Sun: Atmosphere-Ocean Coupling – Possible Limitations
We identify solar cycle signals in the North Pacific in 155 years of sea level pressure and sea surface temperature data. In SLP we find in the North Pacific a weakening of the Aleutian Low and a northward shift of the Hawaiian High in response to higher solar activity, confirming the results of previous authors using different techniques. We also find a broad reduction in pressure across the equatorial region but not the negative anomaly in the sub-tropics detected by vL07. In SST we identify the warmer and cooler regions in the North Pacific found by vL07 but instead of the strong Cold Event-like signal in tropical SSTs we detect a weak WE-like pattern in the 155 year dataset.
We find that the peak SSN years of the solar cycles have often coincided with the negative phase of ENSO so that analyses, such as that of vL07, based on composites of peak SSN years find a La Nina response. As the date of peak annual SSN generally falls a year or more in advance of the broader maximum of the 11-year solar cycle it follows that the peak of the DSO is likely to be associated with an El Nino-like pattern, as seen by White et al. (1997). An El Nino pattern is clearly portrayed in our regression analysis using only data from second half of the last century, but inclusion of ENSO as an independent regression index results in a significant diminution of the solar signal in tropical SST, showing further how an ENSO signal might be interpreted as due to the Sun.
Any mechanisms proposed to explain a solar influence should be consistent with the full length of the dataset, unless there are reasons to think otherwise, and analyses which incorporate data from all years, rather than selecting only those of peak SSN, represent more coherently the difference between periods of high and low solar activity on these timescales.
The SLP signal in mid-latitudes varies in phase with solar activity, and does not show the same modulation by ENSO phase as tropical SST, suggesting that the solar influence here is not driven by coupled-atmosphere-ocean effects but possibly by the impact of changes in the stratosphere resulting in expansion of the Hadley cell and poleward shift of the subtropical jets (Haigh et al., 2005). Given that climate model results in terms of tropical Pacific SST can be dependent on different ENSO variability within the models, our analysis indicates that the robustness of any proposed mechanism of the response to variations in solar irradiance needs to be analyzed in the context of ENSO variability where timing plays a crucial role.
Comment on Dr. Roy’s Methodology
It is challenging to grasp this approach and results because she respects the complexity of solar and climate dynamics. For starters, she is not mining climate data in search of 11 year periodicities as others have done. Dr. Roy takes the dates of observed SSN maxima and minima and compares with repeated effects in climate measurements. Many readers will know that solar cycles are only quasi-11 years long; there is considerable irregularity.
Even more importantly, SSN do not peak midway in the cycle, but can appear early on and show additional peak(s) afterward. She defines minima and maxima in terms of SSN significantly lower or higher than the mean. So Roy’s analysis is not simplistic, but correlates all years in the datasets comparing SSN with climate measures.
Dr. Roy also diligently analyzes confounding factors such as oceanic circulations and the influence of previous years upon succeeding years (system momentum). For example, the above study discussed solar influence on Pacific SST and SLP. This is presented in the following image:
Tropical Pacific SST composites using NOAA Extended V4 (ERSST) data for solar Max (Top) and Min years (Bottom) during DJF. Levels usually significant up to 95% level are overlaid by opposite coloured contour. Plots are generated using IDL software, version 8 with the data from NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at (http://www.esrl.noaa.gov/psd/).
Importantly, the analysis shows little to no solar influence upon the ENSO 3.4 ocean sector, but as the graph above shows the effect is much broader. Roy concludes that ENSO operates mostly independently of solar influence. Even more striking is the result for NH winter, showing solar minima associated with generally warmer SST and maxima generally cooler. Dr. Roy explains the solar influence in terms of two separate processes. Bottom up is fluctuations in SSTs while top-down is UV effects upon the stratosphere extending downward expressed in SLP differentials.
This study investigates the role of the eleven-year solar cycle on the Arctic climate during 1979–2016. It reveals that during those years, when the winter solar sunspot number (SSN) falls below 1.35 standard deviations (or mean value), the Arctic warming extends from the lower troposphere to high up in the upper stratosphere and vice versa when SSN is above. The warming in the atmospheric column reflects an easterly zonal wind anomaly consistent with warm air and positive geopotential height anomalies for years with minimum SSN and vice versa for the maximum. Despite the inherent limitations of statistical techniques, three different methods – Compositing, Multiple Linear Regression and Correlation – all point to a similar modulating influence of the sun on winter Arctic climate via the pathway of Arctic Oscillation. Presenting schematics, it discusses the mechanisms of how solar cycle variability influences the Arctic climate involving the stratospheric route. Compositing also detects an opposite solar signature on Eurasian snow-cover, which is a cooling during Minimum years, while warming in maximum. It is hypothesized that the reduction of ice in the Arctic and a growth in Eurasia, in recent winters, may in part, be a result of the current weaker solar cycle.
In summary, for solar Min years, the warm air column is associated with positive geopotential height anomalies and an easterly wind, which reverses during Max years. Such NAM feature is clearly evident supporting the hypothesis of communicating a solar signal to Arctic via winter NAM (North Annular Mode).
Above: Mechanism to describe the stratospheric pathway for solar cycle variability to influence the Arctic climate. Mechanisms for (a) discuss a route where perturbation in the upper stratospheric polar vortex is transported downwards and impacts the Arctic on a seasonal scale via the winter NAM (flowchart is presented on the right). Mechanisms for (b) discusses the route that involves upper stratospheric polar vortex, tropical lower stratosphere, Brewer-Dobson circulation and Ferrel cell (flowchart is presented to the left). It is created using images or clip art available from Powerpoint.
During DJF, Arctic sea ice extent suggests a strong correlation with SSN (99% significant) and even with AOD (95% significant) (Table 3a). SSN is also found to be strongly correlated with AO (95% significant). Figure 8a shows that significant correlation between Arctic sea ice extent and SSN is still present in other seasons as well. However, the correlation between SSN and AO is only significant in DJF, confirming that the possible route of solar influence on winter Arctic sea ice is via the AO. On the other hand, the influence of AO on Arctic sea ice extent is not present during winter. It is strongest during JJA, though fails to exceed a significant threshold of 95% level.
Results of Correlation Coefficient (c.c) between Sea Ice Extent and various other parameters. (a) Seasonal c.c. for four different seasons are presented using other parameters as SSN and AO, and (b) c.c. for the winter season in different regions using other parameters as AO and AMO. Significant levels of 95% and 99% using a students ‘t-test’ are marked by dashed line and dotted line respectively. Plots are prepared using IDL software, version 8.
In terms of oceanic longer-term variability, here we particularly focus on the AMO and find a strong connection between sea ice and AMO in winter, agreeing with previous studies45,46. Earlier discussions suggested that there are few differences in region A and B relating to trend (Figs S6 and S7), but correlation technique indicated a very strong anti-correlation between the winter AMO index and sea ice in all regions of our considerations (Fig. 8b)). Even using two different data sources (HadSST and ERSST) we arrive at similar results, and it is also true for overall sea ice extent. It could also be possible that, in region B, due to a strong presence of AO influence of the sun, it may mask some of the influence of the longer-term trend (seen in Fig. 2) to suggest a lesser trend, as also noted in Figs S6 and S7.
This Matters As We Reach Solar Minimum for Cycle 24
The latest observations show this solar cycle is over, perhaps the next one beginning. With no sunspots seen since June, this is unusually quiet.
The solar surface at the moment is “Spotless” and has been for a month.
The sun is the primary source of energy in the earth/atmosphere system, but the actual role of the sun and related mechanisms to support varied regional climate responses and its seasonality around the world, are still poorly understood. Solar energy output varies in cycles, of which the 11-year cyclic variability is one of the most crucial ones. It causes differences in the amount of solar energy absorbed in the UV part of the spectrum within the upper stratosphere, varying from 6 to 8%. Such variation is believed to be one of the most important solar energy outputs to influence the climate of the earth and that knowledge of cyclic behaviour can also be used for future prediction purposes. Apart from solar UV related effects on earth’s climate, studies also identified effects related to solar particle precipitation.
Various studies have also detected an influence of the El Nino Southern Oscillation (ENSO)22 and the Pacific Decadal Oscillation (PDO) on Arctic sea ice. An association between the sun and ENSO are discussed in various research. Because of related complexities along with various linear and nonlinear couplings among major modes of variability, the role of the sun on Arctic air temperatures and sea ice extent and related mechanisms remains poorly understood/explored.
While many studies point to anthropogenic influences on the long-term sea ice decline, this study is motivated by the potential links between the sun and the surface climate through stratospheric processes. Alongside warming in the Arctic, a cooling is noticed around Eurasian sector despite continuing rise of greenhouse gas concentrations. Various modelling groups, however, made unsuccessful efforts to detect an association between Eurasian cooling and Arctic sea-ice decline. In this work, we evaluate the impact of the solar 11-year cycle, measured in terms of solar sunspot number (SSN), as a driving factor to modulate Arctic and surrounding climate. The influences of SSN on various surface parameters, such as Sea Level Pressure (SLP), Sea Surface Temperature (SST), and the polar stratosphere are well recognised. If there is indeed a link between the solar cycle and Arctic climate, it is possible that the 11-year solar cycle can be used to improve seasonal and decadal predictions of sea ice. In the present study, we use a combination of observational and reanalysis datasets to uncover relationships between the sun’s variability and Arctic surface climate, via the modulation of NAM and downward propagation of anomaly from upper stratospheric winter polar vortex.
Our result suggests the latest rapid decline of sea ice around the Arctic in the recent winter decade/season could also have contributions from the current weaker solar cycle. The last 14 years are dominated by solar Min years and have only one Max. This is unlike other previous years, where the number of Max and Min years were evenly distributed (five each). The cumulative effect from the past 13 solar Min years could have played a role in the current record decline of the last winter, 2017. The current weaker solar cycle may also have contributions on increase in winter snow cover around the Eurasian sector.
Presenting schematics and flowcharts, we discussed mechanisms of how solar cycle variability influences Arctic climate. In the first route, perturbation in the upper stratospheric polar vortex is transported downwards and modulates the Arctic in a seasonal scale via the winter NAM. Another route was shown, which could involve upper stratospheric polar vortex, tropical lower stratosphere, Brewer-Dobson circulation and Ferrel cell. It could also reinforce the findings of the ‘Solar Max (Min) – cold (warm) Arctic’ scenario.
The image from IMS shows snow and ice on day 296 (yesterday) 2007 to 2017, with focus on Eurasia but also showing Canada and Alaska. You can see that low Arctic ice years, like 2007, 2012 and 2016 have a smaller snow extent on both sides of the Arctic. Conversely, higher Arctic ice years like 2013, 2014 and 2015 show snow spreading into northern Europe, as well as Alaska. The pattern appears as gaining snow and ice 2008 to 10, losing 2011 and 2012, then regaining 2013 to 15, before retreating in 2016. So far 2017 is looking more like 2013 to 15.
From Post Natural Climate Factors: Snow
Previously I posted an explanation by Dr. Judah Cohen regarding a correlation between autumn Siberian snow cover and the following winter conditions, not only in the Arctic but extending across the Northern Hemisphere. More recently, in looking into Climate Model Upgraded: INMCM5, I noticed some of the scientists were also involved in confirming the importance of snow cover for climate forecasting. Since the poles function as the primary vents for global cooling, what happens in the Arctic in no way stays in the Arctic. This post explores data suggesting changes in snow cover drive some climate changes.
The Snow Cover Climate Factor
The diagram represents how Dr. judah Cohen pictures the Northern Hemisphere wintertime climate system. He leads research regarding Arctic and NH weather patterns for AER.
Dr. Cohen explains the mechanism in this diagram.
Conceptual model for how fall snow cover modifies winter circulation in both the stratosphere and the troposphere–The case for low snow cover on left; the case for extensive snow cover on right.
1. Snow cover increases rapidly in the fall across Siberia, when snow cover is above normal diabatic cooling helps to;
2. Strengthen the Siberian high and leads to below normal temperatures.
3. Snow forced diabatic cooling in proximity to high topography of Asia increases upward flux of energy in the troposphere, which is absorbed in the stratosphere.
4. Strong convergence of WAF (Wave Activity Flux) indicates higher geopotential heights.
5. A weakened polar vortex and warmer down from the stratosphere into the troposphere all the way to the surface.
6. Dynamic pathway culminates with strong negative phase of the Arctic Oscillation at the surface.
Variations in Siberian snow cover October (day 304) 2004 to 2016. Eurasian snow charts from IMS.
Observations of the Snow Climate Factor
For several decades the IMS snow cover images have been digitized to produce a numerical database for NH snow cover, including area extents for Eurasia. The NOAA climate data record of Northern Hemisphere snow cover extent, Version 1, is archived and distributed by NCDC’s satellite Climate Data Record Program. The CDR is forward processed operationally every month, along with figures and tables made available at Rutgers University Global Snow Lab.
This first graph shows the snow extents of interest in Dr. Cohen’s paradigm. The Autumn snow area in Siberia is represented by the annual Eurasian averages of the months of October and November (ON). The following NH Winter is shown as the average snow area for December, January and February (DJF). Thus the year designates the December of that year plus the first two months of the next year.
Notes: NH snow cover minimum was 1981, trending upward since. Siberian autumn snow cover was lowest in 1989, increasing since then. Autumn Eurasian snow cover is about 1/3 of Winter NH snow area. Note also that fluctuations are sizable and correlated.
The second graph presents annual anomalies for the two series, each calculated as the deviation from the mean of its entire time series. Strikingly, the Eurasian Autumn flux is on the same scale as total NH flux, and closely aligned. While NH snow cover declined a few years prior to 2016, Eurasian snow is trending upward strongly. If Dr. Cohen is correct, NH snowfall will follow. The linear trend is slightly positive, suggesting that fears of children never seeing snowfall have been exaggerated. The Eurasian trend line (not shown) is almost the same.
The main block/high pressure feature influencing Eurasian weather is currently centered over the Barents-Kara Seas and is predicted to first weaken and then strengthen over the next two weeks.
Blocking in the Barents-Kara Seas favors troughing/negative geopotential height anomalies and cool temperatures downstream over Eurasia but especially Central and East Asia. The forecast for the next two weeks across Central Asia is for continuation of overall below normal temperatures and new snowfall.
Currently the largest negative anomalies in sea ice extent are in the Chukchi and Beaufort Seas but that will change over the next month or so during the critical months of November-February. In my opinion low Arctic sea ice favors a more severe winter but not necessarily hemisphere-wide and depends on the regions of the strongest anomalies. Strong negative departures in the Barents-Kara Seas favors cold temperatures in Asia while strong negative departures near Greenland and/or the Beaufort Sea favor cold temperatures in eastern North America.
Siberian snow cover is advancing quickly relative to climatology and is on a pace similar to last year at this time. My, along with my colleagues and others, research has shown that extensive Siberian snow cover in the fall favors a trough across East Asia with a ridge to the west near the Urals. The atmospheric circulation pattern favors more active poleward heat flux, a weaker PV and cold temperatures across the NH. It is very early in the snow season but recent falls have been snowy across Siberia and therefore I do expect another upcoming snowy fall across Siberia.
In summary the three main predictors that I follow in the fall months most closely, the presence or absence of high latitude blocking, Arctic sea ice extent and Siberian snow cover extent all point towards a more severe winter across the continents of the NH.