In the first post of this three-part series that examines NINO3.4 SST (not NINO3.4 anomaly) data, I illustrated the differences between the NINO3.4 SSTs and the SST anomalies and showed an unusual aspect of NINO3.4 SST data (other than the magnitude of its variations) that differentiates it from other SST data sets. That notable difference in NINO3.4 data is a negative trend from 1854 to 2007 in the annual minimum NINO3.4 SST. In other words, the annual minimum NINO3.4 SST has decreased over the period of the instrument temperature record. In contrast, of the many data sets I’ve checked, the minimum annual temperatures of all SST or LST data sets have increased over the past 150+ years.
In this the second post of the series, I illustrate the temperature differences (Delta T) between NINO3.4 SST data and SST data of the northern and southern hemispheres and between NINO3.4 SST and global land surface and global combined (land plus sea) surface temperatures. There are also underlying oscillations that are exposed by the Delta T graphs. These deserve more research and further explanation.
DELTA T BETWEEN NINO3.4 AND HEMISPHERIC SST
Figures 1 and 2 are noisy graphs of the temperature difference (Delta T) between NINO3.4 SSTs and Northern and Southern Hemisphere SSTs. Both graphs are of monthly SST, and in both graphs, the data has not been filtered. Figure 1 is the longer-term data, covering the period of January 1854 to July 2008. In Figure 2, the short-term data extends from January 1978 to July 2008. They’re provided to show the magnitude of the annual changes in Delta T.
In Figure 3, the Delta T between NINO3.4 and Northern and Southern Hemisphere SSTs has been smoothed with a 12-month running-average filter. There is very little apparent difference in the Delta T between NINO3.4 SST and the SST of the two hemispheres when the data is smoothed. The differences are there. Northern and Southern Hemisphere SST data sets are significantly different. It’s just that the magnitudes of the annual variations in Delta T mask those differences.
THE UNDERLYING OSCILLATION
In Figures 4 and 5, I’ve isolated the Delta Ts between NINO3.4 SST and the Northern and the Southern Hemisphere SSTs. If you were to open both illustrations in separate windows and switch between the two, you’d note that there are minor differences between the data sets. What does stand out, however, especially in the NINO3.4 to Northern Hemisphere Delta T data, is an underlying oscillation with a length of approximately 80 years. I’ve been plotting temperature data for a number of years and I’ve never run across such an obvious oscillation of that length. There also appear to be short-term variations in trend, but it was the long-term oscillation that caught my eye. The only natural oscillation I know of with a frequency of that length is the Gleissberg Cycle, a solar cycle. But I know so little about the Gleissberg Cycle I would not even venture to comment. Also, what shows in the graph could simply be an underlying oscillation with a length that approximates that of the Gleissberg Cycle. The oscillation is apparent and noteworthy, though.
To determine if that long-term oscillation is only a product of the Delta T between NINO3.4 SST and hemispheric SST, I’ve plotted the Delta T of NINO3.4 SST and Absolute Land Surface Temperature in Figure 6 and plotted the Delta T of NINO3.4 SST and Absolute Combined (Land plus Sea) Surface Temperature in Figure 7. Both data sets are smoothed with 12-month filters. Also note that the start year for the NCDC absolute temperature data is 1880, so Figures 6 and 7 have shorter time spans than the other graphs in this post. The underlying long-term oscillation is present in those Delta T data sets as well. I’ve added a polynomial trend to Figure 7 to emphasize it.
One more data set to check: The last graph, Figure 8, is a long-term graph of the Delta T between NINO3.4 SST and Global SST. It contains a poly trend, also for emphasis. And yes, the underlying oscillation shows up in it.
SO WHAT DOES THAT TELL US?
Other than the fact that there appears to be an underlying oscillation in the calculated Delta T data sets, only one thing can be said and it’s obvious: During periods when the Delta T between NINO3.4 SST and the reference temperatures is increasing, NINO3.4 SSTs are rising faster than the reference temperature, and vice versa when the Delta T is decreasing.
PREVIEW OF THE THIRD POST IN THE SERIES
Please scroll up to Figure 2. There appears to be an oscillation with an 11-year length that’s visible in the short-term Delta T graph. It’s also visible in the short term NINO3.4 SST data from the first post of this series, which I’ve duplicated here as Figure 9.
Don’t get your hopes up about what it will show. The correlation between NINO3.4 SST and TSI is reasonably good for the past three solar cycles, but prior to that someone with better analytical capabilities would be required to extract the noise. This assumes there is, in fact, a correlation earlier in the two data sets.
A NOTE ABOUT THE USE OF POLY TRENDS
I’ve used the polynomial trends in this post simply to confirm and emphasize what I was seeing. They don’t work as well as I would like in drawing out the trends. In Figure 8, the poly trend appears to minimize the amplitude, and as you will note in Figure 9, the poly trend can also exaggerate parts of the trends. I would be happier with a different means of filtering or trending, but since I use the polynomial trends so rarely, they will suffice.
Sea Surface Temperature Data is Smith and Reynolds Extended Reconstructed SST (ERSST.v2) available through the NOAA National Operational Model Archive & Distribution System (NOMADS).
NCDC Absolute Temperature data was created from the data supplied here: