Global warming how to stop it?

Guest post by Alden Griffith, creator of Fool Me Once, a new blog featuring video presentations explaining climate science. This blog post is a written version of his first video addressing the argument 'Global warming has stopped'.

Has global warming stopped? This claim has been around for several years, but received new attention this winter after a BBC interview with Phil Jones, the former director of the Climate Research Unit at the University of East Anglia (which maintains the HadCRU global temperature record).

Yes, but only just. I also calculated the trend for the period 1995 to 2009. This trend (0.12C per decade) is positive, but not significant at the 95% significance level. The positive trend is quite close to the significance level. Achieving statistical significance in scientific terms is much more likely for longer periods, and much less likely for shorter periods.

Those pushing the “global warming has stopped” argument immediately jumped on this as validation, and various media outlets ran with the story, e.g. “Climategate U-turn as scientist at centre of row admits: There has been no global warming since 1995” (Daily Mail).

Well, what can we take away from Dr. Jones’ answer? He says that the positive temperature trend is “quite close to the significance level” and that achieving statistical significance is “much less likely for shorter periods.” What does all of this mean? What can we learn about global temperature trends from the past 15 years of data?

Figure 1: Global temperature anomalies for the 15-year period from 1995 to 2009 according to the HadCRUT3v analysis. The black line shows the linear trend.

First though, it’s worth briefly discussing what “statistically significant” means. This is referring to the linear regression test that informs our decision to conclude whether the slope of the trend line is truly different from zero. In other words, is the positive temperature trend that we observed really any different from what we would expect to see from just random temperature variation? By convention, statistical significance is usually set at 5% (Dr. Jones has simply inverted it to 95%). This 5% refers to the probability that we would have observed such a positive trend if in reality there is no trend. The lower this probability, the more we are compelled to conclude that the trend is indeed real.

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