Per Strandberg: The physical forces driving UAH global temperature

Posted: October 13, 2016 by tallbloke in Analysis, ENSO, Forecasting, solar system dynamics

I presented here a while back my research using an Artificial Neural Network analyzing ENSO.

Learn more here http://www.coolingnews.com/the-cause-of-enso

I’m going to write here how it all started, but first I like to show my updated recent ENSO data and forecast which I presented at the recent climate conference in London.

mei-prediction

Fig 1: ENSO result from my ANN. Training period is from 1979 and up to 2005. The testing period is from 2005 and up to the end of 2015. From 2015 and up to the end of 2022 it is a forecast. The red line is the real ENSO value and dark line is the result I got from the ANN. As you can see the dark line is from the average values from ensemble.

zoom

Fig 2: Zoomed up version of the previous graph. As you can see my prediction indicate that the current La Niña is going to deepen and reach it strongest values somewhere around February, March or April.

Something about the background that led me to start to investigate ENSO.  I had learned about Henrik Svensmarks theory of galactic cosmic rays and cloudiness which I taught was a good alternative to the theory of CAGW. At the same time, I saw in the media more and more extreme claims about the coming global warming catastrophe. Eventually I decided to investigate this for myself. I was more interested in looking for data than to read peer review papers. One tool I used was Google’s image function. You search for data and instead of looking for papers you look for graphs in the images function. Then you look at the paper that graph comes from. I quickly found out that the sun’s electromagnetic activity as a climate driver was greatly underestimated.

I had worked with ANN before and know it’s math, so I decided to test it for climate data which I think it is well suited for. I was interested in if CO2 effect could be studied this way and also if GCR according to Svensmark could be effecting the global temperature. One benefit with all the research that has been made in this field is that data are easily collectable is download from the internet. I collected all sorts of possible data that could have effect on global temperature.  I then build an ANN, I put it all together and tested with the in-data going from the previous month and going back 3 years as inputs in the in-going neurons. I then played around with this data and looked if I could get convergence. I tested the network against the global temperature as well as the derivate value of the global temperature. I analyze the result of the derivate value from the network against the derivate of global temperature as measured from UAH as this gives a higher frequency and better statistics. I then started to investigate each parameter individually by registering if they diverge or converge. If they converge I registered the error variance value “the result” for each.

I knew that ENSO affects global temperature, therefore I put its influence on the derivate value of the global temperature to be 100%.

Here are the different parameters in ascending in percent value: SST 110.2%, ENSO 100%, LOD 68.5%, Solar wind speed 49.5%, SOI 45.8%, Kp Magnetic Index 27.4%, Solar wind temperature 26.3%, AMO 22.4%, Ap Geomagnetic index 13.3%, Solar wind density 9.7%, Sunspot number 4.8%, F10.7 radio flux.  4.0%. The exact percent value is not the important point here, but rather the order.

And here are parameters that diverge. In order words, I didn’t get any correlations. Interplanetary magnetic field IMF, Neutron counter -> Galactic cosmic radiation, TSI, PDO.

I would like to stress again that this is results from my ANN on the relations between these parameters and the derivate value of the global temperature as measured from satellite. In other word, this is for short term variations and from pulse like effects. Nevertheless, there are several interesting things that can be said about it.

SST is the global sea surface temperature. That SST has more influence on the temperature than ENSO, makes sense.

LOD Length Of Day which is the same as small changes in Earth’s rotation is affecting changes in Earth’s global temperature anomaly. This may sound a little weird but it makes sense because ENSO and LOD are correlated to each other. In other word, LOD is an ENSO signal. But, why are they correlated?  Well, the most logical reason must be that they are connected by tidal forcing. This was a reason for why I started to investigated possible tidal forcing on ENSO.

Solar wind data and Kp and Ap all show high correlation to the temperature variations. These are all related to electromagnetic variations of the Sun. The correlations with these parameters to temperature variations are all hard evidence that electromagnetic variations of the Sun have an effects global temperature variations.

Next comes AMO or Atlantic Multidecadal Oscillation which is an index over temperature anomaly in the North Atlantic. There are other Oceans indexes which I didn’t examine.

Of less important are the radio flux at F10.7 and the sunspot numbers.

And then there are other parameters that show no linkage to short global temperature changes at all. Among them are TSI which is a measure of the amount of heat beaming down to Earth from the Sun. Note also that the PDO (Pacific Decadal Oscillation) show no linkage to temperature derivate value. There is a reason for this. The definition of PDO is temperature anomaly value north of the tropic in the Pacific Ocean when SST value have been subtracted. This doesn’t mean that it has a long term effect. GCR as measured from the Neutron counter at Oulu university show no correlation with the temperature variations. In fact, my results show that the linkage between solar activity and short term temperature variations is dominated by variations in solar wind and in changes in Earth’s magnetic field.

I have found Artificial Neural Networks or NN for short is a powerful technique for analyzing climate data which depends in many inputs and is subjected to time delays of varying degrees. Alternatives such as statistical regression analysis, frequency analysis and the use of dynamic models to analyze this type of data are all insufficient.

To exemplify this problem, let’s take a look at solar wind data. The temperature derivate response from changes in the solar wind variations is a complex one with different response times. I believe that the solar wind directly influences things like AO and NAO in the northern hemisphere. This is exemplified by phenomena such as sudden stratospheric warming. The response time for this is short usually about a month. But, thing gets more complex when we include the solar winds effects on ENSO. The function of El Niño is that it works as a ventilation mechanism releasing heat from the pool of warm water in western Pacific thru what is called Kelvin Waves which moves warm water toward the East. If this water reaches the surface in eastern pacific we can get an El Niño. This is not always the case as this can be blocked by cold upwelling and the warm water is then being dispersed. These mechanisms are influenced by variations in the trade winds. The normally easterly trade winds in the tropical pacific push warm surface water to the west raising the sea level there and filling it up with a growing pocket of warm water. When what is called the JMO Julian Madden Oscillation is positive in the western pacific in an area called the Kelvin Wave Generation Area then the trade winds change direction and release the water pressure which has built up the higher water level in this area and Kelvin Waves are usually generated. JMO indicates an area in the tropics with enhanced convections. This area of convections moves counter clockwise around the equator. This convection area makes an orbit around the Earth during a period of about 30 to 90 days. I expect that JMO variations is mainly driven by lunar gravitational Perigee pulses and from variations in the electromagnetic variations of the sun, but I haven’t had time to analyze this yet. So part of the changes in solar wind affect the ENSO index while it has an effect on the trade winds. So the solar wind affects the trade wind, say after one month. This lead to the generation of a Kelvin Wave after an additional month. Then this kelvin Wave reaches the surface in the Eastern Pacific “sometimes” after about 3 months and we get an El Niño. The effect from the added humid air during El Niño then affect the global temperature anomaly after about 5 months. The result in my NN that is generated from solar wind variations is thus from an aggregated sum of different time lags which includes it response from its effect on ENSO.

This kind of correlations is almost impossible to do with other methods. I guess, if one use, for example, statistical linear regression and analyses values from individual time lagged months it could be possible to find some weak correlation.

So why do not more people use NN to analyze similar complex relationship where climate and weather related phenomena seems to be ideal?

One reason is that it is complex and takes time to work with NN. And while there it is possible to buy NN software from the selves it is not easy to use especially when the user is unfamiliar with the underlining mechanism.

It is more of a kind of handicraft skill that one need to utilize the full functionality of an NN.

In my case it was about 4 years ago that I discovered that the connection between lunar cycles and ENSO variations was thru the seemingly chaotic variations during individual Lunar Perigee gravitational pulses which was the main driver of ENSO variability. I have still a way to go until I’m completely satisfied with my result. When that is done I can quickly examine other related ENSO indexes and other types of climate data. I just switch from the MEI ENSO to whatever parameter I want to investigate without adding extra program code.

During the following 4 years I have improved and tested different ideas thru successive baby steps. I have now very good results and as I believe that I also have created good forecast for the current expected development of ENSO several years into the future.

While, I’m not here going into how NN works in detail, I’m going to describe some basic principles how it’s works. You find easily information how NN works on the internet. Neural network is built around asymptotic transfer functions in a network. In order to make it work, the network has first to be trained. In my case I use an initial training period where thru successive modification of several hundreds of weights which regulates hundreds of asymptotic transfer functions. The goal with an algorithm I use is to minimize the variance value between the calculated output from the network and the real ENSO value calculated for each month in the training period. At the same time during this calculation I use a test period where I also calculates the variance value in the same way except I use the same weight values which has been calculated in the training period. Not the test part. The goal is to not only minimize the variance value during the training time period but also to minimize the variance for the test period. The variance for the test period is usually converging in the beginning but eventually it starts to diverge because of statistical noise after many iterations. At that time or just a time before that time, the weight values are saved and a recalculation based in the weight values can be made for the ENSO including for a forecast period. I have thus been successful in identifying the underlining forces that is behind ENSO variability by eliminating noise sources or suppress them and by amplifying data which contains correlations between in and output of the NN. I have employed innovative and unorthodox methods so that the NN can differentiate between noise and signals which contain correlations. Nothing in set in stone.

The fact that I have identified the main drivers of ENSO variability, and yet the mainstream climate community has not, raises an interesting question: why haven’t they included variations in the electromagnetic solar activity in their GCM models? After all, if you look at correlations between electromagnetic solar activity and variations in global temperature anomaly on a decadal scale you find a good fit. But first you have to compensate for the current temperature data manipulation by GISS.

 __________________________________

Note: On the temperature spike during the recent El Niño.

While the strength during the resent El Niño was weaker than that of the El Niños of 1982-83 and 1997-98 the recent El Niño was a slow starter with near Modoki El Niño during 2014-15 which warmed the surface in the pacific and tropical air masses. Similar effect to ENSO exist also in the tropical Indian Ocean and tropical Atlantic. The response time is different and weaker. Because this El Niño’s had a slow start, which also included a Modoki phase (westerly displace El Niño), all the tropical water was warmer than normal. This was not the case during the previous stronger El Niños which started quicker and from negative ENSO values.

Comments
  1. oldbrew says:

    Re Fig. 2 above:
    ‘The Climate Prediction Center (CPC), an agency of the National Weather Service, in a monthly forecast pegged the chance of La Niña developing this fall at 70 percent, versus a likelihood of neutral conditions forecast last month.’
    http://www.thegwpf.com/la-nina-uncancelled/

    Leaning in favour of the forecast above.

  2. Paul Vaughan says:

    A useful diagnostic if you explore before 1980 is the BDO (bidecadal oscillation). ENSO does not have a BDO, but global average temperature does.

    On methodology — NN versus or complementary to or whatever to whatever:

    Most of the exploration we’ve seen does not use sufficiently generalized methodology. Exploratory progress is being constrained by unnecessary assumptions (built into artificially narrowed versions of more generalized methods). It’s not the methods that are the problem. It’s the set of assumptions being used by practitioners to artificially narrow the pool of possible insights. (Advisory: Some agents are doing this on purpose to help control the political narrative.) An honest discussion about this is an extremely philosophical topic. There will never be time, especially given how contaminated posturing is by the toxic politics. The sensible thing to do is be aware. I’m not suggesting we discuss this further. There literally isn’t time.

    Hindcasts before 1980 is the main curiosity l’m left with after noting the earliest date on the graphs above.

  3. tallbloke says:

    If Per’s forecast turns out correct, we are in for a La Nina followed by sustained busrsts of El Nino conditions.for the next several years.

    This kind of fits with my contention that when the Sun goes quiet, the ocean takes the opportunity to shed heat. The problem is that the ARGO data is now so compromised with the adjustments and buoy exclusions that we probably won’t see the concomitant fall in ocean heat content that should accompany such conditions. Except perhaps in real world indicators such as sea ice and ice in the great lakes.

  4. One of the next steps I’m going to take, is to use in-data going back to 1950. That way I’ll improve my statistics. I’m not sure however that the data for the MEI is correct so long time back. I’m guessing some of the data is mostly based on the SOI index. I have also other ideas I’m going to implement starting to test in the coming days. My focus is mostly on making my forecast as good as possible, not so much on hindcasting. I think there are improvements I can make on the data over the strength of El Niño peaks. I got the recent El Niño right except I missed the size of its strength. I guess the next high value for ENSO during the beginning of 2018 is too high as the warm pool in the Western Pacific has been depleted after the recent El Niño period. Time will tell.

  5. erl happ says:

    Good to see people looking at the data.

    These variables are indeed closely related to global temperatures: SST 110.2%, ENSO 100%, In including this data one will always get a strong correlation. LOD 68.5%, is a measure that relates to atmospheric variables and is getting closer to a mode of causation. It should relate directly to the strength of the zonal wind.

    I suggest that the chain of causation involves the temperature of the stratosphere that relates directly to its ozone content. Specifically, look at the temperature of the stratosphere at the winter pole and its relationship to sea surface temperature between the equator and the 50th parallel.Good historical data here: http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl

    Sea surface temperature will relate strongly to surface atmospheric pressure in the southern hemisphere where the bulk of the ocean is to be found.

  6. RJ Salvador says:

    This is excellent work and a fascinating read. The model presented by Pers is much more detailed than the one I put forth based on Luni-solar tidal frequencies. I did not use MEI-ENSO data so to compare forecasts I put MEI-ENSO data into my correlator. Below is the result over the same time period as Pers and they make similar predictions though mine is less bullish on the next El NIno.

    Based partially on the forecast of this model months ago I invested in oil and natural gas. I am ahead for now basically for political economic reasons but climate is a big driver so I am hopeful of an even better out come. Pers results has boosted my confidence a great deal.

    The full correlation of MEI-ENSO from 1870 to now is below. The fit is R^2=0.65. Good enough for investment purposes.

  7. Frederick Colbourne says:

    I recently came across a paper on an 18.6-year lunar tidal cycle that affects sea level.

    Baart, Fedor, et al. “The effect of the 18.6-year lunar nodal cycle on regional sea-level rise estimates.” Journal of Coastal Research 28.2 (2011): 511-516.

    Full text PDF on Researchgate.

    Worth a look.

  8. Bamse says:

    This looks interesting though it’s not clear how you’ve built the model – well, at least to me :). I have a few questions:

    1) What type of neural network are you using? I’m assuming some kind of recurrent net?
    2) How are you extrapolating the forecasts into the future? Is it due to the type of network architecture (recurrent) or is it the result of many models, each with a different target (i.e., model A predicts 1 month ahead, model B 6 months etc.)
    3) I gather from what you’ve written the target is the 1 step ahead change in the ENSO value, is that correct? If so, are you integrating the resulting model output for the charts?
    4) When using a training, validation and test set it’s very easy to end up over-fitting the validation set when doing model and feature selection. What happens when you run a walk-forward fitting procedure?
    5) Why won’t a vanilla linear/non-linear regression model produce a similar result?

    I’m probably barking up the wrong tree but it looks like you have a very short out-of-sample (test) period with which to compare predictions with actuals (end of 2015 to Oct 2016). Critics might argue that a naive Enso(t+1)=Enso(t) would do just as well.

    I think the model would gain more traction if you could show the result of a walk-forward expanding window forecast with at least 30 years out-of-sample to compare with actuals. The difficulty is that many people will assume (probably incorrectly) that you’ve over-fitted the data – especially those who learnt about NNs in the 80s-90s 😉

    Just to clarify, the approach looks really interesting. In my view the most persuasive argument against current dogma (if that’s what it turns out to be) will be accurate models that predict on shorter timescales – though I agree with PV’s comments on this subject.

  9. Ian Wilson says:

    Per Strandberg,

    You say that:

    “I expect that JMO [Madden-Julian Oscillations] variations is mainly driven by lunar gravitational Perigee pulses and from variations in the electromagnetic variations of the sun, but I haven’t had time to analyze this yet.”

    “In my case it was about 4 years ago that I discovered that the connection between lunar cycles and ENSO variations was thru the seemingly chaotic variations during individual Lunar Perigee gravitational pulses which was the main driver of ENSO variability.”

    Yet you present these assertions with little or no evidence to back up these claims. In fact I have only seen you claiming these explanations after I posted the following to WUWT. Could you please explain why this is the case?:

    MY APRIL 03RD 2016 POST AT WUWT

    Ian Wilson April 3, 2016 at 7:52 pm

    Moderate to strong El Nino events are triggered by long-term (i.e. inter-annual) variability in the lunar tides. Specifically, the timing of these events is directly related to 31/62 year Perigee/Syzygy lunar tidal cycle.

    I do not have all the answers as to how this actually happens but the best answer that I can come up with is that slow forcings applied to the Earth by the lunar tides influences the formation and subsequent propagation of Madden-Julian Oscillations (MJO) along the Equatorial Indian Ocean and Pacific Oceans.

    A MJO consists of a large-scale coupling between the atmospheric circulation and atmospheric deep convection. When a MJO is at its strongest, between the western Indian and western Pacific Oceans, it exhibits characteristics that approximate those of a hybrid-cross between a convectively-coupled Kelvin wave and an Equatorial Rossby wave. When a MJO moves from the western Indian Ocean into the western Pacific Ocean, it generally accelerates, becomes less strongly coupled to convection, and transitions into a convectively de-coupled (i.e. dry) Kelvin wave.

    Periodically (i.e. roughly once every 4.5 years), the precise alignments of the lunar tidal forcings produce the right conditions that result an upsurge in the number and magnitude of what I call Pacific Penetrating MJO. These are MJO events that travel from the Eastern equatorial Indian Ocean, along the Equator, all the way into the Western Pacific Ocean, where they initiate Westerly Wind Bursts (WWB’s).

    The spawning of these WWB’s takes place as the MJO event is transitioning from a hybrid-cross between, a convectively-coupled Kelvin wave and an Equatorial Rossby wave, and a convectively de-coupled (i.e. dry) Kelvin wave. The spawning of the WWB’s occurs in the Western Equatorial Pacific Ocean, somewhere between 60O E and 150O W longitude. The actual process involves the formation of a typhoon/cyclone pair straddling the equator which produces an intense WWB between the two intense low pressure cells.

    The onset of El Nino event are marked by the weakening of the easterly trade winds associated with the Walker circulation. The actual drop off in easterly trade wind strength is always preceded by a marked increase in WWB’s in the western equatorial Pacific Ocean. The WWB’s help initiate an El Nino event by creating downwelling Kelvin waves in the western Pacific that propagate towards the eastern Pacific, where they produce intense localized warming, as well as by generating easterly moving equatorial surface currents which transport warm water from the warm pool region into the central Pacific.

    The net result of the Moon’s involvement in the initiation of El Nino events means that:

    El Niño events in New Moon epochs preferentially occur near times when the lunar line-of-apse aligns with the Sun at the times of the Solstices.

    El Niño events in the Full Moon epochs preferentially occur near times when the lunar line-of-apse aligns with the Sun at the times of the Equinoxes.

    For a full description of the meaning of Full and New Moon Epochs please read:

    http://astroclimateconnection.blogspot.com.au/2014/11/evidence-that-strong-el-nino-events-are_13.html

  10. Ian Wilson says:

    You will note that in Per Strandberg’s last post on this subject in November of 2015, he does not mention Madden-Julian Oscillations (MJO) nor westerly wind bursts (WWB’s).

    https://tallbloke.wordpress.com/2015/11/28/per-strandberg-enso-caused-by-tidal-pulses-during-perigee-and-by-solar-activity/

    Indeed he gave the following explanation f the connection between Luna tides and the the El Nino phenomenon:

    “In my view, Lunar perigee pulses are the somewhat irregular heartbeats that drives ENSO and act as the main engine of ENSO variability. I think that the lunar perigee pulses push the Pacific gyros to either accelerate in their speed or slow down depending on the strength of these pulses and the angle of the pulse vectors against the equator. At perigee the moon’s angular speed is over 14 degrees per day which cause this effect to by transient with a small time window. The result is that the lunar perigee pulses has a very precise and distinct effect on ENSO from one pulse to the next, yet it gives a seemingly chaotic effect over time. By combing the lunar perigee pulse effect with solar variability most of the change of ENSO can be explained.”

    It would appear that he has just co-opted my April 2015 explanation and added it to his “model” with no attribution to my work.

    We now [13/10/2016] get an updated explanation of the connection between lunar tidal pulses at perigee and El Ninos that reads:

    “When what is called the JMO Julian Madden Oscillation is positive in the western pacific in an area called the Kelvin Wave Generation Area then the trade winds change direction and release the water pressure which has built up the higher water level in this area and Kelvin Waves are usually generated. JMO indicates an area in the tropics with enhanced convections. This area of convections moves counter clockwise around the equator. This convection area makes an orbit around the Earth during a period of about 30 to 90 days. I expect that JMO variations is mainly driven by lunar gravitational Perigee pulses and from variations in the electromagnetic variations of the sun, but I haven’t had time to analyze this yet.”

    Amazing isn’t it.

    Yet we have still NOT been presented with any evidence to back up these assertions.

  11. Chaeremon says:

    @Frederick Colbourne (October 14, 2016 at 5:56 am):

    Thanks for mentioning this paper, quite a wealth of information with comparison between model and observations.

    @Per Strandberg, I’m interested in the perigee data points you feed into your NN, can they be downloaded? TIA

  12. I know that it has been known for some time that Moon cycles is effecting ENSO, at least outside of the climate community. Salvador ‘s forecast based on lunar cycles is better in estimating the sizes of El Niños which shows to me that the problem with estimating the size of El Niño peaks should be easily solvable by me. I just extend the calculations back in time. One thing I plan to do is to create shorter term forecasts, such as forecast for 1-year, 2-year and 4 year forecasts. I plan to do this as a time series forecast where the inputs I use is from combination of real ENSO data and the ENSO result I received earlier thru my previous ENSO forecast. The real ENSO data goes up to the current date and the calculated ENSO data from my previous calculation also include the forecast period. By doing that I should get very accurate forecasts for the near time.

  13. tchannon says:

    This is meant to be constructive: –

    I am unhappy when there seem to be direct or indirect claims of causal where that is very unlikely to be true. A typical case is ‘index xyz’ causes temperature. Does the phase evidence back this up, no?

    If you can tease out any phase information this might suggest where to look.

    In my opinion most of the wobbling in the index data is down to both chaotic and resonant effects. A wildcard which I have not written about yet is how experimental data and index data show the same thing, caused by top heating.

    TSI is far more complex than it seems at first sight: spectral variations mean that the TSI data is “wrong”, particularly there is strong UV change. The effect spectrally on earth is inconsistent, non-linear. There is little historic data on UV and even today satellite data is of dubious worth, reliability issues.

    LoD is a tricky one. About four years ago I published an article showing a strong phase relationship between polar ice and LoD ( 5 months), the implication being this is seasonal mass transfer of water. The ballerina effect does the rest.
    The idea was disputed, particularly by those who think wind causes the spin rate change yet so far as I can see there is no phase confirmation. Wind has enough mass to do much?
    https://tallbloke.wordpress.com/2012/06/27/lod-linked-to-solar-radiation-proxy-polar-ice/

  14. Ian Wilson says:

    If you go to this site called Cooling News you will see that Per Strandberg makes a posted on January 5th 2013.

    http://www.coolingnews.com/artificial-neural-network-weather-climate.html

    This provides a link to a web page:

    enso-and-tidal-forcing.htm

    which takes you to the url:

    http://www.coolingnews.com/the-cause-of-enso

    This is a blog post prior to April 24 th 2013 where he says in intends to investigate “the mechanism of Kelvin wave”.

    “After that, I want to improve on my result by using more precise and accurate tidal calculations. I have found a program from which I can make precise calculations of the Moon and the Sun on a daily basis. Other factors I plan to look into are the mechanism of the Kelvin wave, Walker circulation and MJO which all should influence ENSO to some degree.”

    THEN

    Sometime after JUNE 2016 Per Strandberg puts up a blog post – citing his “independent discovery”
    linking lunar perigee pulses to Kelvin Waves in the Pacific. We know that this post must have been after JUNE 2016 because he uses real data up this date.

    QUOTE
    “Here’s a close up picture over ENSO predictions up to 2022.The ENSO value is for the real MEI value up to and including June 2016.”

    Unfortunately this is more than two months after I posted this discovery at WUWT on April 03rd 2016.

    https://wattsupwiththat.com/2016/04/03/how-much-of-global-temperature-increase-is-due-to-el-nino/

    How Much Of Global Temperature Increase Is Due To El Niño?
    Anthony Watts / April 3, 2016

    Ian Wilson April 3, 2016 at 7:52 pm

    Unless Per Strandberg can point to evidence that shows he made this discovery before Apr 3 2016
    then he is falsely claiming that he is the first to make this discovery.

    I am more than happy to concede that he has found this result if he can show me any on-line or published evidence that he knew of this result prior to June 2016. If not then he must start acknowledging that I made this discovery first and that he has:

    (a) copied it from me without citation
    (b) independently stumbled across the same result.

  15. Poly says:

    Yup Ian, I am supporting you here.

  16. tallbloke says:

    Ian, I note your comment at WUWT elicited no relevant followup comment. It’s a dialogue of the deaf over there.

  17. RJ Salvador says:

    MEI-ENSO and ONI-ENSO etc. are human constructs. The indexes are designed for a zero sum over time. Baseline changes of temperature up or down are averaged out over 30 years. Therefore the solar influence raising the temperature or lowering the temperature over a long period of time will not be evident in these indexes as it has been removed.

    To make it clear the frequencies used in the model I presented above were proposed by Ian Wilson both on his website, his papers, and discussion at Tallblokes Talkshop with Paul Vaughan.

  18. tallbloke says:

    Tim C: The idea was disputed, particularly by those who think wind causes the spin rate change yet so far as I can see there is no phase confirmation. Wind has enough mass to do much?

    I’ve thought LOD changes are externally imposed by Jupiter/Venus/Moon since 2008. I think R.J.s model pretty much confirms that. (When are we due another bi-monthly update R.J.?)

    I think the reason others came to the conclusion it was wind driven was due to the synchronicity of LOD change and solar change. The wild card is that solar wind may affect LOD via interaction with geomag via a back-EMF. Magnetism is a much stronger force than gravity, but solar wind is tenuous, and I don’t know how to quantify the force involved.

    That the same planetary and lunar frequencies are involved in R.J.s ENSO model is the icing on the cake. What I said in my presentation of R.J.s models in London was that once we can unify the three models, solar, LOD and ENSO, we will have strong evidence for our solar-planetary-climatic theory.

    http://bambuser.com/v/6448689

    Ian and Paul’s work in particular has been fundamental in the development of the relevant periods these models use. It’s a triumph of collaborative scientific work, voluntarily undertaken by people with no axe to grind, no financial imperatives (apart from eating), and in a spirit of shared discovery. Per Strandberg has arrived at a similar conclusion from another direction, which is a fitting confirmation of our work here. I expect he’ll let us know how he got to the Lunar Perigee key to his model.

  19. Paul Vaughan says:

    So far as I understand wuwt & ce exist to help one or a few individual elites protect their financial investments from political change (by having a small crew of agents apply crude tools like harassment to herd readers onto an oversimplified lukewarm path).

    These few elite are not the few who matter on the Pareto Principle. Rather the few who matter are luminaries (and not necessarily elite) driven to explore and understand beyond artificial boundaries.

    Given the darkness of the campaigns we’ve seen, boycotting commentary at wuwt & ce is the only sensible option. I do Ctrl-F “ill ill” to hunt for Bill Illis commentary in threads where I suspect he will comment. Aside from that I’m only using wuwt to monitor for any climate news worthy of independent exploration. I do make one exception: When Milankovitch comes up I quick-hunt for insightful graphs.

    Without judging, I’m copying/pasting Ian Wilson’s comment to here where it has a better chance of reaching the few luminaries who actually matter. The few luminaries who actually matter are not beholden to the darkly misguided financial planning of a few elites who are causing the world a lot of problems.

    =
    Ian Wilson
    April 3, 2016 at 7:52 pm

    Moderate to strong El Nino events are triggered by long-term (i.e. inter-annual) variability in the lunar tides. Specifically, the timing of these events is directly related to 31/62 year Perigee/Syzygy lunar tidal cycle.

    I do not have all the answers as to how this actually happens but the best answer that I can come up with is that slow forcings applied to the Earth by the lunar tides influences the formation and subsequent propagation of Madden-Julian Oscillations (MJO) along the Equatorial Indian Ocean and Pacific Oceans.

    A MJO consists of a large-scale coupling between the atmospheric circulation and atmospheric deep convection. When a MJO is at its strongest, between the western Indian and western Pacific Oceans, it exhibits characteristics that approximate those of a hybrid-cross between a convectively-coupled Kelvin wave and an Equatorial Rossby wave. When a MJO moves from the western Indian Ocean into the western Pacific Ocean, it generally accelerates, becomes less strongly coupled to convection, and transitions into a convectively de-coupled (i.e. dry) Kelvin wave.

    Periodically (i.e. roughly once every 4.5 years), the precise alignments of the lunar tidal forcings produce the right conditions that result an upsurge in the number and magnitude of what I call Pacific Penetrating MJO. These are MJO events that travel from the Eastern equatorial Indian Ocean, along the Equator, all the way into the Western Pacific Ocean, where they initiate Westerly Wind Bursts (WWB’s).

    The spawning of these WWB’s takes place as the MJO event is transitioning from a hybrid-cross between, a convectively-coupled Kelvin wave and an Equatorial Rossby wave, and a convectively de-coupled (i.e. dry) Kelvin wave. [The spawning of the WWB’s occurs in the Western Equatorial Pacific Ocean, somewhere between 160 deg E and 150 deg W longitude.] The actual process involves the formation of a typhoon/cyclone pair straddling the equator which produces an intense WWB between the two intense low pressure cells.

    The onset of El Nino event are marked by the weakening of the easterly trade winds associated with the Walker circulation. The actual drop off in easterly trade wind strength is always preceded by a marked increase in WWB’s in the western equatorial Pacific Ocean. The WWB’s help initiate an El Nino event by creating downwelling Kelvin waves in the western Pacific that propagate towards the eastern Pacific, where they produce intense localized warming, as well as by generating easterly moving equatorial surface currents which transport warm water from the warm pool region into the central Pacific.

    The net result of the Moon’s involvement in the initiation of El Nino events means that:

    El Niño events in New Moon epochs preferentially occur near times when the lunar line-of-apse aligns with the Sun at the times of the Solstices.

    El Niño events in the Full Moon epochs preferentially occur near times when the lunar line-of-apse aligns with the Sun at the times of the Equinoxes.

    For a full description of the meaning of Full and New Moon Epochs please read:

    http://astroclimateconnection.blogspot.com.au/2014/11/evidence-that-strong-el-nino-events-are_13.html
    =

    Edited [ ]

    “The spawning of the WWB’s occurs in the Western Equatorial Pacific Ocean, somewhere between 60O E and 150O W longitude.”

    to

    =
    astroclimateconnection
    April 3, 2016 at 8:03 pm

    Of course that should have read: “The spawning of the WWB’s occurs in the Western Equatorial Pacific Ocean, somewhere between 160 deg E and 150 deg W longitude.
    =

  20. Paul Vaughan says:

    It must be a US presidential election year. The torrent of misunderstandings floods so fast no one can correct it. We’re forced by necessity to leave the record wrong. I see the utility of the tactic.

    Where to even start?…

    Kinetic energy is not mass.
    Multidecadal is not semi-annual.
    Temperature is not energy (LATENT).
    Aggregation criteria affect pattern.
    Solar wind reshapes chemistry gradients and direction.

    …and on and on and on.

    Hmm… what do to about all of these misunderstandings…
    I know: I’ll go hiking…

    [ :

    Well, at least a bunch of interesting ideas appear side-by-side. Luminaries will sort through it quietly on their own.

    I noticed Pukite & Strandberg having an exchange on Azimuth (by following a link trail from contextearth).

    Without engaging in argument (always a totally unproductive black hole for precious time) I’ll post a few notes I think will help with clarity of perception, including notes on El Nino Modoki and spatiotemporal aggregation criteria more generally.

    Regards

  21. Answer to Bamse!
    Unfortunately, I can’t answer detailed questions of my NN software or on my approach as this may have a monetary value for me sometime in the future. After all I have to pay my bills. But I will try to answer general questions here.

    Answer to 2) I have as in-data, data going up to 2022, well actually up to 2030 while I don’t display that result here. So having in-data into the future is not difficult as I have the Lunar Perigee data calculated based on the positions and distances of both the Moon and the Sun which are known exactly far into the future. It’s a little trickier for magnetic variations of the Earth and solar wind variations. I can’t know those values into the future. But I know their overall trend. So what I do is that I draw a yearly trend line for each year into the future and add stochastic noise to those values. I base this trend-line on a combination of historical data and the fact that the current solar cycle is weak and that the next cycle also is expected to be weak. Remember also that the Lunar perigee pulse effect is the dominant forcing and the effects from the Sun is a bit weaker.

    4) Yes, I get an overfitting effect, but that is mostly in the training period. Overfitting like that comes with the territory of NN technology. But in the testing period this effect is very small and is eliminated for the forecast period. The reason for this is because the input data for each run of the ensemble is randomly selected and the solar wind and magnetic values for the forecasts are unique for each run with unique seeds for the added noise of those data sets.

    5) How should I answer that one. Well, I tried to describe this in my post above. But the simple answer is that the output signal is a results from superimposed large sum of signals from a series of asymptotic transfer functions with different time lags. Sure, you could get some correlations, but then they probably wouldn’t be significant enough.

    I extended the test period for my latest result and included independent ensemble results from which I calculated the average ENSO value. That makes the current verification period from the beginning of 2016 and up to now very short, as you remarked.
    But, I have previous result which display longer verification period. In Calc12 I have the test period from 2005 and up to the end of 2011. In Calc15 I have the test period from 2005 and up to the end of 2014.

  22. Answer to Ian Wilson
    You claim that I have copied and paste discoveries you have made. This is not the case as I don’t follow your work.
    The source for my conclusion or suggestion that MJO is driven by the same forces which drive ENSO changes is from a fantastic YouTube resource, which I follow. There is one guy, I think in California, which publish videos once every week, which I have followed for well over a year. If someone should be credited for my suggestion for the tidal connection to MJO, it should be him.
    The first 10-15 minutes he talks about surfing condition and wave heights around the Pacific Ocean. In the rest of these videos he examines almost all available data sources connected to ENSO, including MJO and he looks into the current forecast for MJO and when the next positive index for MJO in the Kelvin Wave generation area might occur, which is the source for WWB and Kelvin Waves.

    Of course he doesn’t look for Lunar Perigee Pulses and its connection to ENSO. But, because MJO variation in the Kelvin Wave Generation Area is the main source for Kelvin Waves and Kelvin Waves are the main fuel for El Niño events it was like putting 1 and 1 together and get the number 2. By following his videos over time I have attained deep knowledge of parameters related to ENSO.

  23. Answer to Chaeremon
    I haven’t a download site You can mail me and I will send over this file.
    Right now my effort is to improve my ANN so that my forecast becomes as good as it possible can be.
    Then I’m going to publish my result in a scientific publication. At the same time, I’m going to make these files public and publish tighter with source codes the calculations I make to get the Perigee Pulse data right.
    I should be able to find my email on my website

  24. Ian Wilson says:

    Per Strandberg,

    You seem to have overlook an exchange we had on December 03 2015 – right here at Tallbloke’s talkshop:

    https://tallbloke.wordpress.com/2015/11/28/per-strandberg-enso-caused-by-tidal-pulses-during-perigee-and-by-solar-activity/

    astroclimateconnection says in response to a question:

    December 3, 2015 at 12:50 am
    “How does a tidal force pull the water to one side of the planet without reducing it on the other?”

    Simple, the lunar tidal forces produce an increased number of convectively-coupled equatorial Kelvin waves in the western Indian ocean that become Pacific Penetrating Madden Julian Oscillations that set off a series of westerly wind bursts in the western Pacific ocean that eventually triggers an El Nino event.

    More on this in my upcoming paper.

    ***************************

    Here is your reply to my post. Note that you make NO mention of Kelvin Wave or the MJO. In fact you just restate what you said on your web cite in 2013.

    Per Strandberg (@LittleIceAge) says:
    December 3, 2015 at 7:12 pm
    Hi!
    In my view, Lunar perigee pulses are the somewhat irregular heartbeats that drives ENSO and act as the main engine of ENSO variability. I think that the lunar perigee pulses push the Pacific gyros to either accelerate in their speed or slow down depending on the strength of these pulses and the angle of the pulse vectors against the equator. At perigee the moon’s angular speed is over 14 degrees per day which cause this effect to by transient with a small time window. The result is that the lunar perigee pulses has a very precise and distinct effect on ENSO from one pulse to the next, yet it gives a seemingly chaotic effect over time. By combing the lunar perigee pulse effect with solar variability most of the change of ENSO can be explained.
    I’ve decided to go out with this information and to publish data and calculation related to the lunar perigee pulses so that this goes out into the public domain.

    I have to assume from this that you have no evidence of your claim prior to JUNE 2016. Hence, I will be publishing my paper with NO reference to your work since I cannot cite any published by you. I would have considered highlighting your work in my submitted publication but you clearly have just taken my idea and claimed it as your own with no citation of my work.

  25. Paul Vaughan says:

    One of many great things about the Talkshop is that it’s free of the nasty type of exchanges common at the dark venues.

    Of interest to many will be the timescale highlighted by figure 5 here:
    http://climatologie.u-bourgogne.fr/perso/bpohl/Publications_files/DPRNLN2016.pdf (Is that SOLAR wind signature in African rain?…)

    And look what’s going on with this group of familiar folks:
    https://www.climatescience.org.au/sites/default/files/Wedpost%20-%20Henley_ENSOworkshop_2slides.pdf (IPO tripole index = TPI)

    …It’s like they’re following the Talkshop and getting neat ideas from here and then doing formal publication without giving credit. I’m flattered!

    Also related to what we’re discussing here:
    https://tallbloke.wordpress.com/suggestions-22/#comment-120408

    That’s about 13.68233104 = φ/(J+S) showing up in a free-access LOD EEMD paper flagged by Pukite at contextearth. It won’t be any surprise to RJ.

    There are 2 more points I’ll throw into the discussion to provoke strategically. Finding time to say it how I want to is impossible ….but better to at least obliquely provoke than say nothing.

  26. Paul Vaughan says:

    These authors suggest modeling ENSO alone is NOT enough and that it needs to be paired with a model of Modoki:

    2016 – Reinspecting two types of El Nino: a new pair of Nino indices for improving real-time ENSO monitoring

    It’s free access.

    It’s probably the most comprehensive article on Modoki to date.

    I’ll have a lot more to say about this on Suggestions NEXT month.

  27. oldbrew says:

    PV: one of the authors of the climatescience.org.au paper is Joelle Gergis aka ‘Data Torturer’ according to Climate Audit.
    https://climateaudit.org/2016/07/21/joelle-gergis-data-torturer/

  28. Paul Vaughan says:

    You don’t recognize the other names? Do you realize why they’re on that trail?

  29. oldbrew says:

    No, I just remember complaining once to the Guardian that having made a big splash about it they hadn’t reported that a ‘Gergis et al’ paper had been withdrawn mainly due to Climate Audit pointing out some of its faults.

  30. Paul Vaughan says:

    OB, a tip: I advise against blindly trusting climate audit. Suggestion: Run your own checks first hand. In the one serious exchange I had with the author there I found him to be incompetent and bluffing. It was about something really simple, so I was surprised. I only knew the character by reputation, never having explored his work. I immediately became very suspicious about why he has so many fans given the magnitude of the blindspot I discovered within a few sentences. It’s a mystery I’ll never have time to explore, but after that one exchange I can tell you I decisively do not trust that character. My impression was that he did not want to admit that he didn’t have a clue in front of the audience. I recall that there was one other character present with lucid awareness that he was bluffing.

    – –

    I will be curious to see if Per Strandberg takes up multivariate modeling. Related: I’ll also be curious to see if questions raised by Pukite at Azimuth are addressed.

    Regards

  31. Geoff Sharp says:

    Know how you feel Ian, today I learned that Archibald & Fix are trying to rip off my theory in their latest paper. Luckily I am already published.

  32. RJ Salvador says:

    TB asked: When are we due another bi-monthly update R.J.?

    I put an update in suggestions 21 on September 30th. The LOD data published online always lags by about one month. So the next update will be at the end of November for data available up to the end of October.

    I am pointing out here again (as it is related) the remarkable coherence of the ONI-ENSO to the residual of the LOD model.
    Just consider the LOD model to be an exercise to get a linear result for LOD by passing a curve through it. The difference between that curve (the model) and the actual LOD is shown below along with its 120 day rolling average. (the residual)

    The coherence of the ONI-ENSO to the rolling average of the residual is remarkable as shown below.

    So if one believes that the LOD model accounts for the bulk of the solar-planetary and luni-solar forces interacting with the earth we are left with a residual that looks a lot like the ONI-ENSO. If one believes the residual is the ONI-ENSO then it also adds to or lessens the LOD.

    If one also believes that same luni-solar planetary forces that cause the bulk of the LOD also cause the ONI-ENSO we have an interactive rotational system between the LOD and the ONI-ENSO.

    The interaction between them makes for interesting speculation without even considering changing spatial features on the earth over time.

  33. Here are the different parameters in ascending in percent value: SST 110.2%, ENSO 100%, LOD 68.5%, Solar wind speed 49.5%, SOI 45.8%, Kp Magnetic Index 27.4%, Solar wind temperature 26.3%, AMO 22.4%, Ap Geomagnetic index 13.3%, Solar wind density 9.7%, Sunspot number 4.8%, F10.7 radio flux. 4.0%. The exact percent value is not the important point here, but rather the order.

    And here are parameters that diverge. In order words, I didn’t get any correlations. Interplanetary magnetic field IMF, Neutron counter -> Galactic cosmic radiation, TSI, PDO.

    I think many of the findings would have different values if the sun were in a prolonged protracted minimum period of solar activity.

    In particular I would venture to say correlations would be shown between the IMF, Galactic Cosmic Radiation, and TSI.

    In addition stronger correlations would be present in items such as the AP INDEX, and SOLAR FLUX etc.

    My claim is the 11 year sunspot so called normal cycle and the climate will not show a relationship because the noise in the climate system obscures the slight solar changes not to mention the variations within the 11 year sunspot cycle from maximum to minimum conditions cancel each other out.

    Only when the sun enters extreme prolonged periods of inactivity or activity for that matter are those two issues nullified and hence a solar /climate connection is able to be established. It is no longer obscured.

    I have come up with the minimum solar parameters needed in order to accomplish this by looking at the historical climatic record and how it has responded to solar activity. It shows each and every time the sun enters a protracted period of extreme inactivity the response in global temperatures has been down.

    That is fact and until data shows otherwise I think the case for a solar/climate relationship is strong.

    In addition the sun drives the climate therefore logic follows that any change in solar conditions has to have an effect on the climate to one degree or another. The point is how large is the effect and is it large enough to overcome the noise in the climate system which can obscure small minor solar changes.

    The other side is what are the extreme solar changes in regards to degree of magnitude and duration of time needed to change the climate through solar activity changes themselves and associates secondary solar effects?

    I am sure every one agrees that if solar changes are extreme enough there would be a point where a solar/climate relationship would be obvious. The question is what does the solar change have to be in order to be extreme enough to show an obvious solar/climate relationship?

    Again I have listed the solar parameters which I think satisfy this issue.

    Coming in next post

  34. In my opinion to see just how much the sun really effects the climate the sun needs to go into an extreme mode of prolonged minimum activity. At least Dalton like, anything less and I think the solar effect becomes obscured as I said in my earlier post. To much noise for my liking.

    I have put forth those solar parameters /duration of time which I feel are needed to impact the climate and I think gong forward the solar parameters I have put forth will come to be which will then manifest itself in the climate system by causing it to cool. I dare say I think it has started already.

    How cool it is hard to say because there are climatic thresholds out there which if the terrestrial items driven by solar changes should reach could cause a much more dramatic climatic impact.

    Terrestrial Items

    atmospheric circulation patterns

    volcanic activity

    global cloud coverage

    global snow coverage

    global sea surface temperatures

    global sea ice coverage

    ENSO a factor within the overall global sea surface temperature changes.

    Solar Parameters Needed and Sustained.

    cosmic ray count 6500 or greater

    solar wind speed 350 km/sec or less

    euv light 100 units or less.

    solar irradiance off by .15% or more

    ap index 5 or lower

    Interplanetary Magnetic Field 4.5 nt or lower

    Solar Flux 90 or lower

    Duration of time over 1 year following at least 10 years of sub solar activity in general which we have had going back to year 2005.

  35. I quickly found out that the sun’s electromagnetic activity as a climate driver was greatly underestimated.

    The article says which I agree with ,which is based on the AP index which is related directly to solar activity moderated the strength of the earth’s magnetic field.

    Therefore the AP index and solar wind are very important climate drivers in my opinion.

  36. LOD is related to geological activity which I think is related to solar activity and that being more geological activity when the sun is in a prolonged minimum state.

  37. tallbloke says:

    R.J. Remarkable, thanks for the update and insights. I need to think about what you’ve presented there before further comment.

    Geoff, sorry to hear you haven’t been cited by Archibald and Fix. What a pair of magpies.

    I can confirm IanW was working on his perigee-ENSO stuff way back in early 2015 and has been working carefully on getting a thorough paper written ever since. It’s very understandable he’s concerned that others are lifting his concepts and ‘jumping the gun’.

    I want the talkshop to be a place we can all collaborate and exchange ideas. For the sake of harmony, it’s best if everyone is honest and complimentary to each other. R.J. particularly is to be commended for frequently clarifying where the periodicities he has been modelling with come from and who originated them.

    Where the talkshop leads, others follow.

  38. Paul Vaughan says:

    RJ & Others,
    The ENSO signal in LOD is decades-old common mainstream knowledge. Dickey & Keppenne (1997) is the classic that comes to mind (because they refined expression):

    Dickey, J.O.; & Keppenne, C.L. (1997). Interannual length-of-day variations and the ENSO phenomenon: insights via singular spectral analysis.

    Misunderstandings in climate discussion are widespread and extreme. For years I’ve found absolutely remarkable the widespread extreme ignorance of the implications of Figure 3.

    The easy opportunities for diagnostic refinement are:
    BDO spatiotemporal properties.
    multivariate modeling with attention to nonrandom volatility structure.

    These are big diagnostic opportunities that aren’t being exploited. This is clean stuff that can go mainstream.

    …but when I step back to Pareto Principle perspective I find it fascinating (an exploratory insight into human nature) that there’s so much interest in predicting residuals.

    Is ~15% more insight going to make or break anything important? Maybe. For example a well-timed, opportunistic interannual dominance swing could naturally stabilize for decades. The swing could go the wrong way and lock out possibilities for a whole human lifetime. So yes I think it does matter tremendously.

    Regards

  39. Paul Vaughan says:

    I advise that some of you need to run some spatiotemporal diagnostics on when and where LOD does and does not correlate with SST. I’m noticing a (rather large) awareness gap that I think is holding back discussion progress. Remember that LATENT is nonlinear. When you look at the spatial patterns for LOD vs. SCD, you’ll see that LOD is just a nonlinear aberration around the SCD attractor, accounting for little additional variance. It’s a meaningful amount of variance, so it’s worth pursuing the extra level of detail, but exploratory progress isn’t feasible with base misconception.

    Regards

  40. RJ Salvador says:

    PV:
    I understood that the ENSO would be in the LOD but I was surprised that the evidence of that showed up in the residual. Since the LOD model uses essential the same forces thought to drive the ENSO, I expected that it would have been account for by the model. The reasons it didn’t are interesting to think about. Perhaps there is a timing issue where an LOD change influences the ENSO which then results in a further change in the LOD again?

    Saturday, College football time.

  41. tallbloke says:

    Enjoy the game R.J. I have a long day in the driving seat tomorrow. I’ll use the time to consider the very same issue you’ve identified. I touched on it in my London talk. The tidal bulge on the equator, magnifying the LOD variation. Heat doesn’t do that. Expansion of water by heat lowers density.

  42. oldbrew says:

    Re Salvatore’s link [5.31pm, Oct 15th] this from the same website also looks interesting:

    The Chandler Wobble and the SOIM
    http://contextearth.com/2014/04/05/the-chandler-wobble-and-the-soim/

  43. Paul Vaughan says:

    The classical mainstream approach to analyzing LOD is to remove the fast lunar components, remove semi-annual, remove annual, etc. and arrive at ENSO as residual. Of course when I say “mainstream” here I have in mind primarily Earth Orientation Parameter (EOP) experts, not climate scientists.

    The LOD-SST correlation pattern is a sideways V anchored in the Pacific Warm Pool and angling out towards the mid-latitude Americas. There are bright spots under Alaska and Texas, in Drake Passage, and either side of Greenland. That’s it. Do be sure to look at the residuals if you want to avoid very seriously misinterpreting the Drake Passage correlation. (I made a series of posts about this (on blends versus contrasts) on 1 or 2 recent Suggestions threads.)

    You can pull the pattern out of an EOF analysis of SST, but it will be a lower-ranking component suggesting a tiny modification of the primary PC related to SCD. Such a minor aberration can be interpreted as a combination of nonlinear hydrology, intermittent interregional desynchronization and/or imperfect asymmetry, etc. With rotation the components merge, easing interpretation. An experienced multivariate analyst won’t need to do the rotation to understand and interpret correctly so long as they know how to isolate and interpret the solar terrestrial weave (decadal volatility of semi-annual LOD) and its implications.

    We each have a different role to play. I explore. From my explorations I note that unexploited multivariate diagnostic refinement potential exists. A suggested stepping-stone for others on the path to multivariate modeling: for starters make bivariate forecasts. Here’s a link to a comprehensive article on a PAIR of ENSO indices to try to model SIMULTANEOUSLY:

    2016 – Reinspecting two types of El Nino: a new pair of Nino indices for improving real-time ENSO monitoring

    If I ever assess a LOD model, I’ll focus on 2 key features:
    1. secular.
    2. solar-terrestrial weave.

    If #2 is not accurate, it’s just as fatal for solar-terrestrial modeling as a model of solar activity failing on SCD …although it may be interesting and useful for other purposes.

    I wonder….
    Who will be (or was) noted in history as the issuer of the first successful bivariate ENSO forecast?

    I think I’ve made the points I wanted to make in the context of this thread and I’ll probably leave it there for now and continue on with some notes on Modoki and LOD-SST spatial correlation patterns on Suggestions as/when time permits.

  44. Paul Vaughan says:

    OB, remember when looking at the contextearth site (an interesting site exploring the residual 15%) that the author there bases solar-terrestrial modeling on false assumptions. It’s also quite suspicious that explosive volcanism isn’t more front and center. It’s a worthwhile site to check say monthly for certain types of (low variance) insight, but it deliberately ignores bigger things.

    More generally Monday, Tuesday, Wednesday, Thursday, & Friday do not cause a factory to ship product. Demand for the product causes shipping. The days of the week are NOT THE CAUSE. Similarly I think people looking at lunisolar SCHEDULING misinterpret it. Scheduling is an interesting thing to explore, even more so if it’s not misinterpreted as playing a role that only the sun can play. The sun builds up potential. That potential is there no matter what triggering schedule is there chopping transient signals (lunisolar, solarwind, whatever). Aliasing and aggregation criteria are fundamental considerations that a majority of people just ignore. The political charge doesn’t help. It inclines people to snap with hostility rather than be sensible.

    I would say the author is doing some interesting work on QBO and exploring ENSO. The author has a history of being excessively rude (engaging in intolerable, illogical harassment), so monitoring from afar without engaging directly is advised.

  45. Paul Vaughan says:

    I forgot to say:

    The FIRST diagnostic check I would run on any ENSO model (whether Strandberg’s, Pukite’s or whoever’s):

    On S-22 I’ve started re-introducing SCHEDULING explorations, which should NOT be confused with POTENTIAL explorations (explored on earlier Suggestions threads).

    I’m suggesting we start cleaning up the sloppy conceptual conflation of what primes versus what triggers. Scheduling’s important. Trucks can be delivering to and from your warehouse on different schedules and managers and workers need information to coordinate. A truck may show up triggering all kinds of changes in warehouse activity, but the potential for such triggering is set by customer demand. I’ll let someone else do the marketing job. I’ll explore, including diagnostics.

    If a model doesn’t have the illustrated properties, I certainly wouldn’t trust it …except maybe as a tool for fooling naive competitors into investing the wrong way (trick them into putting their weight on the wrong foot kind of thing).

    The good news is we have a lot more interesting diagnostic opportunities to discuss. The bad news is there will be delays.

  46. Answer to Ian Wilson
    Let’s act like grown up and put away battle axes. First I like to stress that what I have done is developing a NN software and methodology which in my view is a superior technique for analyzing dynamic processes like ENSO. So what I do is that I follow wherever the data leads me. I do this independently without digging in to others work to any large degree. Then, based on my result I try to present what I got and add my own interpretation of these results.

    So I had a situation where I had A) concluded that I was able to recreate and make reliable forecast of ENSO only by using external forcing in the form of gravitational pulses during Lunar Perigee and from changes in Sun’s electromagnetic activity. B) I had learned (In my case from weekly ENSO presentations), I could have as well learned that from books or from other scientific papers, that Kelvin Waves are formed during Westerly Wind Bursts in the Kelvin Generation Area when MJO in this area is positive. While C) Tropical Kelvin Waves represents an important part in the El Niño formation process, logic tells me from A) and B) which I know is true, that MJO must or at least should be driven by the same external forces that cause ENSO variations. So because A) and B) both are true, I reason that C) should also be true. I also wrote that I haven’t investigate MJO data.

    In hindsight because of this conflict I should have written down what I had based my conclusion on. In this case it was because A) and B) both are true, then C) should also be true.
    Note also that I came to this the conclusion by studying charts over the progress of Kelvin Waves, that the time between two consecutive Kelvin Waves correlates to multiples of Perigee Pulse periods. The period between two Perigees is 27.5 days. The most common time difference between two nearby Kelvin Waves are 2*27.5 = 55 days or 3*27.5 = 82.5 days. So my conclusion that MJO is driven by the same external forces as ENSO has not only been based on A) and B) leads to C), but has also been based on the apparent combined linkage between Perigee Pulses, Kelvin Waves and MJO.

    Look, I know you have spent long time researching ENSO, but so have I. I don’t normally make any reference research for web pages I write. On the other hand, if I write a scientific article that I want to publish there is reason to make such reference research. I don’t mind adding references to others work which are related to my research. I don’t mind giving references to others. But, in this case you have first to acknowledge that I didn’t copied my conclusion from your work, but my conclusion was made independent from your work as described here. Then if you ask me, I gladly add a reference to your work from my webpage

    I seem to have more serious problem with Pukite. I blocked him from following my twitter account because he was harassing me. It seems to me that I’m driving him crazy with my work. He called me both a fraud and a liar. He explained that it’s now too late for me to publish my results because he has already taken my result and run with it as his own discovery, of course without referencing me.

  47. oldbrew says:

    Re Pukite: ‘He explained that it’s now too late for me to publish my results because he has already taken my result and run with it as his own discovery, of course without referencing me.’

    And he’s calling you names? Bizarre.

  48. Yes, I agree. Maybe it’s because I’m on to something.

  49. Paul Vaughan says:

    Pukite believes in natural variations and wants them articulated by alarmists.

    He absolutely refuses to be sensible about sun-climate relations. (Do diagnostics on his sun-climate approach and you’ll find an extreme hard-fail.)

    This is a smart guy doing a mix of deception and honest exploration. In his dealings with people he regards as “skeptics”, he’s beyond unethical.

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