The 2014/15 El Niño – Part 8 – The Southern Oscillation Indices

The Southern Oscillation Index has been mentioned often in comments at WattsUpWithThat, in this series of blog posts about the upcoming El Niño. Curiously, Australia’s BOM Southern Oscillation Index for April 2014 is at a positive value that’s near to La Niña conditions, while the sea surfaces of the equatorial Pacific are now warming toward El Niño conditions. What gives?

We recently discussed the Southern Oscillation Index in the post El Niño and La Niña Basics: Introduction to the Pacific Trade Winds. In this post, I’ll only offer a brief introduction to the Southern Oscillation Index, so if you’d like a little more information, please refer to that post.   Then, after the presentation of the BOM Southern Oscillation Index dataset, we’ll discuss the Equatorial Southern Oscillation Index data available from NOAA.

SOUTHERN OSCILLATION INDEX

The Southern Oscillation Index (SOI) is one of many indices that are used to document the timing, frequency and duration of El Niño and La Niña events. The Southern Oscillation Index represents the differences in the sea level pressures between Tahiti and Darwin, Australia…with the Darwin sea level pressures subtracted from those in Tahiti.  See Figure 1 for the locations of both. The source of the illustration is the climate.gov webpage Climate Variability: Southern Oscillation Index.  The INDO and EPAC regions are used for a similar index called the Equatorial Southern Oscillation Index, which we’ll discuss later.

Figure 1 INDO-EPAC_Location_465_0

Figure 1

The Southern Oscillation was first observed by Sir Gilbert Walker back in the 1920s but, if memory serves, it wasn’t associated with El Niño and La Niña events until the 1960s.

The positive value for the Southern Oscillation Index in April indicates the sea level pressure in Tahiti was higher than the sea level pressure in Darwin, which in turn indicates that the trade winds (those located off the equator in the Southern Hemisphere) were stronger than normal in April, blowing from east (Tahiti) to west (Darwin). Stronger-than-normal trade winds are typically associated with La Niña events, not El Niño events.  A negative value would indicate the opposite…that the sea level pressure in Tahiti is lower than the sea level pressure in Darwin, which in turn indicates that westerlies are blowing from west to east.  And a negative value is what we’d expect during an El Niño.

Then again, the El Niño hasn’t developed yet.

Figure 2 compares the Southern Oscillation Index values so far this year to the values during the development of the 1982/83 and 1997/98 El Niño. Again, we’re using those two strong El Niños as reference because some indicators are suggesting the developing El Niño may be strong.  The Southern Oscillation Index had been decreasing as we would expect during the development of an El Niño, but then it made a quick change in April.  Is that a concern if you’re looking forward to an El Niño this year?  Nope.

Figure 2

Figure 2

Figure 3 is a spaghetti graph.  It compares the evolution of the Southern Oscillation Index so far this year in red to the evolutions of the 1986/87/88 El Niño, 1991/92 El Niño, 1994/95 El Niño, 2002/03 El Niño, 2004/05 El Niño, 2006/07 El Niño and the 2009/10 El Niño.  As shown, the Southern Oscillation Index has been positive even later in the year during the development of an El Niño. (See the Oceanic NINO Index for the “official” El Niño events.)

Figure 3

Figure 3

One of the difficulties with the Southern Oscillation Index is that it is based on sea level pressures for locations that are off of the equator, while El Niño events take place along the equator in the Pacific. The second complication is that the sea level pressures are measured at two specific locations and that means they are very susceptible to changes in local weather.   This was discussed back in 1997 in a paper by Kevin Trenberth The Definition of El Niño.  There Trenberth wrote:

Various versions of the SOI exist although, in recent years, most deal only with atmospheric pressures and usually only those at Darwin and Tahiti. In using the SOI based on just two stations, it must be recognized that there are many small scale and high frequency phenomena in the atmosphere, such as the Madden-Julian Oscillation, that can influence the pressures at stations involved in forming the SOI, but which do not reflect the Southern Oscillation itself. Accordingly, the SOI should only be used when monthly means are appropriately smoothed (Trenberth 1984, Trenberth and Hoar 1996a).

[Trenberth (1984) is Signal Versus Noise in the Southern Oscillation.  And Trenberth and Hoar (1996a) is The 1990-1995 El Niño-Southern Oscillation Event: Longest on record, which was an early attempt to tie El Niño events to manmade global warming.  That period has now been broken down into 2 “official” El Niño events, according to the Oceanic NINO Index.]

In Trenberth (1984), he presented the results after smoothing the Southern Oscillation Index data with an “11-term low-pass filter.”  That wouldn’t help us in this short-term look, so let’s use a simple 3-month running mean. (NOAA uses the 3-month running mean for a version of its Equatorial SOI data, to be discussed later.)  Figures 4 and 5 present the same comparisons as the earlier two graphs, but in them the Southern Oscillation Index values have been smoothed with 3-month running-mean filters.  As shown in Figure 4, with that minor filtering, the current evolution does not look out of place compared to the 1982/83 El Niño or the 1997/98 El Niño. And the current evolution appears within the range of the other El Niño events since 1986. See Figure 5.

Figure 4

Figure 4

# # # # # #

Figure 5

Figure 5

But that still doesn’t help us with the fact that the reference points for the Southern Oscillation Index are off the equator while El Niño events are focused along the equator in the Pacific.   Thus…

NOAA’S EQUATORIAL SOUTHERN OSCILLATION INDEX

In their Climate Prediction Center Equatorial Southern Oscillation Index (1949-present) webpage, NOAA describes the dataset as:

Abstract:

This is one of the CPC’s Monthly Atmospheric and SST Indices. It contains Equatorial Southern Oscillation Index (standardized sea level pressure differences between EPAC (5N-5S, 80W-130W) and INDO (5N-5S, 90E-140E)) for the period of 1949-present. The anomalies are departures from the 1981-2010 base period means.

Purpose:

This index is constructed for applications in climate monitoring, climate analysis and verifications of numerical models.

Please refer to Figure 1 again for the locations of the EPAC and INDO regions.  Because they are comparatively large regions, they should be less susceptible to weather noise, and because they are located along the equator, they should better capture the equatorial trade winds.  The Equatorial Southern Oscillation Index is calculated in a similar fashion.  It represents the sea level pressure difference between the eastern equatorial Pacific (EPAC) and the sea level pressure of equatorial Indonesia (INDO)…with INDO subtracted from EPAC.

The Equatorial Southern Oscillation Index data are available from the NOAA Monthly Atmospheric & SST Indices webpage.  The Indonesia (INDO) sea level pressure data (standardized) are here, the Eastern Equatorial Pacific (EPAC) sea level pressure data (standardized) are here, and the Equatorial Southern Oscillation Index data are here (and it appears the difference is then standardized as well.)  NOAA also provides the Equatorial Southern Oscillation Index data as a 3-month running mean here.  But there really doesn’t appear to be the same need to smooth the Equatorial Southern Oscillation Index data, as you shall see.

Figure 6 compares the Equatorial Southern Oscillation Index values so far this year to the values during the development of the 1982/83 and 1997/98 El Niño.  The evolution this year falls in line with the two strong El Niños.

Figure 6

Figure 6

Compared to the other El Niño evolutions, Figure 7, this year appears to be the stronger (more negative) than normal at this stage.

Figure 7

Figure 7

And for those who would like to see the comparisons with the Equatorial Southern Oscillation Index data smoothed with the 3-month running means see Figures 8 and 9.

Figure 8

Figure 8

# # # # # #

Figure 9

Figure 9

COMPARISON OF THE TWO SOUTHERN OSCILLATION INDICES

Figure 10 compares the BOM Southern Oscillation Index data to the NOAA Equatorial Southern Oscillation Index data.  The BOM also multiplies their SOI data by 10 after standardizing it, so for the comparison I scaled it back by dividing their data by that factor.  The correlation between the two indices is not as good as one might suspect, with a correlation coefficient of 0.77.

Figure 10

Figure 10

And NOAA’s Equatorial Southern Oscillation Index data correlates better (-0.83) with NINO3.4 sea surface temperature anomalies (Kaplan SST) than does the BOM Equatorial Southern Oscillation Index data (-0.71).

CLOSING

The Southern Oscillation Index from BOM has been around for a long time.  It is a commonly used ENSO index.  It is noisy and, at times, does not appear to reflect what’s taking place along the equatorial Pacific.  Then again, it is much studied with respect to its impact on weather in Australia and New Zealand.

It appears that NOAA’s Equatorial Southern Oscillation Index better reflects what’s taking place along the equator in the Pacific, where ENSO events take place, but it is not as popular as the BOM SOI.

EARLIER POSTS IN THIS SERIES

And for additional introductory discussions of El Niño processes see:

FURTHER READING

My ebook Who Turned on the Heat? goes into a tremendous amount of detail to explain El Niño and La Niña processes and the long-term aftereffects of strong El Niño events.  Who Turned on the Heat? weighs in at a whopping 550+ pages, about 110,000+ words. It contains somewhere in the neighborhood of 380 color illustrations. In pdf form, it’s about 23MB. It includes links to more than a dozen animations, which allow the reader to view ENSO processes and the interactions between variables.

I’ve lowered the price of Who Turned on the Heat? from U.S.$8.00 to U.S.$5.00.  A free preview in pdf format is here.  The preview includes the Table of Contents, the Introduction, the first half of section 1 (which was provided complete in the post here), a discussion of the cover, and the Closing. Take a run through the Table of Contents.  It is a very-detailed and well-illustrated book—using data from the real world, not models of a virtual world. Who Turned on the Heat? is only available in pdf format…and will only be available in that format.  Click here to purchase a copy.  Thanks. Book sales and tips will hopefully allow me to return to blogging full-time once again.

 

 

 

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About Bob Tisdale

Research interest: the long-term aftereffects of El Niño and La Nina events on global sea surface temperature and ocean heat content. Author of the ebook Who Turned on the Heat? and regular contributor at WattsUpWithThat.
This entry was posted in 2014-15 El Nino Series, El Nino-La Nina Processes. Bookmark the permalink.

50 Responses to The 2014/15 El Niño – Part 8 – The Southern Oscillation Indices

  1. Arska says:

    Hello Bob

    I found quite convicting proof that Nino3.4 index is quite closely tied to speed of the trade winds in the Southern hemisphere blowing to Nino region. (Notice that wind scale is inverted)

    ShtradwindsnsNino34.jpg

    It seems that in area that I pointed out wind speed has increased during latest decade, which means El Ninos can’t be developed very easily. I think in coming years we are favoured by La Ninas because of that wind “anomaly”.

    And as I suggested earlier, warm NH strenghtens SH trade winds….and vice versa.

  2. Bob Tisdale says:

    Arska, El Nino events are most impacted by the trade winds in the western equatorial Pacific. They reinforce the feedback during the development phase.

    Also, there should be little doubt that the Pacific trade winds in both hemispheres have increased in recent years. We’ve gone from a period dominated by El Nino events to one dominated by La Nina events.

  3. Bob Tisdale says:

    Arska, another thought. I note that you haven’t shown the trade wind data for the Northeastern Tropical Pacific. It should be very similar, also showing strengthening in recent years. By excluding data that may not support your hypothesis, you’re biasing your research.

    Cheers

    PS: The tropical Pacific is a tremendously large area. You need to look at it in total, not just one region that supports what you believe.

  4. Arska says:

    Hello Bob

    My hypotesis is that NiNo region trade winds are MOSTLY driven by SH (and specially they “Grow” in area I highlighted in my previos post, so that is why I pay special attention to it)

    In equator there is no driving force for trade winds. If you take a look at current world pressure distribution map, you can see that source for trade wind is in High pressure cells both in SH and NH. Equator region is simply way too “homogenic”.
    worldpressuremap.JPG

    source:http://www.weatheronline.co.nz/

  5. Bob Tisdale says:

    Arska says: “In equator there is no driving force for trade winds.”

    There isn’t? The temperature difference (absolute) between the eastern and western equatorial Pacific dictates the strength and direction of the trade winds. And the strength and direction of the trade winds dictate the temperature difference (absolute) between the eastern and western equatorial Pacific. Have you heard of Bjerknes feedback? Are you aware that NOAA monitors the equatorial trade winds?

    Your hypothesis is flawed.

  6. Steve Keohane says:

    Thanks again Bob.

  7. Arska says:

    Hello Bob

    The temperature difference is not driving any winds, the key is pressure difference. Did you check the picture in my last posting ? Currently there is no absolute pressure difference between western and eastern equatorial Pacific, but trade winds are still blowing because of the HIGH pressure cells on SH and NH.

    Of cource when temperature anomalies get high enough, there will be quite big pressure differences even on equatorial Pacific and that is what Bjerknes feedback is all about.

    My point is:

    1) Trade wind strenght is mainly driven by pressure difference between SH and equatrorial Pacific
    2) During El Nino / La nina events Bjerknes feedback is adding positive feedback to trade wind strenght by generating EXTRA pressure difference to equatorial Pacific

    So the SH is triggering El Nino and Bjerknes feedback is adding more power to it.

  8. Bob Tisdale says:

    Arska, excuse my brief description of the trade winds in my earlier comment. The trade winds are of course driven by the temperature difference between the equator and the extratropics, which in turn create the pressure differences, which cause the surface winds to blow toward the equator. And the equatorward winds are deflected toward the west by the Coriolis effect to create the trade winds. The trade winds also create the temperature difference between the eastern and western equatorial Pacific, while the temperature difference between the eastern and western equatorial Pacific enhance or suppress the trade winds, etc.

    Now to your hypothesis: Let’s take a look at the U-component of the TAO project wind data available at the KNMI Climate Explorer. The buoys were fully installed by the early 1990s, so we’ll start in 1995. That’s a great place to start because it includes the 1997/98 El Nino and it was strong enough to overcome weather noise.

    Arska Trade Winds Absolute By Pacific Sectors

    Yes, you are correct that the trade winds in the southeastern equatorial Pacific are stronger than those in the northeast, northwest and southwest quadrants. Note two things, however. (1) The trade winds are more balanced in the western sectors, and in the northwest sector, they are slightly stronger than in the southwest sector. (2) The trade winds in the southeastern equatorial Pacific are the least volatile and, in response to the 1997/98 El Niño, the trade winds in the southeast sector lagged the variations in the other regions.

    So let’s look at the data in anomaly form for the period of 1995-1999 to capture the 1997/98 El Niño.

    Arska Trade Winds Anomalies By Pacific Sectors 1997-98 El Nino

    The 1997/98 El Niño was initiated by the trade winds in the northwest and southwest equatorial Pacific, not the southeast. There should be no doubt about that. The westerly wind bursts were strong and lasted quite a long time in the western equatorial Pacific. Note also that the trade winds in the Southeast sector didn’t peak for many months and appear to be timed with the increase in surface temperatures there. In other words, the slowing of the trade winds in the southeast sector are a response to the El Niño, not the initiator.

    In other words, the data contradicts your closing statement of “So the SH is triggering El Nino and Bjerknes feedback is adding more power to it.”

    Arska, please study and understand the processes of ENSO in minute detail before attempting to decide what triggers and drives an El Niño. Right now, you’re biased by your hypothesis, which means you’re only looking for things to support it. Please put your hypothesis aside and study ENSO. Your enthusiasm is to be commended but I do not have the time to continue to show you the flaws in your hypothesis.

  9. Arska says:

    Hello Bob
    Thanks for TAO data, it was good reference for my SH trade wind data. And yes, it seems that in 1997 El Nino event Western trade winds was leading the entire process.But in 2010 El Nino Western trades was growing all together with El Nino, so those winds are not good for predicting any major El Nino event.

    So I must abandon my hypotesis with SH trades triggering the El Nino. I think their role is now more like previnting El Ninos, because trade winds are blowing stronger now in SH.

    I made wrap up for these El Nino predictors, and in my point of view still best predictor is dropping NH temperatures while developing El Nino (Nino index between 0,3-0,7)
    ElNino_predictors.JPG

  10. Thanks, Bob. There is always something new to learn from your articles.

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