Digital Diatribes

A presentation of data on climate and other stuff

A Gander at the Caribbean Oscillation Index

Posted by The Diatribe Guy on September 29, 2009

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_200908_raw

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_200908_12

Caribbean Oscillation Data as of 200908 - 12 month Smoothing

Caribbean_oscillation_200908_60

Caribbean Oscillation Data as of 200908 - 5 Year Smoothing

Caribbean_oscillation_200908_120

Caribbean Oscillation Data as of 200908 - 10 Year Smoothing

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2 Responses to “A Gander at the Caribbean Oscillation Index”

  1. docattheautopsy said

    The next thing to do with all of these oscillation indexes would be to overlap them over a long window of time and how well they correlate, and then compare them with global temperatures and look for a match.

  2. Kick-ass article, good looking blog, added it to my favs.

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