Lucia, at rankexploits.com, has been musing over Tilo Reber’s posting of a graph showing flat 11 year trends in the HadCRUT land-ocean global temperature anomaly and the two MSU satellite data sets, UAH and RSS. In answer to the question whether global warming is on an 11 year hiatus, “not quite,” says Lucia. She challenges Tilo’s omission of the GISS data set, because notwithstanding questions about the reliability of GISS, it still shows a positive trend over the 11 year period in question. Unless all the measures show a flat trend, Lucia’s not ready to conclude that global warming has been on an 11 year hiatus.
I understand the desire to look at as many metrics as possible in trying to divine what is going on with globally averaged temperature. I also understand the reasons for questioning the reliability of GISS. What I don’t understand is why the only measure of trend that seems to count is a trend derived from linear regression. William Briggs recently had an interesting post to his blog on the relationship between trends in CO2 and temperature in which he introduced the use of loess lines to track trends that are not represented well by linear regression. Loess refers to a type of locally weighted regression that in effect fits a piecewise linear or quadratic trend through the data, showing how the trend is changing over time. Especially in an environment where the charge of cherry-picking the data — choosing starting and ending points to produce a particular result – is routinely made, loess lines are a relatively robust alternative to simple trend lines from linear regression.
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Figure 1 fits a loess line through the data for GISS using the same 11 year period used by Tilo Reber (except that I’ve normalized all anomalies in this discussion relative to their 11 year mean to facilitate comparison to a common baseline). The red line is the GISS anomaly for this period, about its mean, and the blue line is the loess line. While it varies up and down over the period in question, I would argue that the overall trend is essentially flat, or even slightly negative: the value of line at the end of the period is slightly lower than at the beginning of the period. What this loess line shows is that a linear regression trend is not a particularly good way to represent the actual trend in the data. Without actually fitting a linear trend line, we can reasonably guess that it will trend upwards, because of the way the loess line is lower in the first half of the period in question, and higher in the second half. Linear regression will fit a positive, but misleading, slope through the data, implying that at the end of the period the GISS is on an upward trend when in fact the trend peaked around 2006 and has since declined.
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Figure 2 is rainbow of colors comparing all four of the metrics we tend to follow here on WUWT. Not surprisingly, the loess lines of HadCRUT, UAH and RSS all track closely together, while GISS is the odd duck of the lot. So what does this kaleidoscope of colors tell us about whether global warming is has gone on an 11 year hiatus? I think it tells us rather more than even Tilo was claiming. All of the loess lines show a net decline in the trend over the 11 year period in question. It is relatively minor in the case of GISS, but rather pronounced in the case of the other three. Of the other three, the median anomaly at the beginning of the period, as represented by the loess lines, was 0.125; at the end of the period, the median anomaly had dropped to -0.071, for a total decline of 0.196, or almost 0.2C.
Global warming on hiatus? It looks to me like more evidence of global cooling. Will it continue? Neither linear regression nor loess lines can answer that question. But the loess lines certainly warn us to be cautious in naively extrapolating historical trends derived by simple linear regression.
Not even GISS can support the conclusion from the last 11 years of data that global warming continues to march upward in unrelenting fashion.