The nature and causes of climate change are a worthy challenge for the best scientists using the most sophisticated tools available. Unfortunately, the study of climate change has been co-opted by pseudoscientists using flawed models, rigged data, and hyperbolic claims echoed by ill-informed media and politicians with hidden agendas.

Among the best-known boosters of climate alarm are Gillian Tett at the Financial Times and BlackRocks Laurence Larry D Fink.

Fortunately, there are rigorous scientists using hard data and robust models to address the phenomenon. This more scientific group includes Michael Shellenberger, Steven E Koonin, Bjrn Lomborg, Bruce C Bunker, MJ Sangster, and many more.

These sober voices mostly agree that slight global warming is detectable, but its not a crisis and will not become a crisis in the foreseeable future.

They concur that its unclear whether CO2 emissions are the main cause of warming, even if they are a contributing cause. They point to other causes including solar cycles, ocean salinity, ocean currents like El Nio and La Nina, cloud cover, aerosols, volcanoes, agricultural practices, and natural methane release.

There are also numerous official reports that reach the same conclusion. Although, you may have to scan the footnotes to discover that official reports produce scary headlines heavily diluted by detailed content.

The single most important contribution of real scientists is to demonstrate how badly flawed the models used by the climate alarmists are.

A climate model divides the surface of the planet into a grid with squares of about 360 square miles (932 square kilometres) each over land surfaces, and 36 square miles (92 square kilometres) each over the oceans.

Thats about 101 million squares. Each square is extrapolated into a stack about 30 miles (70 kilometres) high to the outer edge of the stratosphere. All weather occurs in this zone, with most weather occurring within 10 miles (26 kilometres) of the earths surface in the troposphere.

The vertical stacks are sliced horizontally into thin layers like pancakes, and each layer is analysed separately for climate conditions in that slice, the impact of such conditions on adjacent pancakes in adjacent stacks, and so on. One must model this activity to a first approximation before getting to recursive functions.

If each pancake is one mile thick, that comes to 3.03 billion pancakes. Analysing one pancake is tricky. Analysing 3.03 billion pancakes is mind-boggling. Analysing the interaction of each of the 3.03 billion pancakes with each of the other 3.03 billion pancakes, even allowing for attenuated interaction at a distance, is a super-linear function that borders on the impossible in terms of computational complexity!

One scientist estimates that if we had supercomputers 1000 times faster than todays computers, the run time on the problem described above wo...

The second most important concept in economics, behind scarcity, is the idea of marginal analysis. Humans make decisions based on increments, not absolutes.

We do not ask at the outset of a meal, How many slices of pie should I eat? We ask, Should I eat another slice of pie? At least, thats how we make the actual decision.

Thats because each additional slice has slightly less benefit and slightly more cost each time. We continue to eat until the cost of another slice outweighs the benefitsin the case of pies, literally.

Renewable energy upends how this idea of marginal change is applied to our electricity system. Thats because there is almost no marginal cost to producing energy for wind and solar. Almost all the cost is upfront in the initial manufacture and setup. This risks a sunk cost a solar or wind farm that cost a lot of money to build, but which produces unneeded electricity.

Contrast renewables with a power system that uses fossil fuels, and the issue becomes more obvious. Fossil fuel power requires applying more or less fuel to produce more or less energy. The marginal cost and the marginal benefit have a direct relationship with each other. This encourages efficiency and stable production.

It also keeps power prices stable over time. If less energy is needed, less fuel is used. So, the cost of fuel supply and the revenue earned from demand are inextricably linked. They balance.

Power producers conduct a marginal analysis each time they consider producing more or less power. Should I add another tonne of coal or Btu of gas? What does it cost me and what revenue does it earn me?

As the cost of resources rises with demand, the price of electricity falls with rising supply, until the twain shall meet at the mythical equilibrium of supply and demand.

It is unlikely too much electricity will be produced in a fossil fuel system because it costs someone something they make a loss. Also, resources are not wasted because demand and supply can be matched easily by adjusting how much fuel is used.

But we are increasingly moving to a solar and wind system that does not bear the same link between cost and revenue, in a variety of ways. And precisely the consequences a marginal analysis economist would expect are emerging

The Australian Financial Review sums it up:

Power prices surged to their second-highest March quarter in 18 years, despite a glut of solar and wind production that sent prices into the negative during the middle of the day, according to a new report.

Second most expensive while negative for much of the day!? What a combination. A glut of power and high prices something only a government could achieve.

In SA, which is at the vanguard of the global energy transition, wholesale power prices were negative for 17% of the time, and 29% of the time between 9:0...