Climate Models?

Our understanding of global warming and cooling is based on both paleoclimatic analysis and instrumental data. Our understanding of climate change is based on observations of temperatures, sea level changes, hurricane and tornado frequency and intensity, flood and drought frequency and intensity, and other factors. Our understanding of anthropogenic climate change is based on the estimated impacts of emissions and land use changes.

Our understanding of potential catastrophic anthropogenic climate change is based on unverified models, tuned against “adjusted” temperature history, fed with estimated climate sensitivities and feedbacks and uncertain climate forcings. These models are typically referred to as climate models, which suggests that they actually model the real climate. However, the model developers acknowledge that there are numerous factors which affect the climate which are not included in the models because they are not sufficiently well understood. There are also likely to be multiple factors which also affect climate but are not known to do so.

Therefore, it is not reasonable to expect that projections made years ago based on these models would match the observed changes in climate over the recent past; and, it is totally unreasonable to expect that these models have any predictive value regarding future climate. The only way that the current models could match the changes in the real climate is if the factors currently included in the models are modeled accurately, the sensitivities, feedbacks and forcings selected are correct, and the factors which are not currently modeled perfectly cancel each other over the modeled period. In a complex, chaotic environment, these conditions are exceeding unlikely to be met.

Dr. Patrick Frank of the Stanford Synchrotron Radiation Lightsource/SLAC at Stanford University, has recently suggested that errors in climate models are large and that they propagate over the period modeled.

“GCM global air temperature projections are no more than linear extrapolations of green house gas forcing. Linear propagation of error is therefore directly warranted. GCMs make large thermal errors. Propagation of these errors through a global air temperature projection will inevitably produce large uncertainty bars.”

Dr. Frank calculated that current models, using Representative Consumption Pathway 8.5 estimates of future global CO2 emissions, would experience an uncertainty envelope of +/-17°C.

“The large uncertainty bars do not indicate possible increases or decreases in air temperature. They indicate a state of knowledge. The uncertainty bars are an ignorance width.”

This uncertainty envelope is enormous relative to the projected future temperature anomalies. Dr. Frank compared this uncertainty envelope with the Hansen 1988 temperature anomaly projections here at 28:17. Clearly uncertainty of this magnitude suggests that modeled scenarios of potential future climate conditions are of no significant scientific value, though their political value should not be underestimated.

Uncertainties in projections of future climate of this magnitude make a mockery of assertions that “the science is settled”. These uncertainties also highlight the scientific uselessness and political motivation of the numerous “scary scenario” studies funded with federal resources which might otherwise be used to advance the state of climate science.