Update: October 16 Snow and Ice

Yesterday at AER Dr. Judah Cohen provided his Arctic Oscillation and Polar Vortex Analysis and Forecasts biweekly report and outlook regarding the arctic oscillation and the coming winter in Northern Hemisphere. Excerpts with my bolds.

  • As is often the case, the current positive AO is associated with a relatively mild weather pattern across the NH continents including Europe and much of North America.
  • However over the next two weeks with the predicted overall negative trend in the AO a concomitant cooling trend is predicted across the NH continents including the British Isles and Western Europe but especially the Eastern United States (US).
  • Across East Asia troughing will allow a series of fronts to swing through the region keeping temperatures variable but overall close to seasonable.
  • Looking ahead to this upcoming winter, in my opinion both below normal Arctic sea ice and above normal Siberian snow cover so far this month favor more severe winter weather especially mid and late winter across the NH mid-latitudes. Though it is still early and there is much uncertainty in predictions of winter weather.

The flow across the NH is currently mostly zonal especially across North America and this is resulting in an overall mild weather pattern including Europe and the US. The exception to the zonal flow is a block over the Laptev Sea resulting in troughing/negative geopotential height anomalies over both Western and Eastern Asia and colder temperatures.

Expanding Eurasian snow cover and Arctic ice extent October 1 to 16, 2017. Watch the ice growing toward the Siberian snow. Also at the top note ice growing toward Canadian snow cover.

Siberian snow cover has advanced at a relatively rapid pace so far this fall, which has been the recent trend. However snow cover extent this October is so far lagging the pace of last October. My, along with my colleagues and others, research have shown that extensive Siberian snow cover in the fall favors a trough across East Asia with a ridge to the west near the Urals. This atmospheric circulation pattern favors more active poleward heat flux, a weaker PV and cold temperatures across the NH.

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. However sea ice is currently more extensive in the Barents-Kara-Laptev Seas than last year at this time and even more than two years ago. I believe that low sea ice in the Barents Kara sea the past two winters helped anchor blocking in the region that favored cold temperatures in Eurasia relative to North America. That same forcing may not be as strong for the upcoming winter.

I would conclude that the three factors that I consider favorable for severe winter weather increased atmospheric blocking in the fall, more extensive Siberian snow cover and low Arctic sea ice have become the norm more than the exception over the past decade. I do believe that the lack of variability in these three factors, likely reduces their utility in winter predictions.

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.

cohen-schematic2

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.

From Eurasian Snow Cover Variability and Links with Stratosphere-Troposphere
Coupling and Their Potential Use in Seasonal to Decadal Climate Predictions by Judah Cohen.

Variations in Siberian snow cover October (day 304) 2004 to 2016. Eurasian snow charts from IMS.

Observations of the Snow Climate Factor

The animation above shows from remote sensing that Eurasian snow cover fluctuates significantly from year to year, taking the end of October as a key indicator. Snowfall in 2016 was especially early and extensive, 2017 similar but slightly less at this point.

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.

What About Winter 2017-2018?

These data confirm that Dr. Cohen and colleagues are onto something. Here are excerpts from his October 2 outlook for the upcoming season AER. (my bolds)

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.

Summary

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.

Uh oh.  Now where did I put away my long johns?

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CPP has Three Fatal Flaws

 

Captains of industry contending with a sea of Obama era regulations.

Thanks to Rich Lowry’s article at National Review and some other sources, we can see clearly the three fatal flaws bringing down the Clean Power Plan in its entirety. Lowry wrote The Great Regulatory Rollback. Excerpts below with my bolds and images.

1. No federal law governs CO2 emissions.

Lowry: The Clean Power Plan, which sought to reduce U.S. carbon emissions by 32 percent below 2005 levels by 2030, was government by the administrative state on a scale that has never been attempted before. The EPA took a dubious reading of a portion of the Clean Air Act (Section 111, which arguably prevented the EPA from taking this action rather than empowered it to do so) and used it to mandate that the states adopt far-reaching plans to reduce carbon emissions, under threat of the loss of federal highway funds.

In an August ruling of the DC Court of Appeals, the justices put it in writing:

However, EPA’s authority to regulate ozone-depleting substances under Section 612 and other statutes does not give EPA authority to order the replacement of substances that are not ozone depleting but that contribute to climate change. Congress has not yet enacted general climate change legislation. Although we understand and respect EPA’s overarching effort to fill that legislative void and regulate HFCs, EPA may act only as authorized by Congress. Here, EPA has tried to jam a square peg (regulating non-ozone depleting substances that may contribute to climate change) into a round hole (the existing statutory landscape).

The Supreme Court cases that have dealt with EPA’s efforts to address climate change have taught us two lessons that are worth repeating here. See, e.g., Utility Air Regulatory Group v. EPA, 134 S. Ct. 2427 (2014). First, EPA’s well intentioned policy objectives with respect to climate change do not on their own authorize the agency to regulate. The agency must have statutory authority for the regulations it wants to issue. Second, Congress’s failure to enact general climate change legislation does not authorize EPA to act. Under the Constitution, congressional inaction does not license an agency to take matters into its own hands, even to solve a pressing policy issue such as climate change.
From the Court Document On Petitions for Review of Final Action by the United States Environmental Protection Agency. Additional discussion at DC Appeals Court Denies EPA Climate Rules

2. EPA regulates sites, not the Energy Sector.

Lowry: The presumption of the plan was jaw-dropping. The EPA usually targets pollutants; carbon dioxide isn’t one (although the Supreme Court erroneously said that it meets the definition in the case of Massachusetts v. EPA). The EPA has always regulated specific power plants; in this scheme, it went “outside the fence” to mandate broader actions by the states, e.g., the adoption of quotas for renewable energy. The EPA once considered its mandate to be protecting clear air and water for Americans; with the Clean Power Plan, it sought to adjust the global thermostat for the good of all of humanity.

From the EPA document Repeal of Carbon Pollution Emission Guidelines

That the CPP depends on the employment of measures that cannot be applied at and to an individual source is evident from its treatment of coal-fired power plants. The rule established performance standards for coal-fired plants assuming a uniform emissions rate well below that which could be met by existing units through any retrofit technology of reasonable cost available at the time. This means that, in order to comply, many owners or operators of existing coal-fired units were expected to shift generation from such units to gas-fired units or to renewable generation. Similarly, the rule contemplated that gas-fired units would shift generation to renewable generation. The rule therefore is formulated in reliance on and anticipation of actions taken across the electric grid, rather than actions taken at and applied to individual units. Pp 8-9

The EPA is proposing to repeal the CPP in its entirety. The EPA proposes to take this action because it proposes to determine that the rule exceeds its authority under the statute, that those portions of the rule which arguably do not exceed its authority are not severable and separately implementable, and that it is not appropriate for a rule that exceeds statutory authority—especially a rule of this magnitude and with this level of impact on areas of traditional state regulatory authority—to remain in existence pending a potential, successive rulemaking process.Pg 12

After reconsidering the statutory text, context, and legislative history, and in consideration of the EPA’s historical practice under CAA section 111 as reflected in its other existing CAA section 111 regulations, the Agency proposes to return to a reading of CAA section 111(a)(1) (and its constituent term, “best system of emission reduction”) as being limited to emission-reduction measures that can be applied to or at an individual stationary source. That is, such measures must be based on a physical or operational change to a building, structure, facility, or installation at that source, rather than measures that the source’s owner or operator can implement on behalf of the source at another location. The EPA believes that this is the best construction of CAA section 111(a)(1), as explained in detail below, for several reasons.pg 14

Therefore, the EPA proposes that the BSER be limited to measures that physically or operationally can be applied to or at the source itself to reduce its emissions. Generation shifting—which accounts for a significant percentage of the emissions reductions projected in the CPP and without which individual sources could not meet the CPP’s requirements—fails to comply with this limitation. Accordingly, the EPA proposes to repeal the CPP.pg25-26

In addition, while the EPA is authorized to regulate emissions from sources in the power sector and to consider the impact of its standards on the generation mix in setting standards to avoid negative energy impacts, regulation of the nation’s generation mix itself is not within the Agency’s authority. Regulation of the energy sector qua energy sector is generally undertaken by the Federal Energy Regulatory Commission (FERC) and States, depending on which markets are being regulated. Pg.27

3. CPP costs are huge, while benefits are marginal.

Lowry: The last gets to the absurdity of the Clean Power Plan on its own terms — it did virtually nothing to affect global warming. As Benjamin Zycher of the American Enterprise Institute points out, the Obama administration’s Climate Action Plan (which includes the Clean Power Plan) would reduce the global temperature by 15 one-thousandths of a degree by 2100. The point wasn’t to fight climate change per se, but to signal our climate virtue in the hopes of catalyzing action by other nations and, not incidentally, hobble the U.S. coal industry in favor of more politically palatable sources of energy, namely wind and solar.

An irony emerges on this third point. In order to propose a regulatory change, the EPA must present calculations pertaining to the “Social Cost of Carbon (SCC)”, now renamed “Social Cost of CO2 (SC-CO2)”. In the document released by EPA, this Regulatory Impact Analysis (RIA), begins on page 30 with several tables.

Methodology Considerations:

In addition to presenting results from the 2015 CPP RIA, this RIA uses two additional quantitative approaches to analyze the effects of the CPP in order to present information on the potential effects of the proposed repeal of the CPP. The first approach involves a modest reworking of the 2015 CPP RIA to increase transparency and illuminate the uncertainties associated with assessing benefits and costs of the CPP, as reflected in the 2015 analysis, as well as analyzing the potential effects of the CPP repeal. More specifically, this analysis increases transparency of the 2015 CPP analysis by presenting the energy efficiency cost savings as a benefit rather than a cost reduction and provides a bridge to future analyses that the agency is committed to performing. The current analysis also provides alternative approaches for examining the foregone benefits, including more clearly distinguishing the direct benefits from the co-benefits and exploring alternative ways to illustrate the impacts on the total net benefits of the uncertainty in health co-benefits at various PM2.5 cutpoints. This approach shifts the focus to the domestic (rather than global) social cost of carbon, and employs both 3 percent and 7 percent discount rates. Finally, we consider that how changing market conditions and technologies may have affected future actions that may have been undertaken by states to comply with the CPP and how these changes may affect the potential benefits and costs of the CPP repeal. Pg. 30

As the RIA analyzes costs and benefits applying a variety of different methods and discount rates, there is a relatively large number of results. We present the full suite of avoided compliance cost, forgone benefit, and net benefit results discussed in the RIA in Tables 1 through 3. Pg 33

Therefore, in Tables 4 and 5 we offer another perspective on the costs and benefits of this rule by presenting a comparison of the forgone benefits from the targeted pollutant – CO2 – (the costs of this proposed rule) with the avoided compliance cost (the benefits of this proposed rule). Excluded from this comparison are the forgone benefits from the SO2 and NOX emission reductions that were also projected to accompany the CO2 reductions. However, had those SO2 and NOX reductions been achieved through other means, then they would have been represented in the baseline for this proposed repeal (as well as for the 2015 Final CPP), which would have affected the estimated costs and benefits of controlling CO2 emissions alone. Pg.37

Table 5 Gives the Bottom Line (in billions of US$)

Year Discount 
Rate
Compliance Costs 
Avoided
Forgone Domestic 
Climate Benefits
2020 3% ($0.30) $0.10
7% ($0.30) $0.00
2025 3% $14.50 $1.30
7% $14.50 $0.20
2030 3% $14.40 $2.50
7% $14.40 $0.40

 

Summary

There will be lots of pushback on these numbers since they show billions of compliance cost against miniscule benefits.

Lowry: If Congress had authorized the EPA to remake the nation’s energy economy, we would presumably be aware of it and recall an impassioned congressional debate over this radical and costly change. In fact, the opposite is true. Congress has declined to enact laws limiting carbon emissions, including when Democrats held both houses of Congress under President Obama. If the future of the planet is at stake and it requires a generational effort to save it, surely it is not too much to ask that a statute or two be enacted by Congress explicitly committing the country to the task. Yes, this requires winning elections and gaining democratic assent, but such are the challenges of living in a republic and a nation of laws.

 

For background on SCC, now termed SC-CO2:

Social Cost of Carbon: Origins and Prospects

Six Reasons to Rescind Social Cost of Carbon

SBC: Social Benefits of Carbon

 

Hurricane Science, not Fiction

We continue to see activist journalism claiming recent hurricanes prove global warming and the need for efforts like the Paris accord. People writing these articles seem oblivious to the meteorological science pertaining to tropical storms. The intentional deception is discussed more fully in the post Media Duping Scandal.

Joseph D’Aleo of WeatherBELL comes to the rescue with a primer for the public to gain literacy on this topic.

What Made This Hurricane Season So Active in the Atlantic? summarizes for all of us what is common sense weather knowledge, with graphs and images to enhance understanding of this science. Excerpts below with my bolds.

What a hurricane season! It started very early with Arlene in April but the real action held off until the last week of August, when Hurricane Harvey flooded Texas and Louisiana. Harvey was the first hurricane to make landfall in Texas since Ike in 2008 and the first Category 4 hurricane in Texas since Carla in 1961.

(D’Aleo summarizes the sequence of Irma, Jose, Maria and Nate, then digs into the issues.)

Before the landfall of two major storms on the U.S. we had gone just short of 12 years without a major hurricane landfall, the longest such lull since the 1860s.

The quiet period came after three big years. Isabel made landfall on the Mid Atlantic in 2003. Charley, Frances, Ivan and Jeanne in 2004 and Dennis, Katrina, Rita and Wilma in 2005 all made landfall on the mainland. Emily in 2005 was another major hurricane but turned west into Mexico. 2005 holds the record for five Category 4 or greater and four Category 5 impact storms. Some speculated this was the new norm for the Atlantic before nature gave us that 12-year break.

So what causes long quiet spells and then big years like 2004 and 2005 and now 2017?

(D’Aleo then describes the historical context regarding these storms.)

Okay, major hurricanes have occurred even during cold periods, but is there a trend in the modern record?

The Accumulated Cyclone Energy index measures seasonal tropical activity.

The Accumulated Cyclone Energy index takes into account the number, duration and strength of all tropical storms in a season. The ACE index is a wind energy index, defined as the sum of the squares of the maximum sustained surface wind speed (knots) measured every six hours for all named storms while they are at least tropical storm strength.

The ACE index for the Atlantic shows a cyclical behavior with no long-term trend but with spikes in 1893, 1926, 1933 and 1950 then again in 1995, 2004 and 2005. 2017 ranks 8th now with still weeks to go this season.

So what causes long breaks and then big years like 2004 and 2005 and now 2017?

OCEAN TEMPERATURE AND PRESSURE PATTERNS

The North Atlantic, like the Pacific, undergoes multi-decadal changes in ocean temperature and pressure patterns. It has long been known that when the Atlantic is in what is called its warm mode, there are more storms. Since 1995, when the current warm Atlantic mode began, we have average 14.6 named storms per year, more than five greater than the long-term 1851-2017 average.

An important factor that affects whether hurricanes affect the United States is El Niño and La Niña. When El Niños develop, more storms develop in the eastern and central Pacific, threatening Mexico, Hawaii and sometimes in weakened forms Arizona and California.

These storms enhance high-level winds that cross into the Atlantic. These winds produce shear that disrupts developing storms, causing them to weaken or dissipate and/or turn harmlessly north into the North Atlantic. Storms can still develop near the coast where the water is warm like in the Gulf and near the Gulf Stream off the southeast coast.

When La Ninas develop there are usually fewer storms in the eastern Pacific and less shear to disrupt the Atlantic storms.

In warm Atlantic years, that means trouble as the storms can track the entire basin with more time to turn into major hurricanes. Even the East Coast is more vulnerable to a landfalling hurricane. We had eight high-impact East Coast hurricanes from 1938 to 1960 and nine from 1988 to 2012.

The last important La Niña stretch was in 2010/11 to 2011/12. We avoided a major hurricane hit, though major hurricanes at sea made final landfall in the NYC metro — Irene (as a tropical storm) in 2011 and Sandy in 2012 (as a post-tropical cyclone). They caused massive flooding (from rains with Irene in upstate NY and Vermont and from a storm surge with Sandy in New York City and New Jersey).

We are still in the latest Atlantic warm period. This year, a spring attempt at an El Niño failed and La Niña-like conditions developed. Had El Niño succeeded we may have had Harvey, which developed near the Texas coast, and Nate, which came out of the bath water in the western Caribbean, but maybe Irma and Maria would have been weakened or deflected. But with La Niña conditions developing, no shear and warm Atlantic water we saw a return to big storms just as we saw in 2004 and 2005.

Summary

So when we get a year like 2017 or back-to-back bad years like 2004 and 2005, we have to accept that is how the weather works. Permadroughts ended with record wet years for Texas and California this decade. The record nearly 12-year major hurricane “drought” ended with 2017.

Joe D’Aleo is currently a senior co-chief meteorologist with WeatherBELL Analytics. Joe is a CCM, fellow of the AMS and former chair of the AMS Committee on Weather Analysis and Forecasting. He was a college professor of meteorology/climatology, the co-founder and first director of meteorology at The Weather Channel and chief meteorologist with three companies. He is the executive director of Icecap.us since 2007.

Climate Science: Put Up or Shut Up

That’s the theme of an article by Rowan Dean in The Courier-Mail, Australia:  Time for climate scientists to produce evidence that carbon dioxide emissions affect climate  Full text below with my bolds and images.

IT’S time for so-called climate scientists to either cough up one single, solitary shred of genuine scientific evidence that proves that the climate is being changed by mankind’s carbon dioxide emissions, or ‘fess up and admit that the whole thing is a gigantic hoax.

That’s the bottom line.

Asked at the beginning of this year for one of those “predictions for 2017”, I claimed that this would be the year the Australian public wakes up and realises they are being hoodwinked by the whole climate change/renewables scam.

I told Paul Murray’s lively late night TV show on Sky News that 2017 would be the year the climate con comes to an end. So how is my prediction going?

Well, so far this year two extraordinary books have come out, and one insightful film, that support my argument that the public is indeed waking up to the tricks of the climate change/renewables fraud.

Climate Change: The Facts 2017, a series of essays published by the Institute of Public Affairs, not only debunks the entire scare campaign about the Great Barrier Reef, but in a piece of superb investigative work Dr Jennifer Marohasy exposes the Bureau of Meteorology’s embarrassing manipulation of temperature data.

The book has sold out three print runs and gained serious attention overseas. Then came the surprise hit film Climate Hustle by sceptic Marc Morano, which was, ironically, more popular than the scaremongering Al Gore film it challenged.

And this week a new book is coming out by Australia’s Ian Plimer, one of our greatest geologists.

Called Climate Change Delusion and the Great Electricity Rip-off it’s a must-read for anyone who still believes they’re saving the planet by paying through the nose for electricity.  Because you’re not. The planet is doing just fine with or without your financial impoverishment, and whatever changes may or may not be occurring to our planet’s climate, it almost certainly has nothing to do with your gas bill.

As Plimer points out, Australia is blessed with an abundance of the cheapest and cleanest energy on the planet, yet we are paying the highest electricity prices on earth.

Put simply, that doesn’t add up. And when something smells fishy, it’s because it is.

Australian taxpayers are being ripped off by deluded luvvies (Turnbull is one of the worst) pandering to the voracious leeches of the renewables industry and their greedy investors gorging on a bloated smorgasbord of your cash which they siphon up via subsidies, targets and bills.

Yet, as Plimer points out, it’s all in vain. With rigorous scientific and geological data, Plimer provides evidence that the climate “experts” fail to provide. He shows that Earth has frequently warmed up, cooled down, and warmed up again, but this process has never had anything to do with CO2.

Indeed, the geological evidence is that Earth’s coldest periods often had far higher atmospheric CO2 levels than we do now. What’s more, the mild warming we may currently be experiencing (we are, geologically speaking, still in an Ice Age and moving slowly out of it) has always been associated in human history with increased health, wealth, fertility and prosperity.

Mankind’s most successful times have been in periods such as the Roman era or medieval warming when the Earth was warmer than it is now.

Indeed, we are currently seeing flora around the globe getting greener and more fertile as CO2 levels increase.

Meanwhile, desperately trying to reinvigorate the whole tiresome climate change alarmist nonsense, this year we got Al Gore’s latest horror flick-cum-ad for his own renewables investments An Inconvenient Sequel (what an unoriginal title).

Showing suitably terrifying footage of storms, floods and hurricanes, the film was a box-office flop that received lacklustre reviews at best. Oh, and the other day an ANU “climate scientist” made the hysterical (and unprovable) claim that Sydney and Melbourne “could” roast in 50 degree summers by the end of the century.

Global Mean Temperature from land and ocean expressed in absolute degrees F.

That’s it. And still no proof that man-made carbon dioxide emissions are warming the planet. Still no proof that a warmer planet can be avoided, or would actually be a bad thing. Still no proof that removing civilisation’s reliance on coal is even remotely feasible. Still no proof that even if we did do all the things climate fanatics want us to do and destroy our economies and lifestyles, it would make the slightest difference to global temperatures. And still no proof that we even need to.

The biggest con of all is that Australian voters are denied any political leadership courageous enough to call out this scaremongering for what it is, cancel all our subsidies, targets and the Paris Agreement, which only enrich renewables carpetbaggers, and return us to a land blessed with cheap, abundant energy.

 

Natural Climate Factors: Snow

Variations in Siberian snow cover October (day 304) 2004 to 2016. Eurasian snow charts from IMS.

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.

cohen-schematic2

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.

From Eurasian Snow Cover Variability and Links with Stratosphere-Troposphere
Coupling and Their Potential Use in Seasonal to Decadal Climate Predictions by Judah Cohen.

Observations of the Snow Climate Factor

The animation at the top shows from remote sensing that Eurasian snow cover fluctuates significantly from year to year, taking the end of October as a key indicator.

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.

What About Winter 2017-2018?

These data confirm that Dr. Cohen and colleagues are onto something. Here are excerpts from his October 2 outlook for the upcoming season AER. (my bolds)

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.

Summary

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.

Uh oh.  Now where did I put away my long johns?

Climate Model Upgraded: INMCM5 Under the Hood

A previous analysis Temperatures According to Climate Models showed that only one of 42 CMIP5 models was close to hindcasting past temperature fluctuations. That model was INMCM4, which also projected an unalarming 1.4C warming to the end of the century, in contrast to the other models programmed for future warming five times the past.

In a recent comment thread, someone asked what has been done recently with that model, given that it appears to be “best of breed.” So I went looking and this post summarizes further work to produce a new, hopefully improved version by the modelers at the Institute of Numerical Mathematics of the Russian Academy of Sciences.

Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, Russia

Earlier this year came this publication Simulation of the present-day climate with the climate model INMCM5 by E.M. Volodin et al. Excerpts below with my bolds.

In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions.

Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979–2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as  well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings.

The family of INMCM climate models, as most climate system models, consists of two main blocks: the atmosphere general circulation model, and the ocean general circulation model. The atmospheric part is based on the standard set of hydrothermodynamic equations with hydrostatic approximation written in advective form. The model prognostic variables are wind horizontal components, temperature, specific humidity and surface pressure.

Atmosphere Module

The INMCM5 borrows most of the atmospheric parameterizations from its previous version. One of the few notable changes is the new parameterization of clouds and large-scale condensation. In the INMCM5 cloud area and cloud water are computed prognostically according to Tiedtke (1993). That includes the formation of large-scale cloudiness as well as the formation of clouds in the atmospheric boundary layer and clouds of deep convection. Decrease of cloudiness due to mixing with unsaturated environment and precipitation formation are also taken into account. Evaporation of precipitation is implemented according to Kessler (1969).

In the INMCM5 the atmospheric model is complemented by the interactive aerosol block, which is absent in the INMCM4. Concentrations of coarse and fine sea salt, coarse and fine mineral dust, SO2, sulfate aerosol, hydrophilic and hydrophobic black and organic carbon are all calculated prognostically.

Ocean Module

The oceanic module of the INMCM5 uses generalized spherical coordinates. The model “South Pole” coincides with the geographical one, while the model “North Pole” is located in Siberia beyond the ocean area to avoid numerical problems near the pole. Vertical sigma-coordinate is used. The finite-difference equations are written using the Arakawa C-grid. The differential and finite-difference equations, as well as methods of solving them can be found in Zalesny etal. (2010).

The INMCM5 uses explicit schemes for advection, while the INMCM4 used schemes based on splitting upon coordinates. Also, the iterative method for solving linear shallow water equation systems is used in the INMCM5 rather than direct method used in the INMCM4. The two previous changes were made to improve model parallel scalability. The horizontal resolution of the ocean part of the INMCM5 is 0.5 × 0.25° in longitude and latitude (compared to the INMCM4’s 1 × 0.5°).

Both the INMCM4 and the INMCM5 have 40 levels in vertical. The parallel implementation of the ocean model can be found in (Terekhov etal. 2011). The oceanic block includes vertical mixing and isopycnal diffusion parameterizations (Zalesny et al. 2010). Sea ice dynamics and thermodynamics are parameterized according to Iakovlev (2009). Assumptions of elastic-viscous-plastic rheology and single ice thickness gradation are used. The time step in the oceanic block of the INMCM5 is 15 min.

Note the size of the human emissions next to the red arrow.

Carbon Cycle Module

The climate model INMCM5 has а carbon cycle module (Volodin 2007), where atmospheric CO2 concentration, carbon in vegetation, soil and ocean are calculated. In soil, а single carbon pool is considered. In the ocean, the only prognostic variable in the carbon cycle is total inorganic carbon. Biological pump is prescribed. The model calculates methane emission from wetlands and has a simplified methane cycle (Volodin 2008). Parameterizations of some electrical phenomena, including calculation of ionospheric potential and flash intensity (Mareev and Volodin 2014), are also included in the model.

Surface Temperatures

When compared to the INMCM4 surface temperature climatology, the INMCM5 shows several improvements. Negative bias over continents is reduced mainly because of the increase in daily minimum temperature over land, which is achieved by tuning the surface flux parameterization. In addition, positive bias over southern Europe and eastern USA in summer typical for many climate models (Mueller and Seneviratne 2014) is almost absent in the INMCM5. A possible reason for this bias in many models is the shortage of soil water and suppressed evaporation leading to overestimation of the surface temperature. In the INMCM5 this problem was addressed by the increase of the minimum leaf resistance for some vegetation types.

Nevertheless, some problems migrate from one model version to the other: negative bias over most of the subtropical and tropical oceans, and positive bias over the Atlantic to the east of the USA and Canada. Root mean square (RMS) error of annual mean near surface temperature was reduced from 2.48 K in the INMCM4 to 1.85 K in the INMCM5.

Precipitation

In mid-latitudes, the positive precipitation bias over the ocean prevails in winter while negative bias occurs in summer. Compared to the INMCM4, the biases over the western Indian Ocean, Indonesia, the eastern tropical Pacific and the tropical Atlantic are reduced. A possible reason for this is the better reproduction of the tropical sea surface temperature (SST) in the INMCM5 due to the increase of the spatial resolution in the oceanic block, as well as the new condensation scheme. RMS annual mean model bias for precipitation is 1.35mm day−1 for the INMCM5 compared to 1.60mm day−1 for the INMCM4.

Cloud Radiation Forcing

Cloud radiation forcing (CRF) at the top of the atmosphere is one of the most important climate model characteristics, as errors in CRF frequently lead to an incorrect surface temperature.

In the high latitudes model errors in shortwave CRF are small. The model underestimates longwave CRF in the subtropics but overestimates it in the high latitudes. Errors in longwave CRF in the tropics tend to partially compensate errors in shortwave CRF. Both errors have positive sign near 60S leading to warm bias in the surface temperature here. As a result, we have some underestimation of the net CRF absolute value at almost all latitudes except the tropics. Additional experiments with tuned conversion of cloud water (ice) to precipitation (for upper cloudiness) showed that model bias in the net CRF could be reduced, but that the RMS bias for the surface temperature will increase in this case.

A table from another paper provides the climate parameters described by INMCM5.

Climate Parameters Observations INMCM3 INMCM4 INMCM5
Incoming solar radiation at TOA 341.3 [26] 341.7 341.8 341.4
Outgoing solar radiation at TOA   96–100 [26] 97.5 ± 0.1 96.2 ± 0.1 98.5 ± 0.2
Outgoing longwave radiation at TOA 236–242 [26] 240.8 ± 0.1 244.6 ± 0.1 241.6 ± 0.2
Solar radiation absorbed by surface 154–166 [26] 166.7 ± 0.2 166.7 ± 0.2 169.0 ± 0.3
Solar radiation reflected by surface     22–26 [26] 29.4 ± 0.1 30.6 ± 0.1 30.8 ± 0.1
Longwave radiation balance at surface –54 to 58 [26] –52.1 ± 0.1 –49.5 ± 0.1 –63.0 ± 0.2
Solar radiation reflected by atmosphere      74–78 [26] 68.1 ± 0.1 66.7 ± 0.1 67.8 ± 0.1
Solar radiation absorbed by atmosphere     74–91 [26] 77.4 ± 0.1 78.9 ± 0.1 81.9 ± 0.1
Direct hear flux from surface     15–25 [26] 27.6 ± 0.2 28.2 ± 0.2 18.8 ± 0.1
Latent heat flux from surface     70–85 [26] 86.3 ± 0.3 90.5 ± 0.3 86.1 ± 0.3
Cloud amount, %     64–75 [27] 64.2 ± 0.1 63.3 ± 0.1 69 ± 0.2
Solar radiation-cloud forcing at TOA         –47 [26] –42.3 ± 0.1 –40.3 ± 0.1 –40.4 ± 0.1
Longwave radiation-cloud forcing at TOA          26 [26] 22.3 ± 0.1 21.2 ± 0.1 24.6 ± 0.1
Near-surface air temperature, °С 14.0 ± 0.2 [26] 13.0 ± 0.1 13.7 ± 0.1 13.8 ± 0.1
Precipitation, mm/day 2.5–2.8 [23] 2.97 ± 0.01 3.13 ± 0.01 2.97 ± 0.01
River water inflow to the World Ocean,10^3 km^3/year 29–40 [28] 21.6 ± 0.1 31.8 ± 0.1 40.0 ± 0.3
Snow coverage in Feb., mil. Km^2 46 ± 2 [29] 37.6 ± 1.8 39.9 ± 1.5 39.4 ± 1.5
Permafrost area, mil. Km^2 10.7–22.8 [30] 8.2 ± 0.6 16.1 ± 0.4 5.0 ± 0.5
Land area prone to seasonal freezing in NH, mil. Km^2 54.4 ± 0.7 [31] 46.1 ± 1.1 48.3 ± 1.1 51.6 ± 1.0
Sea ice area in NH in March, mil. Km^2 13.9 ± 0.4 [32] 12.9 ± 0.3 14.4 ± 0.3 14.5 ± 0.3
Sea ice area in NH in Sept., mil. Km^2 5.3 ± 0.6 [32] 4.5 ± 0.5 4.5 ± 0.5 6.1 ± 0.5

Heat flux units are given in W/m^2; the other units are given with the title of corresponding parameter. Where possible, ± shows standard deviation for annual mean value.  Source: Simulation of Modern Climate with the New Version Of the INM RAS Climate Model (Bracketed numbers refer to sources for observations)

Ocean Temperature and Salinity

The model biases in potential temperature and salinity averaged over longitude with respect to WOA09 (Antonov et al. 2010) are shown in Fig.12. Positive bias in the Southern Ocean penetrates from the surface downward for up to 300 m, while negative bias in the tropics can be seen even in the 100–1000 m layer.

Nevertheless, zonal mean temperature error at any level from the surface to the bottom is small. This was not the case for the INMCM4, where one could see negative temperature bias up to 2–3 K from 1.5 km to the bottom nearly al all latitudes, and 2–3 K positive bias at levels of 700–1000 m. The reason for this improvement is the introduction of a higher background coefficient for vertical diffusion at high depth (3000 m and higher) than at intermediate depth (300–500m). Positive temperature bias at 45–65 N at all depths could probably be explained by shortcomings in the representation of deep convection [similar errors can be seen for most of the CMIP5 models (Flato etal. 2013, their Fig.9.13)].

Another feature common for many present day climate models (and for the INMCM5 as well) is negative bias in southern tropical ocean salinity from the surface to 500 m. It can be explained by overestimation of precipitation at the southern branch of the Inter Tropical Convergence zone. Meridional heat flux in the ocean (Fig.13) is not far from available estimates (Trenberth and Caron 2001). It looks similar to the one for the INMCM4, but maximum of northward transport in the Atlantic in the INMCM5 is about 0.1–0.2 × 1015 W higher than the one in the INMCM4, probably, because of the increased horizontal resolution in the oceanic block.

Sea Ice

In the Arctic, the model sea ice area is just slightly overestimated. Overestimation of the Arctic sea ice area is connected with negative bias in the surface temperature. In the same time, connection of the sea ice area error with the positive salinity bias is not evident because ice formation is almost compensated by ice melting, and the total salinity source for these pair of processes is not large. The amplitude and phase of the sea ice annual cycle are reproduced correctly by the model. In the Antarctic, sea ice area is underestimated by a factor of 1.5 in all seasons, apparently due to the positive temperature bias. Note that the correct simulation of sea ice area dynamics in both hemispheres simultaneously is a difficult task for climate modeling.

The analysis of the model time series of the SST anomalies shows that the El Niño event frequency is approximately the same in the model and data, but the model El Niños happen too regularly. Atmospheric response to the El Niño vents is also underestimated in the model by a factor of 1.5 with respect to the reanalysis data.

Conclusion

Based on the CMIP5 model INMCM4 the next version of the Institute of Numerical Mathematics RAS climate model was developed (INMCM5). The most important changes include new parameterizations of large scale condensation (cloud fraction and cloud water are now the prognostic variables), and increased vertical resolution in the atmosphere (73 vertical levels instead of 21, top model level raised from 30 to 60 km). In the oceanic block, horizontal resolution was increased by a factor of 2 in both directions.

The climate model was supplemented by the aerosol block. The model got a new parallel code with improved computational efficiency and scalability. With the new version of climate model we performed a test model run (80 years) to simulate the present-day Earth climate. The model mean state was compared with the available datasets. The structures of the surface temperature and precipitation biases in the INMCM5 are typical for the present climate models. Nevertheless, the RMS error in surface temperature, precipitation as well as zonal mean temperature and zonal wind are reduced in the INMCM5 with respect to its previous version, the INMCM4.

The model is capable of reproducing equatorial stratospheric QBO and SSWs.The model biases for the sea surface height and surface salinity are reduced in the new version as well, probably due to increasing spatial resolution in the oceanic block. Bias in ocean potential temperature at depths below 700 m in the INMCM5 is also reduced with respect to the one in the INMCM4. This is likely because of the tuning background vertical diffusion coefficient.

Model sea ice area is reproduced well enough in the Arctic, but is underestimated in the Antarctic (as a result of the overestimated surface temperature). RMS error in the surface salinity is reduced almost everywhere compared to the previous model except the Arctic (where the positive bias becomes larger). As a final remark one can conclude that the INMCM5 is substantially better in almost all aspects than its previous version and we plan to use this model as a core component for the coming CMIP6 experiment.

Summary

One the one hand, this model example shows that the intent is simple: To represent dynamically the energy balance of our planetary climate system.  On the other hand, the model description shows how many parameters are involved, and the complexity of processes interacting.  The attempt to simulate operations of the climate system is a monumental task with many outstanding challenges, and this latest version is another step in an iterative development.

Note:  Regarding the influence of rising CO2 on the energy balance.  Global warming advocates estimate a CO2 perturbation of 4 W/m^2.  In the climate parameters table above, observations of the radiation fluxes have a 2 W/m^2 error range at best, and in several cases are observed in ranges of 10 to 15 W/m^2.

We do not yet have access to the time series temperature outputs from INMCM5 to compare with observations or with other CMIP6 models.  Presumably that will happen in the future.

Early Schematic: Flows and Feedbacks for Climate Models

Degrees of Climate Truth

Previous posts have dealt with science as a mode of inquiry, and described the process of theory and observation by which scientific knowledge is obtained. This post presents work by Andy May to classify the degrees of scientific certainty or truth, and apply these to climate claims.

The essay Facts and Theories comes from his blog Andy May Petrophysicist.
Excerpts below with my bolds.

Categories of Scientific Knowledge

Newton provided us with his descriptive “Law of Gravitation.” Newton’s law tells us what gravity does and it is very useful, but it tells us nothing about how it works. For that we need Einstein’s theory of relativity. Theories and laws are not necessarily related in science. A law simply describes what happens without describing why. A scientific theory attempts to explain why a relationship holds true.

In the scientific community, for both a law and a theory, a single conflicting experiment or observation invalidates them. Einstein once said:

“No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”

So, let’s examine our topics in that light. Newton’s descriptive law of gravity, based on mass and distance, are there any exceptions? Not to my knowledge, except possibly on galactic sized scales, black holes and probably on very, very small sub-atomic scales. In everyday life, Newton’s law works fine. How about Einstein’s theory of gravity (Relativity), any exceptions? None that I know of at any scale.

How about evolution? Species evolve, we can see that in the geological record. We can also watch it happen in some quickly reproducing species. Thus we could describe evolution as a fact. It happens, but we cannot describe how without more work. Early theories of the evolutionary process include Darwin’s theory of natural selection and Lamarck’s theory of heritable species adaptation due to external stresses. Due to epigenetic research we now know that Darwin and Lamarck were both right and that evolution involves both processes. For a summary of recent research into the epigenetic component of evolution see this Oxford Journal article. Thus well-established facts and scientific laws rarely change but theories do evolve. I might add that while facts and laws don’t often change, they are easily dismissed when contradictory data are gathered. The modern theory of evolution is a good example of where competing theories can merge into one.

Most scientific theories begin as hypotheses. A hypothesis is best described as an idea of what might be causing a specific event to occur. A proper scientific hypothesis, like a theory, must be falsifiable. That is, we must be able to design an experiment or foresee an observation that will make the hypothesis false. “Climate change” is not falsifiable, it is not a scientific hypothesis or a theory. “Man-made climate change” is a scientific hypothesis since it is falsifiable. Hypotheses and theories are evolving things, new facts and observations cause them to change. In this way we build the body of science. Science is mostly skepticism. We look for what does not fit, we poke at established facts and laws, at theories and hypotheses. We try and find flaws, we check the numbers. Worse, science done properly means we spend more time proving ourselves wrong than we do proving we are right. Life is tough sometimes.

So how does this fit with the great climate change debate. I’ve made a table of phrases and identified each common phrase as a fact, theory, law, hypothesis, or simply an idea. These are my classifications and certainly open for debate.

In Table 1 we can see that the comparison of man-made climate change and the possibility of a man-made climate catastrophe are not really comparable to the theories of gravity and evolution. Man-made climate change is more than an idea, it is based on some observations and reasonable models of the process have been developed and can be tested. But, none of the models have successfully predicted any climatic events. Thus, they are still a work-in-progress and not admissible as evidence supporting a scientific theory.

The idea of man-made climate change causing a catastrophe at the scale of Islamic terrorism is pure speculation. The models used to compute man’s influence don’t match any observations, this is easily seen in Figure 1 which is Dr. John Christy’s graph of the computer model’s predictions versus satellite and weather balloon observations. I should mention that satellite and weather balloon measurements are independent of one another and they are independent of the various surface temperature datasets, like HADCRUT and GHCN-M. All of the curves on the plot have been smoothed with five year averages.

The purple line going through the observations is the Russian model “INM-CM4.” It is the only model that comes close to reality. INM-CM4, over longer periods, does very well at hindcasting observed temperatures. This model uses a CO2 forcing response that is 37% lower than the other models, a much higher deep ocean heat capacity (climate system inertia) and it exactly matches lower tropospheric water content and is biased low above that. The other models are biased high. The model predicts future temperature increases at a rate of about 1K/century, not at all alarming and much lower than the predictions of the other models. (See Temperatures According to Climate Models)

One can consider each model to be a digital experiment. It is clear that the range of values from these digital experiments exceeds the predicted average temperature increase. This does not give us much confidence in the accuracy of the models. Yet, the IPCC uses the difference between the mean model temperature anomalies and observed surface temperatures since 1950 to compute man’s influence on climate.   (See Climate Models Explained)

In particular Soon, Connolly and Connolly (SCC15) believe that the IPCC chose an inappropriate model of the variation in the sun’s output (TSI or total solar irradiance). There are many models of solar variation in the peer reviewed literature and it is a topic of vigorous debate. Eight recent models are presented in Figure 8 of SCC15 (see Figure 3). Only low solar variability models (those on the right of Figure 3) are used by the IPCC to compute man’s influence on climate although just as much evidence exists for the higher variability models on the left. The scales used in the graphs are all the same, but the top and bottom values vary. At minimum, the IPCC should have run two cases, one for high variability and one for low. SCC15 clearly shows that the model used makes a big difference.

Any computer Earth model must establish a track record before it is used in calculations. The Earth is simply too complex and natural climate cycles are poorly understood. If natural cycles cannot be predicted they cannot be subtracted from observations to give us man’s influence on climate. The debate is not whether man influences climate, the debate is over how much man contributes and whether or not the additional warming dangerous. This observer, familiar with the science, would say the jury is still out. Certainly, the case for an impending catastrophe has not been made as this requires two speculative jumps. First, we need to assume that man is the dominant driver of climate, second we need to assume this will lead to a catastrophe. One can predict a possible catastrophe if the most extreme climate models are correct, but the record shows they are not. Only INM-CM4 matches observations reasonably well and INM-CM4 does not predict anything remotely close to a catastrophe.

In the study of the process of evolution the problem is the same. Some believe that the dominant process is natural selection and epigenetic change is minor. Some believe the opposite. Everyone believes that both play a role. As in climate science, figuring out which process is dominant is tough.

Recent climate history (the “pause” in warming) suggests that we have plenty of time to get our arms around this problem before doing anything drastic like destroying the fossil fuel industry and sending billions of people into poverty due to a lack of affordable energy.

Summary:  Scientific vs. Social Proof

In the IPCC reports certainty is presented in terms of social proofs. For example, an assertion is rated as Very High Confidence, or 95% Certain, meaning almost all consulted experts held that opinion. A claim rated as Moderate Confidence is in fact 50% Certain, meaning it is regarded as equally unlikely. Statements regarded as Low Confidence are thought to be so improbable that one wonders why they are presented. In any case, these are not scientific assessments, but rather opinion polling of people thought to be knowledgeable.

In contrast, Andy May demonstrates how scientific proof is obtained: A law or theory stands as along as no exceptions have been found. Or the law or theory is modified to stipulate more clearly under what conditions it operates. His classification of climate facts, theories and ideas sits well with me and helps to clarify what is presently known and unknown in this field.

As shown above, a theory or hypothesis falls if exceptions are observed.  Are there exceptions to the hypothesis of man-made global warming?  Yes, indeed there are many.  One of the most important disproofs (it only takes one) is actually provided by the climate models.

Figure 5. Simplification of IPCC AR5 shown above in Fig. 4. The colored lines represent the range of results for the models and observations. The trends here represent trends at different levels of the tropical atmosphere from the surface up to 50,000 ft. The gray lines are the bounds for the range of observations, the blue for the range of IPCC model results without extra GHGs and the red for IPCC model results with extra GHGs.The key point displayed is the lack of overlap between the GHG model results (red) and the observations (gray). The nonGHG model runs (blue) overlap the observations almost completely.

IPCC Assessment Reports show that the IPCC climate models performed best versus observations when they did not include extra GHGs and this result can be demonstrated with a statistical model as well.

Full explanation at Warming from CO2 Unlikely

For more on measurements and science see Data, Facts and Information

 

Sorry Climate Science

h/t Scottish Skeptic for referring to this article by James Delingpole in the Sun UK

How scientists got their global warming sums wrong — and created a £1TRILLION-a-year green industry that bullied experts who dared to question the figures

The summary puts the point clearly.  The scientists who produce those doomsday reports for the Intergovernmental Panel on Climate Change finally come clean. The planet has stubbornly refused to heat up to predicted levels.  Read the whole thing.  Favorite excerpts below with my bolds.

I’VE just discovered the hardest word in science.

Not pneumonoultramicroscopicsilicovolcanoconiosis (inflammation of the lungs caused by inhalation of silica dust). Nor palmitoyloleoylphosphatidylethanolamine (a lipid bilayer found in nerve tissue).

No, the actual hardest word — which scientists use so rarely it might as well not exist — is “Sorry”.

Which is a shame because right now the scientists owe us an apology so enormous that I doubt even a bunch of two dozen roses every day for the rest of our lives is quite enough to make amends for the damage they’ve done.

Thanks to their bad advice on climate change our gas and electricity bills have rocketed.

So too have our taxes, our car bills and the cost of flying abroad, our kids have been brainwashed into becoming tofu-munching eco-zealots, our old folk have frozen to death in fuel poverty, our countryside has been blighted with ranks of space-age solar panels and bat-chomping, bird-slicing eco-crucifixes, our rubbish collection service hijacked by hectoring bullies, our cities poisoned with diesel fumes . . .

And all because a tiny bunch of ­scientists got their sums wrong and scared the world silly with a story about catastrophic man-made global warming.

This scare story, we now know, was at best an exaggeration, at worst a ­disgraceful fabrication. But while a handful of reviled and derided sceptics have been saying this for years, it’s only this week that those scientists have fessed up to their mistake.

One scientist has described the ­implications of the new Nature Geoscience report as “breathtaking”. He’s right. What it effectively does is scotch probably the most damaging ­scientific myth of our age — the notion that man-made carbon dioxide (CO2) is causing the planet to warm at such dangerous and ­unprecedented speeds that only massive government intervention can save us.

For a quarter of a century now — it all really got going in 1992 when 172 nations signed up to the Rio Earth Summit — our politicians have believed in and acted on this discredited theory.

Doomsday was predicted, but midnight passed without disaster.

In the name of saving the planet, war was declared on carbon dioxide, the benign trace gas which we exhale and which is so good for plant growth it has caused the planet to “green” by an extraordinary 14 per cent in the last 30 years.

This war on CO2 has resulted in a massive global decarbonisation industry worth around $1.5trillion (£1.11trillion) a year. Though it has made a handful of green crony capitalists very rich, it has made most of us much poorer, by forcing us to use expensive “renewables” instead of cheap, abundant fossil fuels.

So if the science behind all this ­nonsense was so dodgy, why did no one complain all these years?

Well, a few of us did. Some — such as Johnny Ball and David Bellamy — were brave TV celebrities, some — Graham Stringer, Peter Lilley, Owen Paterson, Nigel (now Lord) Lawson — were ­outspoken MPs, some were bona fide scientists. But whenever we spoke out, the response was the same — we were bullied, vilified, derided and dismissed as scientifically illiterate loons by a powerful climate alarmist establishment which brooked no dissent.

Unfortunately this alarmist establishment has many powerful media allies. The BBC has a huge roster of eco-activist reporters and science “experts” who believe in man-made global warming, and almost never gives sceptics air time.

It comes as little consolation to those of us who’ve been right all along to say: “I told you so.”

In the name of promoting the global warming myth, free speech has been curtailed, honest science corrupted and vast economic and social damage done. That ­apology is long overdue.

Footnote:

For a short course in how climate science was exploited, Richard Lindzen provides details and names in this post Climate Science Was Broken

Overview Winter Climate for NH

cohen-schematic2

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.  He explains the dynamics in an interview at Washington Post (here):

My colleagues, at AER and at selected universities, and I have found a robust relationship between two October Eurasian snow indices and the large-scale winter hemispheric circulation pattern known as the North Atlantic or Arctic Oscillation pattern (N/AO).

The N/AO is more highly correlated with or explains the highest variance of winter temperatures in eastern North America, Europe and East Asia than any other single or combination of atmospheric or coupled ocean-atmosphere patterns that we know of. Therefore, if we can predict the winter N/AO (whether it will be negative or positive) that provides the best chance for a successful winter temperature forecast in North America but certainly does not guarantee it.

[Of the two indices we’ve analyzed], the first and longer [more data points] index is simply the monthly mean snow cover extent (SCE) for the entire month [of October] as measured from satellites. This record dates back to at least 1972 and is available on the Rutger’s Global Snow Lab website.

The second index that we developed last year, with the support of NSF and NOAA grants, measures the daily rate of change of Eurasian snow cover extent also during the entire month of October, which we refer to as the Snow Advance Index or SAI.

There have been recent modeling studies that demonstrate that El Nino modulates the strength and position of the Aleutian Low that then favors stratospheric warmings and subsequently a negative winter N/AO that are consistent with our own research on the relationship between snow cover and stratospheric warmings. So the influence of ENSO on winter temperatures in the Mid-Atlantic and the Northeast may be greater than I acknowledge or that is represented in our seasonal forecast model.

How It Works

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.

From Eurasian Snow Cover Variability and Links with Stratosphere-Troposphere
Coupling and Their Potential Use in Seasonal to Decadal Climate Predictions by Judah Cohen

Extensive 2016 Siberian snowfall led to unusually rapid recovery of Arctic sea ice following relatively low September 2016 minimum.

What About Winter 2017-2018?

Dr. Cohen’s Winter Outlook for NH  September 18, 2017

Many important markers are currently being set indicating the atmosphere is beginning in earnest the transition from summer to winter. There are four features that I am monitoring closely over the coming weeks and months to gauge the evolving atmospheric circulation pattern and resultant weather across the NH.

The first is the nascent stratospheric polar vortex (PV). The PV has returned to the NH polar stratosphere. Much recent research including my own has shown that the relative strength of the PV if not forces, certainly leads prolonged periods of temperature anomalies across key regions of the NH. A strong PV is related to relatively milder temperatures across the mid-latitudes of the NH while a weak PV is related to relatively colder temperatures across the mid-latitudes of the NH. This relationship is strongest in mid-winter. Early signs are that the PV will start off relatively weak similar to last fall. This is somewhat surprising because increasing greenhouse gases favor colder stratospheric temperatures and hence a stronger PV. Poleward heat flux or vertical wave activity flux is predicted to be unusually active in the coming two weeks, which is likely the reason for the predicted relatively weak start to the PV.  (my bolds)

The active poleward heat flux is also likely related to the second feature that I will be following – high latitude blocking. The negative AO state is often a manifestation of strong high latitude blocking while the positive AO often reflects a lack of high latitude blocking. The predicted negative AO in the coming two weeks is a result of predicted strong high latitude blocking with the dominant block predicted to reside in the region of Scandinavia and the Barents-Kara seas. In the near term this will lead to a cold and snowy period across most of Siberia. Blocking in this region is favorable for weakening the stratospheric polar vortex and will likely lead to weakening of the PV over the next two weeks. If similar blocking occurs later on during the late fall and early winter it will favor a sudden stratospheric warming (SSW). SSW in the winter often precedes extended periods of severe winter weather across the continents of the NH. (my bolds)

The third feature is Arctic sea ice extent. The minimum in Arctic sea ice extent is achieved this time of year and if the minimum has not already been reached it should occur relatively soon. The past two blogs I suggested the possibility that the sea ice minimum could be similar to the years 2008 and 2010 and that is looking likely. Sea ice extent is extremely low compared to climatology but will not be a new record low. The largest anomalies are in the North Pacific side of the Arctic in the Beaufort Sea. This pattern matches recent Septembers. Typically, the largest anomalies migrate with the progression of fall to the North Atlantic side of the Arctic. It is my opinion that low sea ice favors high latitude blocking but the nature of the blocking is regionally dependent. For example, low sea ice in the Barents-Kara Seas favors blocking in the northwest Eurasia sector resulting in cold temperatures in parts of Asia. (my bolds)

The fourth feature is Siberian snow cover. 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. With a predicted strong negative AO in the coming weeks, snow cover is likely to advance relatively quickly heading into October. 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. Though admittedly, recent Siberian snow cover as a predictor of winter temperatures has been mixed.

Summary

Uh oh.  Now where did I put away my long johns?

Again Falsely Linking Smoking and Climate Science

Sarah Myhre is at it again, claiming climate science links storms to CO2 as certainly as smoking causes cancer.  Fossil fuel activists are obsessed with the smoking analogy, not least because oil companies have even deeper pockets than tobacco companies.

The analogy actually works against her on both sides.  Storms and CO2 are not correlated in the statistics, and she exaggerates the extent to which smoking results in cancer.  A previous post explains.

Original Post:  Climate Risky Business

A new theme emerging out of the IPCC Fifth Report was the emphasis on selling the risk of man-made climate change. The idea is that scientists should not advocate policy, but do have a responsibility to convince the public of the risks resulting from burning fossil fuels.

An article illustrates how this approach shapes recent public communications in support of actions on global warming/climate change.  Treading the Fine Line Between Climate Talk and Alarmism (Op-Ed)  By Sarah E. Myhre, Ph.D. | June 23, 2017.  Excerpts:

What is our role in public leadership as scientists? I would suggest a few action items: Work to reduce risk and cost for the public; steward the public’s interest in evidence; and be steady and committed to the scientific process of dissent, revision and discovery. This means communicating risk when necessary. We would never fault an oncologist for informing patients about the cancer risks that come with smoking. Why would we expect Earth scientists to be any different, when we’re just as certain?

As a public scholar with expertise in paleoclimate science, I communicate alarming, difficult information about the consequences to Earth and ocean systems that have come with past events of abrupt climate warming. As the saying goes, the past is the key to the future. 

We are living through a crisis of trust between the American public and climate scientists, and we must extend ourselves, as scientists and public servants, to rebuild transparency and trust with the public. I will start: I want the global community to mitigate the extreme risk of the warmest future climate scenarios. And, I want my kid to eat salmon and ski with his grandkids in the future. I am invested in that cooler, safer, more sustainable future — for your kids and for mine. Just don’t call me an alarmist.

This provides a teachable moment concerning the rhetorical maneuver to present climate as a risky business. The technique typically starts with a particular instance of actual risk and then makes a gross generalization so that the risk is exaggerated beyond reason.  From the article above:

Climate scientists are just as certain as oncologists are.

Herein lies the moral of this tale. The particular risk is the convincing epidemiological evidence linking lung cancer to smokers. The leap was claiming second-hand smoke puts non-smokers at risk of cancer. The statistical case was never conclusive, but the public was scared into enacting all kinds of smoke-free spaces.

Very few passive smoking/lung cancer studies are published these days compared to the glut of the 1980s and 1990s, but the handful that have appeared in recent years continue to support the null hypothesis. For all the campaigners’ talk of “overwhelming evidence”, the link between secondhand smoke and lung cancer has always been very shaky. It tends to be the smaller, case-control studies which find the associations while the larger, cohort studies do not (and, as the JNCI report notes, case-control studies “can suffer from recall bias: People who develop a disease that might be related to passive smoking are more likely to recall being exposed to passive smoking.”)

Gerard Silvestri, MD, of the Medical University of South Carolina, a member of NCI’s PDQ Screening and Prevention Editorial Board said (here):

“We’ve gotten smoking out of bars and restaurants on the basis of the fact that you and I and other nonsmokers don’t want to die,” said Silvestri. “The reality is, we probably won’t.”

To be clear, I don’t want smokers fouling my space in restaurants, and the policies are beneficial to me esthetically. But there was never any certainty about my risk of cancer, just the spoiling of clean air around me.  What was a matter of opinion and personal preference was settled politically by asserting scientific certainty of my health risk.

To draw the point finely, secondhand smoke shows how science is used by one group (anti-smoking activists) against another group (smokers) by mobilizing support for regulations on the basis of a generalized risk, raising concerns among the silent majority who otherwise were not particularly interested in the issue.

Climate as a Risky Business

Environmentalists have often employed risk exaggeration, beginning with Rachel Carson’s Silent Spring full of innuendo about DDT without any actual epidemiological proof. Currently Junk Science provides a list of EPA exaggerations about environmental pollution, for example The scientific fraud that claims air pollution is killing people

In the climate field, any flat Polynesian island is of course at risk of flooding, and thus by extension they produce images of Manhattan under water. Global risk is trumpeted, ignoring all the local particularities of land subsidence, tidal gauge records, terrain drainage features, infrastructure, precipitation patterns, etc.

Any storm, drought, flood, or unusual weather likewise presents a particular risk in the locale where it occurs. The gross exaggeration is to claim that we are increasing the risk of all these events, and by stopping burning fossil fuels we can prevent them from happening.

Sarah Myhre’s research focuses on ocean dead zones (oxygen-depleted waters), which is a real and long-studied risk. Then comes her leap into the fearful future:

The surface and deep ocean will continue to absorb heat and CO2 from the atmosphere. The heating of the ocean will increase the stratification of water (i.e. ocean mixing will be reduced, as will the strength of thermohaline circulation). Ocean heating will also drive the thermal expansion of the interior of the ocean – this is one of the primary contributors to sea level rise.

The absorption of CO2 from the atmosphere will drive changes in the chemistry of surface and deep waters – there are significant biological consequences to acidifying the global surface ocean. Basically, we are looking at the fundamental reorganization of biological communities and ecological provinces in the ocean. These physical drivers (warming, stratification, acidification) all area associated with significant biological consequences.

This is a continuation of a scare called Climate Change Is Suffocating The Oceans.  Once again climate alarmists/activists have seized upon an actual environmental issue, but misdirect the public toward their CO2 obsession, and away from practical efforts to address a real concern. Some excerpts from scientific studies serve to put things in perspective.  See Ocean Oxygen Misdirection

As a paleoclimate expert the author knows the climate and sea levels have changed many times in the past, and often shifted quickly in geological terms.

And yet the evidence shows clearly that CO2 follows as an effect of changing temperatures, not the cause.

Summary

Warmists are of the opinion that because of burning fossil fuels, our modern climate no longer compares to paleoclimates, a claim in fact that humans are overriding natural forces. But the message from the ice cores is clear: Through the ages, CO2 responds to temperatures and not the other way around.

The other message is also clear: Climates change between warm and cool, and warm has always been good for humans and the biosphere. We should concern ourselves with Adaptation, preparing for the cold times with robust infrastructure and reliable, affordable energy.

See also CO2 and Climate Change for the Ages

See also Claim: Fossil Fuels Cause Global Warming
Updated 2017  Fossil Fuels ≠ Global Warming

Footnote:

Actuaries are accountants specialized in risk statistics like morbidity and mortality, usually working in the insurance industry.

Question:  What is the difference between an Actuary and an Auditor?
Answer:  The Auditor is the one with a sense of humor.
(Old joke from days working at KPMG)

See also:  Cavemen Climate Comics