Eastern Pacific Oscillation and Random Stuff – Believe it or not, a New Post…

Ah, it’s been a while, hasn’t it? My friend Jeff at The Air Vent asked me if I’m giving up. I understand the appearance of this, given my lackluster performance (or more accurately, zero performance) as of late.

Before I present a chart of the EPO Index, which most of us probably don’t care all that much about anyway (if we’ve even heard of it), I have a few random observations:

1) To Docattheautopsy: Ha! I told you! (Check out comment #6 here: http://digitaldiatribes.wordpress.com/2009/09/30/el-nino-is-back-with-the-fury-of-a-woman-scorned/#comments). Good thing, too, because I get enough spam. Anyway, as complex as climate is, it is actually kind of amazing that so much of the simplicity can be missed among the complexity. I know it doesn’t always hold, but there are some rules of thumb that stand up pretty well. La Nina in spring/summer ==> cold Wisconsing Winter. El Nino in Spring/Summer ==> mild Wisconsin winter. It’s not really rocket science. So, each of the last two years gave us frigid temps and lots of snow, and so far this year we have above average temperatures in November. It’s supposed to cool off soon, but nothing unusual. I admit I was nervous in October – it was a very cold and wet October, but November has been beautiful.

2) Climategate: I love it. I don’t “love it” in the sense that it should have ever happened. That part ticks me off, because it’s simply a blight on the scientific process and public trust, and a validation of the more underhanded aspects of the whole thing – it’s about money, politics, control and power. That’s a major shame. But I do “love” the fact that this has been exposed. It may well be true that much of their analysis doesn’t change, and they may actually believe their conclusions. But what is lost in making that simple argument of dismissal about the relevance of the situation is that there are other scientists who have reached different conclusions who were essentially shut of of the public debate, and in doing this it led to a global, incessant mantra that brainwashed policymakers and citizens alike. It’s not whether or not their studies are meritorious, it’s about the fact that the full debate and scientific process was not implemented, and the full range of views were shut out of attaining credibility through reprehensible methods of collusion and intimidation. And really, it just shows the overall poor character of the participants in these exchanges, which also leads to a lack of trust.

3) Where are the temperature charts? Well, I’ll get back to them. I really wanted to spend time on the Oscillation Data, so I’m continuing down that path at the moment. The trends don’t change so much from month to month, and I am in no way avoiding it due to recent uptick in temperatures. I don’t do that, even if Phil Jones and Michael Mann may suggest implementing a trick to disguise the uptick, if they were skeptics.

And so, with that, let me explain the following chart: The Eastern Pacific Oscillation Data are available since 1950 (link to the right) and is just another one of the Oceanic Oscillations. It’s not one we hear about much, and may well not be highly important in the climate discussion. That’s OK. By plowing through the different indices, I hope to isolate the ones that do have an apparent oscillation pattern, because it seems to me that this is an indication that the Oscillation is a driver of temperature, rather than the other way around. The interesting thing about most of the oscillation patterns is that they tend to cycle on a longer time period. Even ENSO, with its shorter term spikes (not on particularly predictable intervals, it seems) has a longer term cycle. The EPO index suggests something else – an 8.9 year cycle.

Caveat: there are no December values in the data set. I have adjusted this by using the average of the November and January values. I have sent an e-mail to NOAA seeking an explanation for this. If I receive a response, I’ll either comment about it or update the post.

EPO Data as of 200910

It’s hard to say how much impact this metric has on global temperatures, and I probably won’t know until I can do a full correlation analysis of all the oscillations, solar index, and CO2, at minimum. But it may have some impact. There is almost no linear trend whatever on this, and the index seems well-centered around a zero anomaly.

There also does seem to be a very shallow 40-year cycle, if I expand the analysis out to look at that, but nothing worth more than a note. The driving cycle is the shorter-term one.

Hope all is well with everyone. If I find I cannot get to data analysis, I will try to do better at posting some fluff just to let you know I’m still here .

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.

A Gander at the Caribbean Oscillation Index

We hear a lot about the ENSO index, the PDO Index, and the AMO Index.

I’ve also taken a look at the Arctic and Antarctic Oscillation Indices.

But there are more. Quite a few more, actually. While I have not done a comprehensive study on these, myself, one would assume that the reason we hear about the PDO, AMO, and ENSO is because these have quite evidently shown correlation to weather patterms that affect a lot of people. And it may well be the case that these are the main drivers that matter, and all the other ones have only negligible contributory effects.

Nevertheless, some time ago I decided I wanted to take a closer look at these. Readers here will notice that I’ve been focusing on Ocean Index posts recently. Based on the wide discussion that has broken out on these posts (yes, that’s sarcasm) it doesn’t appear that this is the main point of interest to a lot of people. That’s OK. Hopefully it’s interesting at some level. But it’s an important aspect of a full study on global temperature. And I still have the goal of doing a full analysis at some point combining the impacts of all these measures, along with solar cycles and CO2 levels.

As the next step in this journey, I have compiled the data from the Caribbean index. It is found as part of this data set (under the CAR column). The permanent link to this is on the right of this page.

I wasn’t sure what to expect on this index. As you recall, the polar regions didn’t demonstrate any shorter-term cyclicality to speak of, while the majors that everyone speaks of did show clear cyclicality.

The results of the raw data plot with the best-fit sine curve are shown here:

Caribbean Oscillation Data as of 200908

It certainly looks as if there’s some cyclical thing occurring here, based on a best-fit analysis. It’s not quite as predominant as the AMO and PDO, but it’s there. There do seem to be short-term spikes with some months of persistence, similar to ENSO.

The best-fit line has the following parameters: A phase reduction of 0.61 degrees per month implies a full cycle of 49.15 years. There is a vertical shift downward of -0.053 needed, with a linear trend of 0.000187 – which is a rate of 0.224 degrees Celsius per Century.

Thus, the index, on average, has been understated enough to be noticeable and has exhibited an upward trend over time. This longer-term upward trend is more noticeable in the charts below as we collapse the data into longer-term rolling averages. Caution is needed to make sure we understand the autocorrelation, but even considering that there is an upward trend in the Caribbean surface temps exhibited.

Similar to ENSO, however, there look to be shorter-term spikes that may play more immediately into the local temperature/weather patterns. Since October 1989, we’ve seen the following stretches of positive/negative anomalies (keep in mind that the best-fit implies that there should be a shift from these figures):

198910 – 199108: 23 consecutive positive anomalies
199109 – 199410: 31 of the 38 months – negative anomalies
199411 – 199601: 15 consecutive positive anomalies
199602 – 199703: 5 consecutive negative / 4 consecutive positive / 3 negative / 1 positive / 1 negative
199404 – 199910: 31 consecutive positive anomalies
199911 – 200007: 9 consecutive negative anomalies
200008 – 2007121: 89 consecutive positive anomalies

Since then, it’s been back and forth.

Caribbean Oscillation Data as of 200908 - 12 month Smoothing

Caribbean Oscillation Data as of 200908 - 5 Year Smoothing

Caribbean Oscillation Data as of 200908 - 10 Year Smoothing

Arctic Ocean Oscillation Data Update – September 2009

It’s been nearly a year since I looked at the Arctic Oscillation data. One reason I haven’t paid closer attention to this is because it doesn’t show the cyclical patterns that AMO, PDO, and ENSO do. I haven’t run a correlation analysis on the data (yet) to determine whether or not it appears to depend more on regional temperature, or whether it seems to drive the regional temperature, but it doesn’t appear – at least in the short term – that there is a clear cycle that we can hang our hat on and say with any certainty that certain conditions can or cannot be expected over the next few years.

The same kind of analysis is done here as presented in my previous posts. I do have a correction to make on the long-term sine wave, however. In my previous post I made an observation that the long-term sine wave suggested a pattern for the Arctic on a 9500 year cycle. That calculation pulled the wrong values. The new fitting and corrected calculation indicates a sine wave with a full cycle completed in 368 years.

Even that number is nothing I’d hang my proverbial hat on. Trying to speak to the length of a cycle that is hundreds or thousands of years old on the basis of 60 years of data is a suspect exercise. I only point it out because I mentioned it as a point of interest in my previous post. I now see that the comparison is not apt and that particular point of interest is meaningless. I apologize for the confusion.

Arctic Oscillation Data as of 200908

Since the last update, we saw a stretch of positive anomalies in 7 of the next eight months. The last three anomalies have been negative. The anomalies for June and July were both less than -1.3000.

The best-fit curve itself is scaled by a factor of 2.929. Whereas the AMO, for example, ranged between +/-0.20, the Arctic ranges between +/-4.00, but mostly between +/-3.00. Thus, the higher scale factor. As mentioned, the curve itself is quite flat, fitted to reveal a 367 year cycle.

There is little vertical shift required, so the zero line is right about where it should be based on the dispersion of the data. The shift is a mere -0.0031, which is close enough to zero to call it that.

One interesting thing I noted in looking through the data was the average squared distance from the curve in different time periods – a variance of sorts, not from the overall mean, but from the best-fit curve. Here are the time-periods and the average variance value:

1950-1954: 0.6603
1955-1959: 1.0570
1960-1964: 0.9414
1965-1969: 1.2891
1970-1974: 0.5337
1975-1979: 1.1788
1980-1984: 0.7463
1985-1989: 1.2549
1990-1994: 1.1941
1995-1999: 0.7523
2000-2004: 0.7847
2005-current: 0.7929

I wish I could tell you if that has any deep meaning. But what I can tell you for sure is that the period-to-period deviations around the curve over the last 15 years shows the most consistent limited fluctuation values in the data. A couple periods were lower, but they are bookended by much higher values. I have no idea if this is an indicator of anything in particular, but I thought it to be an interesting observation.

Again, I present the smoothed charts. The longer-term averages have a lot of autocorrelation, and the spike in average is driven and sustained by 3 pretty high anomalies in the early-mid 1990s. The overall trend of the average is upward because of the combination of those anomalies and the dropping out of some lower anomalies in the 1970s. It’s kind of interesting to see that show up in the longer-period averages since the raw data chart doesn’t seem to show that as much. However, part of the reason for this is the scale. The scale on the longer-term average charts is much lower (+/-0.5 vs. +/-4.0) so the trend looks steeper than it probably is. That said, the 10-year average is what it is, and it is definitely higher now than it was 40 years ago, though it is quite a bit lower than the peak averages of a decade ago.

Arctic Oscillation Data as of 200908 - 12-month smoothing

Arctic Oscillation Data as of 200908 - 60 month smoothing

Arctic Oscillation Data as of 200908 - 120 month smoothing

September 2009 Update on the AMO

I’ve looked at the AMO data set to see what it’s been up to lately, and after a brief plunge into negative territory, it’s come back to a level in accordance with the current sine wave path of the cycle. If you recall, there was a period of 77 consecutive months of positive AMO anomalies, with January 2009 finally breaking that string of positives. We then had 5 consecutive negative anomalies. Historically, such a deviation is not necessarily unexpected, as can be easily enough seen from chart observation. However, it was not an expectation for a persistent state, and we’ve now seen the last three anomalies come in at 0.175, 0.282, and most recently 0.205.

While these are positive anomalies, viewing them relative to the red wave line on the chart shows us that they are right around what would normally be expected.

When looking at certain Oceanic oscillations, the cycle is very clear, and the strength of a given anomaly should be placed in the context of the overall wave path. Deviations from the wave are a stronger indication of the unusualness of an anomaly than the actual value of it.

As I’ve noted in my previous write-ups, we’re nearing the peak of the wave. We should expect many more positive AMO anomalies. In fact, we should expect more positive AMO anomalies for the next 20 years (well, sort of – I’ll explain why this is probably shortened artificially in a bit). Since the wave is at its peak, we will soon see continually cooler anomalies for the next 34 years or so. However, the next few years will still be positive, but dropping.

Here’s the chart:

Atlantic Multidecadal Oscillation Data as of 200908

Maybe it’s just me, but this is one of my favorite charts. Admittedly, the change in it is nearly imperceptible on a month-by-month or quarter-by-quarter basis. But one reason I present it occasionally is because I think it really tells a good story.

The story begins with the cyclicality, which is very evident. This, combined with ENSO and PDO (and I’ll keep looking at other indices) show a clear cyclicality in Ocean Temperatures. In my humble opinion, this should raise a red flag with regard to temperature correlations to anyone who even remotely wishes to get to the truth of what drives global temperatures. Making this cyclicality more clear is the fact that the Arctic and Antarctic Oscillations do not show this behavior at all. Click on the link related to the Arctic to read more about the PDO and ENSO cycles as well.

The next story is, where are we in the cycle? As I’ve alluded to, we are at the peak of the cycle. That means that the anomaly has, on average, risen continually for over the last 30 years. The most rapid point of acceleration of the wave occurs in the early-mid 1990s. Since then, it’s been increasing at a decreasing rate. In a couple years, it will start decreasing at an increasing rate for the next decade and a half.

The AMO is about a quarter-phase out of sync with the PDO (Again, see link above – click on the word “Arctic”). Thus, the PDO has been decreasing over the last number of years. As we’ve seen in the Temperature Charts we’ve been flat for about 12 years now, and we’ve actually seen decreasing temperatures over the last handful of years. This seems to correspond will with an AMO that is only slightly increasing and a PDO that is cooling off more rapidly.

Antarctic Oscillation

I thought I’d start taking a look at the different Oceanic Oscillations to see if there’s anything at all I can glean from the data.

The first set of data is the AAO Index data which goes back to 1979 here. This could be a mistake, but I pulled in data from this source for the pre-1979 numbers. The reason I say it could be a mistake is because the latter source’s numbers do not match all that well to the former’s. This puts the pre-1979 data in question as it relates to the newer data. And, as the chart results came into view, I think we see that splicing this data probably does more harm than good. With that said, I have kept it in for this view of the data, but may choose to eliminate it in future reviews.

We’ll start here with the raw data, and a fitted line that I will explain:

Antarctic Oscillation Data as of 200908

The current anomaly value is -0.686, which is the fourth consecutive negative anomaly. Previously, there were 11 consecutive positive anomalies.

The line on the chart isn’t actually a linear fit, though it is very close. It is actually a best-fit sine wave. However, there are no short-term waves evident in the data, so the best-fit wave is a long-term wave that completes a 360-degree phase over 12,000 years. Obviously, trying to make a strong case for a 12,000 year cycle is a bit silly based on 60 years of data. Nevertheless, it’s interesting to consider that the earth’s precession of the poles moves along this approximate time period. It’s also worth noting that this same approach on the Arctic Oscillation yielded a sine wave of 9500 years. I make no assertions as to the accuracy of this, I just find it a point of interesting congruence.

So, with a 12,000 year fitted wave, the 60 years essentially has a linear fit associated with it. In the chart, it is clearly an upward trend. However, observe the differene between the pre-1979 and post-1979 areas of the chart.

Two things are apparent: (1) the volatility in the anomaly values is much higher prior to 1979, and (2) the upward trend occurs in the pre-1979 data.

Putting numbers to these observations:
1) The Standard Deviation of observations for the data prior to 1979 is 1.749. The standard deviation for 1979 – current is 0.988. The average positive anomaly prior to 1979 is 0.960. The average positive anomaly 1979-current = 0.746. The average negative anomaly pre-1979 is -1.778. The average negative anomaly for 1979-current is -0.830.

2) The slope from 1948 – 1978 represents warming of 5.26 degrees Celsius per Century. The slope from 1979 – current represents 0.68 degrees warming per Century.

It seems pretty clear that the data prior to 1979 is a different animal than post-1979.

AMO Update – June 2009

The Antlantic Multidecadal Oscillation data has been released and the May index value is -0.014. That is the fifth consecutive negative value, and it’s the first time we’ve seen 5 consecutive negative months since the period ending October 1994. Previous to this negative stretch, there had been 77 consecutive positive months.

Similar to my look at the ENSO index, I have updated my best-fit sine wave against the AMO data. The chart is presented here:

Best-fit wave pattern against AMO data.

One nice thing about the AMO data as compared to the ENSO data is that it goes back to the mid 1800s. I cannot speak to the robustness of the index value, particularly for the older periods. I can only assume that it’s as good a measure as we have to work with.

A couple things can be noticed about this graph, especially in relation to the ENSO chart in the post referenced above. First of all, we are right now at the peak of the AMO wave. It last reached a trough in 1979, and has been increasing for the last 30 years. Since we are now at the peak, we will be descending down that wave now for the next 30 years, if the cycle is as presented. It should, however, remain in the warmer mode for the next 15 years of so, even though overall it is in a decline. Compare this to ENSO, where we just crossed the zero line.

It appears, then, that the ENSO (and PDO, as well) is offset almost exactly 90 degrees from the AMO. If true, this helps explain the contribution to warming over the last 30 years, and the stagnation of the last few years. 30 years ago, the AMO wave was at its trough, and the ENSO wave had crossed the zero line, moving upward. The next 15 years showed a situation in which all three waves were increasing. AMO from its trough up to the zero line, and ENSO/PDO from zero to its peak. Then, AMO increased while ENSO/PDO decreased, but both were above the zero line, so temperatures remained elevated, but the increase in temperature slowed and/or stagnated. Is it just coincidence? I suppose it could be. I consider that doubtful, however, because of the identification of waves in the HadCrut data that I presented.

Well, today, we are in the opposite siutuation as we were 30 years ago. The AMO is at a peak, and the ENSO/PDO index is at zero. It would seem, then, that we will experience significant cooling, along the same order as the warming of the 1980-2000 period over the next 20 years or so. Then, the period of time after that will likely be a stagnation of colder weather for 10-15 years, before we see the next warming cycle occur.

I’m sort of repeating what I did in this post. But it bears repeating. It seems fairly obvious to me, and it’s almost implausible to believe that such a relatively straighforward analysis that shows the Ocean cycles and how it affects the temperature cycles is not considered noteworthy when projecting forward temperature changes.

The other thing to note regarding the AMO chart above is that we seem to prematurely be getting some negative index values. I wouldn’t read much into that. Looking back at the chart, there are numerous times where negative readings – even consecutive ones – occur during the warmer side of the wave. In fact, the negative readings we see probably do indicate that we are in the warm wave yet, because the magnitude isn’t great, despite some persistence.

I may just be a layman and a data guy, but between this kind of analysis, a quiet sun and the analysis I’ve done as temperature relates to that, and the simple observation that we haven’t warmed in 12+ years, I can’t help but feel somewhat perturbed at the continuing warnings of global warming, and outright amazed at the audacity of predictions of multi-degree temperature increases by the end of the Century.

At this point, I would give odds on cooling until 2030 or so, regardless of what the fancy climate models say. It’s the only reasonable conclusion by looking at strict data. I suppose maybe the models say something that can’t be foound in the data. We’ll see.

The Unifying Theory of Earth’s Climate

Stephen Wilde contacted me regarding an article that he has presented exclusively on CO2Skeptics.com. It is definitely worth the read. I have posted a couple excerpts here, but I encourage you to CLICK HERE to read the entire paper. Many thanks to Stephen for giving me a heads up on this.

The Unifying Theory of Earth’s Climate
Guest post by Stephen Wilde – excerpts from his paper of the same name.

The claims of those who worry about human damage to the climate become ever more strident despite, or perhaps because of, the real world data rapidly diverging from that which they anticipated.

(Figure 1) The failure of alarmist predictions

It is now ten years since the 1998 culmination of a period of thirty years of unusual ocean warmth that resulted in the atmospheric temperature peak of that year. Additionally during that period the sun was more active than ever previously recorded. ( Figures 2 and 4)

Figure 2 The high solar activity from 1940 to 2000.

AGW proponents accept that the relative coolness of the past 10 years (Figure 3) is a result of cooler oceans but refuse to accept the corollary that the primary cause of the warmer period was warmer oceans. Warmer oceans also expand. ( Figure 5) and release natural CO2. The apparent levelling off in the sea level rise is coincident with recent cooler ocean surfaces.

See CO2Skeptics.com for the full presentation.

My own comments:
Mr. Wilde hits on a couple points I have made myself, which shows an understanding of cyclical changes in trends and the ability to apply simple logic. Most of us – even the skeptics – acknowledge that warming occurred from the 1970s to the end of the century. So, when there has been no warming for the last number of years, yet we hear the arguments that the latest year is still in the top X of our records, it’s kind of silly. I have used the analogy of climbing a mountain, getting to the top, and coming down the other side. Even though your are heading down once over the top, your first steps are still close to the top. In fact, if you trended elevation by time, you would continue to see a positive trend line for quite a while as you headed down, because those elevation points would be near the top of the mountain, even if descending. Ignoring the recent negative changes in elevation and only looking at the overall trend line would lead one to suggest that you’re still climbing up the mountain. While we cannot prove definitively that this is happening with temperature, to completely ignore the possibility is to put blinders on. If this truly is a cycle, then Mr. Wilde is absolutely correct in his assertion that points will cluster for a time at peaks and troughs.

In addition, Mr. Wilde criticizes climate models that are “built upwards from innumerable details rather than downwards from a verifiable overarching concept.” I have also addressed this issue here, and completely agree. I work in a profession that relies on modeling. I can’t tell you how often I scrap a more complex model that tries to capture all the details through numerous inputs in favor of a simple model that looks at things from a broad perspective. The issue is not that complex, comprehensive models are poor in concept. The issue is that if you are building a model in that fashion and you are missing anything, you end up with cross biases where things get inappropriately attributed to certain factors, and the results are nonsensical. More often than we’d like to admit, the better approach is to simply admit that we don’t fully understand all the impacts of all the components, and we need to accept that high-level, general, and simpler models are actually better. Mutliple times a year I read a story about something dealing with climate where there is some unanticipated effect of something-or-another. This tells me, then, that models built on a need for comprehensive analysis are erroneous.

Mr. Wilde’s summary conclusion is that it’s all about the oceans. This encourages me to get back to me more comprehensive correlation analysis on all the ocean indices. (Still waiting on that December PDO reading…)

Pacific Decadal Oscillation (PDO) Index – Back into the Negative

The PDO index is a measure of another one of those weird oceanic oscillation patterns.  The ENSO index is a shorter-term varying event, whereas the PDO index is considered a longer-term event.  Interestingly, however, when you collapse the ENSO index into longer average time periods, there does appear to be persistency in the ENSO index, as well. However, the short-term cyclical nature of the ENSO index is much more evident than the PDO index, even if the averages show similar persistency.

The PDO index is predominant in the Northern Pacific and secondarily evident in the tropics, whereas the ENSO index is the other way around. ENSO receives so much attention because of the large short-term cyclical variations, but the PDO has very significant swings as well, just usually over a longer period of time.

The index, however, is measured on a month-to-month basis and the data can be located here.

November has not yet been updated, but the October index value was -1.76. This was the single coolest reading in any month since November 1999, and was the 14th consecutive negative reading in a row. While there have been other stretches of 14 consecutive negative readings – the last being 1999-2000, it is interesting to note that the current streak of seven consecutive readings of less than -1 has not been seen since the period ending February 1976. That particular stretch ended at 7 months. If this month’s reading is below -1, it will mark the first time since the period ending June 1972. And that streak ended at 8. Beyond that point takes us to a streak in the early 1960s. So I’ll keep an eye on that.

As I did with the ENSO index, I collapsed the raw data into different average periods. Since the PDO does seem to vary over a longer period of time, I went up to a 10 year average. The persistency in the index is very clear once you take longer-term averages.

Below are a few charts of the PDO. The first is the raw data. Taking the edges off with 12-month smoothing follows that. I then present 5-year and 10-year averages.

The PDO monthly index has been negative for a bit already, as has the five-year average. But the 10-year average recently went negative, as well. Of course, all the same arguments apply as in the ENSO discussion – the persistence matters. You keep a heater running and the temperature gets warmer than the temperature an hour ago, depending on insulatory effects. Persistence in both ENSO and PDO correspond with the warming we see in the global temperature readings. The 10-year average PDO is slightly negative, and we’ve cooled slightly in the last few years. Coincidence?

The overall PDO index data since 1900.

The overall PDO index data since 1900 with 12-month smoothing.