Guest post by Bob Tisdale
This is the second part in a series of posts about El Niño-Southern Oscillation (ENSO). They address many of the myths and misunderstandings about the tropical Pacific processes that herald themselves during El Niño and La Niña events. In them, I’m simply reproducing chapters from my recently published ebook Who Turned on the Heat?
For almost 4 years, my presentations about the long-term effects of El Niño and La Niña events indicate the global oceans over the past 30+ years have warmed naturally. The long-term impacts of El Niño and La Niña are blatantly obvious. Proponents of anthropogenic global warming apparently have difficulty comprehending that so they use misinformation to try to contradict what’s plainly visible. Many of the myths they’ve created are failed attempts to neutralize strong El Niño and La Niña events—to redirect the observable causes of the warming over the past 3 decades from natural factors to manmade greenhouse gases.
The following discussion is from Chapter 7.3 A New Myth – ENSO Balances Out to Zero over the Long Term.
***
A new myth about ENSO recently appeared in posts at the website SkepticalScience. This year one author there has been writing something to the effect of, El Niño and La Niña events balance out to zero over the long term. That’s nonsense, plain and simple nonsense. There are a number of ways to show the errors with this myth. The best way is to create a running total of NINO3.4 sea surface temperature anomalies.
Wikipedia provides an easy-to-understand explanation of a Running Total:
A running total is the summation of a sequence of numbers which is updated each time a new number is added to the sequence, simply by adding the value of the new number to the running total. Another term for it is partial sum.
The purposes of a running total are twofold. First, it allows the total to be stated at any point in time without having to sum the entire sequence each time. Second, it can save having to record the sequence itself, if the particular numbers are not individually important.
If, over the long term, El Niño and La Niña events balanced out to zero, then a running total of NINO3.4 sea surface temperature anomalies would equal zero. Does it? Refer to Figure 7-10.
El Niño and La Niña events obviously have NOT balanced out to zero over the past 30+ years. That curve of the running total of NINO3.4 data looks surprisingly similar to the global sea surface temperature anomaly curve. It’s really difficult to miss the very obvious increase.
I’ve actually had someone reply in a blog comment that 30 years was not long enough. I then provided a running total of NINO3.4 sea surface temperature anomalies starting in 1900. That early start year is pushing the boundaries when it comes to equatorial sea surface temperature data. The Panama Canal opened in 1914, and before then, equatorial Pacific sea surface temperature data becomes increasingly sparse.
The base years for anomalies would also impact the running total, especially one that long, so we need to pick some. Trenberth (1997) The Definition of El Niño stated that 1950 to 1979 was the best base period for NINO3.4 sea surface temperature anomalies. Trenberth writes:
Figure 1 shows the five month running mean SST time series for the Niño 3 and 3.4 regions relative to a base period climatology of 1950-1979 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). Mean temperatures are higher in the Niño 3.4 region than in Niño 3 and its proximity to the Pacific warm pool and main centers of convection is the reason for the physical importance of Niño 3.4.
We’ll use 1950 to 1979 as the base period for anomalies for our NINO3.4 sea surface temperature anomalies.
Figure 7-11 is the running total of HADISST NINO3.4 sea surface temperature anomalies, starting in January 1900 and ending in May 2012. It does not return to zero. However, it really looks like the global temperature anomaly curve.
The similarity between the curve of the running total of HADISST-based NINO3.4 sea surface temperature anomalies and a global temperature anomaly curve is remarkable. Unfortunately, it only works with HADISST-based NINO3.4 data. A running total of NINO3.4 data based on the ERSST.v3b or Kaplan datasets bears no similarities to the global temperature curve. Also, it only works with the base years of 1950-1979. That is, if you were to shift the base years so that they were weighted more toward El Niño events, like the period of 1971 to 2000, you’d wind up with a long-term running-mean curve that looks completely different. That makes the curve illustrated in Figure 7-11 a curiosity. Nothing more—just a curiosity, because I can’t justify the use of the base years of 1950-1979. It should definitely make you think, though.
That running total was one of the things that sparked my interest in ENSO. I discovered that curious running-total effect in April 2008, and presented it in a post titled Is There A Cumulative ENSO Climate Forcing? (ENSO isn’t a forcing, but that’s neither here nor there.) If you were to include the effects of volcanic aerosols and solar variability, the fit becomes even better. I presented that in a post titled Reproducing Global Temperature Anomalies With Natural Variables.
Regardless, ENSO has been skewed toward El Niño in recent decades. It has been skewed toward La Niña as well—the period from the 1940s to the mid-1970s for example. This is well known. We’ve shown the “skewness” in the preceding chapter using period average sea surface temperatures for the NINO3.4 region.
The myth that “El Niño and La Niña events balance out to zero over the long term” is simply another very obvious attempt to neutralize El Niño and La Niña. It’s a comical attempt that failed.
***
The illustration from a previous chapter I was referring to above was Figure 7-7 from Chapter 7.1 Myth – ENSO Has No Trend and Cannot Contribute to Long-Term Warming.
I’ll present that chapter next. (Hmm. Just noticed a typo. In the book, the illustration is identifed as Figure 5-7. I’ve corrected it here.)
SOURCES
The sea surface temperature data for Figure 7-10 was downloaded from the NOAA NOMADS website. NOAA uses 1971-2000 as base years. The dataset used in the other graphs is HADISST. It’s available through the KNMI Climate Explorer. There I’ve used the base years of 1950-1979 per the discussion above.
THE REST OF THIS SERIES
The remainder of this series of posts will be taken from the following myths and failed arguments. They’re from Section 7 of my book Who Turned on the Heat? I may select them out of the order they’ve been presented here, and I’ll try to remember to include links to the other posts in these lists as the new posts are published.
ALREADY PUBLISHED
1. El Niño-Southern Oscillation Myth 1: El Niño and La Niña Events are Cyclical. Refer also to the cross post at WattsUpWithThat for comments.
UPCOMING
Myth – ENSO Has No Trend and Cannot Contribute to Long-Term Warming
Myth – The Effects of La Niña Events on Global Surface Temperatures Oppose those of El Niño Events
Failed Argument – El Niño Events Don’t Create Heat
Myth – El Niño Events Dominated the Recent Warming Period Because of Greenhouse Gases
Myth – ENSO Only Adds Noise to the Instrument Temperature Record and We Can Determine its Effects through Linear Regression Analysis, Then Remove Those Effects, Leaving the Anthropogenic Global Warming Signal
Myth – The Warm Water Available for El Niño Events Can Only be Explained by Anthropogenic Greenhouse Gas Forcing
Myth – The Frequency and Strength of El Niño and La Niña Events are Dictated by the Pacific Decadal Oscillation
And I’ll include a few of the failed arguments that have been presented in defense of anthropogenic warming of the global oceans.
Failed Argument – The East Indian-West Pacific and East Pacific Sea Surface Temperature Datasets are Inversely Related. That Is, There’s a Seesaw Effect. One Warms, the Other Cools. They Counteract One Another.
INTERESTED IN LEARNING MORE ABOUT EL NIÑO AND LA NIÑA AND THEIR LONG-TERM EFFECTS ON GLOBAL SEA SURFACE TEMPERATURES?
Why should you be interested? Sea surface temperature records indicate El Niño and La Niña events are responsible for the warming of global sea surface temperature anomalies over the past 30 years, not manmade greenhouse gases. I’ve searched sea surface temperature records for more than 4 years, and I can find no evidence of an anthropogenic greenhouse gas signal. That is, the warming of the global oceans has been caused by Mother Nature, not anthropogenic greenhouse gases.
I’ve recently published my e-book (pdf) about the phenomena called El Niño and La Niña. It’s titled Who Turned on the Heat? with the subtitle The Unsuspected Global Warming Culprit, El Niño Southern Oscillation. It is intended for persons (with or without technical backgrounds) interested in learning about El Niño and La Niña events and in understanding the natural causes of the warming of our global oceans for the past 30 years. Because land surface air temperatures simply exaggerate the natural warming of the global oceans over annual and multidecadal time periods, the vast majority of the warming taking place on land is natural as well. The book is the product of years of research of the satellite-era sea surface temperature data that’s available to the public via the internet. It presents how the data accounts for its warming—and there are no indications the warming was caused by manmade greenhouse gases. None at all.
Who Turned on the Heat?was introduced in the blog post Everything You Every Wanted to Know about El Niño and La Niña… …Well Just about Everything. The Updated Free Preview includes the Table of Contents; the Introduction; the beginning of Section 1, with the cartoon-like illustrations; the discussion About the Cover; and the Closing. The book was updated recently to correct a few typos.
Please buy a copy. (Credit/Debit Card through PayPal. You do NOT need to open a PayPal account. Simply scroll down past where they ask you to open one.). It’s only US$8.00.
VIDEOS
For those who’d like a more detailed preview of Who Turned on the Heat? see Part 1 and Part 2 of the video series The Natural Warming of the Global Oceans. Part 1 appeared in the 24-hour WattsUpWithThat TV (WUWT-TV) special in November 2012. You may also be interested in the video Dear President Obama: A Video Memo about Climate Change.
To demonstrate the fallacy of cumulative sums:
Take 100 random integers between -5 and 5.
http://www.random.org/integers/?num=100&min=-5&max=5&col=1&base=10&format=html&rnd=new
Copy series and right click Paste into excel.
Average the series, if the answer is positive, then a cumulative sums trendline will likely be positive, if the answer is negative, then you already know the trendline will likely be negative.
Perform Cumulative sums of data in column A, by entering =A1+A2+B1 in cell B2, then drag bottom right corner of cell B2 down.
Insert line chart and plot column B.
X Anomaly:
You are doing nonsense math. If you subtract the mean from each datapoint of any cumulative sum you will always end up with zero.
Bob:
Is there a mechanism by which ENSO significantly influences how much infrared radiation escapes the earth or how much sun radiation it absorbs?
Firstly, you need to put =A1 in cell B1 and =A2+B1 in cell B2. Otherwise you’re not doing your cumulative sum correctly.
Do you know what I found? The final value in cell B100 was exactly 100 times the average. If it averaged out to zero, the final value in cell B100 was zero. Otherwise, if the average was not zero, it was above or below zero, as appropriate.
This shows that a random sequence of finite length is not guaranteed to ‘average out’ to zero. The applicability to the issue at question is that even if you assume that in the long term, the ENSO cycle will have a zero effect on global temperatures, the question is how long is “long term”.
Clearly, for a range from -5 to 5, a sequence of 100 numbers is not long enough (your exercise has proven this). Clearly, 30 years of ENSO isn’t enough, either. I suspect the true answer will be in the 1000’s of years… but what do climate models assume? If they assume it’ll average out over 100 years (to make their projections accurate), then I strongly suspect that they’ll be disappointed.
Indeed the recent Rahmstorf et al (2012) paper shows the same thing – they had to take the effect of ENSO out to get climate models to match observations… clearly showing that in the climate model prediction ranges being examined in that paper, that ENSO does NOT average out to zero.
“Firstly, you need to put =A1 in cell B1 and =A2+B1 in cell B2. Otherwise you’re not doing your cumulative sum correctly.”
Thanks for the correction.
“Do you know what I found? The final value in cell B100 was exactly 100 times the average.”
Remarkable. A running mean perhaps?
“This shows that a random sequence of finite length is not guaranteed to ‘average out’ to zero.”
Yes the probability of that happening is slightly above zero.
@Kristjan Jonsson says:
December 11, 2012 at 7:51 pm
“Bob:
Is there a mechanism by which ENSO significantly influences how much infrared radiation escapes the earth or how much sun radiation it absorbs?”
I want to take a shot at this question – but in not technical terms. During repeat La Ninas, more wind piles up tropical ocean water to the west near the low latitudes. The warmer water in the west concentrates there (it does not go away it’s stored deeper down). This exposes a larger extent of cooler water from there all the way to the East. The cooler water evaporates less moisture, creating fewer clouds. Therefore, more of the sun warms the ocean. So ironically, though La Nina’s have an immediate chilling effect on the atmosphere of much of the planet, the planet stores more energy on net –in the oceans, which then can be released later.
I have given this a little more thought, To be objective, I think it is best if one gets the original data, which has not been anomalized.
eg. http://www.esrl.noaa.gov/psd/data/correlation/nina34.data
Then create anomalies based on ALL the data present. In other words the entire series is the base period. So for the above series, the average January temp is 26.51 deg C., then relate all the individual Jan months to 26.51 base, etc. to get anomalies. If there is a surplus, maybe its random? So what, maybe global warming is random…In the January example the average of the anomalies = 1.03143E-15
Which is very close to zero!
For Bob’s analysis we need sea surface data all the way back to 1870’s. If someone can find it….
Then we’ll sea what it looks like, if it matches the temp record….objectively.
I read your book and it is very well done. The graphs and animations are quite convincing. I think that you are right and this is one of the contributors to global warming. However, the end result is still handwaving, and is not significantly different from the hocky stick of Al Gore’s movie. Correlation is good evidence of a relationship but often does not prove cause or effect and certainly is not scientific proof. When is someone going to use basic physics and chemistry, at the molecular or even atomic level, to establish how the ocean waters and the atmosphere act and react within their global environment? This was accomplished, with some limitations, many years ago for the ionosphere using laboratory measurements of the basic processes.
X Anomaly says: “To demonstrate the fallacy of cumulative sums:”
The error is not the running total. The error is assuming that ENSO is represented by the ENSO index, which is what I have been fighting for 4 years. The ENSO index only represents the impacts of ENSO on the variable being measure by the ENSO index. The ENSO index does not represent the aftereffects of the processes of ENSO.
Kristjan Jonsson says: “Is there a mechanism by which ENSO significantly influences how much infrared radiation escapes the earth or how much sun radiation it absorbs?”
Outgoing longwave (infrared) radiation is dictated by the surface temperature of the Earth. ENSO directly impacts the surface temperature of the tropical Pacific by releasing warm water from below the surface of the western tropical Pacific and causing it to spread across the surface of the eastern tropical Pacific. At the conclusion of the El Nino, the warm water is redistributed to the adjoining ocean basins. ENSO also impacts surface temperatures outside of the tropical Pacific through teleconnections. ENSO can raise surface temperature in these regions in a number of ways, including, for example, slowing trade winds in the tropical North Atlantic, which results in less evaporative cooling and less upwelling. See Wang 2005:
http://www.aoml.noaa.gov/phod/docs/Wang_Hadley_Camera.pdf
In the tropical Pacific, cloud cover is coupled with sea surface temperature and trade wind strength. When the trade winds increase in strength during La Nina events, there’s less cloud cover and more downward shortwave radiation enters the oceans. See Pavlakis et al 2008:
http://www.atmos-chem-phys.net/8/5565/2008/acp-8-5565-2008.pdf
Mario Lento says: “During repeat La Ninas, more wind piles up tropical ocean water to the west near the low latitudes. The warmer water in the west concentrates there (it does not go away it’s stored deeper down). This exposes a larger extent of cooler water from there all the way to the East. The cooler water evaporates less moisture, creating fewer clouds…”
In addition, the stronger trade winds push the cloud cover farther to the west.
X Anomaly says: “I have given this a little more thought, To be objective, I think it is best if one gets the original data, which has not been anomalized. eg. http://www.esrl.noaa.gov/psd/data/correlation/nina34.data”
The data you linked is not based on the HADISST dataset used by Trenberth in your original link. The NINO3.4 data at the ESRL website is based on NOAA’s ERSST.v3b sea surface temperature data. Two different datasets. You need to stay with HADISST based NINO3.4 data, otherwise you’re confusing yourself.
X Anomaly says: “For Bob’s analysis we need sea surface data all the way back to 1870′s. If someone can find it….”
More proof that you didn’t read the post. The data sources are linked near the end.
X Anomaly says: “Then we’ll sea what it looks like, if it matches the temp record….objectively.”
Yet even more proof that you didn’t read the post.
“X Anomaly:
You are doing nonsense math. If you subtract the mean from each datapoint of any cumulative sum you will always end up with zero.”
I think it needs to be proved that a cumulative series, based on data which averages out completely, can indeed produce a significant trendline, but will still average to zero.
Take a sine wave segment that produces a camel’s hump:
http://en.wikipedia.org/wiki/File:Sine_and_Cosine.svg
From -3π to -π, cos x is the camel’s hump, and has zero average and zero trend.
From -3π to -π, sin x has a significant trend, and also has zero average.
Sin x is the cumulative sum of cos x, just with different amplitude.
I see many people here what the real base line is, one has to remember that our dear little planet tends to spend 90% of its time with a rather large ice cover. The real base line would lay some where in this cold period. Interglacials I would imagine are climate on a knife edge, where ups and downs really are dependent on the odd fluttering of a butterflies wings. The planet balanced such can be effected with very minor external inputs such as history has noted.
http://en.wikipedia.org/wiki/File:Sine_and_Cosine.svg
Bob, as you can see in the sin /cosine example, when cos x is above the zero line, sin x shots up like a rocket (sound familiar ?).
conversely, when cos x is below the zero line, sin x sinks like a boat.
I can’t make it any clearer, sorry I’m not confused.
http://en.wikipedia.org/wiki/File:Sine_and_Cosine.svg
Where cos x = obliquity, and sin x = temperature, George Kukla believes we are @ur momisugly -3π/2
I think he might be right…
I think one needs to show the physical mechanism here whereby the accumulation of the ENSO impacts actual temperatures.
I’m not sure the 1877 super-El Nino is still impacting temperatures today, but the series of successive El Ninos from 1939 to 1942, left a strong lagged response in rising temperatures throughout the mid-1940s. The string of successive La Ninas in the early 1970s left us with a deep downspike in temperatures up until 1976. These also left a signal in the AMO and participated in its longer-term up and down cycle.
I think the question is time. How long does an accumulation actually work. It has to have a limit in physical mechanism terms.
X Anomaly: You’re wasting your time. Have your read the post or have you only looked at the illustrations? All you’re doing is confirming what I wrote in the post about Figure 7-11. You’re spending all of your time to prove nothing.
The only way you can prove that Figure 7-11 is wrong is to use HADISST-based NINO3.4 anomaly data with the base years of 1950-79. If your running total is different, then we can discuss what you’ve done wrong.
Bill Illis says: “I think one needs to show the physical mechanism here whereby the accumulation of the ENSO impacts actual temperatures.”
I’ve aleady done that, extending the discussion of the East Indian-West Pacific shifts as far back to the early 1900s, but this post has nothing to do with that. This post is a simple response to a nonsensical statement made by someone at SkepticalScience who has no understanding of ENSO.
John B. Lomax says: “However, the end result is still handwaving, and is not significantly different from the hocky stick of Al Gore’s movie.”
There are significant differences. The hockey stick is based on bogus statistical manipulations of paleoclimatological data, where I’ve presented satellite-era sea surface temperature data and other supporting data for that period. Al Gore was parroting the flawed findings of others, where I’ve done my own research to illustrate the causes and impacts of ENSO residuals. I’ve earned the right to wave my hands; Al Gore has not. And I’ll continue to wave my hands.
Other than that, thanks for the kind words about my book. I’m glad you enjoyed it.
Nick Kermode Says:
“For the temperature of both to increase they BOTH need to store more energy. Enhanced GH is the only thing that can explain that.”
This is incorrect. In fact, warmer oceans mean a warmer atmosphere, not the other way around, as AGW theory has it. GHG effect cannot warm ocean because water is opaque to infrared (see absorbency spectrum of water).
Bob,
re your discussion with X Anomaly you should (re-)read this:
http://climateaudit.org/2005/08/14/gambling-runs/
“Even the simple coin-tossing model leads to surprising indeed to chocking results. They are of practical importance becaue they show that contrary to generally accepted views, the laws governing a prolonged series of individual observations will show patterns and averages far removed from those derived for a whole population…
The results are startling. According to widespread beliefs, a so-called law of averages should ensure that in a long coin-tossing game each player will be on the winning side for about half the time and that the lead will pass not infrequently from one player to the other.
(…)
These results show that intuition leads to an erroneous picture of the probable effects of chance fluctuations.”
Duster says:
December 11, 2012 at 1:30 pm
Bob Tisdale says:
December 11, 2012 at 1:04 pm
***. Paleoclimatological data is make-believe data. ***
The data is real enough. The interpretations are where the make believe begins to appear. Though when you start to look at “corrections” and “adjustments” that modern data is being subjected to, I would begin to worry about “post-normal” data processing.
But actually,
Tree ring data becomes make-believe data when used in paleo-climate reconstructions, as such data simply cannot yield a valid result, however applied. Tree rings simply are unsuitable as a proxy for past temperatures. For confirmation of this, see Jim Bouldin of RealClimate, who discusses the issues at his blog. All paleo-climate reconstructions using tree-ring data are invalid, according to Jim Bouldin of RealClimate. This is also my point of view.
El Niño and La Niña cannot net out to zero because they represent the tail end of the deep ocean conveyor that operates on time scales of hundreds of years. It is not a zero sum game.
Energy that was stored centuries ago in the deep oceans upwells to the surface during one phase and is blocked during the other. The effect on the earth’s climate that results, whether there is net warming or cooling, that is determined by what the climate was like hundreds of years ago.
So we gain an increment of temperature with every El Niño? When will it all end?