Category Destruction of all Fossil Fuels

Nov 12 2022

The Dirty Secrets inside the Black Box Climate Models


The Dirty Secrets inside the Black Box Climate Models
By Greg Chapman
“The world has less than a decade to change course to avoid irreversible ecological catastrophe, the UN warned today.” The Guardian Nov 28 2007
“It’s tough to make predictions, especially about the future.” Yogi Berra
Introduction
Global extinction due to global warming has been predicted more times than climate activist, Leo DiCaprio, has traveled by private jet.  But where do these predictions come from? If you thought it was just calculated from the simple, well known relationship between CO2 and solar energy spectrum absorption, you would only expect to see about 0.5o C increase from pre-industrial temperatures as a result of CO2 doubling, due to the logarithmic nature of the relationship.
Figure 1: Incremental warming effect of CO2 alone [1]
The runaway 3-6o C and higher temperature increase model predictions depend on coupled feedbacks from many other factors, including water vapour (the most important greenhouse gas), albedo (the proportion of energy reflected from the surface – e.g. more/less ice or clouds, more/less reflection) and aerosols, just to mention a few, which theoretically may amplify the small incremental CO2 heating effect. Because of the complexity of these interrelationships, the only way to make predictions is with climate models because they can’t be directly calculated.
The purpose of this article is to explain to the non-expert, how climate models work, rather than a focus on the issues underlying the actual climate science, since the models are the primary ‘evidence’ used by those claiming a climate crisis. The first problem, of course, is no model forecast is evidence of anything. It’s just a forecast, so it’s important to understand how the forecasts are made, the assumptions behind them and their reliability.
How do Climate Models Work?
In order to represent the earth in a computer model, a grid of cells is constructed from the bottom of the ocean to the top of the atmosphere. Within each cell, the component properties, such as temperature, pressure, solids, liquids and vapour, are uniform.
The size of the cells varies between models and within models. Ideally, they should be as small as possible as properties vary continuously in the real world, but the resolution is constrained by computing power. Typically, the cell area is around 100×100 km2 even though there is considerable atmospheric variation over such distances, requiring each of the physical properties within the cell to be averaged to a single value. This introduces an unavoidable error into the models even before they start to run.
The number of cells in a model varies, but the typical order of magnitude is around 2 million.
Figure 2: Typical grid used in climate models [2]

Once the grid has been constructed, the component properties of each these cells must be determined. There aren’t, of course, 2 million data stations in the atmosphere and ocean. The current number of data points is around 10,000 (ground weather stations, balloons and ocean buoys), plus we have satellite data since 1978, but historically the coverage is poor. As a result, when initialising a climate model starting 150 years ago, there is almost no data available for most of the land surface, poles and oceans, and nothing above the surface or in the ocean depths. This should be understood to be a major concern.
Figure 3: Global weather stations circa 1885 [3]

Once initialised, the model goes through a series of timesteps. At each step, for each cell, the properties of the adjacent cells are compared. If one such cell is at a higher pressure, fluid will flow from that cell to the next. If it is at higher temperature, it warms the next cell (whilst cooling itself). This might cause ice to melt or water to evaporate, but evaporation has a cooling effect. If polar ice melts, there is less energy reflected that causes further heating. Aerosols in the cell can result in heating or cooling and an increase or decrease in precipitation, depending on the type.
Increased precipitation can increase plant growth as does increased CO2. This will change the albedo of the surface as well as the humidity. Higher temperatures cause greater evaporation from oceans which cools the oceans and increases cloud cover. Climate models can’t model clouds due to the low resolution of the grid, and whether clouds increase surface temperature or reduce it, depends on the type of cloud.
It’s complicated! Of course, this all happens in 3 dimensions and to every cell resulting in considerable feedback to be calculated at each timestep.
The timesteps can be as short as half an hour. Remember, the terminator, the point at which day turns into night, travels across the earth’s surface at about 1700 km/hr at the equator, so even half hourly timesteps introduce further error into the calculation, but again, computing power is a constraint.
While the changes in temperatures and pressures between cells are calculated according to the laws of thermodynamics and fluid mechanics, many other changes aren’t calculated. They rely on parameterisation. For example, the albedo forcing varies from icecaps to Amazon jungle to Sahara desert to oceans to cloud cover and all the reflectivity types in between. These properties are just assigned and their impacts on other properties are determined from lookup tables, not calculated. Parameterisation is also used for cloud and aerosol impacts on temperature and precipitation. Any important factor that occurs on a subgrid scale, such as storms and ocean eddy currents must also be parameterised with an averaged impact used for the whole grid cell. Whilst the effects of these factors are based on observations, the parameterisation is far more a qualitative rather than a quantitative process, and often described by modelers themselves as an art, that introduces further error. Direct measurement of these effects and how they are coupled to other factors is extremely difficult and poorly understood.
Within the atmosphere in particular, there can be sharp boundary layers that cause the models to crash. These sharp variations have to be smoothed.
Energy transfers between atmosphere and ocean are also problematic. The most energetic heat transfers occur at subgrid scales that must be averaged over much larger areas.
Cloud formation depends on processes at the millimeter level and are just impossible to model. Clouds can both warm as well as cool. Any warming increases evaporation (that cools the surface) resulting in an increase in cloud particulates. Aerosols also affect cloud formation at a micro level.  All these effects must be averaged in the models.
When the grid approximations are combined with every timestep, further errors are introduced and with half hour timesteps over 150 years, that’s over 2.6 million timesteps! Unfortunately, these errors aren’t self-correcting. Instead this numerical dispersion accumulates over the model run, but there is a technique that climate modelers use to overcome this, which I describe shortly.
Figure 4: How grid cells interact with adjacent cells [4]

Model Initialisation
After the construction of any type of computer model, there is an initalisation process whereby the model is checked to see whether the starting values in each of the cells are physically consistent with one another. For example, if you are modelling a bridge to see whether the design will withstand high winds and earthquakes, you make sure that before you impose any external forces onto the model structure other than gravity, that it meets all the expected stresses and strains of a static structure. Afterall, if the initial conditions of your model are incorrect, how can you rely on it to predict what will happen when external forces are imposed in the model?
Fortunately, for most computer models, the properties of the components are quite well known and the initial condition is static, the only external force being gravity. If your bridge doesn’t stay up on initialisation, there is something seriously wrong with either your model or design!
With climate models, we have two problems with initialisation. Firstly, as previously mentioned, we have very little data for time zero, whenever we chose that to be. Secondly, at time zero, the model is not in a static steady state as is the case for pretty much every other computer model that has been developed. At time zero, there could be a blizzard in Siberia, a typhoon in Japan, monsoons in Mumbai and a heatwave in southern Australia, not to mention the odd volcanic explosion, which could all be gone in a day or so.
There is never a steady state point in time for the climate, so it’s impossible to validate climate models on initialisation.
The best climate modelers can hope for is that their bright shiny new model doesn’t crash in the first few timesteps.
The climate system is chaotic which essentially means any model will be a poor predictor of the future – you can’t even make a model of a lottery ball machine (which is a comparatively a much simpler and smaller interacting system) and use it to predict the outcome of the next draw.
So, if climate models are populated with little more than educated guesses instead of actual observational data at time zero, and errors accumulate with every timestep, how do climate modelers address this problem?
History matching
If the system that’s being computer modelled has been in operation for some time, you can use that data to tune the model and then start the forecast before that period finishes to see how well it matches before making predictions. Unlike other computer modelers, climate modelers call this ‘hindcasting’ because it doesn’t sound like they are manipulating the model parameters to fit the data.
The theory is, that even though climate model construction has many flaws, such as large grid sizes, patchy data of dubious quality in the early years, and poorly understood physical phenomena driving the climate that has been parameterised, that you can tune the model during hindcasting within parameter uncertainties to overcome all these deficiencies.
While it’s true that you can tune the model to get a reasonable match with at least some components of history, the match isn’t unique.
When computer models were first being used last century, the famous mathematician, John Von Neumann, said:
“with four parameters I can fit an elephant, with five I can make him wiggle his trunk”
In climate models there are hundreds of parameters that can be tuned to match history. What this means is there is an almost infinite number of ways to achieve a match. Yes, many of these are non-physical and are discarded, but there is no unique solution as the uncertainty on many of the parameters is large and as long as you tune within the uncertainty limits, innumerable matches can still be found.
An additional flaw in the history matching process is the length of some of the natural cycles. For example, ocean circulation takes place over hundreds of years, and we don’t even have 100 years of data with which to match it.
In addition, it’s difficult to history match to all climate variables. While global average surface temperature is the primary objective of the history matching process, other data, such a tropospheric temperatures, regional temperatures and precipitation, diurnal minimums and maximums are poorly matched.
Even so, can the history matching of the primary variable, average global surface temperature, constrain the accumulating errors that inevitably occur with each model timestep?
Forecasting
Consider a shotgun. When the trigger is pulled, the pellets from the cartridge travel down the barrel, but there is also lateral movement of the pellets. The purpose of the shotgun barrel is to dampen the lateral movements and to narrow the spread when the pellets leave the barrel. It’s well known that shotguns have limited accuracy over long distances and there will be a shot pattern that grows with distance.  The history match period for a climate model is like the barrel of the shotgun. So what happens when the model moves from matching to forecasting mode?
Figure 5: IPCC models in forecast mode for the Mid-Troposphere vs Balloon and Satellite observations [5]
Like the shotgun pellets leaving the barrel, numerical dispersion takes over in the forecasting phase. Each of the 73 models in Figure 5 has been history matched, but outside the constraints of the matching period, they quickly diverge.
Now at most only one of these models can be correct, but more likely, none of them are. If this was a real scientific process, the hottest two thirds of the models would be rejected by the International Panel for Climate Change (IPCC), and further study focused on the models closest to the observations. But they don’t do that for a number of reasons.
Firstly, if they reject most of the models, there would be outrage amongst the climate scientist community, especially from the rejected teams due to their subsequent loss of funding. More importantly, the so called 97% consensus would instantly evaporate.
Secondly, once the hottest models were rejected, the forecast for 2100 would be about 1.5o C increase (due predominately to natural warming) and there would be no panic, and the gravy train would end.
So how should the IPPC reconcile this wide range of forecasts?
Imagine you wanted to know the value of bitcoin 10 years from now so you can make an investment decision today. You could consult an economist, but we all know how useless their predictions are. So instead, you consult an astrologer, but you worry whether you should bet all your money on a single prediction. Just to be safe, you consult 100 astrologers, but they give you a very wide range of predictions. Well, what should you do now? You could do what the IPCC does, and just average all the predictions.
You can’t improve the accuracy of garbage by averaging it.
An Alternative Approach
Climate modelers claim that a history match isn’t possible without including CO2 forcing. This is may be true using the approach described here with its many approximations, and only tuning the model to a single benchmark (surface temperature) and ignoring deviations from others (such as tropospheric temperature), but analytic (as opposed to numeric) models have achieved matches without CO2 forcing. These are models, based purely on historic climate cycles that identify the harmonics using a mathematical technique of signal analysis, which deconstructs long and short term natural cycles of different periods and amplitudes without considering changes in CO2 concentration.
In Figure 6, a comparison is made between the IPCC predictions and a prediction from just one analytic harmonic model that doesn’t depend on CO2 warming. A match to history can be achieved through harmonic analysis and provides a much more conservative prediction that correctly forecasts the current pause in temperature increase, unlike the IPCC models. The purpose of this example isn’t to claim that this model is more accurate, it’s just another model, but to dispel the myth that there is no way history can be explained without anthropogenic CO2 forcing and to show that it’s possible to explain the changes in temperature with natural variation as the predominant driver.
Figure 6: Comparison of the IPCC model predictions with those from a harmonic analytical model [6]

In summary:
Climate models can’t be validated on initiatialisation due to lack of data and a chaotic initial state.
Model resolutions are too low to represent many climate factors.
Many of the forcing factors are parameterised as they can’t be calculated by the models.
Uncertainties in the parameterisation process mean that there is no unique solution to the history matching.
Numerical dispersion beyond the history matching phase results in a large divergence in the models.
The IPCC refuses to discard models that don’t match the observed data in the prediction phase – which is almost all of them.
The question now is, do you have the confidence to invest trillions of dollars and reduce standards of living for billions of people, to stop climate model predicted global warming or should we just adapt to the natural changes as we always have?
Greg Chapman  is a former (non-climate) computer modeler.
Footnotes
[1] https://www.adividedworld.com/scientific-issues/thermodynamic-effects-of-atmospheric-carbon-dioxide-revisited/
[2] https://serc.carleton.edu/eet/envisioningclimatechange/part_2.html
[3] https://climateaudit.org/2008/02/10/historical-station-distribution/
[4]            http://www.atmo.arizona.edu/students/courselinks/fall16/atmo336/lectures/sec6/weather_forecast.html
[5] https://www.drroyspencer.com/2013/06/still-epic-fail-73-climate-models-vs-measurements-running-5-year-means/
Whilst climate models are tuned to surface temperatures, they predict a tropospheric hotspot that doesn’t exist. This on its own should invalidate the models.
[6] https://wattsupwiththat.com/2012/01/09/scaffeta-on-his-latest-paper-harmonic-climate-model-versus-the-ipcc-general-circulation-climate-models/
Nov 11 2022

The UK is Not Prepared for a Prolonged Recession


Armstrong Economics Blog/Central Banks Re-Posted Nov 11, 2022 by Martin Armstrong

People are simply not prepared for a sharp economic downturn. The Money and Pensions Service conducted a poll in the UK in which it found around 25% of adults have under £100 in savings. The 3,000-person survey found that 17% reported having absolutely nothing set aside. Around 5% reportedly had under £50, while 4% had between £50 and £100.

The drastically increased cost of living has many living paycheck to paycheck. The Building Societies Association (BSA), as reported by the BBC, conducted a separate survey that found that 35% of people in the UK simply stopped saving due to inflation. Around 36% said they are already dipping into their savings accounts to pay the bills.

The Bank of England is anticipating a long recession ahead. The central bank sees economic conditions contracting through the first half of 2024. The central bank’s prediction of five consecutive quarters of contraction would mark the longest recession in UK history. The people have not experienced the full effects of this recession, and most are simply not prepared for what lies ahead.

Nov 11 2022

President Trump Fires Back Against Ron DeSantis, Con Inc and Coordinated Narrative Midterm Effort


Posted originally on the conservative tree house on November 10, 2022 | Sundance

President Trump can see and hear the same things everyone else can see and hear, including the coordinated media and GOPe effort to diminish him and the MAGA movement within the Republican club.

The Democrats and professional Republican class both want to see the populist movement destroyed for the same reason Mitch McConnell wanted the Tea Party destroyed in 2010.  The assembly of the united middle-class and blue-collar base inside the Republican Party, essentially the broad MAGA movement, represents a Main Street threat to Wall Street control of the GOPe.

There are trillions at stake.

As Florida Governor Ron DeSantis’ megadonor and Citadel hedge fund billionaire, Ken Griffin, openly admitted recently the Wall Street goals are (1) stop the populist movement and (2) get the Republican Party back in alignment with the multinational “corporate world.”  These are the same goals of the Republican leadership in Washington DC and the same goals as the corporate media who serve as the public relations firms for Wall Street.

The collaborative group, which includes the entirety of the funding mechanism and management behind Ron DeSantis, viewed the 2022 midterm election as an opportunity to reset the Republican Party away from the populist MAGA influence.  The strategy was to roll out of the August DOJ Mar-a-Lago targeting, directly into a nationally rebranded DeSantis operation and then lead up to the 2022 midterm election.

Anything that can cast Donald Trump as a negative would be enhanced, and anything that would cast the MAGA movement as a positive would be diminished.  In part, this is the intent behind the delayed positive election results from key MAGA races in CO, WA, NV and AZ, combined with emphasis on the negative -albeit controlled- election ballot outcomes from Michigan and Pennsylvania.

At the 30,000-foot level the attacks against President Trump are, quite frankly, attacks against the MAGA populist movement represented by President Trump.

The professional political class, both DNC and RNC club members, politicians and donors, want to get back to normal political business operations in Washington DC.  The key element at the core of their concern is financial and economic control.  Again, there are trillions at stake.

Just like we can see this coordinated effort, so too can President Trump see the construct of the narrative as it is being engineered and delivered.  We can see the Paul Ryan wing, the Mitch McConnell wing and the corporate media division all working in concert.  The entities described genuinely do not think the larger Republican base can see it, but they underestimate us at their own peril.

Things are never going to return to normal for them, but they refuse to accept that.  The most adamant of the professional Republican apparatus, in concert with the multinational financial world, would rather see the GOP lose every election – if that’s what it takes to stop the MAGA movement.  They view this as a zero-sum game, and they have planted proactive seeds for exactly this purpose.

A more than happy to assist CONservative Inc new media apparatus, the “influencers” as they call them, are part of the dynamic that was recruited in early 2022 {See Here}. It’s the use of this crew and others of like-minded disposition that helps the corporate group drumbeat an anti-populist, anti-MAGA message with the intention to eliminate the head of the movement.

In addition to their common vertical challenges, the DeSantis 2024 influence group are almost identical to the Cruz 2016 group.  The difference this time around is the pretending game; where they pretend DeSantis is not the intended beneficiary of their relentless anti-Trumpism in both print and broadcast appearances.

The group was recruited in January 2022 and includes Fox News’ Lisa Marie Boothe, Turning Point USA’s Benny Johnson, Newsweek opinion editor Josh Hammer, The Rubin Report’s Dave Rubin, New York Post and FoxNews.com columnist Karol Markowicz, Claremont Institute fellow David Reaboi and conservative writers like Jordan Schachtel, John Cardillo, along with Ben Shapiro and Guy Benson.

Florida Governor Ron DeSantis has been positioned as the intended recipient for the disenfranchised MAGA movement’s support, if they can just get President Trump out of the equation and exploit the vulnerability in his absence.  However, all previous efforts to shake the bond between President Trump and the MAGA movement have failed.

Using the 2022 midterm election control, they are pounding the wedge harder now, with increased ferocity and urgency to break the bond.

Just like in 2016, the GOPe multinationals, corporatists, Wall Street donors, Never Trump CONservatives, and just about all controlled media systems are being enlisted in this effort.  President Trump can see the construct just as clearly as you can.

That’s why President Trump is hitting back against the effort by singling out the wedge they are trying to use.

President Trump isn’t pretending.  He’s targeting Florida Governor Ron DeSantis because President Trump, like us, can clearly see the nature of the construct that has been manufactured to oppose the MAGA movement.  This is a fight for the future of the Republican party.

DeSantis is playing too-cute-by-half, in pretending not to be a participant in the professional republican operation.  If Governor Ron DeSantis was not an active participant, he would not be playing coy with his 2024 GOP nomination intent.   Trump isn’t going to play pretend.  As long as DeSantis pretends, he will be targeted by President Trump because Trump isn’t going to allow the professional republican apparatus to destroy the populist movement.

Let Con Inc go and form a new party now of acceptable republicans.  Let the people of selfie-importance assemble to take pictures of their lunches and dinners for social media shares, while the scruffnecks in MAGA assemble to push back against the new American corporatist agenda that finances them.

The new republican party is the working-class people’s party, the MAGA party, and President Donald J Trump is going to defend it.

Steadfast….  This is “The Big Ugly“!

Nov 11 2022

CPI Report – Inflation on Food, Fuel, Home Heating and Essentials Continues Growing – Overall Inflation Moderation Now Claimed as Calendar Cycles


Posted originally on the conservative tree house on November 10, 2022 | Sundance

The Bureau of Labor and Statistics (BLS) provides the latest data on consumer prices (inflation) [DATA HERE].  We explained in 2021 how inflation would grow on a month-over-month and year-over-year basis until the calendar became more friendly and the government officials could claim “diminished inflation growth.”  Well, we are now entering that phase of economic parseltongue.

October consumer prices increased 0.4% over September.  However, we are now comparing year-over-year (Y0Y) inflation to the period where last year’s prices had already skyrocketed, so YoY inflation seems to be moderating at 7.7%, it’s a false premise. {Go Deep}

As expected, the energy-driven consumer inflation in the food sector has arrived.  The proverbial field inflation is arriving at the fork, and the October CPI now shows the third wave of food price increases we had previously discussed.

Table 2 Details: Egg prices increased +10.1% last month and now 43% higher than last year.  Butter +1.9% last month, 26.7% for year.  Margarine +1.3% for month, 47.1% for year.  Coffee +1.3% for the month, 15.6% for the year.

Heading into baking season we find flour +0.2% for the month, +24.6% for year.  Essentially, as expected, all of the holiday foodstuffs are now rising in price as the increased field and commodity prices hit the store shelves.

Some row crops are starting to moderate in price growth, while dairy products continue rising throughout the fall season.  It is going to be painful on the checkbook grocery shopping this holiday season.

On the energy front, home heating oil increased 19.8% in October and is now a whopping 68.5% higher than last October.  Unleaded gasoline increased another 3.5% and now is now 20.9% higher than last year (Oct ’21), which was already 40% higher than January 2021.

Food, fuel, electricity, home heating and housing costs continue growing monthly, but give the illusion of moderating when compared to last year.

Food away from home (restaurants etc.) are starting to show the cumulative price impacts for restaurants, hotels and cafeterias.  Additionally, as the kids returned to school the lunchroom prices have skyrocketed a jaw-dropping +3.8% for October and +95% compared to last year [Table 2].  Packing lunches for kids is going to become an even more important aspect for the family food budget.

The stock market is happy with the news because the lowered 7.7% (YoY) inflation number, a product of the calendar and nothing else, gives optimism the Fed may moderate the increased federal reserve rate hikes.  However, don’t count on it because inflation is easily identified as embedded now.  Lemons at the grocery store are now $0.99/each.

Think about that.  $1 for a single lemon and roughly 50¢ per egg at the supermarket.  A full shopping cart of groceries now easily exceeding $200.  This is devastating for those on fixed incomes and blue-collar workers.

Wages are nowhere near keeping up with this level of price increase.

(CNBC) The consumer price index rose less than expected in October, an indication that while inflation is still a threat to the U.S. economy, pressures could be starting to cool.

The index, a broad-based measure of goods and services costs, increased 0.4% for the month and 7.7% from a year ago, according to a Bureau of Labor Statistics release Thursday. Respective estimates from Dow Jones were for rises of 0.6% and 7.9%.

Excluding volatile food and energy costs, so-called core CPI increased 0.3% for the month and 6.3% on an annual basis, compared with respective estimates of 0.5% and 6.5%.

A 2.4% decline in used vehicle prices helped bring down the inflation figures. Apparel prices fell 0.7% and medical care services were lower by 0.6%.

“The report overstates the case that inflation is coming in, but it makes a case inflation is coming in,” said Mark Zandi, chief economist at Moody’s Analytics. “It’s pretty clear that inflation has definitely peaked and is rolling over. All the trend lines suggest that it will continue to moderate going forward, assuming that nothing goes off the rails.” (read more)

The Biden energy policy is the root of the consumer inflation. Nothing will happen to moderate overall consumer inflation on Main Street until energy policy changes.

Additionally, with the 2022 election in the rear-view mirror, we should start to see layoffs and unemployment increasing now.  The bureaucrats will now let the recession become evident.

Nov 10 2022

In Politics – People Want to Believe on What They Want to Hear


Armstrong Economics Blog/Politics Re-Posted Nov 9, 2022 by Martin Armstrong

COMMENT: The post dealing with the mid-terms had this gem: “This is why all the Greek philosophers from Socrates to Plato were against democracy. It allowed a thin majority to become tyrannical.”
What then is the alternative, for there will never come a time when we all agree about anything, let alone everything? The unstated alternative is that a minority becomes tyrannical and enforces their vision on everyone. Those are the two choices. There aren’t others just waiting to be discovered. Either the majority has it or the minority has it and as this is supposed to be a battle between ideas, the idea getting the most support should be the one chosen. Otherwise, candidates would try to lose the election so as that their plans would be enacted. Sorry, but that is just too stupid to be taken seriously by anyone with a still functioning brain in their head.
As Churchill noted, “Democracy is the worst form of government there is, except for all the others.” And he was absolutely correct. If you don’t like what the majority is doing, change the minds of those who are persuadable; don’t bitch about not getting your way because your ideas were not popular. That is what infants do!

VK

REPLY: A friend invited me to dinner. There was another there who was a major programmer for Microsoft. He was a Biden supporter and convinced that climate change may have always existed, but we are the cause right now. There are people among the Democrats who have just been brainwashed with sophistry. If they were not being mentally manipulated by a small group of elites with an agenda they would never agree with if the truth were told, then there would be perhaps a more reasonable world.

Then you have egos. Trump felt his endorsing power was not what he and others thought it was. So he told the WSJ he knew some dit on DeSantis. This is the problem. Trump was on the right track and he was what the people rallied behind – term limits and draining the swamp. But now his personal ego is surfacing and that becomes a problem in politics. It is hard to resist when everyone says you control the power.

The best form of government I have ever seen was that of Genoa where the Doge (president) rotated annually amount the wealthy families. This was before Marxism. There was no social warfare. They ran Genoa more like a company competing against Venice and Florence. Because the Doge rotated, nobody would pass a law that was draconian since they would have to live under that law the following years and it would be more than a decade before the wheel would return to their family.

Marxist Socialism has been highly destructive. It has begun the division that undermines the purpose of civilization – that we all come together because we all benefit. When one group targets another, that is it. You begin the process of economic suicide. The Democrats no longer know how to run for office without promising to rob one group for the benefit of another.

Republics are always the worst form of government because they can be bribed. Look at the bankers. They have blown up the world economy countless times and NEVER has a single banker ever been charged. They own the SEC and CFTC – the case is closed for they will never be held accountable – EVER! 

I tried to warn the Republicans, but they too want to hear what they prefer to believe. I warned them that they would NOT be able to reverse what Biden has set in motion.