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.

Update on What’s Going on in the Tropics – RSS

Continuing my series (Antarctica, Arctic) of looks at the more regional breakdown of the RSS Temperature Anomaly Data, I am now moving on to the Tropics.

This is actually a fairly interesting region to observe. This, along with the Antarctic(ish) region was a contributor to the higher July anomaly.

Data Point
The July anomaly was 57.90 units (where 1 unit = 0.01 degrees Celsius). This was a pretty warm anomaly, ranking 14th out of 367 total observations in the data set, and ranking tops as the warmest July on RSS record (31 years of records). The increase over last July was 54.10 units, and the increase over June 2009 was 36.1 units. It would have been a great time for your equatorial vacation if you like running around in a Speed-o (note to readers: I do not wear a Speed-o).

It should be noted that the overall average anomaly in the data set is actually 6.27, and not zero. So, if one considers the overall average to be the point of departure from which an anomaly should be measured, the values are slightly overstated. Not as much as in the Arctic, but overstated nonetheless. This may seem conniving, but I don’t read much into it. Restating all historical anomalies every month to consider the latest average makes it difficult for the casual reviewer to come to grips with trends, and since all values would be changing, some may question whether or not the change is anything more than a readjustment to baseline. No, it probably is best to make only the occasional adjustment if and when the average drifts too far from zero. In this case, I probably would leave the Tropics as is. One could probably argue that the Arctic baseline should be changed and the anomalies adjusted, but it all really only matters if you let the perception of a high number cloud the issue. Unfortunately, too many people – including those who probably know better – will tend to look at the magic number of 100.00, for example, and freak out about the high number.

Streaks
One of the interesting things I noted in the anomaly record was the tendency of this region to have some persistency in relative temperature. Starting with April 2004, we saw a stretch of 9 consecutive months where the anomaly was cooler than previous year. That was followed by a stretch of 9 consecutive months with anomalies warmer than previous year. After that, we had a stretch of 12 consecutive months where the anomaly was cooler than previous year. In the next year, 10 of the 12 months were warmer than previous year. Then, we saw 12 consecutive months of anomalies that were cooler than previous year. We are now in the midst of a stretch of warmer-than-previous-year anomalies, with July being the 10th consecutive such month.

Averages
Thanks to the last couple higher anomalies, the 12-month average is 15.3, which is the highest average since the year ending January 2008. The 12-month average reached a low of -13.1 10 months ago and has steadily increased since then to current level.

Trends:

Overall:

RSS TROPICS Overall Trend Line

Update on Arctic Temperature – RSS July Anomaly

Since the Arctic always seems to be the “hot” discussion point in the discussion of climate change and global warming (does it seem unusual to anyone else that a discussion of a supposed global phenomenon almost always seems to come back to a discussion of melting ice in the Arctic?) I thought I’d provide an update on the Arctic charts. Since I’ve already mentioned the ice, let’s see what that’s up to (from the IJIS data – link on the right):

IJIS Arctic Ice Extent

I posted this on a comment on The Air Vent but I’ll repeat it here:

Anyway, in looking at the IJIS chart (not only above, but the current one) it seems pretty much as expected. I’m going to reference a post I made in early June: http://digitaldiatribes.wordpress.com/2009/06/04/quick-hit-post-on-the-arctic-ice/

Where I said this: “As of today, June 4, it is below the 2003 level, but holding in second position. As an aside, I wouldn’t at all be surprised to see this tail off quite a bit and dip below most of the years again. Looking at 2008 this happened, but not to the extent that it melted in 2007. It can reasonably be expected that the ice just won’t jump by leaps and bounds at maximum melt, while still in an increasing mode. So, 2009 may well dip below normal before it’s said and done, but my own guess is that it will still end up higher than 2008, thus continuing the upward trend.”

Unless we get some serious meltage going on soon, it looks like I’ll be right. Am I proud? Not really. It’s pretty much common sense along with a rudimentary understanding of Physics, energy requirements, and heat transfer. One doesn’t need to be an expert to look at the temperature trends along with 2007 ice levels and develop the idea that there will be a likely slow positive accumulation of ice over time.

So, what do I mean by these temperature trends? I mean, it’s warming in the Arctic, right?

Let’s take a look. All data is directly from the RSS data link that is located on the right, under resources. I suppose if you believe it to be bogus, you can take it up with them…

A Warm July in the Antarctic

After seeing the July RSS anomaly that showed a warm July, I was perturbed that – once again – I was languishing in cool weather in Wisconsin while someplace else apparently “suffered” from warmer temperatures. Looking at the territorial data, one of the culprits for that nasty warm weather was the extreme south. It was rightly pointed out to me a while back that I must be careful in presenting the RSS data as “Antarctic,” since it only goes to the latitudinal line of -70 degrees. So, please know that when I reference the Antarctic region here, it simply means the -60 to -70 region, which is as far dwon as RSS goes.

The July anomaly in this region was 1.0490 (a full degree Celsius and then some), which was a pretty warm one. It is the 5th highest anomaly in the 367 data points and is the 2nd warmest July in the 31 data points. It is nearly 7 tenths of a degree warmer than a year ago and the anomaly if 0.56 units higher than last month.

Keep in mind that it’s winter down there right now. I point that out because I guess I’m just not sure how much of a difference a degree makes in July with regard to melting ice. I know that when it’s winter here, -19 doesn’t seem to do much more than -20. But what do I know? I’m just an actuary. And a Packer fan. Are you watching these guys? The offense is looking phenomenal! Preseason or not, I’m getting pumped for the season to start.

But I digress.

Anyway, the last 13 12-month average anomalies had been negative, but thanks to the most recent one, the current 12-month average is at 0.45 (0.0045 in degrees Celsius). That’s not even a hundredth of a degree, so it’s essentially flat.

There’s no real streak of warming or cooling to consider. This is the second straight year-over-year increase, after 2 decreases. In fact, there really have been no real streaks to speak of for years. You have to go back to 2003 just to find the last time there was 6 months of consecutive anything. And that one was a consecutive cooling stretch.

Trends

Overall Antarctic Trend since inception of RSS data

Despite the current large anomaly, it is evident that there is no particular long-term trend. There are fluctuations both positive and negative about an almost perfectly flat zero line. Also, there doesn’t seem to be any particular indication that things are fluctuating wildly about any more than they have in the past. In fact, the last 10 years saw no anomalies above an absolute value of 1.000 until this one, which is the largest gap in the data. We often hear about how climate change is producing more extremes, but we don’t see that in this data.

Latest Flat/Cooling Antarctic Trend - RSS

August 2009 Update on Global Temperature – RSS

Don’t look now, but I’m actually posting a temperature update!

We’re looking at the July anomaly release for Global RSS Data. 

Data Point

The July anomaly was 0.392 (or 39.2 in terms of 0.01 C, which is what I’ll use).  This is an increase of 23.4 units over last year’s anomaly, and an increase of 31.1 units over June’s anomaly.   Perhaps that El Nino that everyone started talking about a while back has had an impact?

Rank

This is the 3rd highest July anomaly in the RSS data, of 31 observations. (90th percentile)

It is the 26th highest anomaly overall in the data set, of 367 observations. (92nd percentile).

It is the 1st most aggravating anomaly for me to observe.  July was miserably cold, with record low highs in Wisconsin.   I’m simply not catching a friggin’ break with the warmer anomalies.   Dear God: If we’re going to be warm, that’s OK.  Please afflict Wisconsin with some of it.  Thanks!

Average

The 12-month average anomaly ending July 2009 was 20.3.  This is now the highest 12-month average since February 2008.

Streaks

After hitting a low with negative anomalies last year, we are now experiencing a streak of 8 consecutive months where the year-over-year anomaly is higher than previous year.

Trends

Overall Trend since inception of RSS data

Recent Non-Warming Trend - over 12 years

June 2009 Update on Global Temperature – UAH

The UAH anomaly this month was 0.043. The link to the data can be found on the right of the page, under the Temperature Resources section.

The May data point
If you think that an anomaly near zero sounds about average, you’re right. In fact, it’s also around median (slightly below, actually). Go figure… The current anomaly ranks 16th of 31 May anomalies (48th percentile) and 202nd out of 366 overall anomalies (44th percentile).

The anomaly is stated in terms of degrees Celsius, but I will use the convention of 0.01 degrees Celsius, which translates to an anomaly of 4.3. When I say “units” I mean “0.01 degrees Celsius.” Units is more convenient.

The May anomaly was 4.7 units less than the April anomaly. However, due to a sharp negative reading last year, we were up 22.6 units this May over last May.

Averages

The current 12-month average is 14.0. Despite the lower anomaly this month, the annual average actually increased due to the fact that a cold anomaly dropped off from a year ago in the 12-month average calculation. The current average is the highest since the period ending April 2008. I’ve shown the plotted running 12-month average below. Note the easily seen single-step upward that looks to occur around 1997-98. I’ve noted that in the past.

12-month running average anomaly - UAH

For giggles, I looked at a couple other running averages, as well. The 36-month average is 18.85 ending May 2009. Interestingly, this average had trended downward every month since September 2007 until this month. It blipped up a bit this time around from the last month’s average of 18.70. (For those who like to accuse me of cherry-picking data, note that all the averages from 18-month average to 30-month average declined, and then every average from 42-months through 108-months declined from last month). Obviously, if you’ve thought about the math on this, it means that a low anomaly from three years ago dropped off. Going forward, it is probable that this average will continue to decline, barring some major warming.

36-month running average anomaly - UAH

Finally, I pulled the 120-month running average anomaly, which was 20.26. This is the fifth consecutive increase in the 120-month average. It is likely that we will see this average continue to increase over the next year+, unless we start seeing consistent single-digit or negative anomalies.