Masquerade Charade Warning

Sylvia Shawcross provides the alert in her article The Maskparade Charade.  Excerpts in italics with my bolds and added images. H/T Tyler Durden

In the ridiculous world of the New Abnormal where we apparently find ourselves it is critically important to add your opinion to the cacophony of why we are who we are, where we are on the path to seeming totalitarianism and… why people are still wearing masks.

Here in Canada apparently 7 out of 10 members of the public would want mask mandates back while most of the rest of the world has abandoned the concept to the rearview mirror.

Perhaps understandable if you have a medical condition but now study after study. Peer-reviewed. Well-researched. Top quality medical journals. Top-of-the-line researchers. All saying these masks do very little good.**

Even Fauci himself said so once…before he changed his mind as he tends to do when the landscape changes with the weather.

And in response, of course, drug companies and governments sponsored researchers in duelling studies to prove the opposite because that’s the game being played. It’s all about who you believe. It’s not about “the science”. Quite the game really.

In fact, most now know that masks are harmful in many cases, with children paying the biggest price by far on many different levels.

We know now masks don’t work for covid but perhaps they work for RSV or the flu? Maybe that’s why the push is on again. Because here in Canada it certainly is. Maybe that’s why we have the new narrative and being good abnormal citizens we must comply.

Do you think?  Don’t be silly. We know why. We just don’t want to say.

So the Media and their polls have told us that 7 out of 10 people want to keep the masks. And why might that be?

They can hide their crooked teeth. Or their unbrushed teeth. Or their morning-after-the-night-before breath. They don’t have to wear make-up. Or shave. Or wash their faces or their children’s faces.

They can stick their tongue out at people without being caught. They can whisper without lip readers. They can smile and smirk and bite their lips. They can hide their cosmetic surgery in progress. They can hide their chin hairs and warts and zits and leftover food in their moustaches.

They can rob a bank or say whatever they want to strangers because no one knows who they are and even the cameras don’t know.

God only knows what’s going on behind those masks!

But! Those mask-wearing people are free in a weird weird way. Advocates of the new abnormal have found a form of freedom from social norms behind a mask.

How is that possible? Is it possible that masks are freedom? No wonder we’re all mixed up. We don’t even know what freedom is anymore.

Or is it because we lost the freedom to have crooked teeth, no makeup and snarky opinions in the real world due to ever evolving relentless social norms and now have to hide for any sort of freedom…Hmmm…

Seems to be true for a lot of things now doesn’t it?

(Except for anything sexual. You can pretty much proclaim or do anything publicly now. Except child molestation. You can apparently sniff but not anything else. But I’m doing that digression thing again…)

So, let’s get this straight— when we see someone in a mask are they to be feared as nasty snaggle-toothed leprous sneaky sociopaths with sharp tongues and nefarious intentions?

Or are they just victims grasping for what little freedom they can garner in a socially punishing world? Hmmm… It could well be either one… How would we know?

Nevertheless, this is all terribly alarming. WHAT is going on? 7 out of 10 of us!!!

Well, I have a theory. Beyond the usual theories of enforced enslavement, virtue signaling, forced shame, neurosis, herd-like conditioning, continued fear porn dehumanization/ objectification/ subjugation/ alienation, circumvention of facial-recognition systems, gateway moves to social credit scores, anti-feminist one-step-to-the-forced-wearing-of-shuttlecock-burkas assault and the ultimate theory that this poll is nonsense propaganda from our captured media.

All of these theories are as good as the next as long as science seems to have little to do with mask mandates. I mean, real science by independent researchers.

Beyond these theories is the “we’re in the Dark Ages during the plague years of 1346 or so again” theory of mine which I thought I might as well throw into the mix now that we’re all mixed up about freedom and stuff.

Not that there is a plague or anything really at the moment but because people’s reactions don’t change. Not through all these centuries. We’ve changed NOT at all.

Here’s my theory: People wearing masks are the flagellants of the dark ages during the plague years who would run around whipping themselves publicly for God’s forgiveness and atonement or something.

Now during the plague years we would have asked a priest about all this guilt and fear stuff that drive flagellants to be flagellants but today we ask the psychologists.

This is because many if not all of the first world countries have become atheistic and have abandoned religion. But human nature needs what human nature needs—hence the psychologists for priests e.g. or Fauci as Pope and Schwaub as God and Greta as Mother Mary Marx.

Some people believe either technology, money, or medicine has replaced religion but it is clearly evident that it is the Green movement. If we can accept that religion is something that people participate in every day in a meaningful way, then clearly the Green movement has it all. It has priests, codes of behaviours, dictates and forbidden things.

It has a hell (the world as it is going now) and it has a heaven (sustainable development in utopia) It has worshippers. It has the holy and the damned. It has flagellants. And the people now wearing masks are them.

After thirty or so years of being told humans are responsible for killing the planet and being driven to weeping guilt over spending and frivolity and recycling and plastic and gas and beef-pork pies, humans are despicable.

They know it.  They’re guilty as hell. They want to be punished. They believe they deserve it and they are doing this as an appeal to their new Gods of the Environment.

Masks appear not to be about the virus, but about supporting the true religion of the Environmental Zealotry in all its glory and condemnation no matter whatever absurd, illogical or terribly hurtful thing that might bring in whatever sphere of influence.

For many masks might even be called the uniform of the uninformed.

No wonder they read the riot act to the truckers protest of Canada over things like mask mandates. Those heretics!

Well… that’s my theory. It’s as good as any of those other ones, isn’t it? Or maybe not. What do I know… As far as wearing masks is concerned, I appreciate that people are afraid and don’t wish to make too much light of it. Fear isn’t fun. It’s just important to know what to fear and why. Mostly I’m all for following the law of the land as long as the law isn’t an ass. That’s the hard part to figure out.

Two sides of the same coin.

 

 

Unreal Election Numbers in Arizona

Dennis Lund explains in his American Thinker article Arizona’s numbers don’t add up.  Excerpts in italics with my bolds.

The media and the Democrats want us to believe that Kari Lake, along with others, lost because the “Red Wave” did not exist, and that close association with President Trump was the kiss the of death for Republicans. Really?

Let’s take a closer look at the numbers to see what actually occurred in Arizona.

When unethical people take in ballots to control the election process, they do so by obtaining ballots from those mailed out in various regions of the state. The ballots are then filled out for their favored candidates. The focus is always on the so called “up-ballot” races (president, senators, governors, and statewide offices). Ignored are the “down-ballot” candidates: Congress and local legislatures. The reasons for this are twofold: time and ballot differences. The “up-ballot” candidates are the same for the entire state. The “down-ballot” races are distinct for the locale of that particular precinct or district.

Let’s take a closer look at the numbers for the up-ballot races versus the down-ballot races.

The four up-ballot races, won by Democrats, were governor, senator, attorney general, and secretary of state. Republican Kimberly Yee won for state treasurer.

Looking at those four races and taking the average of the votes for each position, we have this:

Democrats: 1,285,500 average votes per candidate

Republicans: 1,219,750 average votes per candidate

Differential is: 65,750 (Lake is losing by 17,250 votes as of this writing)

Now let’s consider what happened in the congressional races. Arizona, which has nine congressional districts, had only seven races, as Democrats did not run candidates in two of the seven districts. Looking at the numbers, we have this:

Total votes in nine districts for Republicans: 1,369,000, which averages to 152,000 per district.

Total votes in seven districts for Democrats: 938,000, which averages to 134,000 per district.

Equalizing the average for the Democrats, we would have 1,206,000 votes cast for Democrat members of Congress, compared to 1,369,000 votes cast for Republican members of Congress. In other words, it would appear that approximately 163,000 more votes were cast for Republicans than for Democrats.

Now compare that number to the up-ballot numbers, which indicate that about 98,000 more votes were cast for the Democrat candidates than for the Republican candidates.

The conclusion would be that about 68,000 voters who preferred the Republican for Congress voted Democrat for governor, senator, A.G., and secretary of state.

Additionally, the numbers indicate that 150,000 more people voted for all nine Republican candidates than voted for the four statewide offices under consideration for this exercise.

Both of those facts defy logic.  When we consider the travails of Election Day experienced by many voters, the unacceptably high numbers of equipment issues, and the fact that the Democrat secretary of state refused to recuse herself from the election tabulation, one has to believe that there were serious issues regarding the fairness of the election.

We cannot let this continue.

Footnote: 

Jay Valentine adds his American Thinker article Election Fraud 2.0! O.K., So What Are You Gonna Do About It? Briefly in italics with my bolds.

Let’s ask the question nobody is asking: Why were candidates spending millions on ads and organizations while ignoring the work of cleaning up the voter rolls?

The Democrat, leftist ballot strategy has one absolute, must have, ingredient: Floating ballots.

A floating ballot is the one that goes to 434 Prescott Street for Bill Jones. But the address is an apartment building, so it cannot be delivered because it does not indicate that Bill is Unit 34. That free-floating ballot is collected by someone – and eventually voted.

This happens in almost every state in about every multi-unit building. We saw it in many states in 2020 and 2022.  In 2022, innovative Republican candidates, a very few, mailed postcards to every voter in their congressional district. The cards that came back = NON-DELIVERABLE ADDRESS. They challenged ballots sent to these addresses, and perhaps they sent volunteers to find some of those accumulated ballots.

Why do we not see every major political campaign have an outreach to identify phantoms and stop the ballot-harvesting? Clue: The Republican organizations are as into keeping phantoms on the voter rolls as the Democrat leftists.

Phantom voter fraud is the heart and soul of ballot-harvesting election-stealing.

If we eliminate phantom voter fraud, people will still screw with machines, Maricopa County will make sure its voting machines do not work in Republican precincts, but the fake-ballot harvesting at scale will end. It’s where the big votes are!

Election fraud is an industry. It is core to the fabric of both Democrat and Republican establishments.

 

Fear Not! Arctic Ice Tops 10 Wadhams in November 2022

Arctic Ice Roaring Back Following Halloween

The animation shows Arctic ice recovery from October 10 to October 31, 2022. On the lower center right, Canadian Arctic Archipelago (CAA) freezes over entirely more than doubling up to 832k km2, 97% of its maximum.  Center bottom Beaufort Sea closes off the NW passage, reaching 1 Wadham in just that basin, 95% of its max.  On the left, the Russian shelf seas fill with ice, closing off the Northern Sea Route.  Laptev and East Siberian seas reached 100% of their maxes, together adding 2 Wadhams of ice extent.

The graph below shows Mid November daily ice extents for 2022 compared to 16 year averages, and some years of note. As of yesterday, Arctic ice extent tops 10 Wadhams, or 10M km2.

The black line shows during this period on average Arctic ice extents increase ~3.5M km2 from ~6.4M km2 up to ~9.9M km2.  The 2022 cyan MASIE line started the month 90k km2 above average and on day 320 increased its surplus to 200k km2.  The Sea Ice Index in orange (SII from NOAA) tracked MASIE the entire month with slightly lower extents. 2007 started with an 700k km2 deficit, but ended virtually average. 2020 had the lowest extent in the record, starting 1.1M km2 down and ending 600k km2 in deficit.

Why is this important?  All the claims of global climate emergency depend on dangerously higher temperatures, lower sea ice, and rising sea levels.  The lack of additional warming is documented in a post Still No Global Warming March 2022

The lack of acceleration in sea levels along coastlines has been discussed also.  See USCS Warnings of Coastal Flooding

Also, a longer term perspective is informative:

post-glacial_sea_levelThe table below shows the distribution of Sea Ice on day 320 across the Arctic Regions, on average, this year and 2007.

Region 2022320 Day 320 Average 2022-Ave. 2007320 2022-2007
 (0) Northern_Hemisphere 10072814 9872802 200012 9824193 248621
 (1) Beaufort_Sea 1051741 1065159 -13418 1059182 -7441
 (2) Chukchi_Sea 606810 653669 -46859 519486 87324
 (3) East_Siberian_Sea 1087137 1077200 9937 1055581 31557
 (4) Laptev_Sea 897845 897567 278 897845 0
 (5) Kara_Sea 716470 671740 44729 774297 -57827
 (6) Barents_Sea 121787 166029 -44242 149482 -27695
 (7) Greenland_Sea 463580 470580 -7000 533946 -70365
 (8) Baffin_Bay_Gulf_of_St._Lawrence 693335 527100 166236 545899 147437
 (9) Canadian_Archipelago 854843 851090 3753 852539 2304
 (10) Hudson_Bay 315416 250421 64995 244531 70885
 (11) Central_Arctic 3178409 3176760 1649 3163043 15366

The overall surplus to average is 200k km2, (2%).  Small deficits in Chukchi and Barents seas are more than offset by surpluses elsewhere, especially Baffin and Hudson Bays and Kara sea. 2022 ice extent exceeds that of 2007 by 1/4 Wadham, most of the difference being in Chukchi and Baffin Bay.

bathymetric_map_arctic_ocean

Illustration by Eleanor Lutz shows Earth’s seasonal climate changes. If played in full screen, the four corners present views from top, bottom and sides. It is a visual representation of scientific datasets measuring Arctic ice extents.

Land Warms UAH Temps October 2022

The post below updates the UAH record of air temperatures over land and ocean.  But as an overview consider how recent rapid cooling  completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016).  The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022  (UAH baseline is now 1991-2020).

For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa.  While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~55 ppm, a 15% increase.

Furthermore, going back to previous warmings prior to the satellite record shows that the entire rise of 0.8C since 1947 is due to oceanic, not human activity.

gmt-warming-events

The animation is an update of a previous analysis from Dr. Murry Salby.  These graphs use Hadcrut4 and include the 2016 El Nino warming event.  The exhibit shows since 1947 GMT warmed by 0.8 C, from 13.9 to 14.7, as estimated by Hadcrut4.  This resulted from three natural warming events involving ocean cycles. The most recent rise 2013-16 lifted temperatures by 0.2C.  Previously the 1997-98 El Nino produced a plateau increase of 0.4C.  Before that, a rise from 1977-81 added 0.2C to start the warming since 1947.

Importantly, the theory of human-caused global warming asserts that increasing CO2 in the atmosphere changes the baseline and causes systemic warming in our climate.  On the contrary, all of the warming since 1947 was episodic, coming from three brief events associated with oceanic cycles. 

Update August 3, 2021

Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT

image-8

 

mc_wh_gas_web20210423124932

See Also Worst Threat: Greenhouse Gas or Quiet Sun?

October Update Mild Warming of Land and Sea 

banner-blog

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  While you will hear a lot about 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in.  The UAH data analyzed below shows that warming from the last El Nino was fully dissipated with chilly temperatures in all regions. May NH land and SH ocean showed temps matching March, reversing an upward blip in April, and then June was virtually the mean since 1995.

UAH has updated their tlt (temperatures in lower troposphere) dataset for October 2022. Posts on their reading of ocean air temps this month came after  updated records from HadSST4.  So I have already posted on SSTs using HadSST4 NH Leads Ocean Cooler October 2022. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years. Sometimes air temps over land diverge from ocean air changes.  However, July showed air temps over all ocean regions warmed sharply, lifting up Global ocean temps. Then in August air over both land and ocean cooled off again. Now in September both land and ocean in SH dropped sharply offsetting slight warming elsewhere.

Note:  UAH has shifted their baseline from 1981-2010 to 1991-2020 beginning with January 2021.  In the charts below, the trends and fluctuations remain the same but the anomaly values change with the baseline reference shift.

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.  Thus the cooling oceans now portend cooling land air temperatures to follow.  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?

After a change in priorities, updates are now exclusive to HadSST4.  For comparison we can also look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for September.  The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the revised and current dataset.

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 air temps since January 2015.

Note 2020 was warmed mainly by a spike in February in all regions, and secondarily by an October spike in NH alone. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October.  That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June.  After an upward spike in July, ocean air everywhere cooled in August and also in September.   In October NH cooled, the Tropics changed little, and a spike in SH was enough to mildly warm the Global anomaly.

Land Air Temperatures Tracking Downward in Seesaw Pattern

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for October is below.

Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land.  Land temps are dominated by NH with a 2021 spike in January,  then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere. Land temps dropped sharply for four months, even more than did the Oceans. March and April 2022 saw some warming, reversed In May when all land regions cooled pulling down the global anomaly. In July, Tropics and SH land rose sharply, NH slightly, pulling up the Global land anomaly. Note the sharp drop in SH land temps in August and September, while NH Land rose, leaving the Global anomaly unchanged. Now in October NH and SH land temps spiked warming the Global land anomaly.

The Bigger Picture UAH Global Since 1980

The chart shows monthly Global anomalies starting 01/1980 to present.  The average monthly anomaly is -0.06, for this period of more than four decades.  The graph shows the 1998 El Nino after which the mean resumed, and again after the smaller 2010 event. The 2016 El Nino matched 1998 peak and in addition NH after effects lasted longer, followed by the NH warming 2019-20.   A small upward bump in 2021 has been reversed with temps having returned close to the mean as of 2/2022.  March and April brought warmer Global temps, reversed in May and the June anomaly was almost zero. The upward spike in July was almost 0.3C, lower in August and September and a slight rise in October.

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, nearly 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  TLT measures 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.

 

NH Leads Ocean Cooler October 2022

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

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

HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated.  HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3.  The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4.  More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for HadSST4 is here.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through October 2022.  A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016. 

Note that in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  In 2021 the summer NH summer spike was joined by warming in the Tropics but offset by a drop in SH SSTs, which raised the Global anomaly slightly over the mean. Now in 2022, another strong NH summer spike has peaked in August, but this time both the Tropic and SH are countervailing, resulting in only slight Global warming, now receding to the mean.  October shows a small SH rise, not enough to offset a sharp drop in NH and slight Tropics cooling.

A longer view of SSTs

Open image in new tab to enlarge.

The graph above is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July.1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino. 

The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2. 

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8,  a lower peak warming in 2009-10, following by cooling in 2011-12.  Again SSTs are average 2013-14.

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

The highest summer NH peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021.  Now in 2021-22 there are again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, now in October by NH and Tropics cooling.

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

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.

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

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The heavy blue line shows that 2022 started warm, dropped to the bottom and stayed near the lower tracks.  Note the strength of this summer’s warming pulse, in September peaking to nearly 24 Celsius, a new record for this dataset. Now in October the SSTs are still high but closer to the middle.

Summary

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

Footnote: Why Rely on HadSST4

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

HadSST4 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

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

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

uss-pearl-harbor-deploys-global-drifter-buoys-in-pacific-ocean

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

Footnote Rare Triple Dip La Nina Likely This Winter

Here’s Where a Rare “Triple Dip La Niña” Might Drop the Most Snow This Winter Ski Mag

The unusual weather phenomenon might result in the snowiest season in years for some parts of the country.

The long-range winter forecast could be good news for skiers living in the certain parts of the U.S. and Canada. The National Oceanic and Atmospheric Administration (NOAA) estimates that the chance of a La Niña occurring this fall and early winter is 86 percent, and the main beneficiary is expected to be mountains in the Northwest and Northern Rockies.

If NOAA’s predictions pan out, this will be the third La Niña in a row—a rare phenomenon called a “Triple Dip La Niña.” Between now and 1950, only two Triple Dips have occurred.

Smith also notes that winters on the East Coast are similarly tricky to predict during La Niña years. “In the West, you’re simply looking for above-average precipitation, which typically translates to above-average snowfall, but in the East, you have temperature to worry about as well … that adds another complication.” In other words, increased precip could lead to more rain if the temperatures aren’t cooperative.

The presence of a La Niña doesn’t always translate to higher snowfall in the North, either, as evidenced by last ski season, which saw few powder days.

However, in consecutive La Niña triplets, one winter usually involves above-average snowfall. While this historical pattern isn’t tied to any documented meteorological function, it could mean that the odds of a snowy 2022’-’23 season are higher, given the previous two La Niñas didn’t deliver the goods.

 

 

No Ballot Box Accountability in US?

So it’s early in US Election week (month?) but the results so far are disturbing.  All of the last polls, confirmed by exit polls on election day, pointed to an electorate determined to oust incumbents who governed over the destructive and outrageous last two years.  Yet this morning, if the numbers hold up and are to be believed, the public are serfs voting in favor of more and harder abuses of power.

Judging by the behavior of Democrat candidates, they were told to keep a low profile, don’t debate. And if their voting while in office followed the party line, loyalty would be rewarded with re-election.  Don’t ask how, don’t tell.   Surprise, surprise:  candidates who distrusted results from the last election were defeated in this one.  Axios says distrusting a US election is Chinese propaganda.

It is said that performance matters in politics, and it was true in 2019 when President Trump was in cruise control with a message of “Promises Kept.”  Then came the pandemic, norms and rules and freedoms were overturned, and Biden became POTUS despite hiding in his basement.  And now it appears that brain damage and lack of accomplishment doesn’t disqualify to be US Senator from Pennsylvania.

At the State level, performance was recognized and Governors were rewarded by voters in Florida, Georgia and Texas.  Those also happened to be places where federal DOJ election monitors were excluded.

Democracy was in fact on the ballot yesterday, and it may have been lost in some places, though not everywhere.

 

Climate Loss and Damage, Legal House of Cards

The big news out of COP27 Sharm El-Sheikh concerns funding for climate “loss and damage.”

Reuters  At COP27, climate ‘loss and damage’ funding makes it on the table

Columbia Climate School Loss and Damage: What Is It, and Will There Be Progress at COP27?

CarbonBrief COP27: Why is addressing ‘loss and damage’ crucial for climate justice?

Etc., Etc., Etc.

Mike Hulme explained the house of cards underlying the claims for compensation from extreme weather loss and damage.  He addressed this directly in his 2016 article Can (and Should) “Loss and Damage” be Attributed to Climate Change?.  Excerpts in italics with my bolds and added images.

One of the outcomes of the eighteenth negotiating session of the Conference of the Parties (COP18) to the UN Framework Convention on Climate Change, held in Doha last December, was the agreement to establish institutional arrangements to “address loss and damage associated with the impacts of climate change.” This opens up new possibilities for allocating international climate adaptation finance to developing countries. A meeting this week in Bonn (25–27 February), co-organized by the UN University Institute for Environmental and Human Security and the Loss and Damage in Vulnerable Countries Initiative, is bringing together various scholars and policymakers to consider how this decision might be implemented, possibly by as early as 2015.

At the heart of the loss and damage (L&D) agenda is the idea of attribution—that specific losses and damages in developing countries can be “associated with the impacts of climate change,” where “climate change” means human-caused alterations to climate. It is therefore not just any L&D that qualify for financial assistance under the Convention; it is L&D attributable to or “associated with” a very specific causal pathway.

Developing countries face some serious difficulties—at best, ambiguities—
with this approach to directing climate adaptation finance.

This is particularly so given the argument that the new science of weather attribution opens the possibility for a framework of legal liability for L&D, which has recently gained prominence (see here and here). Weather attribution science seeks to generate model-based estimates of the likelihood that human influence on the climate caused specific weather extremes.

Weather attribution should not, however, be used to make the funding of climate adaptation in developing countries dependent on proving liability for weather extremes.

There are four specific problems with using the post-Doha negotiations on L&D to advance the legal liability paradigm for climate adaptation. First, with what level of confidence can it be shown that specific weather or climate hazards in particular places are caused by anthropogenic climate change, as opposed to a naturally varying climate? Weather attribution scientists claim that such knowledge is achievable, but this knowledge will be partial, probabilistic, and open to contestation in the courts.

Second, even if such scientific claims were defendable, how will we define “anthropogenic?” Weather attribution science—if it is to be used to support a legal liability paradigm—needs to be capable of distinguishing between the meteorological effects of carbon dioxide emissions from fossil fuels and those from land use change, and between the effects of carbon dioxide and other greenhouse gases, black carbon (soot), and aerosol emissions. Each of these sources and types of climate-altering agents implicates different social and political actors and interests, so to establish liability in the courts, any given weather or climate hazard would need to be broken down into a profile of multiple fractional attributions. This adds a further layer of complexity and contestation to the approach.

Third, L&D may often be as much—or more—a function of levels of social and infrastructural development as it is a function of weather or climate hazard. Whether or not an atmospheric hazard is (partially) attributable to a liable human actor or institution is hardly the determining factor on the extent of the L&D. A legal liability framework based on attribution science promotes a “pollutionist approach” to climate adaptation and human welfare rather than a “developmentalist approach.” Under a pollutionist approach, adaptation is primarily about avoiding the dangers of human-induced climate change rather than building human resilience to a range of weather risks irrespective of cause. This approach has very specific political ramifications, serving some interests rather than others (e.g., technocratic and centralized control of adaptation funding over values-centered and decentralized control).

Finally, if such a legal framework were to be adopted, then what account should be taken of “gains and benefits” that might accrue to developing countries as a result of the impacts of climate change? Not all changes in weather and climate hazard as a result of human influence are detrimental to human welfare, and the principle of symmetry would demand that a full cost-benefit analysis lie at the heart of such a legal framework. This introduces another tier of complexity and contestation.

Following Doha and the COP18, the loss and damage agenda now has institutional force, and the coming months and years will see rounds of technical and political negotiation about how it may be put into operation. This agenda, however, should not place climate adaptation funding into the framework of legal liability backed by the new science of weather attribution.

Hulme goes more deeply into the Loss and Damage difficulties in his 2014 paper Attributing Weather Extremes to ‘Climate Change’: a Review.  Excerpts in italics with my bolds.

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.

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.

Synopsis of this paper is at X-Weathermen are Back!

Integrated Storm Activity Annually over the Continental U.S. (ISAAC)

See also Data vs. Models #3: Disasters

 

 

 

 

Advancing National Takeover of Energy Industry

Tom Luongo writes at his blog The Oil Nationalization Two-Step.  Excerpts in italics with my bolds and added images.

You’ve all heard me rant about the “Straussian Two-Step,” which is nothing more than a retread of the Hegelian Dialectic.   Here’s the formal definition:

An interpretive method, originally used to relate specific entities or events to the absolute idea, in which some assertible proposition (thesis ) is necessarily opposed by an equally assertible and apparently contradictory proposition (antithesis ), the mutual contradiction being reconciled on a higher level of truth by a third proposition (synthesis ).

In modern politics it’s used to create a false reality by asserting something that is
partially true (at best) or a truth that you yourself created as a person in power.

In today’s case it’s a manufactured energy crisis across the West.

In order to see the Straussian Two-Step however you have to work backwards. This process is not an a priori deduction or an exhaustive fit of investigative journalism.

Rather it is an inductive conclusion based on awareness of the motivations of those in power and seeing how they lead a mass of people to a pre-ordained conclusion. In other words, schizo-posting.

Carbon fighters attacking the Exxon Mobil bastion, here seen without their shareholders disguises.

Thesis

So, say your goal is to legitimize the state takeover, or advance another step forward the state takeover, of an industry. Let’s use oil and gas for today’s lesson.

The first thing you do is manufacture a crisis that will disrupt the supply of the product you want to takeover. In this case, it started with COVID-19, which disrupted far more than just the energy sector.

More than 2 million barrels per day of refining capacity was lost world wide thanks to COVID-19. Given the current hostility to new refineries (more on this later), those barrels are not coming back.

Don’t forget, that for a “Straussian Two-Step” this big you will have to brainwash and/or gaslight two entire generations into hating themselves for being rich, wasteful, spoiled, alive or worse, just plain white.

So, they are already primed to hate all the things at play here — capitalism, Big Oil, Banks, Old White Guys (rich or poor) — and enrage your useful idiots by pushing their already tenuous hold on reality to the literal breaking point.   “I can’t even….” isn’t the most common phrase uttered on Tik-Tok for nothing.

That’s the Thesis part.

So, when the crisis hits thanks to natural gas disruption you forbid buying of from a particular country… you demonize not only Vlad but the industry itself for price gouging and preying on the widdle guy during a war.   There’s a word for this… chutzpah.

Antithesis

Predictably, you then allow your fake political opponents …[enter Cocaine Mitch from Stage Right]… to produce the opposite argument. In this case, the counter is obviously we need free markets to produce oil and gas. The refiners are just responding to the market.

That fake opposition, of course, also blames Vlad for this crisis to ensure the market’s champion looks not only patriotic but also suitably bought and paid for by Big Oil, Old White Guys, etc.

Both sides of this argument have now been framed 90 degrees away from the real source of the problem–government intrusion into the flow of oil and gas to your homes.

This is a crisis that if left solved to human ingenuity and, yes, the studious application of greed, would be over in a matter of weeks as refineries shut down during COVID would come back online, supply chains reorganized etc.

While the crisis phase would be over quickly, the long term investment cycle set off in refining would take longer to structurally immunize the industry against future supply shocks to accomplish.

Prices may not return to normal for years but the market, without intervention by rapacious morons both in government and running them from behind the curtain, would eventually grind the arbitrage out of the fuel industry nearly entirely.

Synthesis

Remember the goal. Destroy free markets, nationalize oil and gas.

This means also preparing the next move to get rid of another aspect of the free market while zeroing in on the current crisis. In this theoretical case, we’re looking at the massive diesel crack spreads of refineries, fueling the perpetual motion machine of Marxism’s inherent envy.

Moreover, this situation exploded on the eve of a crucial election to put into the mouths of the crisis actors we call colloquially, “Members of Congress.”

Their solution? Put windfall profit taxes on refiners who are taking advantage of the vulnerable and needy common man. They are evil ‘price gougers’ by accepting the bids from the market for the fruits of their labors which occurred precisely because of artificially inducing a shock to the system.

In the case of diesel fuel in the US this is clearly a manufactured crisis.

COVID took a lot of refineries in the Northeast (PADD-1) offline. And given the hostility of the Biden administration and environmentalists to the oil industry as a whole, as I alluded to earlier, those refineries are not coming back online anytime soon.

Don’t take my word for it, take it from the ones who own the refineries.

“Building a refinery is a multi-billion dollar investment. It may take a decade. We haven’t had a refinery built in the United States since the 1970s. My personal view is that there will never be another refinery built in the United States.”

According to Wirth, oil and gas companies would have to weigh the benefits of committing capital ten years out that will need decades to offer a return to shareholders “in a policy environment where governments around the world are saying ‘we don’t want these products to be used in the future’”.

Why would they? If it were your money would you begin the insane process to build an oil refinery in the US today even with crack spreads at $70+ per barrel? Of course not. By the time you filed the first Environmental Impact Assessment application form the spreads could be back to $20 because it’s politically advantageous for the “Straussian Two-Steppers” to take the pressure off for a few months.

Government is keeping the market in a supply/demand mismatch on purpose. That’s the only conclusion you can draw. Because if “Biden” wanted to solve this problem he wouldn’t be draining the SPR, he’d be rolling back regulations on refining oil or offering some of that ‘infrastructure money’ to help the industry rebuild post-COVID.

High Bid Wins the Prize

Diesel fuel demand is mostly inelastic, since it’s simply necessary for our daily life. Any supply disruption will cause massive price spikes because people will fall all over themselves bidding up the price of available supply to get what they can.

This is the one thing morons leftists can’t wrap their head around. Producers aren’t withholding supply and ‘raising prices’ in an open market economy. That’s propaganda. The reality is that consumers bid up the price for everything in demand or withhold those bids when the cost/benefit isn’t in their favor.

This is the dynamic at play when I use the term cost-push inflation. A supply shortage pushes the bids for basic goods up out of necessity and pouring money into the system through government handouts only accelerates this effect.

Low cost or free dollars flow to the things people need the most and that is the main source of our inflation today.

So, when you see the headlines full of scaremongering like the US only has 20 days of diesel fuel left, this undergirds the bids for limited supply. The futures markets are stripped of their power to coordinate supply over time and producers are stuck being demonized by low quality agitprop from the likes of AOC and Lizzie Slapaho.

Nationalization: The Next Two-Step

Windfall profit taxes are already on the way in Germany, 90% of all profits taxed away to the state. Energy production, when that bill passes, will be nationalized in Germany. The end of rational energy pricing will be gone.

Germany will become another energy subsidizing hellscape like we see all over the world.

The choice in front of German energy companies now is Uniper’s fate, nationalization through bailout, or remain ‘private’ but on a government-mandated cost-plus business model the profits from which will never outcompete the depreciation curve.

Today here in the US the Democrats are pushing for outright nationalization of all oil and gas production. That was the goal all along, the thesis. The fake antithesis is the “Drill baby, Drill,” crowd on Capitol Hill, crying crocodile tears over the loss of the Keystone XL pipeline for more than a decade.

The synthesis this time around will be finally getting through their long-sought after billionaire’s tax in the form of a windfall tax starting with evil Big Oil. Even if they don’t get it, it’s not like they don’t have other things on their to-do lists to get it done.

They are starting here again because they know no one will seriously consider outright nationalization (the next synthesis) unless there’s a war with Russia…

Blood Clotting from Spike Proteins

Dr. Yuhong Dong and Dr. Jordan Vaughn write at Epoch Health Why Spike Protein Causes Abnormal, Foot-Long Blood Clots, 200 Symptoms.  Excerpts in italics with my bolds.

In this two-part paper, we aim to give an overview on COVID-19 related abnormal blood clots, how they form, how to detect them early, and how they’re being treated

Strange Blood Clots

Since mid-2021, unusual, lengthy blood clots found in the vessels of COVID-19 patients and jab recipients have been reported across the world.  

Fibrous Clots found in corpses by Richard Hirschman (Courtesy of Richard Hirschman)

Where do these strange, fibrous clots come from? How do they form?

Spike Protein: The First Domino Toppled

Blood is a liquid that circulates under pressure through the blood vessels in our whole body, like the water flowing through the house that you then use to shower, do the dishes, and so on.

Following a vascular injury, any blood “leaking out” must rapidly be converted into a gel (a “clot”) to fill in the hole and minimize further blood loss.

Normally, the plasma portion of blood contains a collection of soluble proteins that act together in a series of enzyme activation events that result in the formation of a fibrin clot. This process is protective, as it prevents excessive blood loss following injury.

Unfortunately, the blood clotting mechanism can also lead to unwanted blood clots inside blood vessels (pathologic thrombosis), e.g. heart attack or stroke, both of which are a leading cause of disability and death in the world.

COVID-19’s way of causing abnormal blood clots has spurred many discussions since early 2020.

It appears that the virus’s unique spike protein triggers the cascade via many “non-traditional” pathways.

The spike protein’s direct invasion of the epithelium cells is the first domino toppled.  Subsequent cascade effects finally cause the blood clotting. 

CV Spike Proteins Work in Multiple Ways

The article goes on to discuss the several mechanisms employed by spike proteins to clot blood.

Spike Proteins Impair Epithelium Cells

Spike Proteins Trigger the Clotting Cascade

Spike Proteins Dysregulate RAAS, Worsening the Clotting State

Spike Proteins Directly Disrupt the Clot Dissolving Mechanism

Spike Proteins Form Amyloid-Like Substance

Spike Proteins Inhibit Another Anti-Clot Mechanism

Spike Protein Is the Smoking Gun

There is clinical evidence that the SARS-CoV-2 spike protein has been detected in clots retrieved from COVID-19 patients with acute ischemic stroke and myocardial infarction.

Recent research conducted by cardiologists from the University of Colorado sheds light on the crucial role of spike protein in the pathology of COVID and COVID vaccine-related injuries.

They analyzed seven COVID-19 patients and six mRNA vaccinated patients with myocardial injury and found nearly identical alterations in gene profiling patterns that would predispose them to clotting state, inflammation, and myocardial dysfunction.

In other words, whether the myocarditis was caused by the virus or vaccine, similar
changes were exhibited in the expression of genes responsible for prothrombotic state
in response to spike protein, inflammation, and myocardial dysfunction.

Based on gene analysis, COVID-19 and post-mRNA vaccine injury have a common molecular mechanism.  The altered genes pattern includes down-regulation in ACE2, ACE2/ACE ratio, AGTR1, and ITGA5, and up-regulation in ACE and F3 (tissue factor).

Rendering of SARS-CoV-2 spike proteins binding to ACE2 receptors. (Shutterstock)

What is more alarming and not reported before is that microvascular thrombosis has been found in post-vaccinated patients, indicating that spike protein itself is able to trigger blood clots in susceptible patients.

Tip of the Iceberg

Based on the causal relation between ChAdOx1-S vaccines (the AstraZeneca adenovirus COVID vaccine) and thrombosis with thrombocytopenia syndrome, the product information for ChAdOx1-S has been updated to include thrombosis with thrombocytopenia syndrome as a very rare side effect.

This has been named as vaccine induced immune thrombotic thrombocytopenia (VITT), due to the fact that in almost every patient in these reports, high levels of antibodies to platelet factor 4 (PF4)–polyanion complexes were identified in their body.

These unusual blood clots in combination with thrombocytopenia were reported predominantly in women aged under 60 years. Accordingly, several European countries restricted the use of adenovirus vaccines in younger age groups.

This risk has been recently systematically analyzed in an international network cohort study from five European countries and the United States, confirming pooled 30 percent increased risk of thrombocytopenia after a first dose of the ChAdOx1-S vaccine, as well as a trend towards an increased risk of venous thrombosis with thrombocytopenia syndrome after Ad26.COV2.S (the Janssen COVID vaccine) compared with BNT162b2 (the Pfizer-BioNTech COVID vaccine).

However this may be only the tip of the iceberg. There are many more events that could be attributed to the clotting issues including sudden death, cardiovascular events, cardiac death, stroke, disabilities, thrombotic events, etc.

Blood vessels are in all our organs. The vessel problems could explain a wide range of symptoms from the dysfunction to mild decline of our brain, heart, lung, and extremities.

Footnote  Why I Boosted with Novavax

Fed Govt./Big Tech Censorship Lawsuit Update: Senior Biden People Will Be Deposed

Zachary Stieber  reports at Epoch Times Judge Rejects Biden Administration’s Attempt to Block Depositions in Big Tech-Government Censorship Case.  Excerpts in italics with my bolds and added images.

U.S. District Judge Terry Doughty, a Trump appointee, rejected a request for a partial stay of his Oct. 21 order authorizing the depositions of eight officials, including President Joe Biden’s chief medical adviser Dr. Anthony Fauci.

Government lawyers asked the judge to impose the partial stay as an appeals court weighs a request to vacate the part of his order that enables the depositions of Surgeon General Vivek Murthy, a Biden appointee; Cybersecurity and Infrastructure Security Agency Director Jen Easterly, a Biden appointee; and Rob Flaherty, a deputy assistant to the president.

Absent a stay, “high-ranking governmental officials would be diverted from their significant duties and burdened in both preparing and sitting for a deposition, all of which may ultimately prove to be unnecessary if the Court of Appeals grants” their request, the government said.

Doughty ruled that the government failed to show how the officials would be irreparably harmed apart from referencing a diversion from “significant duties.” That didn’t meet the standard for showing irreparable harm, he said.

U.S. Surgeon General Dr. Vivek Murthy speaks during a press briefing in the Brady Briefing Room of the White House in Washington on July 15, 2021. (Saul Loeb/AFP via Getty Images)

From the Judge’s MEMORANDUM ORDER

For the reasons set forth herein, Federal Defendants’ Corrected Motion for Partial Stay is DENIED. (Excerpts in italics with my bolds.)

1. Surgeon General Murthy

Details regarding the allegations as to Murthy are set forth in the Memorandum Order Regarding Witness Depositions. Murthy was found to have first-hand knowledge by (1) publicly criticizing tech companies by asserting they were responsible for COVID-19 deaths due to their failure to censor “mis-information”; (2) issuing a Request for Information on March 2, 2022, requesting tech companies to provide him with “mis-information”; and (3) engaging in communication with high-level Facebook executives about greater censorship of COVID-19 “misinformation.”

Although Murthy was a high-ranking official, the potential burden imposed on Murthy was outweighed by the need to determine whether First Amendment rights of free speech have been suppressed. The Court found exceptional circumstances were present and that the substantive reasons for taking the deposition were sufficient.

2. CISA Director Jen Easterly

Details of the allegations as they relate to Easterly are set forth in the Memorandum Order Regarding Witness Depositions.  Easterly was found to have first-hand knowledge by (1) supervising the “nerve center” of federally directed censorship; (2) directly flagging alleged “misinformation” to social media companies for censorship; (3) stating that social media speech by Americans is a form of infrastructure that allows the CISA to police online speech; (4) being involved in extensive oral communications and meetings between CISA officials and social-media platforms; and (5) being personally involved in text messages specifically discussing how greater censorship of social-media platforms would be done by exerting federal pressure on social-media platforms to increase censorship.

The Court also conducted its analysis of Easterly as if she were a high-ranking official and found that her personal knowledge required her deposition. The Court further found that the burden upon her was outweighed by the need to determine whether First Amendment free speech rights are being suppressed. The Court found exceptional circumstances were present and that the substantive reasons for taking the deposition were sufficient.

3. White House Director of Digital Strategy Rob Flaherty

Details of the allegations as to Flaherty are set forth in the Memorandum Order Regarding Witness Depositions. Flaherty was found to have first-hand knowledge by (1) having extensive oral meetings with social-media platforms including Twitter, Meta and You-Tube on vaccine hesitancy and combatting “mis-information”; (2) directly communicating with Meta’s director of U.S. Public Policy through “Covid Insight Reports” (which details trends/posts by social media users on Meta); (3) Meta’s reporting to Flaherty about Meta’s intentions to censor disfavored opinions about vaccine effectiveness for new groups for which vaccines were authorized; (4) having specific knowledge on Meta’s attempts to censor groups referred to by Flaherty as the “Disinformation Dozen”; and (5) being aware of the President-Elect-Joe Biden transition team’s efforts to stifle “mis-information” through Meta.

The Court also assumed that Flaherty was a high-ranking official and conducted its analysis
as such. It found special circumstances were present to take his deposition. The Court further found the burden upon Flaherty was outweighed by the need to determine whether First Amendment free speech rights are being suppressed; therefore, the substantive reasons for taking his deposition were sufficient.

For the reasons set forth herein, the Court also finds Federal Defendants are not likely to
succeed on the merits of their mandamus petition.

Background from previous post: Fed Govt./Big Tech Censorship Lawsuit: 47 New Biden People Added

Zachary Stieber writes at Epoch Times 47 New Biden Administration Defendants Named in Government–Big Tech Censorship Lawsuit.  Excerpts in italic with my bolds.

Nearly 50 new government defendants have been added to the lawsuit that alleges the government induced censorship of state officials and others on social media.

The second amended complaint in the case, Missouri v. Biden, includes six new agencies, bringing the total to 13, and 41 new individual defendants, bringing the total to 54.

Altogether, 67 officials or agencies are accused of violating plaintiffs’ First Amendment rights by participating in a “censorship enterprise” through pressuring Big Tech firms like Facebook, Google, and Twitter to take action against users offering alleged misinformation.

Evidence backing the claims has been produced in discovery, including exchanges between White House officials and Meta, Facebook’s parent company and messages showing meetings between administration officials and the firms.

The new defendants include the FBI; former White House senior COVID-19 adviser Andrew Slavitt; Dana Remus, counsel to President Joe Biden; Elvis Chan, an FBI special agent based in San Francisco; Janell Muhammed, deputy digital director at the Department of Health and Human Services; Allison Snell, an official at the Cybersecurity and Infrastructure Security Agency; the Food and Drug Administration (FDA); the State Department; and Mark Robbins, interim executive director of the U.S. Election Assistance Commission.

One or more of the Big Tech firms that were subpoenaed in the case identified the officials as possibly communicating with them on content moderation relating to “COVID-19 misinformation,” the New York Post’s story about Hunter Biden’s laptop, the administration’s since-disbanded Disinformation Governance Board, and/or “election security, integrity, outcomes, and/or public confidence in election outcomes (not to include issues of foreign interference or related issues).”

Slavitt was named because emails show he was in communication with Facebook regarding the combating of alleged misinformation. The messages show that Facebook was committed to censoring and de-emphasizing posts that were “departing from the government’s messaging on vaccines,” plaintiffs said. Slavitt also called for Twitter to ban Alex Berenson, an independent journalist, previously released messages show.

Muhammed, meanwhile, was in touch with Facebook to ask the company to take down pages and accounts that were allegedly misrepresenting themselves as representing the government. “Absolutely,” one of the Facebook employees responded.

Other discovery suggests the FDA “has participated in federally-induced censorship of private speech on social media about questions of vaccine safety and efficacy, among other subjects,” plaintiffs said.

The agencies that were added to the case did not respond to requests for comment.

U.S. District Judge Terry Doughty, a Trump appointee overseeing the case, recently ordered defendants named in earlier complaints to comply with demands, including Dr. Anthony Fauci, a top medical adviser to Biden. The new documents do not include any more information from Fauci or the White House press secretary’s office.

Footnote: 

From Your news: Biden Admin Showered Millions On Government’s ‘Misinformation’ Czars After 2020 Election

The four groups in question – Stanford Internet Observatory (SIO), the University of Washington’s Center for an Informed Public, the Atlantic Council’s Digital Forensic Research Lab, and social media analytics firm Graphika – comprise the “Election Integrity Partnership,” which exists as a ‘concierge-like’ service for federal agencies such as Homeland’s Cybersecurity Infrastructure Security Agency (CISA) and State’s Global Engagement Center to flag online content for censorship or monitoring by Big Tech using a “ticket” system.

Unsurprisingly, the head of Stanford’s Internet Observatory is a Clinton donor who previously served as Facebook’s Head of Security – while the University of Washington’s Center for an Informed Public is largely funded by the Knight Foundation, whose board exclusively contributes to Democrat or Neocon entities. 

Meanwhile, the Biden administration empowered three liberal groups to file tickets seeking censorship; the Democratic National Committee, Common Cause and the NAACP.