Is There an Improved Method of El Niño Forecasting? –And– There’s No Consensus About ENSO in Paleo-Studies
AN IMPROVEMENT IN EL NIÑO FORECASTING?
A recently published paper by Ludescher et al (2013) Improved El Niño forecasting by cooperativity detection (paywalled) claims to be able to forecast an El Niño event more than a year in advance. The EurekAlert press release is here. And the preprint version of the paper is here. WattsUpWithThat provides an introductory post here.
Statistical and dynamical models are presently used to predict whether the upcoming winter with be impacted by an El Niño or a La Niña, or if it will be a neutral El Niño-Southern Oscillation (ENSO) season. Those models are hindered by a phenomenon called the spring predictability barrier. But this new method, which is another statistical model, is supposed to be able to hurdle that barrier and make predictions a year ahead based on measured variables from more than 200 locations around the Pacific. But it is limited to El Niño events—at present.
I hope the method presented in Ludescher et al (2013) works. But I do recall papers in the past that have made similar claims—never to be heard of again.
WHAT THE PRESS HAS TO SAY
In USA Today, Dan Vergano and Doyle Rice provide an overview of the findings of Ludescher et al (2013), but the reporters do have a number of errors and poor wordings in an early paragraph. They write:
El Niños strike every decade, driven by warm Pacific Ocean water piling on the West Coast and affecting weather worldwide, triggering floods, droughts and heat. The most recent El Niño ended in 2007.
The most recent official El Niño occurred during 2009/10, so they missed one. See Figure 1. It represents the sea surface temperature anomalies of the NINO3.4 region (5S-5N, 170W-120W), which is an east-central portion of the equator in the Pacific, starting in November 1981. Sea surface temperature anomalies in that region are a commonly used index for the frequency, strength and duration of El Niño and La Niña events. El Niño events are the large upward spikes and La Niñas are the downward ones. That monthly ENSO index actually reached El Niño conditions (NINO3.4 sea surface temperature anomalies warmer than 0.5 deg C) during the (boreal) summer of 2012, but they did not stay there long enough to have been classified as an official El Niño event, nor did they extend into the normal El Niño and La Niña (boreal) winter season. Nonetheless, the tropical Pacific did release extra heat into the atmosphere last year, but it was only for a short time—a couple of months.
Figure 1
(Figure 1 is from my most recent sea surface temperature update.)
And not all El Niños reach the west coast of South America. The ones that do are called East Pacific El Niños, and the ones that do not extend all the way to the coast of the Americas are called Central Pacific El Niño events or El Niño Modoki. (See the El Niño Modoki discussions here, here and here.)
And it’s true that El Niños strike every decade, but that could be misleading, because they strike multiple times a decade. In the 1950s, there were 4 El Niños, according to NOAA’s Oceanic NINO Index-based table of Historical El Nino/ La Nina episodes (1950-present). The 1960s had 3, including one that lasted through 2 ENSO seasons. The 1970s had 3. During the 1980s, the frequency dropped, there were only 2 El Niños, but one was extremely strong and the second lasted for about a year and half. The 1990s initially saw two moderate El Niños, followed by the colossal 1997/98 El Niño. Then the 2000s saw a string of 3 moderate El Niños and it ended with the formation of the 2009/10 El Niño. So the 1950s and the 2000s both had 4 El Niños; the 60s, 70s and 90s had 3 each; and the 1980s had 2.
For those who want to look at the decades before the 1950s, see the Oceanic Nino Index-like tables created from HADISST-based NINO3.4 sea surface temperature anomalies here. Keep in mind that observations are very sparse along the equatorial Pacific in the early part of the data (especially before the opening of the Panama Canal in 1914) and that Giese et al (2009) indicate that a few of the El Niño events before 1950 were likely stronger.
The USA Today article also includes quotes from Anthony Barnston, an ENSO researcher from Columbia University’s International Research Institute for Climate and Society (IRI), and from Michael Mann, paleoclimatologist, both of whom are skeptical of the results of Ludescher et al (2013).
Best of luck to Ludescher et al (2013). It would be nice to be able to predict ENSO events more than a few months in advance.
NO CONSENSUS ABOUT ENSO IN PALEO-STUDIES
Personally, paleoclimatological studies do not stand high on my list of believable climate studies. I prefer data-based studies. Which proxies paleo-studies use and the weighting of the proxies have significant impacts on the outcomes, and some of the methods and proxies used in paleoclimatological studies have been found to be questionable. So paleo-studies always seemed to me to be open to too much of the authors’ preconceptions. When paleo-studies add climate models, they require another leap of faith because climate models are imperfect representations of climate: make-believe models trying to simulate make-believe data.
The USA Today article by Dan Vergano and Doyle Rice also give honorable mention to Li et al (2013) El Niño modulations over the past seven centuries (Paywalled). Supplementary Information is here. Li et al (2013) has been getting a lot of press over the past few days. Anthony Watts has a quick post about it here. Vergano and Rice write about Li et al (2013):
A related study in the Nature Climate Change journal suggests that the chances of that next El Niño might be more likely because of the world’s warming climate. Led by Jinbao Lu [sic] of the University of Hong Kong, the study looked at 2,222 tree-ring growth records over the last seven centuries from the Pacific Rim. They find El Niño happened a lot more than normal over the last 50 years, just as temperatures worldwide rose due to global warming, suggesting a connection. Past studies have been more uncertain about climate effect’s [sic] on El Niño.
It appears Vergano and Rice may even have misspelled Dr. Jinbao Li’s name.
That aside, if “Past studies have been more uncertain about climate effect’s [sic] on El Niño” but Li et al (2013) are more certain, that strongly suggests that there is no paleo study-based consensus about ENSO—not that Li et al (2013) are correct.
The Li et al (2013) abstract includes:
Our data indicate that ENSO activity in the late twentieth century was anomalously high over the past seven centuries, suggestive of a response to continuing global warming.
The word “continuing” is a nice touch.
Ray & Giese (2012) Historical changes in El Niño and La Niña characteristics in an ocean reanalysis came to a different conclusion. Their 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.
Also, Vergano and Rice interviewed Michael Mann about Ludescher et al (2013), but they failed to mention that Mann, a paleoclimatologist, was part of another very detailed paleoclimatological study of El Niño, the results of which were published at the end of last year.
That 2-part paper was Emile-Geay et al (2012) “Estimating Central Equatorial Pacific SST variability over the Past Millennium”. The abstract of Part 1 is here and the paper is here. The abstract of Part 2 is here and the paper is here.
The conclusions of Emile-Geay et al (2012) begin on page 20 of the second part of the paper linked above. They did not come to the same conclusion as Li et al (2013). The last 2 sentences of the Emile-Geay et al (2012) conclusions read (my boldface):
Progress on this question is most pressing: whether or not the tropical Pacific climate responded consistently to natural radiative forcing in the recent past bears directly on the question of its real-world sensitivity to anthropogenic climate change. Therefore, this knowledge could directly impact our ability to predict global and regional climate variability over the coming century.
My favorite conclusion of Emile-Geay et al (2012), though, is the first one. In it, they blame the sparseness of the sea surface temperature data in the NINO3.4 region since the 1850s for much of the uncertainty in the paleoclimatological results. While they propose methods for improving the sea surface temperature data, any reconstruction of sea surface temperature of the central equatorial Pacific is still speculation.
And then there’s Ault et al (2013) “Characterizing decadal to centennial variability in the equatorial Pacific during the last millennium”. Preprint version is here. Their abstract reads (my boldface):
The magnitude of sea surface temperature variability in the NINO3.4 region of the equatorial Pacific on decadal and longer timescales is assessed in observational data, state-of-the-art (CMIP5) climate model simulations, and a new ensemble of paleoclimate reconstructions. On decadal to multidecadal timescales, variability in these records is consistent with the null hypothesis that it arises from “multivariate red noise” (a multivariate Ornstein-Uhlenbeck process) generated from a linear inverse model of tropical ocean-atmosphere dynamics. On centennial and longer timescales, both a last millennium simulation performed using the Community Climate System Model 4 (CCSM4) and the paleoclimate reconstructions have variability that is significantly stronger than the null hypothesis. However, the time series of the model and the reconstruction do not agree with each other. In the model, variability primarily reflects a thermodynamic response to reconstructed solar and volcanic activity, whereas in the reconstruction, variability arises from either internal climate processes, forced responses that differ from those in CCSM4, or non-climatic proxy processes that are not yet understood. These findings imply that the response of the tropical Pacific to future forcings may be even more uncertain than portrayed by state-of-the-art models because there are potentially important sources of century-scale variability that these models do not simulate.
It’s no surprise that climate models can’t simulate ENSO variability on century time scales. Climate models can’t simulate the basic processes of ENSO. Why would researchers think they’d perform well over long terms? I’ve linked the following study many times in the past and I’ll link it here again. It’s Guilyardi et al (2009) Understanding El Niño in Ocean-Atmosphere General Circulation Models: progress and challenges. It discusses decadal, annual and seasonal model failings when trying to simulate ENSO. It includes a statement that’s very similar to the quote I provided above from Emile-Geay et al (2012). Guilyardi et al (2009) wrote:
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 (Joseph and Nigam 2006; Power et al. 2006).
DID GLOBAL WARMING CAUSE THE EL NIÑOS OR DID EL NIÑOS CAUSE GLOBAL WARMING?
Numerous datasets indicate that El Niño events are fueled naturally. Additionally, satellite-era sea surface temperature records indicate that El Niño events are responsible for the warming of sea surface temperatures over the past 31 years, not vice versa as Li et al (2013) have suggested. If this topic is new to you, refer to my illustrated essay “The Manmade Global Warming Challenge” [42MB].
Bob: Please try the follwoing. Add a longer running average to the one you have at 13 months in the plot in Fig 1. One say in the 36-48 month bracket. Plot it all simulateously and tell me what you see, if anything.
Bob Tisdale says:
El Niño events are responsible for the warming of sea surface temperatures over the past 31 years, not vice versa
Entirely agree.
Until someone conclusively shows what drives the ENSO and the southern atmospheric pressure oscillation (SOI), one could be forgiven to assume that the ENSO is triggered by the equatorial Pacific’s tectonics.
http://www.vukcevic.talktalk.net/ENSO.htm
I compiled this nearly two years ago and will have to update it sometime. There is also a similar correlation in the North Pacific with the PDO (also related to the ENSO)
http://www.vukcevic.talktalk.net/PDO.htm
one could be coincidence but two increases probability that tectonics is a major climate factor. Let’s not forget the North Atlantic and the AMO
http://www.vukcevic.talktalk.net/SST-NAP.htm
Correlation of three out of three major climate indices should encourage climate science researchers to consider long term ocean currents variability with respect to the available geological data.
vukcevic says:
July 3, 2013 at 5:42 am
“Correlation of three out of three major climate indices should encourage climate science researchers to consider long term ocean currents variability with respect to the available geological data.”
I begin to suspect that detailed combined solar, moon gravity maps of earth with particular regard to latditudes at 50-60 degrees to the direction to the gravity source mat well resolve a ot of questions.
RichardLH says: “Bob: Please try the follwoing. Add a longer running average to the one you have at 13 months in the plot in Fig 1. One say in the 36-48 month bracket. Plot it all simulateously and tell me what you see, if anything.”
I believe you’d like me to show that there’s an apparent 11-year cycle in the NINO3.4 data and that it mimics the solar cycle. Unfortunately, the two datasets do not agree as well as you travel back in time.
And this discussion usually generates comments.
Regards
e.g. Compare these and think 37 month, 4 year and harmonics.
http://en.wikipedia.org/wiki/File:Field_tidal.png
http://en.wikipedia.org/wiki/File:Jetcrosssection.jpg
Bob; No i was trying to get you do do the start of a decompilation of the ‘energy’ in the system into broad frequency bands.
For good statistical reasons i would use a full series based on 3,4,5,7,9,12,…. but even havig two is a start.
Now you can separte out where in time the ‘energy’ distribution is timewise.
The rest follows.
I have done it with UAH. I would love to see what it does with your work.
And so, because I am trying very hard to aviod confirmation bias to what I have seen, I ask that you try and see it also. If you even slightly come up with the same values I have done we are done and dusted.
RichardLH says: July 3, 2013 at 5:52 am
…….
Direct solar input is demonstrable in the N. Atlantic
http://www.vukcevic.talktalk.net/SSN-NAP.htm
but I have not found one in the Pacific
vukcevic says:
July 3, 2013 at 6:33 am
RichardLH says: July 3, 2013 at 5:52 am
…….
Direct solar input is demonstrable in the N. Atlantic
http://www.vukcevic.talktalk.net/SSN-NAP.htm
but I have not found one in the Pacific
I am not talking about sloar input.input. I am talking about gravitational paterns at 50-60 degress to the orbits on Earth.
RichardLH says: “Bob; No i was trying to get you do do the start of a decompilation of the ‘energy’ in the system into broad frequency bands.”
RichardLH, please do not take this the wrong way. I have way too much on my plate for me to change my research interests. You may well be onto something, but, unfortunately I don’t have the time to investigate it. Sorry. On the bright side, I have no problem with you discussing it on this thread with others.
Regards
Bob: Thanks. It is just a standard decompliation of the ‘energy’ into separate frequency/period bands.
Very little work required. Next time you need to do a graph with running means, add a few extra columns to make a 3 pole filter as required and get an idea of what you are looking at.
I think it is fun and interesting. I understand if you have other work.
P.S. Do I come across as a cycle loony. Sorry – this is diven by standard maths and physics and I’m trying hard to avoid the loony tag.
I think the fact that the ENSO has Zero trend since 1850 or 1871 (depending on when you think a reliable record starts), says something very important about what it is and something very important about its historical trend.
First on historical trend. If a weather phenomenon has Zero trend over nearly 2,000 months, nearly 60,000 days, I think we can say it has probably always been like this. Maybe slightly lower when the Earth was cooler, maybe slightly higher when the Earth was warmer, but very close to its current arrangement in past history.
In fact, there has probably been an ENSO for about 400 million years ever since the Pacific and its predecessors became a large deep ocean at the equator. In fact, the general driver of the ENSO, the winds and the rotation of the Earth, means that there has probably always been an ENSO-like oscillation somewhere on Earth whenever there was a large deep ocean at the equator ever since the oceans and the atmosphere formed.
Now onto what it is. When an El Nino forms, tropical storms form at its end-point at the International Dateline. These can be nearly continuous storms that form mid-day every day and cover a truly huge region. The warmth of the ocean rises, meets the cooler troposphere 5 kms up and clouds and rain result. You can set your watch by it. The energy changes here are a truly huge +/- 50.0 Watts/m2. Just for perspective, CO2 doubling is only supposed to be +3.7 Watts/m2. So the ENSO oscillation causes changes in a certain (large but small compared to the whole Earth) region which are 13 times bigger than global warming is supposed to result in.
It is similar to Willis’ thunderstorm thermostat hypothesis. Sea surface temps get to 32.0C, and then it rains. The ocean dumps its heat in the cool atmosphere and it never really gets much warmer than this. Eventually, all that cloud cover (when the Sun is not warming the ocean any longer) and all this heat dumping rain cools the ocean off to a normal 30.0C. El Nino over. Planet warms up as all this heat is moved from the ocean to the atmosphere. Just temporarily and lagged 3 months behind the ocean warmth peak.
La Nina. No clouds and no thunderstorms at the International Dateline. Ocean slowly warms up from 28.0C to a normal 30.0C but the lack of heat-trapping clouds means the Planet cools off. Temporarily and lagged 3 months behind.
Can the 32.0C limit change over time. Perhaps. But it hasn’t for nearly 60,000 days now. One would need much better evidence than tree rings to say it is now different than it has been for 2000 months.
If I am right (and that is a big, big step at this time – which is why I am searching so hard for other field confirmation) then I may have an outside chance possibility of at least partially explaining ENSO.
Think of a slow undersea cold wave bouncing North to South between the combined gravity field at 50-60 degrees to orbits to sun and moon.
That would mean that East to West is a visual illusion.
It has the required 37 month, 4 year periods that I have seen. It will be irregular with some periodic features.
It fits roughtly with what I see in UAH
The rest is guesswork
vukcevic says:
July 3, 2013 at 5:42 am
one could be forgiven to assume that the ENSO is triggered by the equatorial Pacific’s tectonics.
As Al Gore said: “if one does not know anything, everything is possible”.
Bob: Do you have the series in Fig 1 in a csv or other form that I can easily read into excel? (or any other format come to that :-)). I can do the work and post it back if that makes any difference.
lsvalgaard @ vukcevic
As Al Gore said: “if one does not know anything, everything is possible”.
Or as my late granddad use to say:
The one who knows everything wrote the ten commandments, the others may know everything about nothing.
Hey doc, Al Gore said this too: “A zebra does not change its spots.”
lsvalgaard says:
July 3, 2013 at 7:38 am
vukcevic says:
July 3, 2013 at 5:42 am
one could be forgiven to assume that the ENSO is triggered by the equatorial Pacific’s tectonics.
As Al Gore said: “if one does not know anything, everything is possible”.
<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<>>>>>>>>>>>>>>>>>>>>>>>>>
Since I do not know everything, I guess I can say say that for me anything is not possible.
Centuries ago, an Arab traveler visited the Baku oil springs and reported “When the sky is clear[high pressure] the oil does not flow but when the weather is thick and cloudy [low pressure] the oil flows copiously.” Apparently the subsurface pressure had achieved a sort of equilibrium with weather.
So there, Vuk, put this in your file of fantasmigora, no need to thank me.
The most recent official El Niño occurred during 2009/10, so they missed one.
According to their report, they missed almost half: they claim a hit rate above 50%; I am sure that if they could have claimed a hit rate above 60% they would have, so I infer that they miss at least 39%. They claimed a low false alarm rate, below 10%.
If you randomly forecast a year in advance using a frequency of 1 every 5 years, you would miss about 80% of them and have about a 20% false alarm rate. So they are doing better than such a chance scheme. If you flipped a coin a year in advance and predicted an El Niño every time heads came up, you’d miss half of them and have a 50% false alarm rate. So they are doing better than chance.
RichardLH says: “Bob: Do you have the series in Fig 1 in a csv or other form that I can easily read into excel.”
I use the NOAA NOMADS system for the Reynolds OI.v2 SST anomaly data for the NINO3.4 region:
http://nomad3.ncep.noaa.gov/cgi-bin/pdisp_sst.sh?ctlfile=monoiv2.ctl&varlist=on&new_window=on&lite=&ptype=ts&dir=
Select: Anomalies from the “Field” drop down menu. Then, for the NINO3.4 region, enter the coordinates of 5S to 5N latitude & 170W to 120W longitude, which is input as (-5) to (5) & (-170) to (-120).
After you hit enter, a new webpage will open with a graph. There’s a link at the lower left-hand corner of the graph to the data. If you’ve left the months and years as their defaults, the data starts in November 1981. You’ll have to define your own months. If you’d rather not define your own months..
…you can download the Reynolds OI.v2 SST through the KNMI Climate Explorer.
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere
Select “1982-now: 1° Reynolds OI v2 SST,” and hit enter. On the next page, enter the coordinates listed above (no need to worry about the % because the Reynolds OI.v2 data is spatially complete) and hit enter. There are three graphs on the next page. Select “raw data” above the third (anomaly) graph. It provides you with the months and the data.
The anomalies from KNMI will look at little different than what I’ve shown. NOAA uses 1971-2000 as the base years through their NOMADS system, while KNMI has 1981-2010 as the default base years.
Regards
RichardLH says: “Do I come across as a cycle loony. Sorry – this is diven by standard maths and physics and I’m trying hard to avoid the loony tag.”
You don’t come across as loony. As far as I’m concerned, you simply have interests that are different than mine. I’m interested in the processes of ENSO, including the generation of the warm water during the La Nina that precede the El Nino and the redistribution of warm water following the El Nino…or, in more basic terms, where does the warm water come from to fuel the El Nino and where does the warm water go after the El Nino.
Regards
Additionally, satellite-era sea surface temperature records indicate that El Niño events are responsible for the warming of sea surface temperatures over the past 31 years, not vice versa as Li et al (2013) have suggested.
a. if the El Niño events are warming the sea surface, and if there is no net global accumulation of energy (with concomitant global temperature mean temperature increase), then there must be a region or regions from which El Niño events draw that energy, and those regions must have declining temperature. It would be interesting to know/study what those regions might be.
b. if the El Niño events are warming the sea surface and if there is no region or set of regions that are cooling because the El Niño events are drawing away energy, then there is net global warming.
c. there are more possibilities: El Niño events could be a part of a negative feedback mechanism acting like Willis Eschenbach’s hypothesized “thermostat”.
However, a, b, c, and others, El Niño events are parts of global heat transfer, not independent drivers of them.
Matthew R Marler: In response to my statement, “The most recent official El Niño occurred during 2009/10, so they missed one,” you wrote, “According to their report, they missed almost half:..”
Sorry for the confusion. I shouldn’t have used a pronoun. “They” in what you quoted referred to the “USA Today” reporters, not the authors of the study.
Regards
vukcevic says: @ July 3, 2013 at 5:42 am
Vukcevic, I love your graphs but could you please label them so a layman understands what he is looking at? WUWT has a lot of lurkers may of whom are new and it pays to keep that in mind when presenting data.
Thanks
Bob Tisdale: or, in more basic terms, where does the warm water come from to fuel the El Nino and where does the warm water go after the El Nino.
I think you make a good case that the ENSO system functions “very like” Willis’ hypothetical “thermostat”. You don’t claim it’s complete, and my comments and questions aim to probe the missing pieces.
Bob Tisdale: “They” in what you quoted referred to the “USA Today” reporters, not the authors of the study.
Sorry. I ought to have made it more clear when I was citing the authors of the study (hit rate, etc.), and when the authors of the news item. I think I introduced a confusion.
Matthew R Marler says: “if the El Niño events are warming the sea surface, and if there is no net global accumulation of energy (with concomitant global temperature mean temperature increase), then there must be a region or regions from which El Niño events draw that energy, and those regions must have declining temperature.”
Not if the preceding La Nina provides the warm water for the El Nino and the trailing La Nina replenishes the warm water released by the El Nino. Then you see an increase in warm water during the La Nina, followed by the decrease during the El Nino, which in turn is followed by an increase in response to the trailing La Nina. And that’s exactly what we see in the ocean heat content of the tropical Pacific leading up to and following the 1997/98 El Nino:
http://oi40.tinypic.com/9l97wh.jpg
The last two periods highlighted in red in the graph are the “official” NOAA ONI months of the 1995/96 and 1998-01 La Nina events.
ENSO acts as a natural recharge-discharge oscillator.
Regards
Gail Combs says:
July 3, 2013 at 10:57 am
Vukcevic ….. your graphs… could you please label them so a layman understands what he is looking at?
You are right, I often forget to put units label at the ordinate axis, unless it is a regression graph when both labels may be left out. Need to be less sloppy, else will never write a serious research article. My apologies.
mpainter says: July 3, 2013 at 9:40 am
Apparently the subsurface pressure had achieved a sort of equilibrium with weather.
……..
Thanks, an interesting idea. From wiki:
Oceanic crust is significantly simpler than continental crust and generally can be divided in three layers.
Layer 1 is on an average 0.4 km thick. ….
Layer 2 could be divided into two parts:
layer 2A – 0.5 km thick uppermost volcanic layer of glassy to finely crystalline ….
layer 2B – 1.5 km thick layer composed of diabase dikes….
Layer 3 is formed by slow cooling of magma beneath the surface and consists of coarse grained gabbros and cumulate ultramafic rocks. It constitutes over two-thirds of oceanic crust volume with almost 5 km thickness….
http://en.wikipedia.org/wiki/Oceanic_crust
During strong quakes there is a liquefaction of the ground, so it should be expected on the ocean floor too, which may give a new perspective to the change in the balance of forces controlling ocean currents and subsequently the atmosphere above.
p.s.
I am used to the oft repeated battering of my ‘intellectual capacity’ 🙂 🙂
“””””…..RichardLH says:
July 3, 2013 at 5:05 am
Bob: Please try the follwoing. Add a longer running average to the one you have at 13 months in the plot in Fig 1. One say in the 36-48 month bracket. Plot it all simulateously and tell me what you see, if anything…….””””
I betcha that the peaks go down, even further, if you do that. Of course the “data” record has to have 18-24 months clipped off each end when you do that.
Carried to completion, you will end up with just a single “data” point somewhere in the middle.
No idea, what the y co-ordinate of that point will be; but it’s an absolute certainty, that it has no meaning whatsoever.
Personally; I like black on white graphs ; blue just leaves me cold.
george e. smith says:
July 3, 2013 at 2:05 pm
“I betcha that the peaks go down, even further, if you do that.”
Well not really. If you have ever heard of 1/3 octave bandpass splittters with a ‘brick wall’ characteristic applied to temperature data then it does a lot more than show the peaks! High or low. It shows ‘enegry’ diistribution and cyclic behaviour.
“””””…..RichardLH says:
July 3, 2013 at 4:12 pm
george e. smith says:
July 3, 2013 at 2:05 pm
“I betcha that the peaks go down, even further, if you do that.”
Well not really. If you have ever heard of 1/3 octave bandpass splittters with a ‘brick wall’ characteristic applied to temperature data then it does a lot more than show the peaks! High or low. It shows ‘enegry’ diistribution and cyclic behaviour……”””””
“””””…..“””””…..RichardLH says:
July 3, 2013 at 5:05 am
Bob: Please try the follwoing. Add a longer running average to the one you have at 13 months in the plot in Fig 1. One say in the 36-48 month bracket. Plot it all simulateously and tell me what you see, if anything…….””””
So Richard L H;
Since you are the expert on 1/3rd octave bandpass splitters; please point out just where in Bob Tisdale’s 13 month running average filter, is the place HE put the 1/3rd octave bandpass splitters, and just where you want him to put them in your requested 36 to 48 month running average; and just to help my failing eyes; could you point out in Bob’s black and blue graphs, just a few examples of where the peaks increased, rather than decreased, and where you would expect to see peak growth with your 36 to 48 month running average filter. (with 1/3rd octave bandpass splitters of course;) speaking of which: no, I have never heard of them.
But I’m quite familiar with time and frequency division multiplexing, using bandpass filter combs, in either frequency or time domains, for packing more data into broadband data communication fibre optics. I suppose if the communication system called for 1/3rd octave apart sub carriers, that one could use filters of that type. Dunno about the brick walls though; brick walls have a habit of generating overshoot artifacts, that will reduce noise margins, and tend to close down the eye diagram.
But nuff of that; where did Bob Tisdale say he used them in his 13 month running average filter ??
george e. smith says:
July 3, 2013 at 8:13 pm
I would say “calm down dear” but those words are difficult to use now with Prime Minsters getting their hands slapped for using them (interal UK ref).
I have no critisisms of Bob’s work. It appears to be very meticulous.
I do have the required ciruiitry (in simple maths) that can create a ‘brick wall’ approximately 1/3 octave bandpass spiltter of the required characteristics.
This one is completely de-tuned. That is, it is at the opposite end of the spectrum (pun) from ‘normal distribution, multi-cycle, highly tuned filters.
The sort of thing you get with DSP sweeps and the like. Those will never show mixed cycles in the presense of lots of noise. Well not unless you have many, many cycles which we do not have here.
It does show mathematically that there is a cycle in the 28-37 month range. Also a cycle in the 37-49 month range. Now do a sweep and that all will be lost as the 3 and 4 are ‘interger’ mixed. That is to say there are sequencies of 3 with 4 mixed in (as a 7). Not a pretty picture. The first harmonic at 12 years is much clearer (and yes that does show up in the right band). That has only 3 (count them 3) samples in the UAH record. Not what you might call statistical science.
Bo’s record is also short in time terms so, by definition, the reolution will be poor.
I just want to see if these cycles show up in Bob’s figures. If they do I will have found them if three sperarate temperature sources, satellite, land thermometer and water thermometer. Ful, set!
Ok. So here are the results.
http://i1291.photobucket.com/albums/b550/RichardLH/nino34-lowpass_zps0aeec10d.png
http://i1291.photobucket.com/albums/b550/RichardLH/NINO34-Bandpass_zpsce85f520.png
These are effecitivly the outputs from a standard, well known methodology in other fields being applied to temperature data (though it doesn’t care about that).
Splits the ‘signal’ into frequency/period bands with a ‘brick wall’ filter characteristic.
Can also be further extended to get RMS ‘power’ in those bands if you wish.
Caution: No cycles have been addded to the presentation, It is just the data and summaries of that data.
See any patterns anyone?
Fig 1
http://i1291.photobucket.com/albums/b550/RichardLH/UAH-Comparisonofcascadedlowpassfilteroutputmonthsrunningaverage_zpsf1883e44.png
Fig 2
http://i1291.photobucket.com/albums/b550/RichardLH/CET-4YearAverageDailyAnomolyfromAnnual_zpsa1bbe38c.png
Fig 3
http://i1291.photobucket.com/albums/b550/RichardLH/NINO34-Bandpass_zpsce85f520.png
george e. smith says:
July 3, 2013 at 8:13 pm
So George, does your Digital Filter Library include such a circuit? If not I claim it first!
And I think I will leave to much later why the series contains 12,37, 49 which is almost is the exact ratio the main components are separating out into, 12, 37,48 . That just cannot be co-incidence. Numeroligist will have a field day and there must be something linking it all physically.
Ideal digital sampling series for a bandpass splitter in Climate research.
next = rounded(previous*1.3371) starting from 3.
It precisely ‘nulls’ the 12 month signal whilst leaving all of its harmonics and all other frequencies intact.
(The same applies to any sample frequency that has one of the later poles as its direct multiple.)
This is a digital implementation of a ‘brick wall’ cascaded low pass/bandpass splitter circuit (approx 1/3rd octave).
As it is a digital average, it has a ‘square wave’ sampling methodology on the source data.
The well known side effects of this ‘square wave’ sampling are cancelled out by using the 1.3371 inter-stage multiplier.
On the plus side, it has a infinite(?) roll off per octave between stages so the bands are precise, though not tunable.
Also, as it is completely de-tuned in the passbands, it is completely insensitive to internal data distribution ‘in band’.
On the digital side, this is just the well know 3 pole filter arrangement which running means require, extended to the full cascaded filter set.
It can be used on either normalised (at 12 months) or non-normalised data.
When used as a simple 3 stage filter on daily data it can provide a 28 day smooth which is more scientifically accurate than a human Monthly one.
When looking at temperature data, this series and circuit should be used rather than Normals of any period.
Because of the 4 year period it discovers in temperature series, Yearly Normals should be discarded.
When used in Splitter mode (each stage subracted from the previous stage) it provides a ‘DC’/zero referenced view of each passband.
The final stage can be set to ‘DC’/zero or a ramp as required for any very long term trends (such as CO2).
Nodes can be extracted by using, -previous*next between each stage, or other such similar arrangements.
RMS power can be extracted from each passband in the normal way.
The maximum period that can be discovered by this method is limited by the record length and this is a power series. Getting very long cycles will require correspondingly much longer input data!
P.S. Will that do as ‘publishing’ 🙂
Or of course, this could just be the filter series beating with the data but I don’t think so.
“… 12, 37,48 . That just cannot be co-incidence. … ” [RichardLH]
I agree. I wish I could independently verify it. All I can do is say that it is, indeed, intriguing and, I believe, likely significant.
YOU SHOULD PUBLISH YOUR FINE WORK, Richard L. H.. Ask the WUWT scientists how you might do that!
Ask them. Sigh. That’s the easy part, huh? I’m so sorry to see that your thorough and insightful posts above are not being acknowledged at all today. This forum can be very disappointing in that regard. People seem to so quickly move on and there’s no way to “bump” up a post to the top of an active post queue or to create a new thread. I with some of the science giants would respond to you here.
Take heart, Richard L. H., your research has not gone unnoticed (just no comments, I’m sure) and just writing it all down here has helped your brain process your ideas even further which will inevitably lead to new insights.
(wherever you are) HAPPY FOURTH OF JULY!!
Heh, heh, heh… I have a lithp today — “I wish some…” #[:)]
Janice Moore says:
July 4, 2013 at 1:11 pm
Thanks. I have great hopes but it needs others to verify and approve it. At the moment it is just a suggested way of looking at things.
Actually, that should be 12,28,37 and 48(9). All parts of the series relate to the gravitational fields as experienced here on Earth. No complex physics, just simple Gravity (and a bit of fluid mechanics 🙂 hopefully ).
Re. Emile-Geay et al (2012):
“Wavelet coherence analysis reveals a robust antiphasing between solar forcing and Niño-3.4 SST on bicentennial time scales, but not on shorter time scales.”
http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-11-00511.1?journalCode=clim
I think the short scale is there, but maybe they don’t know what to look for. Looking at Nino 3.
I can see anti-phase changes in relation to recent monthly land temperature anomalies (say UK/Europe) and AO/NAO status. http://www.bom.gov.au/climate/enso/indices.shtml
2012 saw cold in Feb, then very warm in March, 2013 saw a warm start to winter, then turned increasingly cold mid Jan into March which was very cold. How do I know these are solar forced? because I made solar based forecasts for these anomalies.