Digital Diatribes

A presentation of data on climate and other stuff

Archive for the ‘El Nino’ Category

Uh Oh… Does the plummetting ENSO Index portend a cold winter?

Posted by The Diatribe Guy on July 10, 2010

We’ve had a wetter than average summer, but the temperatures here have been glorious. Out East, they have been scorching temps as of late, and a lot of people are making a lot of hay about that (I’ve never really understood that expression).

Global temperatures have been warmer. It is what it is. No use pretending otherwise.

But this wasn’t completely unexpected. In fact, as a resident skeptic, I personally suggested prior to last winter that we’d have mild one. It isn’t rocket science. The ENSO index was into persistent El Nino territory and that was that. My prediction turned out to be right. Oh, sure, as always in Wisconsin, we had our extremely cold days, but all in all it was warmer, we had more days than normal get into temps that melted snow, and we had an early spring. And thanks, at least in part, to an ENSO index that stayed above the 0.5 mark from the 2009 May/June reading to the 2010 April/May reading we have continued to see warm temps.

So, imagine my surprise when I just randomly clicked on the index to see a May/June reading of -0.412.

Now, without any other context, this isn’t an extraordinarily low number. But there is a bit of context here that makes this a fairly fascinating number.

First, the index tracks on a two-month average basis. Thus, going from an April/May value of 0.539 to a May/June value of -0.412 (a drop of 0.951) must imply a very dramatic cooling in June. It’s one thing to see that kind of number when the previous one was -0.2, it’s quite another to see it after an El Nino-esque reading in the prior period.

So, I was curious to see how this compared to previous drops in the index.

I was both surprised, and not surprised, to see that this drop is the largest single month-to-month negative change in the index since the beginning of the readings in 1950.


I am not entirely sure what this means, and I suppose we need to see what happens over the next couple months. But I don’t like the timing. The impact of La Nina will have a few month lag, which puts us squarely in line for a harsh winter.

If you’re curious about the other laregest drops and what happened after those drops:

2nd place: -0.915 May/June 1998. This was a drop from an extremely high index reading to a still high reading. (From 1.982 tp 1.067) Within 3 months we saw La Nina, and it persisted 19 months, if you include one reading just above -0.5.
3rd place: -0.825 Apr/May 1954. This was a shift from a shallow La Nina value (-0.598) to a deep La Nina reading (-1.423). Including the initial value, this started a La Nina that persisted for 34 months.
4th place: -0.799 Oct/Nov 1950. This was a move from a negative reading (-0.381) to La Nina (-1.180). Something seems odd here. Deep La Nina readings are in place from the first month of 1950, then we had a jump, and then this drop. La Nina persisted another 5 months.
5th place: -0.775 May/June 1988. This was a move from barely positive (0.090) to La Nina negative (-0.685). This started a La Nina that persisted for 12 months.

Not to be a pessimist, but if you’re in my area, enjoy the next 2-3 months while you can.


Posted in Cycles, Data, Earth, El Nino, ENSO, La Nina, Oceans | Tagged: , , , , , | 10 Comments »

Curve-Fitting the ENSO Index Suggests We Have the Highest El Nino Event since 1998

Posted by The Diatribe Guy on January 28, 2010

ENSO 200912

ENSO Index and Fitted Curves @ 12/31/2009

I’ve continued to work, as I have the time to, on pulling the Oceanic Oscillation data, developing a fitting spreadsheet for each index, to get some idea of what the underlying cyclical nature of the oscillations may be.

I decided to post the above chart on ENSO, since I (a) completed it, (b) we’re currently in the midst of an El Nino, and (c) most amateur climatologists know about it and occasionally like to take a look at it.

The source for the data can be found on the right side of this page. The largest hurdle in the curve-fitting is that good(?) data only goes back to 1950. Even this may be a little questionable, and from what I’ve read, any proxied data prior to that is even less reliable. But, we’ll run with the data we have with the caveat that is always there about analysis only being as good as the accuracy of the data and all that.

I’ve been very interested in trying to understand the tendency of these oscillations to cycle (or not cycle, as the case may be). The ENSO index, in particular, can have the appearance of a random variation with no particular pattern.

At this point, I need to explain what I did here, and then I need to explain what I am saying and what I am not saying regarding the conclusions.


1) I have simultaneouosly fitted a long-period wave and a short-period wave to the ENSO data
2) The following elements have been fitted:

For the long period wave:

  1.  Best fit sine wave with a period of at least 30 years
  2. A scale factor to determine amplitude of the wave
  3. A phase increment amount to determine the length of the wave
  4. A starting point on the wave cycle to be fitted at the beginning of the data
  5. A vertical shift, to account for bias in the zero-anomaly base assumption
  6. A slope of linear trend

For the short wave:

  1. Best fit sine wave with a period less than 30 years
  2. A scale factor for amplitude
  3. A phase increment amount to determine cycle length
  4. A start point on the wave at the beginning of the data

There is no shift or trend determined on the short wave determination, since this will follow the path of the long wave.

Through a simultaneous and recursive process, all these elements are simultaneously solved to produce the minimum value of squared differences from the point on the short wave to actual ENSO index readings.   The ultimate solution is not necessarily incorporating the best-fitted long wave taken in isolation.   I initially ran the long-wave fit first, and then separately ran the best fit short wave along that curve.   Moving to running everything simultaneously helped the overall fit and actually reduced the length of the long-wave.    The difference is not huge, but since it is the best fit and the results appear reasonable, I went with that.


The results of this analysis show a 50.5 year ENSO cycle that underlies the shorter-term variations.   I have shown this before, and it is an interesting consideration in evaluating the relative magnitude of certain ENSO events, not so much as it relates to the zero value, but as it relates to the long-term wave.   The current long-term wave is on a decline, and may, in fact, be bottoming out in another four or five years.

The starting point is just past the halfway mark of the cycle, so we see a lower-index period at the beginning of the chart.  The amplitude of the wave is about 0.32 at its peak.   So, from top to bottom (with no linear trend) there is a difference of 0.64 in the magnitude contributed to ENSO events from one period to another, depending on where the long-term cycle is at.

There seems to be, in addition to the cycle, a linear trend in the data for which the long-term cycle moves along, at least since 1950.   It may be that there is a third cycle that is substantially longer that is being mistaken for a linear trend.   This may matter in the long run, but for a 60-year time period the linear approximation should suffice.   However, it may well be that we need a number of additional years of data to better fit this and judge whether or not there is a linear trend, or some other cycle at work.  For now, though, I go with the best fit, and for that the rate of change is 0.7 degrees Celsius per century.

This long wave is being fit simultaneously with a short wave placed on its path.   The period of this short wave is 4.93 years.  Its scale is 0.49.   So, at the top of this wave, plus the top of the long wave, we are adding 0.81 degrees to the ENSO index.   The first wave starts at about the 220 degree mark of a cycle.

Key Assumptions (What I’m doing versus what I’m suggesting)

There are a couple key assumptions here.  The primary assumption is the selection of a sine wave for fitting.  I am not saying this is the best assumption.  All I am saying is, given this assumption, there is a best fit.   As I look at the data, it actually doesn’t do too bad a job in aligning with peaks and valleys.  However, it is far from perfect.   There are other ways to manipulate this, if desired.  One can select a skewing assumption so that the wave peaks earlier or later in the cycle than at 90/270 degrees.   Or, once can assume that there is a factor that compresses or expands length over time (or both in some oscillating pattern over years).   Another thing to look at is to see if the length of sunspot cycles impacts the difference in timing of ENSO peaks/valleys, as I’ve seen suggested.

All these are potential refinements that could improve results.   However, all that said, I still think there are some interesting results here.   The most significant El Nino events do seem to correspond well with peaks in both waves.

The other assumption is that there are two cycles to consider.  A third assumption that can be questioned is the validity of a linear trend in the data.


One may think that the waves represent the anticipated direction of the ENSO index.  That is actually not what the waves imply.  The red wave pattern marks the “starting point” for the current index.  From there, deviations may go up or down.    This may be the most confusing aspect on how to read the chart.   It’s not so much about predicting El Nino or La Nina, it’s about showing how the ultimate magnitude is affected.


June 1955 ENSO index = -2.270; Wave value = -0.76.  Negative deviation = -1.51

September 1973 ENSO index = -1.71; Wave value = +0.20.  Negative deviation = -1.91.

One could argue that the 1973 event was substantially more profound than the 1955 event, even though the actual ENSO index reading was lower in 1955.


The most profound El Nino event, in terms of a deviation from the underlying wave, actually occurred in 1983 – not 1998.  The March 1983 reading = 3.11, and the wave value = 0.77, for a differential of 2.34.    The maximum deviation during the “Super El Nino” was actually August 1997 – a difference of 2.03.

In fact, we actually have a fairly significant event occurring right now.   The December 2009 deviation from the wave is +1.54, which is the largest difference since April of 1998!

Posted in Cycles, Earth, El Nino, ENSO, Oceans, Pacific Ocean, Science | Tagged: , , | 4 Comments »

It’s a Warm January – What Gives?

Posted by The Diatribe Guy on January 21, 2010

It’s kind of humorous watching the blogosphere play “It’s cold / it’s hot” tennis when these things happen. When it gets cold, the AGW-proponents grumble to themselves in silence as the skeptics/deniers/ throw out anecdote after anecdote of cold weather. Then when it gets hot, Gore’s fan club, no doubt emboldened and perturbed at the previous volley, come out swinging to once again announce the science is settled and Watts and Cavuto and others are nitwits with their collective heads in the sand.

Of course, we all try to adhere by a few rules, and few of us really adhere to them as completely as we should. The first is that “weather is not climate.” The second is that “the earth is complex, and variation happens on a day to day or month to month basis.”

But what fun is that?

And so, we delve into the question that has the pro-AGW crowd giddy with all sorts of excitement: Why did we just recently have the warmest January day in history (history meaning, since 1999), according to UAH? You can link to the site that tells us that here. You may need to recreate the chart, which is easy enough. Just hit “draw” and then select all the years and hit “redraw.” Make sure you’re on the “near surface” option.

As an official member of the community of skeptics, should I hide from this? Should I explain it away?

Nope. And the reason is simple: it is what it is. More important than any agenda-driven concerns, I’d rather give puzzling news that’s true, rather than a bunch of mumbo-jumbo that isn’t.

The truth is, I don’t know why we saw that sudden jump in temperature, just after a period where many places in the globe were seemingly getting hammered by cold and severe winter weather. And the real truth is that nobody else can possibly know why one or two days is suddenly so high. And let’s be honest – it was an impressive temperature reading. It’s not like it just barely nipped the 11-year record. It left no doubt. Further, the entire month of January promises to show a warm reading. Don’t fret about it. Accept it as the truth it is.

As I’ve said many times, we skeptics are somewhat in a corner. Most of us actually prefer warming – I know I do. But we don’t accept the AGW premise, and we see other evidence suggesting that we’re not warming – at least not catastrophically – and we have a desire to see these alarmists get their come-uppance that we, in a way, want to see it cool. But as perverse as that may be, it doesn’t hold a candle to the AGW crowd. You see, they get themselves so worked up over warming that they start seeing nice, warm, weather as a threat to existence rather than a nice, warm day. Instead of enjoying it, they lose sleep over their children’s futures and wonder why we can’t go back to the “good old days” where we had freezing rain throughout the month of April.

So, given all that introspection, let’s at least take a look at some obvious contributors to the warm beginning of 2010.

Exhibit One: El Nino.

There’s an El Nino that is impacting temperatures right now. Whenever there’s cooling during a La Nina, the pro-AGW crowd trips over themselves to point it out, but when there’s an El Nino up and about, they somehow fail to mention it when talking about -for example – how warm this January is shaping up to be.

The last 7 readings have exceeded 0.500, the traditional benchmark for El Nino. 3 readings in a row makes it official, so were well into a good old El Nino, which we know affects temps in an upward manner. And this may well make 2010 a nice, cozy year, since the December reading is the largest of the seven.

We know there’s a 4-6 month lag effect of El Nino (if I remember my facts as related to me from Bob Tisdale), so the first half of the year should reflect that, and if the El Nino persists we could see warmer temps throughout the year. This is a good thing, because my garden has had major issues the last couple years. Cool, damp weather really sucks for raising a garden.

It’s probably a stretch to suggest, as some do, that 2010 will be the warmest year ever, though. While we’ve gone up over 1.0 on the El Nino reading, it is by no means an unusually high value, and it pales in comparison to the consistently super-high values from 1997-98, which almost hit 3 at the highest point. There is nothing to indicate that we can expect such high values from this El Nino. I suppose anything can happen, though.

Exhibit Two: The AMO cycle.

The AMO had taken a dip below zero preceding last year’s ridiculously unpleasant summer, but the values jumped back up to levels above 0.2 a couple months ago, which is likely contributing to the January temps. But the AMO cycle overall has peaked, and while it will probably remain around these current levels, it won’t continue to rise any more, at least not on a prolonged basis. But current levels will contribute to a warmer 2010 than last year, but the contribution is really no more than the couple years before that and is very unlikely to reach levels from 2005-06.

Exhibit Three: Even the PDO is joining in the fun.

The PDO has gone into its long-term cold cycle, but variations about that wave still occur for short-term periods. We can see that it was quite negative over the last couple years. Over the last five months it has increased, even above zero in four of the five months. No doubt the lack of a negative PDO influence has also contributed to our nice January, and will start off 2010 with more pleasant temps than the previous couple years. There is little likelihood, though, that this will soar to levels that push 2010 to record temps, though temps are certainly likely to be higher than the last couple years.

Now, as for the spiking temperatures of a single day, you’re just going to have ask God about that when you see Him next. Even these shorter-term variations in these indices don’t explain day-to-day variations, but they can certainly help explain our elevated temperatures in January on a general basis. I’m sure there are numerous other contributors to climate and temperature that play a part, and sometimes these things happen to align themselves in such a way that a spike or dip occurs.

Quite honestly, it’s really a silly proposition to constantly be arguing about how climate change is about long-term trends, and then trumpet a daily temperature reading, but we’re all probably guilty as charged to one extent or another.

Posted in Atlantic Multidecadal Oscillation (AMO), Atlantic Multidecadal Oscillation (AMO) Index, Climate Change, Data, Earth, El Nino, ENSO, Global Warming, PDO, Temperature Analysis | Tagged: , , , , , , | 14 Comments »

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

Posted by The Diatribe Guy on September 30, 2009

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.

Posted in Cycles, Data, Earth, El Nino, ENSO, La Nina, Oceans, Science | Tagged: , , , , | 13 Comments »

April 2009 Update on the ENSO Index

Posted by The Diatribe Guy on April 22, 2009

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.

Smoothed ENSO

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.

Posted in Cycles, Earth, El Nino, ENSO, La Nina, Oceans, Science | Tagged: , , , , , , | Leave a Comment »

January 2009 Update on Global Temperature – UAH

Posted by The Diatribe Guy on January 21, 2009

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. Read the rest of this entry »

Posted in Climate Change, Cycles, Earth, El Nino, ENSO, Global Warming, Science, Temperature Analysis | Tagged: , , , , , , | 14 Comments »

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

Posted by The Diatribe Guy on November 21, 2008

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.

Read the rest of this entry »

Posted in Climate Change, Cycles, Earth, El Nino, ENSO, Global Warming, La Nina, Science, Temperature Analysis | Tagged: , , , , , | 6 Comments »