Will Global Warming Increase the Intensity of El Niño?

FIRST CLIMATE MODELS HAVE TO BE ABLE TO SIMULATE EL NIÑO AND LA NIÑA PROCESSES—CAPABILITIES THEY CONTINUE TO LACK AFTER DECADES OF MODELING EFFORTS (PERSONALLY, I DON’T THINK THE MODELERS ARE REALLY TRYING)

BBCNews published an article yesterday by Matt McGrath “Global warming will increase intensity of El Nino, scientists say.” The article includes the usual phraseology:

Now, in this new paper, published in the journal Nature, researchers give their most “robust” projections yet.

And there’s the obligatory quote from an “uninvolved” third party, who just happens to work for the same organization as the authors:

According to Dr Wenju Cai, a scientist at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), who was not involved with the study, the paper is “significant”.

Does significant mean the study will make a loud noise when we throw it into the dustbin?

You’ll likely choose to immediately dismiss the paper based on the following sentence in the BBCNews article:

Using the latest generation of climate models, they found a consistent projection for the future of ENSO.

Climate models can’t simulate the vast majority of the fundamental coupled ocean-atmosphere processes that drive El Niño and La Niña events. That is, the past (CMIP3) and current (CMIP5) generations of climate models create virtual El Niños and La Niñas that bear little resemblance to those that occur in the real Pacific Ocean.

The paper being discussed is Power et al. (2013) Robust twenty-first-century projections of El Niño and related precipitation variability. The abstract reads:

The El Niño–Southern Oscillation (ENSO) drives substantial variability in rainfall, severe weather, agricultural production, ecosystems and diseasein many parts of the world. Given that further human-forced changes in the Earth’s climate system seem inevitable, the possibility exists that the character of ENSO and its impacts might change over the coming century. Although this issue has been investigated many times during the past 20 years, there is very little consensus on future changes in ENSO, apart from an expectation that ENSO will continue to be a dominant source of year-to-year variability. Here we show that there are in fact robust projected changes in the spatial patterns of year-to-year ENSO-driven variability in both surface temperature and precipitation. These changes are evident in the two most recent generations of climate models, using four different scenarios for CO2 and other radiatively active gases. By the mid- to late twenty-first century, the projections include an intensification of both El-Niño-driven drying in the western Pacific Ocean and rainfall increases in the central and eastern equatorial Pacific. Experiments with an Atmospheric General Circulation Model reveal that robust projected changes in precipitation anomalies during El Niño years are primarily determined by a nonlinear response to surface global warming. Uncertain projected changes in the amplitude of ENSO-driven surface temperature variability have only a secondary role. Projected changes in key characteristics of ENSO are consequently much clearer than previously realized.

So the key finding is:

By the mid- to late twenty-first century, the projections include an intensification of both El-Niño-driven drying in the western Pacific Ocean and rainfall increases in the central and eastern equatorial Pacific.

According to Power et al (2013), the climate models simulate at least one portion of El Niño-Southern Oscillation (ENSO) processes properly. In order for you to understand why, during an El Niño, precipitation increases in the central and eastern tropical Pacific and decreases in the west, we need to discuss a few fundamentals. Don’t worry. There’s nothing difficult about it. Precipitation just tags along with the warm water.

ENSO BASICS 101:

Under normal conditions in the tropical Pacific, there is a trade wind-created pool of warm water in the western tropical Pacific (called the West Pacific Warm Pool). That sunlight-fueled pool of warm water can extend to depths of 300 meters and cover an area the size of Russia or twice the size of the U.S. In other words, there can be a monumental amount of sunlight-created warm water in the western tropical Pacific from time to time. Because the water there is naturally so much warmer than other locations, a lot of evaporation and precipitation takes place at the West Pacific Warm Pool.

During an El Niño, the warm water from the surface and below the surface of the western tropical Pacific floods into the central and eastern tropical Pacific and spreads across its surface. The warm water is focused primarily along the equator (brought there by a prolonged surge in the flow of the equatorial countercurrent, which travels from west to east).

Because the warm water has traveled into the central and eastern tropical Pacific during the El Niño, that causes that the evaporation, cloud cover and precipitation that is normally in the western tropical Pacific to accompany the warm water eastward.

Logically, precipitation increases in the eastern tropical Pacific and decreases in the western tropical Pacific during an El Niño. So the models, according to Power et al. (2013) appear to simulate that basic relationship.

DATA CONTRADICT MODELS

In order for there to be “an intensification of both El-Niño-driven drying in the western Pacific Ocean and rainfall increases in the central and eastern equatorial Pacific” in the future, as claimed by Power et al. (2013), El Niño events have to become stronger, or last longer, or occur more often, or a combination of the three, in their number-crunched, CO2-driven, climate model-based virtual worlds. The other possibility: there has to be a global warming-caused change in the background state of the tropical Pacific in the models.

However, Ray & Giese (2012) Historical changes in El Niño and La Niña characteristics in an ocean reanalysis found that El Niño events had not become stronger, or lasted longer, or occurred more often (among other things) since 1871. And manmade greenhouse gases are said to have caused global warming during that time period. The Ray & Giese (2012) abstract ends:

Overall, there is no evidence that there are changes in the strength, frequency, duration, location or direction of propagation of El Niño and La Niña anomalies caused by global warming during the period from 1871 to 2008.

So one wonders how climate models could simulate a future change in ENSO when there have been no changes in almost 140 years.

With respect to the background state of tropical Pacific, let’s look at the modeled and observed warming (and cooling) rates of the sea surface temperatures of the Pacific Ocean during the satellite era (basically 1982 to present). The following two illustrations are from my book Climate Models Fail. I’ve thrown a few notes on them for this blog post, simply to point out the locations of the tropical Pacific and the equator for the climate modelers. The data are NOAA’s satellite-enhanced optimum interpolation sea surface temperature dataset, Reynolds OI.v2. The models are represented by the average of all of the simulations (model runs) from the climate models stored in the CMIP5 archive–those that provided simulations of sea surface temperatures. (The CMIP5 archive was prepared for and used by the IPCC for their 5th Assessment Report.) We use the multi-model mean because it best represents how climate models indicate the sea surface temperatures should have (would have, could have) warmed in response to human-induced global warming. (For further information, see the blog post On the Use of the Multi-Model Mean.) The forcings that drive the models are a mix of historic though 2005 and RCP6.0 afterwards.

Figure 7-29 is a graph that presents the sea surface temperature trends for the Pacific Ocean on a zonal-means basis. (Zonal means is another way of saying latitude average.) The vertical axis (y-axis) is scaled in deg C/decade. In other words, the positive numbers indicate rates at which the sea surface temperatures warmed and the negative numbers indicate cooling rates. The horizontal axis (x-axis) is latitude, with 90S (-90) the South Pole, “zero” (0) the equator, and 90N (90) the North Pole. El Niño and La Niña events occur in the tropical Pacific but are focused along the equator. So let’s look at the trends at the equator. The climate models indicate that if (big if) the sea surface temperatures of the equatorial Pacific were warmed by manmade greenhouse gases, the sea surface temperatures there should have warmed at a rate of about 0.2 deg C/decade…or more than 0.6 deg C over the past 3+ decades. But, the data indicate the sea surface temperatures of the equatorial Pacific actually COOLED over the past 31 years. Overall, there are few to no similarities between how data indicate the Pacific actually warmed over the past 30 years and how the models indicate they shoulda’, woulda’, coulda’ warmed in response to the increased emissions of manmade carbon dioxide.

Figure 7-29

Figure 7-30 presents maps of the modeled and observed rates of warming and cooling in the Pacific for the same basic period (1982 to 2012), using the same dataset and model mean as in Figure 7-29. There are no similarities between how the sea surface temperatures of the Pacific Ocean actually warmed over the past 3+ decades and how the models indicate they should have warmed, if they were warmed by manmade greenhouse gases.

Figure 7-30

Note: The observed “C-shaped” warming pattern in the Pacific (right-hand cell of Figure 7-30) is one associated with a period when strong, naturally occurring, El Niño events released vast amounts of naturally created warm water from below the surface of the tropical Pacific, which was then subsequently redistributed after the El Niños into the western Pacific Ocean (and East Indian Ocean, not illustrated) by ocean currents. The warm water “collects” in the region east of Japan referred to as the Kuroshio-Oyashio Extension (KOE) and in the region east of Australia and New Zealand called the South Pacific Convergence Zone (SPCZ). The modelers obviously missed the naturally occurring spatial pattern of warming that takes place in the Pacific Ocean. That’s an important climate model failing for a simple reason: how, when, and where the oceans warm and cool dictate in part how, when and where land surface air temperatures warm and cool.

PEER-REVIEWED PAPERS ABOUT HOW POORLY CLIMATE MODELS SIMULATE EL NIÑO- AND LA NIÑA-RELATED PROCESSES

Power et al. (2013) cited Guilyardi et al. (2009), which is a paper I have referred to numerous times in blog posts (example here). Did Power et al. (2013) overlook one of the critical findings of Guilyardi et al. (2009)?:

Because ENSO is the dominant mode of climate variability at interannual time scales, the lack of consistency in the model predictions of the response of ENSO to global warming currently limits our confidence in using these predictions to address adaptive societal concerns, such as regional impacts or extremes.

In other words, because climate models cannot accurately simulate El Niño and La Niña processes, the authors of Guilyardi et al. (2009) have little confidence in climate model projections of regional climate or of extreme events.

Bellenger, et al. (2013) “ENSO Representation in Climate Models: From CMIP3 to CMIP5,” is a more recent confirmation of how poorly climate models simulate El Niños and La Niñas. (Preprint copy is here.) The section titled “Discussion and Perspectives” begins:

Much development work for modeling group is still needed in order to correctly represent ENSO, its basic characteristics (amplitude, evolution, timescale, seasonal phaselock…) and fundamental processes such as the Bjerknes and surface fluxes feedbacks.

  • “Amplitude” refers to the strengths of ENSO events.
  • “Evolution” refers to the formation of El Niños and La Niñas and the processes that take place as the events are forming.
  • “Timescale” can refer to both the how long ENSO events last and how often they occur.
  • “Phaselock” refers to the fact that El Niño and La Niña events are tied to the seasonal cycle. They peak in the boreal winter.
  • “Bjerknes feedback,” very basically, means how the tropical Pacific and the atmosphere above it are coupled; i.e., they are interdependent, a change in one causes a change in the other and they provide positive feedback to one another. The existence of this positive “Bjerknes feedback” suggests that El Niño and La Niña events will remain in one mode until something interrupts the positive feedback.

In short, according to Bellenger, et al. (2013), the current generation of climate models (CMIP5: used by the IPCC for their 5th Assessment Report and by Power et al (2013)) still cannot simulate basic coupled ocean-atmosphere processes associated with El Niño and La Niña events–basic processes.

Power et al (2013) must have really had to search through the climate model simulations to find some ENSO-related response that appeared to mimic reality.

THE TAIL WAGGING THE DOG

I was alerted to the BBCNews article and the paper by blogger mwhite in a comment this morning. (Thanks, mwhite.) mwhite’s note “The tail wags the dog???” refers to the fact that satellite-era sea surface temperature records indicate strong El Niño events are responsible for the warming of global sea surface temperatures over the past 3 decades, not manmade greenhouse gases. And ocean heat content records indicate the warm waters that fuel El Niño events were created during La Niña events—a process that is driven by sunlight, not greenhouse gases. So mwhite was asking rhetorically whether Power et al. (2013) had confused cause and effect.

If the subject of the natural warming of the global oceans is new to you, refer to my illustrated essay “The Manmade Global Warming Challenge”(42MB). The way data portrays how the oceans warmed may come as a surprise to you, especially with all we’ve been told about human-induced global warming. If you like audio-video presentations, see my two-part YouTube video series “The Natural Warming of the Global Oceans”. Part 1 is here and Part 2 is here.

WANT TO LEARN MORE ABOUT CLIMATE MODEL FAILINGS AND ABOUT EL NIÑO AND LA NIÑA EVENTS AND HOW THEY PROVIDE LONG-TERM GLOBAL WARMING?

Last year I published the ebook Who Turned on the Heat? It explained in minute detail (and in easy-to-understand ways for those without technical or scientific backgrounds) the processes that drive El Niño and La Niña events and how they contributed to the long-term warming of the global oceans. (Who Turned on the Heat? continues to sell quite well.)

However, before you click on the following links to Who Turned on the Heat? I also addressed the subject of the natural warming of the global oceans in Section 9 of my new book Climate Models Fail, but not in as much detail as in Who Turned on the Heat?

I have been publishing comparisons of data with climate models outputs for about two years. The climate models used by the IPCC clearly cannot simulate Earth’s surface temperatures, precipitation or sea ice area. Additionally, there are numerous scientific research papers that are very critical of how climate models perform specific functions. The following lists the processes that CLIMATE MODELS STILL SIMULATE POORLY:

  • The coupled ocean-atmosphere processes of El Niño and La Niña, the largest contributors to natural variations in global temperature and precipitation on annual, multiyear, and decadal timescales.
  • Responses to volcanic eruptions, which can be so powerful that they can even counteract the effects of strong El Niño events.
  • Precipitation — globally or regionally — including monsoons.
  • Cloud cover.
  • Sea surface temperatures.
  • Global surface temperatures.
  • Sea ice extent.
  • Teleconnections, the mechanisms by which a change in a variable in one region of the globe causes a change in another region, even though those regions may be separated by thousands of kilometers.
  • Blocking, which is associated with heat waves.
  • The influence of El Niños on hurricanes.
  • The coupled ocean-atmosphere processes associated with decadal and multidecadal variations in sea surface temperatures, which strongly impact land surface temperatures and precipitation on those same timescales.

Looking at those papers independently, the faults do not appear too bad, but collectively they indicate the models are fatally flawed.

In my book Climate Models Fail, I have collected my past findings about climate models, and illustrated others, and I’ve presented highlights from the research papers critical of climate models—and I “translated” those research findings for persons without scientific or technical backgrounds. And as noted earlier, there is also a discussion of the natural warming of the global oceans. The free preview of Climate Models Fail is available here. It includes the Introduction, Table of Contents and the Closing. Climate Models Fail is available in pdf and Kindle formats. Refer to my blog post New Book: “Climate Models Fail” for further information, the synopsis from the Kindle webpage and purchase/download links.

Back to Who Turned on the Heat?: It is only available in .pdf form. A preview is here. Who Turned on the Heat? is described further in, and is available for sale through, my blog post “Everything You Ever Wanted to Know About El Niño and La Niña”.

CLOSING

It seems as though Power et al. (2013) went in search of some small portion, any small portion, of ENSO that climate models appeared to simulate correctly and then published the typical climate science paper that generates alarmist nonsense in newspaper articles.

When data contradict models in most scientific and engineering endeavors, the modelers rework the models. Not in climate science. In climate science, the climate scientists/modelers simply proclaim the findings of the fatally flawed models more often and with greater certainty, without revealing the model flaws. (Thus, the IPCC’s 5th Assessment Report.)

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Pippen Kool
October 15, 2013 9:34 pm

Dmilodonharlani says “I’m pretty sure, Mr. Kool, that Mr. Courtney knows a lot more about relevant scientific subjects than you (whatever might be the gaps in his historical data base). Do you really want to go down the Yellow Brick credential comparison road, joining as Scarecrow the board’s own Tin Woodsman (fill in the blank) & Cowardly Lion Poptech?”
Don’t worry, Dmilodonharlani, I am not convinced that Tisdale or Courney know anything that I do not know. The fact that Tisdale has never published in peer reviewed media suggest that he that knows is stuff would get ripped apart, and he doesn’t really take criticism well because he thinks he knows more than the experts.He’s a pretty good example of Dunning–Kruger effect, at its best.

October 15, 2013 10:39 pm

Pippen Kool says:
“I am a skeptic.”
heh.
Pippen Kool is about as skeptical as a witch doctor’s acolyte.

Greg Goodman
October 16, 2013 2:42 am

Bob, I’ve been splashing around in Nino waters this week too, looking for relaationship to LOD.
One think came out of this that may interest you. I noticed that SST in Nino1.2 region 0-10S; 80-90W seems to be positive spikes sitting on a decadaly variable base line.
I note that, unlike MEI index from a number of physical factors, SST in this region only has very small negative swings. That seems to point to the kind of asymmetric process you have been trying to highlight for some time.
Nino 1+2 has the strongest and sharpest El Nino peaks so would seem to the key region to study (rather than the usual focus on Nino 3.4)
Here you can see the lack of negative swings:
http://climategrog.wordpress.com/?attachment_id=554
here we see how El Nino in this region directly correlates with acceleration / deceleration in Earth’s rotation (implying evaporation and energy transfer to atmosphere):
http://climategrog.wordpress.com/?attachment_id=556
This may provide direct regional confirmation of your ENSO pumping hypothesis.
(No detrending, no volcanoes needed.).

Greg Goodman
October 16, 2013 2:47 am

BOB says ” Do you see any similarity between the 1st EOF of sea surface temperatures in the tropical Pacific (1982-2012)…”
Since you ask, there’s a little green bit in the top right hand corner that’s quite similar, also orangey bit in bottom right.
Other than that, I can’t see a lot of similarity. 😉

richardscourtney
October 16, 2013 4:54 am

Pippen Kool:
You continue to attempt to disrupt this thread with irrelevant and nonsensical babble. For example, at October 15, 2013 at 9:34 pm you say

I am not convinced that Tisdale or Courney know anything that I do not know.

Assuming that by “Courney” you mean me, then there are many things I am sure I know that you don’t; for example, the maiden name of my maternal grandmother.
If you are capable of understanding the issues being discussed – and your posts in this thread indicate you lack that capability – then please address those issues. Otherwise, please go away because you are being a disruptive nuisance.
Richard

MattN
October 16, 2013 5:30 am

Please stop feeding the troll.

Richard Barraclough
October 16, 2013 7:47 am

To change direction entirely, what’s happened to this month’s analysis of the global temperatures for September, as reported by UAH, NASA, Hadcrut, etc?

Pamela Gray
October 16, 2013 9:15 am

Interesting. A relative newcomer in short term ENSO forecasting comes from a hybrid model. Dynamical Ocean coupled with a statistical atmosphere model. I am searching the net for how it is made to see what, if any, AGW pieces are in the model and whether or not plans are being put together to turn this into a long-range component of GCM projections. I love my ENSO prediction pages. So full of great reading.
http://essic.umd.edu/joom2/index.php/current-news/featured-essic/1250

Pamela Gray
October 16, 2013 10:00 am

So here is what I have learned. This model depends on the injection of actual current SST temperatures prior to each forecast, done on a monthly basis. The forecast extends to 12 months each time. Though this model produces errors, it is more accurate than nearly all other ENSO models. No wonder. It uses actual SST data to initiate each forecast period, and as far as I can tell, model components that do not have AGW pieces in them (though I am still looking into that).
http://www.math.nyu.edu/faculty/kleeman/Zhang05.pdf
Here is the real point. If this model, based on real data and quite good at forecasting ENSO events, has errors in it that grow within 12 months, no wonder GCM ENSO forecasts are in another Universe.
Summary thinking about connections between ENSO forecasting and GCM projections. To improve GCM projections, it is likely they will have to re-initialize with real SST or land temperature data on a regular basis in order to reduce overestimating projected warming. Which tells us that GCM projections are probably only good out to a year before you have to schedule another session with the super-duper computer. Bad business for IPCC. It would come to a screeching halt and folks around the globe would be wanting their money back. On the bright side, try to get any political body to pass anything related to mitigation or reduction in something that is 12 months or less away.
Note: The authors mention that the hindcast accuracy (which was amazingly good) could be artificial. And they tell us why. They used historical data to train the model. Stating the obvious,
“As such, the skill for SST [hindcast] predictions can be artificial, because of observational information of SST and variability covering the prediction period being already included in
the training period.”
In other words, they coulda said “duh” and probably wanted to. Is this mentioned anywhere in the WG1 summary document for AR5 regarding its GCM hindcastings?

Matthew R Marler
October 16, 2013 10:44 am

Bob Tisdale: Do you see any similarity between the 1st EOF of sea surface temperatures in the tropical Pacific (1982-2012)…
Exactly what have you plotted there, that is, what model?

Matthew R Marler
October 16, 2013 10:45 am

Bob Tisdale: (PERSONALLY, I DON’T THINK THE MODELERS ARE REALLY TRYING)
On what do you base that?

DavidS
October 16, 2013 12:39 pm

“Experiments with an Atmospheric General Circulation Model reveal that robust projected changes in precipitation anomalies during El Niño years are primarily determined by a nonlinear response to surface global warming.”
I’m no doubt showing my ignorance of climate models and what they are capable of, but Is it reasonable to say you can run an experiment with a model? Isn’t the result pre-determined based on the parameters set by the modeler?

Pamela Gray
October 16, 2013 12:56 pm

The result of the paper states what has been known thus is no new information. Precipitation during El Nino years is primarily determined by a nonlinear response to surface global warming caused by El Nino oceanic/atmospheric teleconnections. ENSO dynamical and statistical models have been demonstrating this for years.

richardscourtney
October 16, 2013 1:02 pm

DavidS:
At October 16, 2013 at 12:39 pm you ask

Is it reasonable to say you can run an experiment with a model? Isn’t the result pre-determined based on the parameters set by the modeler?

The answers to your questions are
No it is not “reasonable”
and
Yes the result tells about the model’s performance but nothing else.
The mistake you point out is commonly made in so-called ‘climate science’, and it goes to the heart of the criticism of the paper by Bob Tisdale.
Richard

Pamela Gray
October 16, 2013 1:42 pm

We have a pretty good statistical data set of the percent of the time a particular precip or temp pattern happens under El Nino or La Nina conditions. Because of this data set and the relatively stable no-trend-visible 3.4 area of the Nino geographical area, I would hope to shout that most oceanic/atmospheric models get this right. It would certainly be the data set I would train a model on. Which leads me to speculate that the paper’s conclusion that they got one section right, therefore the rest of the model must be good too is probably artifactually based on what data they trained the model on and not because the model as a whole is a good one. It seems a step too far in terms of giving us confidence in the projection as a whole.
http://www.cpc.ncep.noaa.gov/products/precip/CWlink/ENSO/composites/

Reply to  Pamela Gray
October 16, 2013 4:23 pm

Pamela,
Becaues they find a statistical relationship between ENSO and atmospheric concentrations does not mean that CO2 is “forcing” a temperature rise. It is more likely that the accumulation of CO2 is following a rise in temperature. In order for their model to have any predictive quality, they need to know what is causing ENSO. CO2 is a laging indicator.

DavidS
October 16, 2013 3:51 pm

Thanks, Richard and Bob for the comments.

October 16, 2013 4:02 pm

Will Global Warming Increase the Intensity of El Niño?
No, intense El Nino’s occur when the solar plasma speeds are much slower through enough months: http://snag.gy/UtqpX.jpg

Pamela Gray
October 16, 2013 6:34 pm

hmmm. I don’t think I mentioned atmospheric concentrations of CO2. I don’t know which part of my comments you are responding to.