El Nino is back with the Fury of a Woman Scorned!

OK, not really. But the headline is kind of catchy, no?

El Nino is, in fact, back. And to hear some of the early prognostications about it, we would all melt like the Wicked Witch of the West mighty soon. And this was going to prove once and for all that global warming was real, because – we heard – the recent cooler temperatures were a byproduct of recent La Ninas. (Please forgive my laziness in not including the squiggly lines over my n).

I admit to not quite understanding that argument. The skeptics among us have pointed out that the increase in global temperatures that took place a decade ago were driven by a Super El Nino. And at the time, we heard that global warming was causing more severe El Ninos. But then the severity decreased and we had La Nina, and we were told that such statements were never really made. Or, at least, not by serious scientists. Which, if true, would mean that they should have agreed that the increase in warming at that time was exacerbated by the big and mean El Ninos. (Which, as an aside, brought very enjoyable winters in the Midwest. Why do people want to send us really cold weather all the time?) But other than some footnoted statements on page 23 of the reference section in a boring document, few people have been told the story about how El Nino affects should be viewed independently from overall warming.

That is, they didn’t know this until La Nina affects brought us some cooler temperatures. Then, suddenly, we heard about some “unusually cold” La Ninas, and how this affected global temperatures, and skeptics were being disingenuous by not properly considering that. And to the extent that such a criticism is true, they are right. But there is a strange thing that happens when ideology is part of the equation: you fail to heed your own criticism when the reverse occurs.

And so we have now seen three consecutive measures above 0.5 in the ENSO index. This is hardly unusual, but it does qualify – to my understanding – as a true El Nino. And before that, the La Nina waned, so we had a relatively neutral index for a couple months leading up to El Nino. So it’s been 5 consecutive measurements now since the La Nina has ceased. I remember when it became evident that an El Nino was on the way. This was going to prove skeptics wrong! Why? I have no idea. If El Nino had an anomaly of 1.00, 2.00, or 5,432.00 it would not prove anything other than when there is a natural warming of the Ocean, it warms our global temps. Wow… there’s a revelation. The fact that this has nothing to do with Carbon emissions is beside the point when it fits the argument.

Even stranger, skeptics tend to accept the cyclic variations as the legitimate explanation for warming. We don’t dispute warming periods. So, the skeptic will nod and agree that an elevated ENSO index will probably lead to warmer global temperatures. But then, we kindly point out, don’t blame carbon. Or people. And don’t get all in a tizzy when a La Nina comes around and we see cooler temperatures. What the hell do you expect? Sorry it doesn’t fit the model.

Having said all that, I certainly don’t expect any records to be broken in this recent El Nino. Sorry, experts. I base this simply on data analysis, admittedly knowing very little about all the climatolological influences that could prove me wrong. But what does the data indicate? Looks like it’s time for a chart:

ENSO Data as of 200908

The first observation from the data is that we’ve had four consecutive positive anomalies, and three consecutive positive anomalies greater than 0.5. Note here that a single data point is actually a two-month running average, which helps smooth out month-to-month fluctuations. The latest reading is 0.978, which is the largest of the four positive anomalies. Prior to this period, there were 9 consecutive negative anomalies, with a stretch of 7 months less than -0.50. This was on the heels of only a two month set of barely positive anomalies after a stretch of 12 consecutive negative anomalies that included an eith-month stretch less than -0.5.

So, it is pretty clear that after some real solid La Nina-esque reality, we’ve now flipped to El Nino. What is not clear is the ultimate magnitude and persistence of our new friend, Mr. Nino. But we can talk likelihoods. And for that, we observe the path of the best-fit sine wave.

The red curve below has been fitted in accordance with the other Ocean Oscillations I have observed. Take a sine wave and manipulate it in a few ways in order to ascertain the minimum least-squares deviation from the curve. You see, while El Nino exhibits noticeable short-term variation, it seems to do so about a longer-term cyclical pattern. Thus, a large deviation in one direction at point A on the curve will not produce the same magnitude El Nino at point B on the curve.

The specifics of the best-fit curve are as follows: The 1950 starting point in the data looks to be at 268 degrees in the full 360 degree cycle. The length of the best-fit curve appears to be 102 years for a full cycle. This is an imperfect estimate, since we don’t even have 102 years of data. It is also a longer fit than what was made last year when I did a similar exercise. But the calculation is what it is.

You can see from the chart that the magnitude of ENSO events can have quite a range: -2 to +3 in the data provided. The scale factor applied to the wave is +1.24 in order to achieve the best fit. However, it looks as if the anomalies in the index may be significantly overstated, at least near the beginning of the curve. The best fit line requires an upward shift of all values of the curve of +0.98. This means that the early part of the curve should have appeared “colder” than it did. The interesting thing to me is that, despite the apparent rise in the average ENSO index levels, the best-fit curve actually has a negative linear slope element to it that is pretty significant: -0.00316, or -3.792 degrees Celsius per Century. This actually means that those high El Nino anomalies are centered around a curve that, without that negative trend line, would have been significantly higher – possibly as much as a degree and a half.

So, where are we now? We are 122 degrees into the cycle, which means we have a ways to go into the negative yet, if this best-fit curve is correct. While it appears to the eye that we’re past the 180-degree point, this is not so because of the negative linear slope the curve lies along. No, if this is right, we will not reach the minimum depth of the ENSO curve until around 2050. The curve itself has a staggering implication of coldness – what was a depth of around -0.4 degrees in the 1950s would be -4.0 degrees in 2050. Should we proceed along these lines, we can continue to expect positive and negative significant deviations from the curve, as we see today. But the positive deviations will produce fewer, shorter and less severe El Ninos while the negative deviations produce more, greater and more persistent La Ninas.

OK, here’s the good news: unlike climate modelers, I don’t proclaim this analysis to be infallible. First of all, we’re fitting the best curve to data that is quite variable in its short-term fluctuations. Second of all, the best-fit curve tells us that the cycle period is a longer period than the data period for which we are evaluating. I already know that this supposed cycle period has fluctuated quite a bit from analysis a year ago.

If I had to rank my certainty on the subject, I would bet confidently that (1) there is a long-term ENSO cycle of somewhat indeterminate period, probably somewhere between 60 and 100 years, (2) that we are entering the negative phase of the cycle and we can expect less severe El Ninos and more severe La Ninas.

I am far less certain about the linear trend of the cycle, and the extent of any such trend, as I am about the shift of the curve. These elements are probably much better measured as more data arises over time.

However, in any case, I think it looks very unlikely that we will see any record-breaking El Ninos for quite some time, in either persistence or in magnitude. We may, however, see some major La Ninas surface over the next few decades.

And that won’t be our fault, either.

April 2009 Update on the ENSO Index

It’s been a few months since I’ve taken a good look at the ENSO index, so I thought I’d check that out and provide some context for that data.  First, let’s start with a couple nifty little charts (click on them for larger charts):

ENSO Chart One - Raw Anomalies with best-fit sine wave.

ENSO Chart Two - 5-year moving average of ENSO index readings.

I’ll discuss those in a moment. First, a little housekeeping on the data and the latest readings, and recent historical context.

First, keep in mind that the ENSO index is based on a two-month average. The data is released in terms of JanFeb, FebMar, MarApr, … So, by default, the “monthly” readings are really a two-month moving average. I don’t think that matters all that much to the analysis, but it’s worth noting. For simplicity in conversation, I’ll refer to the anomalies as “monthly” anomalies, but we all know what that means. (I’m lazy)

The current anomaly is -0.737, which is the fourth consecutive month where the reading is lower than the previous month. It is the seventh consecutive month where the reading is below -0.500, which is that point where they consider the period a “La Nina” period. It is the eighth consecutive negative anomaly. This stretch followed two readings that barely peeked above zero (0.050 and 0.028) after a previous period of 12 consecutive readings below zero. The prior stretch was colder (Spetember 2007 – December 2007 were all below -1.100).

The last time there was a stretch where 21 of the last 23 readings were below zero occurred during the period ending March 2002. However, the average anomaly during this stretch is a bit cooler than that one. The average of the last 23 readings is -0.703, and the last time we had 23 readings with at least that low of an average was the period ending September 2000.

Back to the charts…

Chart one shows the raw anomalies. We often hear of the ENSO index cycling in a somewhat irregular, short-term manner. It is evident from the chart that this is the case from a more short-term basis. However, I think we also need to recognize that there is also a longer-term cycle underlying the data. Admittedly, due to the paucity of the data period, this is based on what appears to be roughly one full cycle, and after another 200-300 years, we’ll know more. Since I won’t be around then, I can only work with what I have to work with.

The explanation makes some sense, though. Simple observation of the chart seems to indicate a general low phase and a high phase. If you look a the peaks and valleys from the zero anomaly only, recent spikes look like an aberration. If you look at them relative to the sine wave, it’s less of an aberration.

The sine curve was determined by utilizing the “Solver” add-in in Excel. It simultaneously solves for the parameter values that minimize the least square differences from the raw anomalies to the sine curve.

The sine curve was determined by solving for (1) point on the curve at January 1950, that optimally fits the rest of the data, (2) the scale of the wave, in magnitude (in terms of degrees Celisus), (3) the monthly phase reduction of the wave (basically this establishes the length of the optimal wave), and (4) vertical shift in the curve.

The results show an optimized sine curve fit that started 17.3% into its downward cycle as of January 1950, with a full (360 degree) cycle length of just over 61 years. This differs slightly from a previous analysis, and the main difference is that I did not consider a vertical shift in that previous analysis. But that needs to be considered because just because we’re told that there’s a zero anomaly for purposes of measurement doesn’t mean that it works that way in reality.

The scale of the long term curve is 0.4337. This may not seem overly large, but it is significant. From peak to trough, the difference is nearly 0.9 degrees. Consider an ENSO event that deviates in a given month positively by 2 degrees Celsius. At the trough of the longer-term cycle, this will be a 1.5-1.6 anomaly. At the peak of the cycle, it’s a 2.4-2.5 anomaly. The short-term event is no different, but it’s happening at a different point in the cycle, and the conclusions that may be drawn from it as a startlingly high event could be erroneous.

In addition to that, there is, in fact, a small bias towards higher anomalies in the data. One would expect all anomalies to balnce out to zero on a best-fit basis if there were no bias. I found that a vertical shift of 0.0325 degrees was needed in an upward direction to get the best fit of the sine wave. This is not a large amount, but in conjunction with the scale factor, it helps put the recent spikes in perspective.

Take, for example, the peak value in the index from 1997 (2.872). The sine curve vlaue at that point was 0.360, for a difference of 2.512. This is a significant deviation, to be sure. But if we review the data, is it completely out of the norm? I guess it depends on what one decides is out of the norm, but here are otehr months where the deviation was at least as large:

• April 1983 – 2.644
• March 1983 – 2.759
• February 1983 – 2.615

That’s it.  So, that deviation was still pretty significant, although it was less that the deviation in each of those readings in 1983.   However, it is still not quite as significant as it first appeared.  Compare the raw anomaly of 2.872 (deviation from curve of 2.512) to a reading, for example, for the good old days of the cold and freezing 1970s.   July, 1972 showed a raw anomaly of 1.816.  That’s a decent anomaly, but it is more than a full degree less than the 1997 reading we just looked at.   However, the sine curve in 1972 had a negative value of -0.091, creating a difference of 1.907.  the gap in the difference is now only 0.6 degrees Celsius.    This in now disregards the 1997 peak value as a significant deviation, but it mitigates the degree to what the actual deviation was, and helps put it in context.

There are very few of these data points to draw any kind of conclusion, but the peak positive deviations (+2.0 or more) do outweight the “peak” negative deviations (-2.0 or less).  1983 and 1997 experienced those peak positive deviations, while  1988 experienced the sole negative deviation of at least two degrees.  Note that, while 1988 was in fact the largest negative deviation from the wave in the data, it is only the 5th lowest trough point on a raw basis.  

As for Chart 2, it is simply a 5-year smoothed presentation of the ENSO data.  Purely for observation, it basically corresponds to the idea that there is a longer-term cyclical nature to the ENSO index.   Pre-1990, anomalies, on average, were negative.   Post-1980, anomalies, on average, have been positive.  It is much more akin to a step function, or what could be expected with a cycle, than any sort of linear trend.   What is happening on the right hand side of the chart indicates a potential transition point, though one should be a little careful about declaring positive anomalies dead.  On the left side of the chart, I don’t know how far back the actual anomalies fell below the zero line.   Looking at the double peak in the periods ending 1960 and 1970 may have looked like a transition point at that time.  But La Nina wasn’t quite done yet, giving us one last good blast in the mid 1970s.   After that, there was a clear transition into a stronger El Nino phase.   The 2003 and current dip looks similar in nature to me.   However, the double maximum peak in 1983 – 1997 looks similar to the double negative trough in 1957 and 1976, as well.  So, this is where I could go either way on whether or not the transition is now or in another 5-10 years.   But if I consult Chart 1,  1976 was just entering the positive phase of the cycle, and we’re just now entering the negative phase.  So if I had to wager my 3rd child, I’d go with “the transition is now.”

Of course, entering the cold phase doesn’t mean there will be no more El Ninos (or at the very least, positive deviations from the wave).  They still occur, perhaps as frequently, but the deviations from a negative phase wave translates into a lower raw anomaly.

At least, that’s how I see it.

January 2009 Update on Global Temperature – UAH

Note: I realized I screwed up my naming convention. I already had a December update on UAH. This one is January…

Sorry it took so long to get this up. I had a couple things I wanted to look at here and since this isn’t my day job, every now and then other priorities get in the way.

The December anomaly from the UAH data is 0.183. This was 0.069 degrees warmer than December 2007, but was 0.068 below the November anomaly. According to UAH, it is the 11th warmest December out of the 30 Decembers in the data. It is ranked 102nd out of 361 overall monthly anomalies. It is the second consecutive warmer anomaly year-over-year after the streak of 14 consecutive cooler anomalies.

The longest we can go back in the UAH data without showing a warming trend line is May 1997. Based on the way January seems to be coming in, it would be surprising if this moved forward after this month. It may even move back to April 1997, but we’ll see on that.

I’m not going to show the different trend charts here, because I actually want to point out something else this month. But here’s a quick recap of what is going on with the trend lines:

60-month: -0.309158 represents the third consecutive increase. So, there has been a bit of a moderation in the rate of cooling we have seen lately.

A Quick Look At the ENSO Index (Another La Niña on the Way?)

Don’t look now, but the ENSO Index is once again entering “La Niña” territory, which is generally recognized as the point where the ENSO index falls below a deviation of -0.5. 

If this continues, we are sure to see the effects of it manifest in the way of cooler weather and varying precipitation events by regions affected in one way or another by the phenomenon.  And if this occurs, then we can expect to see a perpetuation of the negative trend lines we have seen in recent years.  This will be met with a predictable response by AGW supporters whenever they see a chart of negative trend lines:  “Well, of course it’s negative!  It’s because of La Niña on the heels of that really big El Niño a decade ago!”

Of course, they may well be right in that, so I will give credit where credit is due.  The only problem with the argument seems to be this belief that prior to 1998 the ENSO Index either fluctuated perfectly between cool and  warm, or didn’t fluctuate at all.   Therefore, the 30 year warming trend is really because of people and has nothing much to do with the ENSO index, and only the cooling of the last decade is a reflection of aberrations in the ENSO swings.

I decided to take a quick look at the index with some simple charts.   The presentation isn’t rocket science.  Just plot the values, and then take a look at what happens when you collapse them into 12-month, 36-month, and 60-month periods.   These collapsed periods will provide insight into not just short-term ENSO fluctuations, but longer term variations.  

Why is that important?  It’s simple physics.   Suppose you have a heating source that gets very warm.  The energy emitted from that source warms the surrounding area.  Now, cool that heating source down.   The surrounding area, depending on insulatory effects and the like, will cool down also, but at a slower rate.   If you warm that heating source up again before things cool back down to “normal” then you are now transmitting more heat energy into your area but starting at a warmer base.   If you keep doing this over an extended period of time, you will continue to reach higher and higher temperatures.

Contrast this to a perfectly cyclical situation.  Your heating source warms, gets turned off, then an A/C unit turns on, gets turned off, then the heating source starts again, and so on.   While short-term temperatures will rise and fall in your area, the overall average will be fairly constant.

If the ENSO index shows a persistent positive or negative value when smoothed over longer-period averages, then it is an indication that temperatures have been – at least in part – driven upward or downward by that persistent activity.  

So, let’s take a gander at the charts.

The overall ENSO data are presented here. There is a slight linear trend upward over time, which does show a general rise in the index. However, more important than this is the persistence in Index values above and below the line. General observation seems to indicate that prior to the 1970s much more time was spent in La Nina territory, and since then more time has been spent in El Nino territory.

The same basic picture is presented here with 12-month smoothing. It's a little clearer to see with the jagged edges removed, but there are still a lot of cycles apparent.