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Friday, March 13, 2009

Low Frequency ENSO Oscillations

I’ve moved to WordPress.  This post can now be found at Low Frequency ENSO Oscillations
INITIAL NOTE: In this post, I did not filter the data. The smoothing of the NINO3 and SOI data with a 30-year Gaussian-weighted filter was performed by Jones et al. I simply inverted the Jones et al data in Figures 2 through 5 so that Sea Surface Temperature (SST) was depicted in a manner that’s familiar to most people.

The NOAA Paleoclimatology Program website contains a webpage devoted to the Jones et al (2001) paper “The Evolution of Climate Over the Last Millennium”.

Figure 1 is Cell A of Figure 4 on that webpage. With a quick glance, it appears to be similar to other long-term graphs of climate indices that show an increase...until you note the variable, the Southern Oscillation Index (SOI). What’s not obvious to those unfamiliar with the SOI is, variations in the SOI are inversely related to NINO SST anomalies. That is, a decrease in the SOI is usually followed by a rise in SST in the NINO regions of the equatorial Pacific. Note that the one temperature index on the graph, the Mann et al NINO3 Reconstruction, has been inverted. In other words, Figure 1 actually shows that smoothed NINO3 SST anomalies decreased over most of the period from the mid-1600s to the late 1900s. A link to the data used in the graph is here:
Figure 1

For those who question my interpretation, the text for that Figure reads, “Fig. 4. Boreal winter Southern Oscillation Index (SOI, standardized anomalies relative to 1961-1990). Observed October to March mean SOI (black, 1867-2000), the reconstruction of Stahle et al., rescaled to match the observed mean and variance over 1867-1977 (blue, 1706-1977), and the Nino 3 sea surface temperature reconstruction of Mann et al., inverted and then rescaled to match the observed SOI mean and variance over 1867-1977 (red, 1650-1980). All series have been smoothed with a 30-year Gaussian-weighted filter.”

Multiplying the data by -1 presents it in a form where the temperature index is of the correct sign and the SOI data have been inverted. Refer to Figure 2. It clearly shows the decrease in NINO3 SST anomalies.
Figure 2

Note: The long-term decrease in the Mann NINO3 SST anomalies is consistent with other SST reconstructions, especially the Indo-Pacific Warm Pool SST Reconstruction and the Subtropical South Pacific SST Reconstruction, Figures 3 and 9 in my SST Reconstructions post.


The recent rise in the Observed SOI data (black curve) from ~1976 to 2000 in Figure 3 is quite obvious. This was a period when the magnitude and frequency of El Nino events were much greater than any other period during the 20th Century. It includes the 1997/98 “El Nino of the Century” and a “Super El Nino” in 1982/83. Additionally, a significant multiyear El Nino occurred in 1986/87/88. That 1986/87/88 El Nino, like the 1997/98 El Nino, created a step rise in the SST anomalies of the East Indian and West Pacific Oceans and in the North Atlantic.

Note, however, in the scaled NINO3 data, Figure 3, there were earlier periods with similar rises. I do realize that I’m comparing two different variables, but Jones et al scaled the Observed SOI data so that its variations would correspond with the Mann NINO3 and the Stahle SOI datasets. In fact, Jones et al compared the three datasets in their discussions. They wrote, “Both series show similar interannual and interdecadal variability back to the 1700s (38).” They further explained, “On the 30-year time scale (Fig. 4A), many of the low frequency features agree (41), although the Mann et al. (27, 40) series tends to have more warm phase (low SOI) events before 1800.”

The link to the Jones et al 2001 paper:
Figure 3

Then Jones et al added a clarification, “The recent 25-year period during which warm phases have dominated appears to be unique in the tree-ring-based reconstruction and in the Mann et al. (27, 40) series since 1800, but the uncertainty in the reconstructions needs to be fully quantified before this statement can be made with confidence.”

The data seems to contradict the Jones et al statement that the recent 25-year period is unique in the Mann series since 1800, because the rise in the Mann data in the early 1800s (peak ~1831 in Figure 3) was also similar in magnitude to the recent rise. Regardless, whether the dividing time is 1800 or 1850, the Jones et al clarification does not say that the recent surge is unique; it only states that it’s unique since 1800. Comparing the recent 25-year period to the two major variations prior to 1850, there’s nothing unusual about the recent rise in El Nino (warm) events.


In Figure 4, the maximums in the decadal variations of the Mann NINO3 data have been highlighted. The peaks occurred in 1691, 1719, 1744, 1767, 1794, 1831.5 (the NINO3 SST anomalies for 1831 and 1832 were the same), 1853, 1878, 1902, 1941, and 1964. The minimum span was 21.5 years (1831.5 to 1853), while the maximum was 39 (1902 to 1941). The average time span was approximately 27 years.
Figure 4


I’ve provided Figure 5 solely for those wondering how the Mann reconstructed NINO3 data (that’s been smoothed with the 30-year Gaussian Filter by Jones et al 2001) compares with Global Temperature Anomalies (raw HadCRUT3GL data). I’ve only inverted the Mann data from the Jones et al 2001 dataset, bringing it back to its proper form as I had in Figures 2 through 4. Other than that I’ve applied no scaling or other filtering to either dataset.

When El Nino (warm ENSO) events dominate, global surface temperatures rise, and when La Nina (cool ENSO) events are dominant, global surface temperatures decline.
Figure 5


In addition to the data available through the above links, the raw Mann et al NINO3 data is available here:
It’s from the NOAA Paleoclimatology Program listing of Climate Reconstructions here:
The raw Stahle et al “winter” SOI (DJF) data is available here:

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