A small “Signal-to-Noise Ratio” means that there is not enough real information (signal) compared to the background noise to make a definitive statement about something. With a sufficiently high Signal-to-Noise Ratio, it is possible to make statistically valid statements about some measure or observation. This applies to a lot of day to day decisions you make in life.
Climate change denialists understand this principle and they use it to try to fool people into thinking that “the jury is still out” on Global Warming, or that scientists are making up their data, and so on. Here, I want to explain very clearly what a Signal-to-Noise Ratio is and now it works in a totally understandable way; What this means for understanding Global Climate Change (in particular, warming); and to point you to an excellent paper (“Separating Signal and Noise in Atmospheric Temperature Changes: The Importance of Timescale”) about to be published by Ben Santer and several other authors. Sander’s paper effectively puts an end to Climate Change denialists misuse of data which has come to be known as “cherry picking” but that I prefer to call “dishonesty.”
Continue reading Global Warming: Separating the noise from the signal