The fear of anthropogenic global warming is based almost entirely upon computerized climate model simulations of how the global atmosphere will respond to slowly increasing carbon dioxide concentrations. There are now over 20 models being tracked by the IPCC, and they project levels of warming ranging from pretty significant to catastrophic by late in this century. The following graph shows an example of those models’ forecasts based upon assumed increases in atmospheric carbon dioxide this century.
While there is considerable spread among the models, it can be seen that all of them now produce levels of global warming that can not be ignored.
But what is the basis for such large amounts of warming? Is it because we know CO2 is a greenhouse gas, and so increasing levels of atmospheric CO2 will cause warming? NO!…virtually everyone now agrees that the direct warming effect from extra CO2 is relatively small – too small to be of much practical concern.
No, the main reason the models produce so much warming depends upon uncertain assumptions regarding how clouds will respond to warming. Low and middle-level clouds provide a ‘sun shade’ for the Earth, and the climate models predict that those clouds will dissipate with warming, thereby letting more sunlight in and making the warming worse.
[High-altitude (cirrus) clouds have the opposite effect, and so a dissipation of those clouds would instead counteract the CO2 warming with cooling, which is the basis for Richard Lindzen's 'Infrared Iris' theory. The warming in the models, however, is now known to be mostly controlled by the low and middle level clouds – the “sun shade” clouds.]
But is this the way nature works? Our latest evidence from satellite measurements says “no”. One would think that understanding how the real world works would be a primary concern of climate researchers, but it is not. Rather than trying to understand how nature works, climate modelers spend most of their time trying to get the models to better mimic average weather patterns on the Earth and how those patterns change with the seasons. The unstated assumption is that if the models do a better job of mimicking average weather and the seasons, then they will do a better job of forecasting global warming.
But this assumption can not be rigorously supported. To forecast global warming, we need to know how the average climate state — and especially clouds — will change in response to the little bit of warming from the extra CO2. Indeed, the model that best replicates the average climate of the Earth might be the worst one at predicting future warming.
This fact gets glossed over – or totally ignored – as the IPCC dazzles us with the level of effort that has been invested in computer modeling of the climate system over the last 20 years. The IPCC can show how many people they have working on improving the models, how many years and how much money has been invested, how big and fast their computers are, and how many peer-reviewed scientific publications have resulted.
But unless we know how clouds change with warming, it is all a waste of time from the standpoint of knowing how serious manmade global warming will be. Even the IPCC admits this is their biggest uncertainty…so why is so little work being done trying to answer that question?
AN APPEAL TO THE DECISION MAKERS
We now have billions of dollars in satellite assets orbiting the Earth, continuously collecting high-quality data on natural, year-to-year changes in climate. I believe that these satellite measurements contain the key to understanding whether manmade global warming will be catastrophic, or merely lost in the noise of natural climate variability.
That is why I spend as much time as I can spare trying to understand those satellite measurements. But we need many more people working on this effort. Despite its importance, I have yet to meet anyone who is trying to do what I am doing.
To be fair, the modelers do indeed compare their models to satellite measurements. But those comparisons have not been detailed enough to answer the most important questions…like how clouds respond to warming.
The comparisons they have done have been confusing and inconclusive, which is part of the reason why they don’t rely on the satellite measurements very much. The modelers claim that the satellite measurements have been too ambiguous, and so they increasingly rely only upon the models.
But I will continue to assert (until I am blue in the face or die, whichever comes first) that their confusion stems from a very simple issue they have overlooked: mixing up cause and effect. The previous satellite observations that showed clouds tend to decrease with warming does not mean that warming causes clouds to decrease!
We have recently submitted to Journal of Geophysical Research a research paper that shows how one can tell the difference between cause and effect — between clouds causing a temperature change, and temperature causing a cloud change. And when this is done during the analysis of satellite data, it is clear that warming causes an increase in the sunshade effect of clouds. (While the data did suggest strong positive water vapor feedback, which enhances warming, that was far exceeded by the cooling effect of negative feedback from cloud changes.)
These results suggest that the climate system has a strong thermostatic control mechanism – exactly opposite to the way the IPCC models have been programmed to behave — and that the widespread concern over manmade global warming might well be a false alarm.
The potential importance of this result to the global warming debate demands a reexamination of all of the satellite data that have been collected over the last 25 years, with the best minds the science community can spare. Simply asserting that ‘Dr. Spencer does not know what he is talking about’ will not cut it any more.
We now have two papers in the peer-reviewed scientific literature that paved the way for this work (here and here), and so one can not simply dismiss the issue based upon some claim that we ‘skeptics’ do not publish our work.
I just presented our latest results at the NASA CERES Team meeting to about 100 attendees, and there were no major objections voiced to my analysis of the results. (CERES is the instrument that monitors how global cloud changes affect the energy balance of the Earth). I was pleased to see that there are still some scientists who are interested in the science.
Rather than simply asserting that I am wrong, why not take a fresh look at the data that have been collected over the years? Given the importance of the issue, it would seem to be the prudent thing to do. A red team-blue team approach is needed here, with the red team specifically looking for evidence that the IPCC has been wrong in their previous evaluation of the satellite data.
I suggested this years ago in congressional testimony, but one thing I’ve learned is that most congressional hearings are not designed to uncover the truth.
Maybe those in control of the research dollars are afraid of what might be found if the research community looked too closely at the satellite measurements. There are now billions — if not trillions — of dollars in future taxes, economic growth, and transfers of wealth between countries that are riding on the climate models being correct.
Scientific debate has all been shut down. The science of climate change was long ago taken over by political interests, and I am not hopeful that the situation will improve anytime soon. But I will continue to try to change that.