“What really matters is: what happens in developing countries such as China, India, Indonesia, Brazil and Nigeria”, says Lewis, who gave a presentation at De Groene Rekenkamer Foundation this week in Amsterdam. According to him, it is much more important that developing countries quickly become richer and how rising CO2 emissions that this entails can be limited.
“We have a lot of knowledge and expertise in Europe. We can spend our money better than investing billions in subsidies and other climate policies that have virtually no effect on global emissions.”
Lewis would prefer to see investments in the development of clean nuclear energy or techniques to get CO2 out of the air and shut down coal-fired plants. “That could then be rolled out over the rest of the world.”
Climate models play a central role in the attribution of global warming or climate change to human causes. The standard argument takes the following form: “We can get the model to do X, using human causes, but not without them, so human causes must be the cause of X.” A little digging reveals that this is actually a circular argument, because the models are set up in such a way that human causes are the only way to get change.
The finding is that humans are the cause of global warming and climate change is actually the assumption going in. This is circular reasoning personified, namely conclude what you first assume.
This circularity can be clearly seen in what many consider the most authoritative scientific report on climate change going, although it is actually just the most popular alarmist report. We are talking about the Summary for Policymakers (SPM), of the latest assessment report (AR5), of the heavily politicized UN Intergovernmental Panel on Climate Change (IPCC). Their 29 page AR5 SPM is available here.
Reliability of future global warming projections depends on how well climate models reproduce the observed climate change over the twentieth century. In this regard, deviations of the model-simulated climate change from observations, such as a recent “pause” in global warming, have received considerable attention. Such decadal mismatches between model-simulated and observed climate trends are common throughout the twentieth century, and their causes are still poorly understood. Here we show that the discrepancies between the observed and simulated climate variability on decadal and longer timescale have a coherent structure suggestive of a pronounced Global Multidecadal Oscillation. Surface temperature anomalies associated with this variability originate in the North Atlantic and spread out to the Pacific and Southern oceans and Antarctica, with Arctic following suit in about 25–35 years. While climate models exhibit various levels of decadal climate variability and some regional similarities to observations, none of the model simulations considered match the observed signal in terms of its magnitude, spatial patterns and their sequential time development. These results highlight a substantial degree of uncertainty in our interpretation of the observed climate change using current generation of climate models.
La géologie, une science plus que passionnante … et diverse