Climate models cannot model the climate
- Models rely on untested, assumptions e.g. of constant relative humidity with rising temperatures. This is an 120 year old assumption no climate modeler thinks worth testing. Why not?
- The ground station data that models use is mostly incomplete. Especially so over oceans which are 70% of earth's surface
- Models omit many causative factors, such as the Sun (it's various cycles both long and short-term), Volcanoes, ...
- Models do a poor job describing ocean circulation, and ocean heat emission (e.g. from El Niño). Oceans act as heat reservoirs, and hold 1000 × more heat than the atmosphere can. So oceans are crucial to any good model. Climate modelers understand oceans badly.
- Scientists have an incomplete understanding of weather and climate. e.g. Do clouds have a net warming or cooling effect? They cannot say for certain.
- Models work at too course a resolution to be 'simulations', which they, wrongly, claim to be.
- The climate is more complex than modelers make out. They can only run their models by grossly simplifying things.
- It would take about a hundred million, trillion years to run a computer model at something close to the correct resolution.
- A fundamental model mistake is an assumption that IR absorbed by GHG is retransmitted instantaneously. That's both impossible and wrong. Reemission of absorbed IR will take many hundreds of milliseconds. During each millisecond, a molecule will collide with 1 million other air molecules. So any IR (heat) absorbed will be shared with them. Or 'thermalized'. So the 'heat' to be retransmitted as IR is in fact dissipated to the surrounding atmosphere. This rather messes up the downwelling IR model.
Leading experts at modeling have consistently explained that climate models cannot be trusted. So anyone claiming climate model accuracy is denying both modeling best practice and science.
1. Leading Expert Modeler, Prof. Christopher Essex, tells Why Climate Models Hardly Better Than Hocus Pocus: “Welcome To Wonderland”!
2. According to expert modelers: Kesten Green and J. Scott Armstrong:
Scientific forecasting knowledge has been summarised in the form of principles by 40 leading forecasting researchers and 123 expert reviewers. The principles summarise the evidence on forecasting from 545 studies that in turn drew on many prior studies. Some of the forecasting principles, such as ‘provide full disclosure’ and ‘avoid biased data sources,’ are common to all scientific fields. The principles are readily available in the Principles of Forecasting handbook.
We then audited the IPCC forecasting procedures using the Forecasting Audit Software available on ForPrin.com. Our audit found that the IPCC followed only 17 of the 89 relevant principles that we were able to code using the information provided in the 74-page IPCC chapter. Thus, the IPCC forecasting procedures violated 81% of relevant forecasting principles. It is hard to think of an occupation for which it would be acceptable for practitioners to violate evidence-based procedures to this extent. Consider what would happen if an engineer or medical practitioner, for example, failed to properly follow even a single evidence-based procedure.
- Kesten C. Green & J. Scott Armstrong, in Climate Change: The Facts.