Yesterday I posted an extended analysis of Dr. Pat Frank’s recent publication entitled Propagation of Error and the Reliability of Global Air Temperature Projections. That paper claims that because there are large uncertainties in climate models’ various component energy fluxes which determine global temperature, there are large uncertainties in those models’ future temperature forecasts.

While this sounds reasonable, I pointed out that none of the ~20 models produce large, spurious warming in their forecasts when “control runs” are made to test the models long-term stability. The reason is that if one component of the model is known to have a systematic error (for example in global cloud cover), other model processes are adjusted to compensate for it. I am not necessarily defending this practice. I am only pointing out that the models are energy-balanced before being run with increasing CO2 for their “global warming” runs, and this prevents the models from having spurious warming or cooling due to component energy fluxes being in error.

Dr. Frank graciously provided rebuttals to my points, none of which have changed my mind on the matter. As several commenters on my blog and at WUWT have suggested, maybe the main point of Pat’s paper is that if the component energy fluxes in the climate models have large errors, how can we trust their long-term forecasts?

While I have made it clear that I don’t trust their long-term forecasts (for different reasons), here’s why I still believe the italicized statement above is not valid:

The ~20 different models from around the world cover a WIDE variety of errors in the component energy fluxes, as Dr. Frank shows in his paper, yet they all basically behave the same in their temperature projections for the same (1) climate sensitivity and (2) rate of ocean heat uptake. The models themselves then demonstrate that these errors do not depend upon those bias errors in the components of the energy fluxes (such as global cloud cover). That’s partly why different modeling groups around the world build different climate models: so they can test the impact of different assumptions on the models’ temperature forecasts.

Again, I am not defending current climate models’ projections of future temperatures. I’m saying that errors in those projections are primarily due to the processes controlling climate sensitivity (and the rate of ocean heat uptake). And climate sensitivity, in turn, is a function of (for example) how clouds change with warming, and apparently not a function of errors in a particular model’s average cloud amount, as Dr. Frank claims. The behavior of the wide variety of different models with differing errors is proof of that.

via Roy Spencer, PhD.

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September 12, 2019 at 06:15AM