97% of climate science papers support the consensus. What about those that don't? The one thing they seem to have in common is methodological flaws like cherry picking, curve fitting, ignoring inconvenient data, and disregarding known physics.
Good modeling will constrain the possible values of the parameters being used so that they reflect known physics, but bad ‘curve fitting’ doesn’t limit itself to physical realities. For example, we discuss research by Nicola Scafetta and Craig Loehle, who often publish papers trying to blame global warming on the orbital cycles of Jupiter and Saturn. (emphasis mine)We found that the ‘curve fitting’ approach also used in the Humlum paper is another common theme in contrarian climate research. ‘Curve fitting’ describes taking several different variables, usually with regular cycles, and stretching them out until the combination fits a given curve (in this case, temperature data). It’s a practice I discuss in my book, about which mathematician John von Neumann once said,
With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.