Integrating ENSO: Multidecadal Changes In Sea Surface Temperature

Guest post by Bob Tisdale

Longer Title: Do Multidecadal Changes In The Strength And Frequency Of El Niño and La Niña Events Cause Global Sea Surface Temperature Anomalies To Rise And Fall Over Multidecadal Periods?

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UPDATE (November 19, 2010): I’ve added a clarification about the running total of scaled NINO3.4 SST anomalies and its implications. I changed a paragraph after Figure 13, and added a discussion under the heading of “What Does The Running Total Imply?”

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OVERVIEW

This post presents evidence that multidecadal variations in the strength and frequency of El Niño and La Niña events are responsible for the multidecadal changes in Global Sea Surface Temperature (SST) anomalies. It compares running 31-year averages of NINO3.4 SST anomalies (a widely used proxy for the frequency and magnitude of ENSO events) to the 31-year changes in global sea surface temperature anomalies. Also presented is a video that animates the maps of the changes in Global Sea Surface Temperature anomalies over 31-year periods, (maps that are available through the GISS Map-Making web page). That is, the animation begins with the map of the changes in annual SST anomalies from1880 to 1910, and it is followed by maps of the changes from 1881 to 1911, from 1882 to 1912, etc., through 1979 to 2009. The animation of the maps shows two multidecadal periods, both containing what appears to be a persistent El Niño event, one in the early 1900s and one in the late 1900s to present, and between those two epochs, there appears to be a persistent La Niña event.

INTRODUCTION

A long-term (1880 to 2009) graph of Global Surface Temperature anomalies or Global Sea Surface Temperature (SST) anomalies (Figure 1) often initiates blog discussions about the causes of the visible 60-year cycle. The SST anomalies rise from early-1910s to the early-1940s, drop from the early 1940s to the mid-1970s, then rise from the mid-1970s to present. Natural variables like the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO) are cited as the causes for these variations.

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Figure 1

Note: HADISST data was used for the long-term SST anomaly graphs in this post. The exception is the GISS SST data, which is a combination of HADISST data before the satellite era and Reynolds OI.v2 SST data from December 1981 to present.

THE PDO CANNOT BE THE CAUSE

The SST anomalies of the North Pacific region used to calculate the PDO are inversely related to the PDO over decadal periods. This was shown in the post An Inverse Relationship Between The PDO And North Pacific SST Anomaly Residuals. This means that the SST anomalies of the North Pacific contribute to the rise in global SST anomalies during decadal periods when the PDO is negative and suppress the rise in global SST anomalies when the PDO is positive. The PDO, therefore, cannot be the cause of the multidecadal rises and falls in global SST anomalies. That leaves the AMO or another variable.

MULTIDECADAL CHANGES IN GLOBAL SST ANOMALIES

If we subtract the annual global SST anomalies in 1880 from the value in 1910, the difference is the change in global SST anomalies over that 31-year span. Using this same simple calculation for the remaining years of the dataset provides a curve that exaggerates the variations in global SST anomalies. This dataset is identified as the “Running Change (31-Year) In Global SST Anomalies” in Figure 2. The data have been centered on the 16th year.

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Figure 2

Why 31 years? A span of 31 years was used because it is approximately one-half the apparent cycle in the datasets, and it should capture the maximum trough-to-peak and peak-to-trough changes that occur as part of the 60-year cycle. Using 31 years also allows the data to be centered on the 16th year, with 15 years before and after.

The curve of the “Running Change (31-Year) In Global SST Anomalies” is very similar to the curve of annual NINO3.4 SST anomalies that have been smoothed with a 31-year filter. Refer to Figure 3. (NINO3.4 SST anomalies are commonly used to illustrate the frequency and magnitude of El Niño and La Niña events. For readers new to the topic of El Niño and La Niña events, refer to the post An Introduction To ENSO, AMO, and PDO – Part 1.) Both datasets are centered on the 16th year. Considering how sparse the SST measurements are for the early source data, the match is actually remarkable at that time.

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Figure 3

Let’s take a closer look at that relationship. The purple curve represents the running 31-year average of annual NINO3.4 SST anomalies, and it shows that, for example, at its peak in 1926, the frequency and magnitude of the El Niño events from 1911 to 1941 were far greater than the frequency and magnitude of La Niña events. The blue curve, on the other hand, portrays the change in global SST anomalies based on a 31-year span, and it shows, at its peak in 1926 that global SST anomalies rose more from 1911 to 1941 than it did during the other 31-year periods in the early 20th century. Skip ahead a few decades to 1960. Both curves reached a low point about then. At 1960, the purple curve indicates the frequency and magnitude of La Niña events from 1945 to 1975 outweighed El Niño events. And over the same period of 1945 to 1975, annual global SST anomalies dropped the greatest amount. Afterwards, the frequency and magnitudes of El Niño events increased (and/or the frequency and magnitude of La Niña events decreased) and the multidecadal changes in global SST anomalies started to rise, eventually reaching their peak around 1991 (the period of 1976 to 2006).

Since Global SST anomalies respond to changes in NINO3.4 SST anomalies, this relationship implies that the strengths and frequencies of El Niño and La Niña events over multidecadal periods cause the multidecadal rises and falls in global sea surface temperatures. In other words, its shows that global sea surface temperatures rose from 1910 to the early 1940s and from the mid-1970s to present because El Niño events dominated ENSO during those periods, and it shows that global sea surface temperatures dropped from the early 1940s to the mid 1970s because La Niña events dominated ENSO.

This apparent relationship contradicts the opinion presented by some climate studies that ENSO is only noise, that ENSO is only responsible for the major year-to-year wiggles in the global SST anomaly curve. Refer back to Figure 1. Examples of these studies are Thompson et al (2009) “Identifying Signatures of Natural Climate Variability in Time Series of Global-Mean Surface Temperature: Methodology and Insights” and Trenberth et al (2002) “Evolution of El Nino–Southern Oscillation and global atmospheric surface temperatures”.

Link (with paywall) to Thompson et al (2009):

http://journals.ametsoc.org/doi/abs/10.1175/2009JCLI3089.1

Link to Trenberth et al (2002):

http://www.cgd.ucar.edu/cas/papers/2000JD000298.pdf

Keep in mind, when climate studies such as Thompson et al (2009) and Trenberth et al (2002)attempt to account for El Niño and La Niña events in the global surface temperature record they scale an ENSO proxy, like NINO3.4 SST anomalies, and subtract it from the Global dataset, removing the major wiggles. They then assume the difference, which is a smoother rising curve, is caused by anthropogenic greenhouse gases.

The relationship in Figure 3 (that the multidecadal variations in strength and frequency of ENSO events are responsible for the rises and falls in global sea surface temperature) also contradicts the basic premise behind the hypothesis of anthropogenic global warming, which assumes that the rise in global sea surface temperatures since 1975 could only be caused the increase in anthropogenic greenhouse gases.

The first question that comes to mind: shouldn’t a multidecadal rise in Sea Surface Temperatures require an increase in radiative forcing? The answer is no, and I’ll discuss this later in the post. Back to Figure 3.

Once more, the relationship in Figure 3 illustrates that multidecadal variations in the frequency and magnitude of El Niño and La Niña events cause the multidecadal changes in SST anomalies. But how do I verify that this is the case, and how do I illustrate it for those without science backgrounds? Again, for those who need to brush up on El Niño and La Nina events, refer to the post An Introduction To ENSO, AMO, and PDO – Part 1.

THE ANIMATION OF MULTIDECADAL CHANGES IN SST ANOMALIES

The Goddard Institute of Space Studies (GISS) Global Map-Making webpage allows users to create maps of global SST anomalies and maps of the changes in global SST anomalies (based on local linear trends) over user-specified time intervals. Figure 4 is a sample map of the changes in annual SST anomalies for the 31-year period from 1906 to 1936. In the upper right-hand corner is a value that represents the change in annual SST anomalies over that time span. GISS describes the value as, “Temperature change of a specified mean period over a specified time interval based on local linear trends.” And as far as I can tell, these local linear trends are weighted by latitude. I downloaded the GISS maps of the changes in annual global SST anomalies, starting with the interval of 1880 to 1910 and ending with the interval of 1979 to 2009, with the intent of animating the maps, but the data they presented was also helpful.

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Figure 4

Figure 5 shows the curve presented by the GISS Multidecadal (31-year span) Changes In Global SST anomalies for all those maps, with the data centered on the 16th year. Comparing it to the “Running Change (31-Year) In Global SST Anomalies” data previously calculated, Figure 6, illustrates the similarities between the two curves. The GISS data from the maps presents a much smoother curve.

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Figure 5

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Figure 6

And if we compare the curve of the GISS Multidecadal (31-year span) Changes In Global SST anomalies from those maps to the NINO3.4 SST anomalies smoothed with a 31-month filter, Figure 7, we can see that the multidecadal changes in Global SST anomalies lag the variations in strengths and magnitudes of ENSO events. The lag prior to 1920 appears excessive, but keep in mind that the early source SST measurements are very sparse. The fact that there are similarities in the curves in those early decades says much about the methods used by researchers to infill all of that missing data.

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Figure 7

THE VIDEO

The animations are presented in two formats in the YouTube video titled “Multidecadal Changes In Global SST Anomalies”. The first format is as presented by GISS, with the Pacific Ocean split at the dateline. That is, the maps are centered on the Atlantic. Refer back to Figure 4. The second format is with the maps rearranged so that the major ocean basins are complete. Those maps are centered on the Pacific. With the maps centered on the Pacific, the animation shows what appear to be two (noisy) multidecadal El Niño events separated by a multidecadal La Niña event.

As noted in the video, the long-term El Niño and La Niña events appear in the patterns, not necessarily along the central and eastern equatorial Pacific. For those not familiar with the SST anomaly patterns associated with ENSO, refer to Figure 8. It is Figure 8 from Trenberth et al (2002) “Evolution of El Nino–Southern Oscillation and global atmospheric surface temperatures”. Link to Trenberth et al (2002) was provided earlier.

Figure 8 shows where Sea Surface Temperatures warm and cool during the evolution (the negative lags) of an ENSO event, at the peak of an ENSO event (zero lag), and during the decay of ENSO events (the positive lags). The reds indicate areas that are positively correlated with ENSO events, and the blues are areas that are negatively correlated. That is, the red areas warm during an El Niño and the blues are the areas of that cool during an El Niño. During a La Niña event, the reds indicate areas that cool, and the blues indicate areas that warm.

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Figure 8

And for those wondering why the ENSO events don’t always appear along the equatorial Pacific in the animated maps, keep in mind that the maps are showing the multidecadal changes in SST anomalies based on linear trends. The long-term linear trend of the equatorial Pacific SST anomalies are incredibly flat, meaning there is little trend. Refer to Figure 9, which shows the annual NINO3.4 SST anomalies and linear trend from 1900 to 2009.

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Figure 9

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http://www.youtube.com/watch?v=O_QopFYSyGE

Video 1

And here’s a link to a stand-alone version of the video. The only difference is that the following version includes a detailed introduction, discussion, and conclusion, which are presented in this post. It’s about 5 minutes longer.

http://www.youtube.com/watch?v=SMKA_uG3zK0

Link To Stand-Alone Version Of Video

DOES THE VIDEO AND DATA PRESENT MORE THAN MULTIDECADAL VARIABILITY IN GLOBAL SST ANOMALIES?

Yes. This has actually been stated a number of times, but the following explanation may be helpful.

One of the arguments presented during discussions of multidecadal variations in global SST anomalies is that the Atlantic Multidecadal Oscillation (AMO) is detrended and that it strengthens or counteracts the basic long-term rise in global SST anomalies. However, the data associated with the GISS maps used in the video are based on linear trends. And Figure 7 shows that the Global SST anomalies rose from 1910 to 1944 and from 1976 to 2009 because El Niño events dominated, and dropped from 1945 to 1975 because La Niña events dominated.

That is, the animation of the GISS maps and the data GISS provides with those maps show that the trends in global sea surface temperature are driven by the multidecadal variations in the strengths and magnitudes of El Niño and La Niña events. The “GISS Multidecadal (31-year span) Changes In Global SST anomaly” data peaked in 1931 at 0.39 deg C. Refer back to Figure 5. That is, from 1916 to 1946, global SST anomalies rose 0.39 deg C (based on local linear trends). That equals a linear trend of 0.13 deg C per decade. And the “GISS Multidecadal (31-year span) Changes In Global SST anomaly” data peaked in 1989 at 0.41 deg C, and that equals a trend of 0.137 deg C per decade from 1974 to 2004. Let’s look at the “Raw” Global SST anomaly data. The linear trends of the “Raw” Global SST Anomalies for the same periods, Figure 10, are approximately 0.12 deg C per decade. Again, the peaks in the “GISS Multidecadal (31-year span) Changes In Global SST anomaly” data represent the periods with the greatest linear trends, and, as shown in Figure 7, they lag the peaks of the multidecadal variations in NINO3.4 SST anomalies.

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Figure 10

Note: The highest trend in the later epoch of the GISS-based “change data” is about 5% higher than the highest trend in the earlier warming period. And that’s not unreasonable considering the early period was so poorly sampled. Again, the similarities in trends between the two epochs speaks highly of the methods used by the researchers to infill the data

A NOTE ABOUT THE NORTH ATLANTIC

Oceanic processes such as Atlantic Meridional Overturning Circulation (AMOC) and Thermohaline Circulation (THC) are normally cited as the cause of the additional multidecadal variability of North Atlantic SST anomalies. This additional variability is presented in an index called the Atlantic Multidecadal Oscillation or AMO. The AMO data are simply North Atlantic SST anomalies that have been detrended. As discussed in the post An Introduction To ENSO, AMO, and PDO — Part 2, the NOAA Earth System Research Laboratory (ESRL) Atlantic Multidecadal Oscillation webpage refers readers to the Wikipedia Atlantic Multidecadal Oscillation webpage for further discussion. And Wikipedia’s description includes the statement, “While there is some support for this mode in models and in historical observations, controversy exists with regard to its amplitude…” The phrase “some support” does not project or instill a high level of confidence.

Early in this post we prepared a dataset that illustrated the “Running Change (31-Year) In Global SST Anomalies” by subtracting the annual SST anomalies of a given year from the SST anomalies 30 years later and repeating this each year for the term of 1880 to 2009. We can prepare the “Running Change (31-Year) In North Atlantic SST Anomalies” using the same simple method. Those two datasets (based on global and North Atlantic SST anomalies) are shown in Figure 11. The “Running Change (31-Year) In North Atlantic SST Anomalies” dataset appears simply to be an exaggerated version of the “Running Change (31-Year) In Global SST Anomalies”.

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Figure 11

And comparing the “Running Change (31-Year) In North Atlantic SST Anomalies” to the NINO3.4 SST anomalies smoothed with a 31-year filter, Figure 12, shows that the NINO3.4 SST anomalies lead the multidecadal changes in North Atlantic SST anomalies.

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Figure 12

Putting Figures 11 and 12 into other words, the AMO appears to simply be the North Atlantic exaggerating the cumulative effects of the variations in the frequency and magnitude of ENSO. During epochs when El Niño events dominate, the SST anomalies of the North Atlantic rise more than the SST anomalies of the other ocean basins, and when La Niña events dominate, the North Atlantic SST anomalies drop more than the SST anomalies for the rest of the globe.

Why? The South Atlantic (not a typo) is the only ocean basin where heat is transported toward the equator (and into the North Atlantic). So warmer-than-normal surface waters in the South Atlantic created by the changes in atmospheric circulation during an El Niño should be transported northward into the North Atlantic (and vice versa for a La Niña). This effect seems to be visible in the animation of Atlantic SST anomalies from September 23, 2009 to November 3, 2010, Animation 1. (Note: By the start of the animation, September 2009, the 2009/10 El Niño was well underway.) Unfortunately, there is a seasonal component in those SST anomaly maps, and it’s difficult to determine whether the seasonal component is enhancing or inhibiting the appearance of northward migration of warm waters. Rephrased as a question, is the seasonal component in the SST anomalies creating (or detracting from) an illusion that makes it appear that the warm SST anomalies are migrating from the South Atlantic to the North Atlantic?

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Animation 1

The northward migration of warm waters from the South Atlantic to the North Atlantic also appears to be present in the following animation of the correlation of NINO3.4 SST anomalies with Atlantic SST anomalies at time lags that vary from 0 to 12 months, Animation 2. Again the correlation maps show areas that warm (red) or cool (blue) in response to an El Niño and the positive lags represent the number of months following the peak of the El Niño. Three month average NINO3.4 and Atlantic SST anomalies were used.

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Animation 2

Another reason the North Atlantic exaggerates the effects of ENSO is because the North Atlantic is open to the Arctic Ocean. El Niño events cause increases in seasonal Arctic sea ice melt during the following summer. It would also seem logical that El Niño events would increase the seasonal Greenland glacial melt as well. Refer again to Animation 2. Starting around the 9-month lag, positive correlations (warm waters during an El Niño) migrate south from the southern tip of Greenland, and starting around the 4-month lag from the Davis Strait, along the west coast of Greenland. Is that from glacial ice melt in Greenland and Arctic sea ice melt, with the melt caused by the El Niño? They’re correlated with NINO3.4 SST anomalies.

Regardless of the cause, in the North Atlantic, there are significant positive correlations with NINO3.4 SST anomalies 12 months after the peak of the ENSO event, and for at least 6 months after the ENSO event has ended. And this means that the El Niño event is responsible for the persistent warming (or cooling for a La Niña event) in the North Atlantic.

MYTH: EL NIÑO EVENTS ARE COUNTERACTED BY LA NIÑA EVENTS

One of the common misunderstandings about ENSO is that La Niña events are assumed to balance out the effects of El Niño events.

The fact: correlations between NINO3.4 SST anomalies and global sea surface temperatures are basically the same for El Niño and La Niña events; that is, El Niño and La Niña events have similar effects on regional sea surface temperatures; they are simply the opposite sign.

But that does not mean the effects of the El Niño event will be counteracted by the La Niña event that follows. First problem with that logic: La Niña events do not follow every El Niño event. That’s plainly visible in instrument temperature record. Refer to the Oceanic Niño Index (ONI) (ERSST.v3b) table. Also an El Niño event may be followed by a La Niña event that lasts for up to three years. And sometimes there are multiyear El Niño events, like the 1986/87/88 El Niño.

The easiest way the show that La Niña events do not counteract El Niño events is by creating a running total of annual NINO3.4 SST anomalies. If La Niña events counteracted El Niño events, a Running Total would return to zero with each El Niño-La Niña cycle. Refer to the Wikipedia webpage on Running total. The running total of NINO3.4 SST anomalies (to paraphrase the Wikipedia description) is the summation of NINO3.4 SST anomalies which is updated each year when the value of a new annual NINO3.4 SST anomaly is added to the sequence, simply by adding the annual value of the NINO3.4 SST anomaly to the running total each year. I’ve scaled the NINO3.4 SST anomalies by a factor of 0.06 before calculating the running total for the comparison graph in Figure 13.

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Figure 13

And what the Running Total shows is that El Niño and La Niña events do not tend to cancel out one another. There are periods (from 1910s to the 1940s and from the mid 1970s to present) when El Niño events dominated, and a period when La Niña events dominated (from the mid-1940s to the mid-1970s). And with the scaling factor, the running total does a good job of reproducing the global SST anomaly curve. Global temperature anomalies can also be reproduced using monthly NINO3.4 SST anomaly data. This was illustrated and discussed in detail in the post Reproducing Global Temperature Anomalies With Natural Forcings.

UPDATE– The original paragraph has been crossed out and the updated version follows.

Figure 13 implies that 6% of each El Niño and La Niña event remains within the global surface temperature record and that it is this cumulative effect of ENSO events that raises and lowers global Sea Surface Temperatures.

Figure 13 appears to imply that 6% of each El Niño and La Niña event remains within the global surface temperature record and that it is this cumulative effect of ENSO events that raises and lowers global Sea Surface Temperatures. Let’s examine that later in the post.

So that’s two ways, using sea surface temperature data, that the multidecadal rises and falls in global sea surface temperatures appear to be responses to the frequency and magnitude of El Niño and La Niña events.

HOW COULD THE OCEANS WARM WITHOUT AN INCREASE IN RADIATIVE FORCING?

Someone is bound to ask, how could the global Sea Surface Temperatures rise over multidecadal periods without an increase in radiative forcing? The answer is rather simple, but it requires a basic understanding of why and how, outside of the central and eastern tropical Pacific, sea surface temperatures rise and fall in response to ENSO events. Refer back to Figure 8, which includes the correlation maps from Trenberth et al (2002), and note that there are areas of the global oceans outside of the central and eastern equatorial Pacific that warm and cool in response to ENSO events. During an El Niño event, the warming outside of the eastern and central equatorial Pacific is greater than the cooling, and global SST anomalies rise.

But why do global SST anomalies rise outside of the eastern and central tropical Pacific during an El Niño event?

There are changes in atmospheric circulation associated with ENSO events, and these changes in atmospheric circulation cause changes in processes that impact surface temperatures. Let’s look at the tropical North Atlantic as an example. Tropical North Atlantic SST anomalies rise during an El Niño event because the trade winds there weaken and there is less evaporation. This is discussed in detail in the paper Wang (2005), “ENSO, Atlantic Climate Variability, And The Walker And Hadley Circulation.” Wang (2005) link:

http://www.aoml.noaa.gov/phod/docs/Wang_Hadley_Camera.pdf

Reworded, the reduction in trade wind strength due to the El Niño causes less evaporation, and since there is less evaporation, tropical North Atlantic sea surface temperatures rise. The weaker trade winds also draw less cool water from below the surface. So there are two effects that cause the Sea Surface Temperatures of the tropical North Atlantic to rise during El Niño events. And, of course, the opposite would hold true during La Niña events.

Again for example, during multidecadal periods when El Niño events dominate, the tropical North Atlantic trade winds would be on average weaker than “normal”, there would be less evaporation, less cool subsurface waters would be drawn to the surface, and tropical North Atlantic sea surface temperatures would rise. The western currents of the North Atlantic gyre would spin the warmer water northward. Some of the warm water would be subducted by Atlantic Meridional Overturning Circulation/Thermohaline Circulation, some would be carried by ocean currents into the Arctic Ocean where it would melt sea ice, and the remainder would be spun southward by the North Atlantic gyre toward the tropics so it could be warmed more by the effects of the slower-than-normal trade winds. Similar processes in the tropical South Atlantic also contribute to the warming of the North Atlantic, since ocean currents carry the warmer-than-normal surface waters from the South Atlantic to the North Atlantic.

Refer again to the correlation maps in Figure 8. Those are snapshots of monthly SST anomaly correlations. If those patterns were to persist for three decades due to a prolonged low-intensity El Niño event, global SST anomalies would rise. And the opposite would hold true for a prolonged La Niña event.

Let’s look at the average NINO3.4 SST anomalies during the three epochs of 1910 to 1944, 1945 to 1975, and 1976 to 2009. As shown in Figure 14, the average NINO3.4 SST anomalies were approximately +0.15 deg C from 1910 to 1944; then from 1945 to 1975, they were approximately -0.06 deg C; and from 1976 to 2009, the NINO3.4 SST anomalies were approximately 0.2 deg C. This is a very simple way to show that El Niño events dominated the two periods from 1910 to 1945 and from 1976 to 2009 and that La Niña events dominated from 1945 to 1975.

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Figure 14

Figure 15 compares annual Global SST anomalies to the average NINO3.4 SST anomalies for those three periods. Global SST anomalies rose from 1910 to 1944 because El Niño events dominated, and because the SST anomaly patterns (caused by the changes in atmospheric circulation) associated with El Niño events persisted. Because La Niña events dominated from 1945 to 1975, and because the SST anomaly patterns associated with La Niña events persisted, Global SST anomalies dropped. And Global SST anomalies rose again from 1976 to 2009 because El Niño events dominated, and because the SST anomaly patterns associated with El Niño events persisted.

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Figure 15

The fact that the rise in global Sea Surface Temperature anomalies since the early 1900s can be recreated without an increase in radiative forcing implies a number of things, one being that anthropogenic greenhouse gases do nothing more than cause a little more evaporation from the global oceans.

UPDATE – The following discussion (What Does The Running Total Imply?) has been added.

WHAT DOES THE RUNNING TOTAL IMPLY?

Earlier I wrote, Figure 13 [which was the comparison graph of global SST anomalies versus the running total of scaled NINO3.4 SST anomalies] appears to imply that 6% of each El Niño and La Niña event remains within the global surface temperature record and that it is this cumulative effect of ENSO events that raises and lowers global Sea Surface Temperatures. But is that really the case?

Keep in mind that the running total is a simple way to show the rise in global SST anomalies can be explained by the oceans integrating the effects of ENSO. It does not, of course, explain or encompass many interrelated ENSO-induced processes taking place in each of the ocean basins. Each El Niño and La Niña event is different and the global SST anomalies responses to them are different. For example, the South Atlantic SST anomalies remained relatively flat for almost 20 years, but then there was an unusual warming Of The South Atlantic during 2009/2010. Why? I have not found a paper that explains why South Atlantic SST anomalies can and do remain flat, let alone why there was the unusual rise. In this post, the gif animation of NINO3.4 SST anomaly correlation with North Atlantic SST anomalies, Animation 2, showed that the response of the North Atlantic can persist far longer than the El Niño or La Niña, but if I understand correctly, this type of analysis will emphasize the stronger events. What happens during lesser ENSO events? And there’s the East Indian and West Pacific Ocean. In January 1999, I began illustrating and discussing how the East Indian and West Pacific Oceans (60S-65N, 80E-180 or about 25% of the global ocean surface area) can and does warm in response to El Niño AND La Niña events. The first posts on this cumulative effect were Can El Nino Events Explain All of the Global Warming Since 1976? – Part 1, and Can El Nino Events Explain All of the Global Warming Since 1976? – Part 2. And the most recent post was La Niña Is Not The Opposite Of El Niño – The Videos. The Eastern Pacific Ocean is, of course, dominated by the ENSO signal along the equator. However, because of the North and South Pacific gyres, the East Pacific also influences and is influenced by the West Pacific, which can warm during El Niño and La Niña events. And there’s the Indian Ocean with its own internal variability, represented in part by the Indian Ocean Dipole (IOD). The decadal variability of the IOD has been found to enhance and suppress ENSO, and, one would assume, vice versa.

HOW MUCH OF THE RISE IN GLOBAL TEMPERATURES OVER THE 20TH CENTURY COULD BE EXPLAINED BY THE GLOBAL OCEANS INTEGRATING ENSO?

As shown in Figure 13 and as discussed in detail in the post Reproducing Global Temperature Anomalies With Natural Forcings, virtually all of the rise in global surface temperatures from the early 1900s to present times can be reproduced using NINO3.4 SST anomaly data. The scaled running total of NINO3.4 SST anomalies establishes the base curve and would represent the integration of ENSO outside of the eastern and central equatorial Pacific. Scaled NINO3.4 SST anomalies are overlaid on that curve to represent the direct effects of ENSO on the eastern and central equatorial Pacific. Add to that scaled monthly sunspot data to introduce the 0.1 deg C variations is surface temperature resulting from the solar cycle and add scaled monthly Stratospheric Aerosol Optical Depth data for dips and rebounds due to volcanic eruptions, and global surface temperature anomalies can be reproduced quite well. Refer to Figure 16, which is Figure 8 from the post Reproducing Global Temperature Anomalies With Natural Forcings.

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Figure 16

Basically, that was the entire point of this post. One of the mainstays of the anthropogenic global warming hypothesis is that there are no natural factors that could explain all of the global warming since 1975. But this post has shown that ALL of the rise in global sea surface temperatures since 1900 can be explained by the oceans integrating the effects of ENSO.

CLOSING

This post presented graphs and animations that showed Global SST anomalies rose and fell over the past 100 years in response to the dominant ENSO phase; that is, Global SST anomalies rose over multidecadal periods when and because El Niño events prevailed and they fell over multidecadal periods when and because La Niña events dominated. Basically, it showed that the oceans outside of the central and eastern tropical Pacific integrate the impacts of ENSO, and that it would only require the oceans to accumulate 6% of the annual ENSO signal (Figure13) in order to explain most of the rise in global SST anomalies since 1910. And the post provided an initial explanation as to why and how the global oceans could rise and fall without additional radiative forcings. It also showed that the Atlantic Multidecadal Oscillation (AMO) appears to be an exaggerated response to the dominant multidecadal phase of ENSO. Hopefully, it also dispelled the incorrect assumption that La Niña events tend to cancel out El Niño events.

SOURCES

The HADISST data used in this post is available through the KNMI Climate Explorer:

http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere

The maps used in the video are available from the GISS map-making webpage:

http://data.giss.nasa.gov/gistemp/maps/

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DirkH

Re Fig 10: assume that the 2 warming periods are each 22 years long; and contrast it with what Piers Corbyn says here in a comment:
http://climaterealists.com/index.php?id=6658
“Indeed we (eg WeatherAction) know the Earth’s weather and climate is controlled by solar activity specifically the magnetic – ie 22yr cycle […]”
Just a coincidence?

latitude

Bob, thanks a million
and that La Niña events dominated from 1945 to 1975.
=========================================
Exactly when the coming of the next ice age was predicted.

R. de Haan

Great job.
Any chance you can turn this into scientific paper for peer review?

DirkH says: “Re Fig 10: assume that the 2 warming periods are each 22 years long; and contrast it with what Piers Corbyn says here in a comment…”
Figure 10 shows trends for two periods: from 1916 to 1946 and from 1974 to 2004. Both are spans of 31 years. I’m not sure where you arrive at “2 warming periods are each 22 years long.”
Regards

sky

Physical systems with capacitance components can accumulate/discharge energy or other extensive variables in a manner that resembles exponentially-faded integration in the time domain. But they cannot integrate intensive variables such as temperature or their anomalies. Trenberth’s ENSO3.4 is a temperature index that is NOT centered on its long term-average. Its average obtained over any shorter interval thus is dependent upon the offset inherent in the base period. That a certain similarity is visually apparent between such an ad hoc metric and the putative “global temperature” tells us virtually nothing physical about what drives the latter. It’s simply a phenomenological curiosity.

R. de Haan says: “Any chance you can turn this into scientific paper for peer review?”
Writing a scientific paper would be work. I’m retired from work–a four-letter word. I blog to entertain myself. But feel free to write a paper about the topic. Just remember where you saw this first.

SS

So El Nino (directly) & La Nina (indirectly) both cause warming essentially.
So, hypothetically, how would it be possible for global cooling start to start and last for a similar time period (~130 years)?
Seems like there is not mechanism to cool the earth then? ENSO apparently doesn’t…

sky says: “Trenberth’s ENSO3.4 is a temperature index that is NOT centered on its long term-average.”
Agreed. Trenberth’s NINO3.4 SST anomaly data has base years of 1950 to 1979, because, as Trenberth writes in “The Definition of El Niño” (1997), “it is representative of the record this century.”
ftp://grads.iges.org/pub/kjin/BADGER/1021/Trenberth-1997-BAMS(ElNino.Define).pdf
The full quote: “Figure 1 shows the 5-month running mean SST time series for the Niño 3 and 3.4 regions relative to a base period climatology of 1950–79 given in Table 1. The base period can make a difference. This standard 30-year base period is chosen as it is representative of the record this century, whereas the period after 1979 has been biased warm and dominated by El Niño events (Trenberth and Hoar 1996a).”
And those base years, which Trenberth describes as, “representative of the record this century,” for the NINO3.4 SST anomaly data, establishes the right ratio of positive to negative NINO3.4 SST anomalies that permit the scaled running total to portray the global SST anomalies.
You wrote, “Physical systems with capacitance components can accumulate/discharge energy or other extensive variables in a manner that resembles exponentially-faded integration in the time domain. But they cannot integrate intensive variables such as temperature or their anomalies.”
Newman et al (2004) appears to contradict your opinion. Link:
http://courses.washington.edu/pcc587/readings/newman2003.pdf
They write. “Deep oceanic mixed layer temperature anomalies from one winter become decoupled from the surface during summer and then ‘reemerge’ through entrainment into the mixed layer as it deepens the following winter (Alexander et al. 1999). Thus, over the course of years, at least during winter and spring, the North Pacific integrates the effects of ENSO.”
Regardless of whether or not the oceans integrate ENSO and portray it in sea surface temperature anomalies, the West Pacific and East Indian Oceans warm in response to both El Nino and La Nina events, so there is a cumulative response to ENSO by a major portion of the global oceans. This then could be the ultimate cause of the apparent integration.
Regards

jorgekafkazar

“…Tropical North Atlantic SST anomalies rise during an El Niño event because the trade winds there weaken and there is less evaporation….”
But why do the trade winds weaken?

SS says: “So El Nino (directly) & La Nina (indirectly) both cause warming essentially.”
The warming during a La Nina is direct for the East Indian and West Pacific Oceans. During a La Nina, “leftover” warm water from the El Nino is pushed to the west and carried to the higher latitudes by the western boundary currents. And some works its way into the Indonesian Throughflow and on into the East Indian Ocean. Also, during the La Nina, the strengthened trade winds shift cloud cover to the west, allowing more downward shortwave radiation the warm the tropical Pacific ocean, and like the “leftover” warm water, it is carried to the Kuroshio Extension, the SPCZ, and the eastern tropical Indian Ocean.
You wrote, “So, hypothetically, how would it be possible for global cooling start to start and last for a similar time period (~130 years)?”
The East Indian and West Pacific Oceans warmed to the combination of specific El Nino and La Nina events, not all. The effect is apparent with the 1986/87/88 El Nino combined with the 1988/89 La Nina and with the 1997/98 El Nino combined with the 1998/99/00/01 La Nina. So the combined El Nino/La Nina warming there requires significant El Nino events followed by significant La Nina events. To answer your hypothetical question, if there was a period with minor El Ninos and when La Ninas dominated due to a higher frequency and magnitude, global SST anomalies should drop. The global effects of the La Nina events would outweigh any warming taking place in the West Pacific and East Indian Oceans.
Thanks. I hadn’t addressed that point.

jorgekafkazar says: “But why do the trade winds weaken?”
Due to changes in Hadley and Walker Circulation associated with the relocation of tropical Pacific convection during the El Nino. That is, during the El Nino, the warm water from the West Pacific Warm Pool shifts east, bringing the convection with it. The relocation of the convection alters normal Hadley and Walker Circulation globally and one of the results is that the trade winds in the tropical North Atlantic weaken.

From this post I get the impression the climate scientists measuring the average conditions of weather at discreet time intervals and following the change in the average over time is a very limited approach seeking to identify causes and effects, when we have known for a long time the major inputs in the climate such as insolation, orbital characteristics, evaporation, condensation and etc.. Perhaps a more useful approach is the one taken by Bob and looking at the climate as the integral of the eather would provide a more useful model of the climate.

DeNihilst

Jeez Bob, if this is how you entertain yerself in retirement, you musta been a hell of a worker! Just absolutely one of the most fascinating posts i have ever seen. Kudos to you!

Ninderthana

Bob,
31 years, 31 years……? Where have I heard that time period before…..?
This period ensures a close alignment between lunar perigee and solar/lunar syzygy
(i.e. New or Full Moon). It also involves a close agreement between the lunar perigee/syzygy and BOTH the perihelion of the Earth’s orbit and the time of passage of the Moon through one of its nodes.
It is actually a half cycle, flipping between Full and New Moon. The full cycle is 62.01371 years, and it is known to be a significant luni-solar cycle in producing enhanced gravitational force on the Earth as a result of large lunar parallaxes and close lunar distances at perigee.
7 x (lunar evectional period) + 3 x (Saros cycle) = 62.0134 years
7 x (1.131778) + 3 (18.030331) = 62.0134 years
This is the other variable that you have been missing.

DR

Bob, you said:

You wrote, “So, hypothetically, how would it be possible for global cooling start to start and last for a similar time period (~130 years)?”
The East Indian and West Pacific Oceans warmed to the combination of specific El Nino and La Nina events, not all. The effect is apparent with the 1986/87/88 El Nino combined with the 1988/89 La Nina and with the 1997/98 El Nino combined with the 1998/99/00/01 La Nina. So the combined El Nino/La Nina warming there requires significant El Nino events followed by significant La Nina events. To answer your hypothetical question, if there was a period with minor El Ninos and when La Ninas dominated due to a higher frequency and magnitude, global SST anomalies should drop. The global effects of the La Nina events would outweigh any warming taking place in the West Pacific and East Indian Oceans.
Thanks. I hadn’t addressed that point.

Where is the cause and effect? It would seem counter intuitive to say it “just happens”.

Now we’re talking!
Fantastic analysis as ever Bob. Now all we need is for Ninderthana to confirm the lunar-solar-LOD connection over a couple of centuries in his forthcoming paper and we can put a new and better theory of climate variation together.

Keith Minto

During a La Nina, “leftover” warm water from the El Nino is pushed to the west and carried to the higher latitudes by the western boundary currents. And some works its way into the Indonesian Throughflow and on into the East Indian Ocean.

Interesting, Bob, as this region being relatively shallow with close island chains, would provide some resistance to flow compared to deeper water, restricting the volume entering the eastern Indian Ocean area, also this mechanism may be reason the Indian Ocean Dipole is negative (warm) and together with La Nina, bringing welcome rain to SE Australia.

A lot to read and think about. Thanks for this cogent analysis. I could not find any flaws in logic or claims not supported by the data.

Tesla_X

“To answer your hypothetical question, if there was a period with minor El Ninos and when La Ninas dominated due to a higher frequency and magnitude, global SST anomalies should drop. The global effects of the La Nina events would outweigh any warming taking place in the West Pacific and East Indian Oceans.
Thanks. I hadn’t addressed that point.”
Bob, you are further proof that the ‘retired’ Elders among us are an under-appreciated and underutilized goldmine of both experience and insight…thank you.
Could I trouble you for a SWAG at what you think the general weather outlook for Central/Northern CA might look like over the next handful of years?
I have a few Farming neighbors here who might want to know if things are getting wetter/colder or not (and by what ~rough~ order of magnitude).
I’m also curious about things like trends in increasing amounts of cloud-cover and decreasing levels of brightness as it might relate to some of the larger solar farms going up (20-200MW) and what it might mean for, for example, for the 25 year trend in average kilowatt-hours per square meter per day (kW·h/(m2·day) hitting the ground in Fresno, CA (constant or declining?) as I know for a fact that no business model today accounts for this. Since 1996, visible brightness is off less than a percent, but in some non-visible UV bands, it is off ~6%.
As time and the solar/climactic cycles march on, natural changes ahead might end up putting a -not insignificant dent- in the harvested energy (measured in kwh/yr) of a larger 20MW PV system over a quarter century.
Bottom line is your SWAG on the above is probably more meaningful than anything NASA or other more mainstream sources could put out these days…and I’d be privileged and appreciative of any thoughts you might share on the above.
Too bad we couldn’t distill your intuition into the Solar/Farmers Almanac 2.0.
Great stuff above….thank you for sharing.

Geoff Sherrington

When looking at set after set of temperatures in many places, one of the enduring features is a hot 1914 year. If you add not 31 but 28 years again and again to that, you get the series 1914, 1942, 1970 and 1998.
If you then go back to your first graph of Annual Global SST anomalies HADISST, you will find most of the major hot years appearing in this sequence, +/- a year or so. The biggest swings from hot to cold (or vice versa) year on year also happen at about these periods of 28 years. Might your figures work better on a 28 year cycle?
It puzzles me that these hot SST years are commonly hot land temperature years as well. Whatever the mechanism, it has to be quite fast to transfer sea temperature properties to air over land so rapidly.
Do you believe that the El Nino/La Nina effect causes SST changes because of the time lag between them, or because of a to-be-postulated mechanistic effect? My intuition would say that changes in SST promoted climate like El Nino. That would leave me with a need to explain where the heat goes to and comes from in a closed system. (If the system is closed). I’l read your essay more closely now.

Stephen Wilde

Excellent work as usual, Bob, but you won’t be surprised that I’m still trying to see how your ENSO material can be worked into the climate cycling from MWP to LIA to date without some other force altering the relative strengths of El Nino and La Nina over longer timescales than the multidecadal. I would have though that absent any such additional forcing the El Nino and La Nina would indeed cancel out over enough time but as you point out they clearly do not cancel out on multidecadal timescales.
My thinking continues to be that the relative strengths must indeed be altered by variations in solar insolation to the oceans given that the oceans have such a profound effect on the temperature of the air masses above them.
The way it could work is by variations in solar activity altering the size and intensity of the polar vortexes. I have explained elswhere how that could work.
The size and intensity of the polar vortexes then has an effect on the latitudinal position of the jetstreams which then alters total cloud quantities (and reflectance) so as to alter global albedo and thereby alter solar energy input to the oceans.
Thus when more energy enters the oceans the strength of El Nino will be enhanced relative to La Nina and the effect will be cumulative over time for so long as the sun is sufficiently active with the jets sufficiently poleward. The opposite when the sun is less active.
That would produce the step like upward progression that we have seen over the past century or so in tropospheric temperatures because the sun did get more active during the period. The external forcing would become more apparent with each phase ENSO cycle. Stepping upwards during a rising solar cycle and stepping downward during a falling solar cycle.
It would also deal with the observation that from time to time such as during solar cycle 20 there was a slight cooling period despite the fact that solar activity was still high in historical terms (though 20 was a little weaker than 19 and 21). The La Nina part of the cycle would have been temporarily more than offsetting the fact that even cycle 20 was still adding energy to the oceans albeit at a lower rate than cycles 19 and 21.

Phil's Dad

What predictive capability does this explanation yield?

William

The AGW crowd have repeated their mantra a sufficient number of times to create a paradigm (a belief among the general population such as a portion of the news media and a portion of the general public). The paradigm has been accepted as fact by the believers such that those who question the mantra can be labeled by the believers as skeptics or deniers. (idiots or bad guys)
Part of the preparer work (propaganda) for the AGW movement was to eliminate past cyclic changes from the paleoclimatic record. If planetary temperature increased and decreased in the past there must be some unexplained cyclic forcing function. For example the sun. Few people have read paleo-climatology text books, are aware of the glacial/interglacial cycle, are aware that the paleoclimatic record has unequivocal evidence of cyclic gradual changes and cyclic abrupt climate events, are aware that the abrupt climate change events such as the abrupt termination of the last 22 interglacial periods lacks an explanation, are aware that all of the past interglacial periods are short (roughly 12,000 years) and that they have ended abruptly, and so on. The complete climate change scientific facts are not part of the public discussion. (The observations are filtered and manipulated to support an agenda.)
The sun was at its highest activity level in 10,000 years during the last 40 years of the 2oth century. It appears that most of the 20th century warming has due to changes in the solar cycle. (There are papers noting a decade by decade reduction in planetary cloud cover during the warming period. There are also papers explaining the mechanisms by which specific solar cycle changes could reduce planetary cloud cover and there is observational evidence that shows sub cycles of warming and cooling with the sub cycles correlating to the specific solar mechanisms during the 20 year period at which time there was satellite measurement of planetary cloud cover. (There is more than one solar mechanism. i.e. The theory/hypothesis to explain the 20th century warming was due to solar cycle changes not atmospheric CO2 increases is advanced and logically supported by the observations and the paleo record. There is a cycle in the past of warming and cooling with correlation of cosmogenic isotopes. There is smoking gun evidence that it left at the past cyclic climate changes gradual and abrupt that points to the sun. The question is not if the sun is responsible for the observations but rather how.)
Solar cycle 24 appears to be an interruption to the solar cycle. If let say 0.4C of the 0.5C of the 20th century warming was due to the high solar cycle, then we can expect a -0.8C change (0.4C high forcing is removed and -0.4C due to the interrupt in solar cycle 24.)
The paleoclimatic record was cycles of 1470 years (Bond cycle. Gerald Bond has able to tracked 30 cycles through the Holocene interglacial and into the glacial period. Bond found cosmogenic isotope changes at each of the climate change events which it is accepted are due solar magnetic cycle changes but was not able to provide at the time of publishing of his results (2000) an explanation as to mechanism.) of warming and cooling (roughly 0.8C warming and cooling followed occasionally by (with a super cycle of 2400 years and 8000 years) of abrupt cooling events of 2C to 4C. The complete set of cycles appears to be solar driven however there are different solar mechanisms involved which explains the differences in the cycle times and the differences in the amount of climate change for the different solar events. What happened cyclically before, happened for a reason. There was a physical cause.
The AGW supporters are rightly concerned about climate change, however, the problem is abrupt cooling (the -2C to -4C events) not gradual warming. It will be interesting to watch how the paradigm will change, if there is observed gradual cooling (0.4C to 0.8C).
Atmospheric CO2 increases are positive to the biosphere not negative. Plants eat CO2. It is odd (surreal) that those who purport to support environmental protection have aligned with the AGW paradigm and the corruption group that is now pushing it. The entire scientific premise is incorrect.
Weather change observations precede climate change.
http://i53.tinypic.com/14j50et.jpg
http://www.osdpd.noaa.gov/data/sst/anomaly/2010/anomnight.11.18.2010.gif
http://www.accuweather.com/video/432724657001/extreme-winter-travel-conditions-thanksgiving-week.asp
http://www.accuweather.com/video/681364180001/the-cold-train-rides-roughshod-over-europe.asp?channel=vbbastaj

Michael

Michael says:
Your comment is awaiting moderation.
November 19, 2010 at 8:25 pm
Now there’s art, and then there’s blog smart.
Oh come on, can’t you give me some credit for this quote?

Steve Schaper

Ninderthana, but are the tidal changes powerful enough to produce the effect, and how do they produce the effect? The co-incidence is interesting, but for an hypothesis you need to show -how- that can work.

the oceans outside of the central and eastern tropical Pacific integrate the impacts of ENSO, and that it would only require the oceans to accumulate 6% of the annual ENSO signal (Figure13) in order to explain most of the rise in global SST anomalies since 1910.
Brilliant, just brilliant!
Thanks Dr. Tisdale
(see http://www.oarval.org/ClimateChange.htm and http://www.oarval.org/meteorologFL.htm)
(in Spanish at http://www.oarval.org/CambioClima.htm and http://www.oarval.org/meteorolog.htm)

William,
Fine post, very thought-provoking. The Bond event troughs are truly scary.
The real concern is global freezing, not beneficial warming.

Michael

Smokey says: wrote
November 19, 2010 at 9:03 pm
William,
“Fine post, very thought-provoking. The Bond event troughs are truly scary.
The real concern is global freezing, not beneficial warming.”
Now that’s scary.

John F. Hultquist

The date in the middle of the large paragraph under the heading
WHAT DOES THE RUNNING TOTAL IMPLY?
in this line: . . . Ocean. In January 1999, I began illustrating . . .
should be 2009, not 1999

Jimmy Haigh

Bob Tisdale says:
November 19, 2010 at 4:49 pm
R. de Haan says: “Any chance you can turn this into scientific paper for peer review?”
“Writing a scientific paper would be work. I’m retired from work–a four-letter word. I blog to entertain myself. But feel free to write a paper about the topic. Just remember where you saw this first.”
Excellent post Bob. I would think there might be a few people here interested in writing a joint paper with you. If not “Tisdale and de Haan, 2010” I’m thinking “Tisdale and Eschenbach”? Or “Tisdale and Maue”?

John F. Hultquist says: Thanks for finding the typo. Yes, it should read January 2009. I’ve corrected it on the original at my blog.

Phil’s Dad says: “What predictive capability does this explanation yield?”
Little. It would require the ability for climate models to predict the frequency and strengths of future ENSO events, and none have displayed any ability to do that in the short term, let alone long term. Will the 60-year cycle repeat? Don’t know.

Geoff Sherrington says: “Might your figures work better on a 28 year cycle?”
Thanks for noting the 28-year peaks. I’ve looked at other periods based on 10year spans but not 28 years.
You wrote, “It puzzles me that these hot SST years are commonly hot land temperature years as well. Whatever the mechanism, it has to be quite fast to transfer sea temperature properties to air over land so rapidly.”
Keep in mind that the land surface temperatures are also changing due to changes in atmospheric circulation, not due to a direct transfer of heat. It takes well less than a year for the changes in atmospheric circulation to migrate their way east and circle the globe. The Trenberth et al paper linked in the post does a good job of explaining it, once one comes to term with all of the scientific jargon.
You asked, “Do you believe that the El Nino/La Nina effect causes SST changes because of the time lag between them, or because of a to-be-postulated mechanistic effect?”
There are known changes in atmospheric processes that cause the SST anomalies outside of the tropical Pacific to vary in response to the ENSO event.

Tesla_X says: Sorry. I don’t make predictions. Maybe Anthony can help along those lines.

Keith Minto says: “Interesting, Bob, as this region being relatively shallow with close island chains, would provide some resistance to flow compared to deeper water, restricting the volume entering the eastern Indian Ocean area…”
The Indo-Australian landmass is why the warm water pools in the west Pacific. The Pacific trade winds can’t push the warm surface waters any farther. It pools there and all the convection associated with it establishes rainfall patterns around the globe. But some of the warm water squeeks through.

There is a natural process going on in the Pacific, with all necessary attributes to generate long term oscillations.
http://www.vukcevic.talktalk.net/PDOc.htm
But of course, there are many other factors involved acting on much shorter scale.

HelmutU

Hello Bob,
is it possible toget Your post as a pdf-file?
regards

stephen richards

Phil’s Dad says:
November 19, 2010 at 8:22 pm
What predictive capability does this explanation yield?
Predictions are for Gypsy Rose Lee. No-one can see the future and particularly the future of a non-linear system as vast as the climate.
Incidently BOB, I’m getting really tired of saying this but WELL DONE. As someone has already said you must have been one hell of a worker!!

tallbloke says:
November 19, 2010 at 7:40 pm
…….Now all we need is for Ninderthana to confirm the lunar-solar-LOD connection…
Hi Rog
Here is my take on the planet’s wobble-temperature possible relationship.
I made an attempt to separate, what one could consider to be natural oscillations, from an apparent man-made input, result is shown in this graph:
http://www.vukcevic.talktalk.net/CETng.htm
GP ‘Global precursor’ (green line, based on the JPL ephemeredes, kind of a ‘mini Milankovic’ effect ) shows a promising result. If large volcanic eruptions (Katla 1755, then in the early 1800’s Mayon and Tambora) are taken into account, than GP ‘proxy’ has a good track with the CETs for nearly 350 years span.
Period of significant divergence starts in the 1950s, when various man made influences (CO2, UHI, CFCs etc) may have come into play.
For time being GP is just an interesting correlation, energy is miniscule, while NAP has all the necessary attributes to do that, but again indirectly via N. Atlantic currents.
However, I might work out something in the future.

anna v

A reminder that Tsonis et all using a neural net model to simulate chaos and the behavior of ocean currents, give predictions for the next century.

HelmutU says: “is it possible toget Your post as a pdf-file?”
Sorry. I only have Adobe reader.

Henry Galt

tallbloke says:
November 19, 2010 at 7:40 pm
Now we’re talking!
“”
Between Bob, Ian and Erl Hap there is a sufficient, coherent supply of silver bullets to kill the CAGW vampire(s)

Henry Galt

^sorry Erl^
Dear Mr Happ, please forgive my lack of Ps and Qs.

Andres Valencia says: “Thanks Dr. Tisdale”
You’re welcome, but there’s no Dr. before my last name, just Bob.

Cirrius Man

Great effort Bob!
This is possibly the most profound piece of climate analysis ever posted on any blog!
Those who support a solar-climate link will of course now concentrate on how the solar cycle might influence the El Nino/ La Nina magnitudes and frequencies.
Now, how to get the IPCC models adjusted ? Perhaps send a copy to Gavin over at Real (CO2) Climate ?

Hi Vuk,
interesting graph.
“Period of significant divergence starts in the 1950s, when various man made influences (CO2, UHI, CFCs etc) may have come into play.”
Or non-linearity due to high OHC. Or diddling of the record. Or….
“For time being GP is just an interesting correlation, energy is miniscule, while NAP has all the necessary attributes to do that, but again indirectly via N. Atlantic currents.”
After my chat with some experts on the geomagnetic field, I think there is still a lot we don’t know about LOD and the global electromagnetic circuit. Ocean circulation still holds secrets.

Cirrius Man says: “Now, how to get the IPCC models adjusted ? Perhaps send a copy to Gavin over at Real (CO2) Climate ?”
The GISS Model E does not model the oceans and therefore has no ENSO capabilites.

Hi Bob
I have recorded post as a .pdf file, it is Ok except for the animation (only work via link). It is too big to upload on my website, but I could email it to you.

lgl

Great job Bob,
but I have a problem with fig. 13. The flatness between 1940 and 1980. Did you use the +0.2 scaling like in fig. 7 ? Could you please link to the numbers behind fig. 9?

Stephen Wilde

“Cirrius Man says:
November 20, 2010 at 3:32 am
Those who support a solar-climate link will of course now concentrate on how the solar cycle might influence the El Nino/ La Nina magnitudes and frequencies. ”
Already done Cirrius, see here:
http://climaterealists.com/index.php?id=6645&linkbox=true&position=7
“How The Sun Could Control Earth’s Temperature”
Just shift the clouds latitudinally to change solar input to the oceans and thereby skew the relative intensities of El Nino and La Nina.