A Fatal Flaw with Climate Models

Well worth reading. Here’s the key paragraph:

The IPCC has looked at a number of different cases and it reports that temperatures could be, in the worst case, up to 4 ̊C higher by 2100. However, based on Frank’s work, when considering the errors in clouds and CO2 levels only, the error bars around that prediction are ±15 ̊C. This does not mean–thankfully– that it could be 19 ̊ warmer in 2100. Rather, it means the models are looking for a signal of a few degrees when they can’t differentiate within 15 ̊ in either direction; their internal errors and uncertainties are too large. This means that the models are unable to validate even the existence of a CO2 fingerprint because of their poor resolution, just as you wouldn’t claim to see DNA with a household magnifying glass.

All scientists understand confidence intervals. Which leads me to wonder why climate scientists don’t (or won’t, or can’t). 

Some of the backstory: 

Patrick Frank is a scientist at the Stanford Synchrotron radiation Lightsource (SSRL), part of the SLAC (formerly Stanford Linear Accelerator Center) national Accelerator Laboratory at Stanford University. The SSLR produces extremely bright x-rays as a way for researchers to study our world at the atomic and molecular level.

In a bit of a shift, Frank has shone a bright light on general circulation models (GCMs)–models used to predict long-term changes in climate–and illuminated some fatal flaws. His bottom line is that these models, as they stand today, are useless for helping us understand the relationship between greenhouse gas emissions and global temperatures. This means that all the predictions of dramatic impending warming and ancillary calls for strong government action are based on conjecture.