Guest essay by Craig Lindberg
In a recent post, A Relationship Between Sea Ice Anomalies, SSTs, and the ENSO? (https://wattsupwiththat.com/2014/02/13/a-relationship-between-sea-ice-anomalies-ssts-and-the-enso/), I introduced the Sea ice Anomaly Oscillation (“SAO”) – an observation that there is an oscillation in the sign and magnitude of the changes in the relationship between the hemispheric sea ice anomalies over time. This post takes a look at one possible internal mechanism of the SAO: sea level pressure (“SLP”).
The SAO is the moving, trailing-356-day regression of the Northern Hemisphere sea ice anomaly vs. the Southern Hemisphere sea ice anomaly (“NH” and “SH” respectively) as calculated from the daily data available at Cryosphere Today / Arctic Climate Research at the University of Illinois (Figure 1).
The SAO appears to have a 32 year period that is almost exactly half that of the Atlantic Multidecadal Oscillation (“AMO”) and also that of a similar index calculated for the North Pacific I call the PMO (the detrended mean 20N-65N, 100W-100E SST anomaly). Minimums, maximums, and zero crossings of the SAO all appear to coincide with certain related aspects of the relationship between the AMO and PMO as detailed in my previous post.
In general, when the SAO is negative, the hemispheric sea ice anomalies tend to move in opposite directions; that is, when the anomaly increases in one hemisphere, it tends to decrease in the other (either up or down). When the SAO is positive, the opposite is true.
Figure 1 – the Northern and Southern Hemisphere sea ice anomalies and the SAO. Any point in the SAO represents the sign and magnitude of the relationship between the NH and SH sea ice anomalies for the preceding 365 days.
The SAO and SLP
Looking into the relationship between the SAO and SLP, I used the NP Index, and a similar index calculated for the North Atlantic (the “NASLP”) – the mean N. Atlantic SLP (0-70N, 280-360E).
The NCAR website (https://climatedataguide.ucar.edu/climate-data/north-pacific-np-index-trenberth-and-hurrell-monthly-and-winter) describes the NP index as “the area-weighted sea level pressure over the region 30°N-65°N, 160°E-140°W. The NP index is defined to measure interannual to decadal variations in the atmospheric circulation. The dominant atmosphere-ocean relation in the north Pacific is one where atmospheric changes lead changes in sea surface temperatures by one to two months. However, strong ties exist with events in the tropical Pacific, with changes in tropical Pacific SSTs leading SSTs in the north Pacific by three months.”
The first and most obvious thing you see in the monthly NP Index is the similarity to the NH sea ice anomaly over the past seven years or so. With a four month lag, the two line up very closely (2007.00 – 2013.58: r^2 = 0.39). A similar relationship appears to exist between the NH anomaly and the NASLP (r^2 = 0.19), Figure 2.
With both the NP Index (N. Pacific SLP) and the NASLP (N. Atlantic SLP), it appears that after the SAO turns positive at around 1996, the correlation between the NH sea ice anomaly and the SLP gradually changes from negative to positive. In addition, Figure 3 appears to show that when the SAO is negative, the NH anomaly correlates fairly well with the inverse N. Pacific SST (Sea Surface Temperature), and when the SAO changes to the positive phase, SLP becomes the main driver.
Figure 2 – the NH sea ice anomaly compared to the NP Index lagged 4 months, and the mean N. Atlantic SLP lagged 3 months. Both the North Pacific and North Atlantic SLP appear to be negatively correlated to the NH Anomaly in the negative phase of the SAO and gradually change to a positive correlation after entering the positive phase of the SAO.
Figure 3 – the NH sea ice anomaly compared to the inverse mean N. Pacific SST (top) and the NP Index (bottom). The NH sea ice anomaly appears to be directly correlated to the NP SST when the SAO is negative and the NP SLP when the SAO is positive.
Another observation that is less obvious, and perhaps less expected, is that when smoothed with a 13-month centered simple moving average filter (no lag), the NP Index correlates fairly well with the SH sea ice anomaly. As can be seen in Figure 5, the sign of the SH anomaly correlation appears to be inversely related to the phase of the SAO. When the SAO is negative, the correlation coefficient is positive and vice versa. Correlation coefficients: 1980-1996 (SAO negative) = 0.39, 1996-2012 (SAO positive) = -0.09, and 2012-2014 (SAO negative) = 0.34).
Unlike with the NH anomaly which appears to have a SAO-correlated relationship with both the NP Index and the NASLP, the SH sea ice anomaly appears to have such a relationship with only the NP Index. In the case of the SH anomaly and the NASLP, the two appear to be uncorrelated or perhaps slightly inversely correlated across the entire record. Correlation coefficients: 1980-1996 = -0.08, 1996-2012 = -0.10, and 2012-2014 = -0.67. This imbalance may contribute to the oscillation of the SAO.
Figure 4 – the SH sea ice anomaly compared to the NP Index (top) and the NASLP (bottom) both smoothed with a 13-month centered SMA filter. The SH anomaly correlation to the NP Index appears to follow the phases of the SAO with the SH anomaly being directly correlated to the NP Index when the SAO is negative. A similar relationship is not apparent with the SH anomaly and the NASLP. The insert shows the SH anomaly compared to the inverted smoothed NP Index to illustrate the direct correlation to the inverted NP Index when the SAO is positive.
In addition to relationships between SLP and the hemispheric sea ice anomalies that are correlated to the trend-modeled phases of the SAO, there are also clear visual similarities between the SAO itself and the 13-month smoothed NP Index (Figure 5).
Figure 5 – The NP Index compared to the SAO over the duration of the SAO record.
The SAO, SLP, and the ENSO
In my original SAO post, I noted a possible relationship between the SAO and the ENSO – as seen in the historical N. Atlantic and N. Pacific SST patterns and also in the similarities between the SAO and ENSO indexes such as the NINO3.4 when the index is inverted at the SAO inflection points as illustrated in the bottom chart in Figure 6. As such, it is probably not surprising that the NP Index also appears to have a relationship to the (inverted) NINO3.4 (Figure 6 top).
Figure 6 – the NP Index compared to the inverse NINO3.4 (top), and the SAO compared to the NINO3.4 inverted at the SAO inflection points (bottom).
It appears likely that SLP is an important driver in the sea ice anomaly changes. If so, the logical next question is what is driving the changes in SLP? If GHGs are responsible for the decreasing NH sea ice anomaly as some would have us believe, Figures 2 and 3 above would seem to suggest that GHGs must be significantly influencing SLP. In my opinion, this is not the case. Rather, I think the evidence supports the natural cycles theory. For one thing, the pattern of the SAO – which also appears to be a pattern of the ENSO and SLP – can be seen in the SSTs of both the N. Pacific and N. Atlantic. In the case of the N. Atlantic, the pattern goes back at least 100 years (see my previous post for specifics).
Data, sources, and the methodology used can be found in an Excel file here: